NeuroTOC

One major hallmark of alcohol use disorder (AUD) is the persistence of drinking despite negative consequences. Among indicators of AUD vulnerability, binge drinking has been identified as one of the strongest risk factors. Although the lifetime prevalence of both binge drinking and AUD has historically been higher in men than women, this gap has dramatically narrowed in the last decade. Additionally, sex differences in AUD and binge drinking have been found in clinical and preclinical studies. At the neurobiological level, the insular cortex plays an important role in AUD, with the anterior (aIC) and posterior (pIC) divisions supporting different functions. However, the contributions of the aIC and pIC sections in sexual dimorphism of alcohol binge drinking and the persistence of alcohol drinking despite aversion remain to be uncovered. Using the drinking in the dark model in mice, we validated that female mice have a higher binge ethanol intake compared to males. To evaluate persistent ethanol consumption despite aversion, we supplemented ethanol with the bitter compound quinine, and found a higher persistent drinking in females compared to males. Using fiber photometry recordings, we revealed that aIC activity was increased during binge and persistent ethanol consumption independently of sex, whereas pIC glutamatergic neuron activity was higher during persistent ethanol drinking, specifically in female mice. Using chemogenetics, we revealed that inhibition of aIC glutamatergic neurons reduced intake of bitter solutions independently of the solvent (ethanol or water) in both sexes. In addition, inhibition of pIC glutamatergic neurons exclusively reduced persistent ethanol drinking in females, while decreasing quinine consumption only in males. These findings suggest a sex-dependent function of the pIC in the persistence of ethanol consumption, providing a starting point in understanding sex-specific functions of the insular cortex in the neurobiology of AUD.

A key challenge of network neuroscience is to understand the role of interactions between brain regions and how they contribute to the encoding and broadcasting of information within cognitive processes. This demands computational tools to infer directional relations between brain regions from neural time series. For fMRI, the most common approaches are based on Granger causality (GC) analysis and effective connectivity (EC) models. Despite their different conceptual framing, GC and EC models for fMRI are based on similar mathematical assumptions, grounded on continuous- and discrete-time linear stochastic models. Based on a mapping between multivariate Ornstein-Uhlenbeck (MOU) and multivariate autoregressive (MVAR) processes, we analytically obtain an approximately quadratic relation between EC and GC, after rescaling the GC to compensate for unequal noise variances of the source and target. Simulations show that these relations can be observed in finite time series only if a large amount of data is available, implying that they may emerge only at a group level in real fMRI experiments. We verified this prediction by systematically comparing EC and GC in a large-scale fMRI data set from the Human Connectome Project. Overall, our findings can provide methodological and interpretational guidance in the usage of GC and EC for brain network reconstruction, by clearly elucidating what is common between the two methods, but also their respective specificities and biases.

Autism Spectrum Disorder (ASD) is a highly heritable condition with diverse clinical presentations. Approximately 20% of ASDs genetic susceptibility is imparted by de novo mutations of major effect, most of which cause haploinsufficiency. We mapped enhancers of two high confidence autism genes - CHD8 and SCN2A and used CRISPR-based gene activation (CRISPR-A) in hPSC-derived excitatory neurons and cerebral forebrain organoids to correct the effects of haploinsufficiency, taking advantage of the presence of a wildtype allele of each gene and endogenous gene regulation. We found that CRISPR-A induced a sustained increase in CHD8 and SCN2A expression in neurons and organoids, with rescue of gene expression levels and mutation-associated phenotypes, including gene expression and physiology. These data support gene activation via targeting enhancers of haploinsufficient genes as a therapeutic intervention in ASD and other neurodevelopmental disorders.

AO_SCPLOWBSTRACTC_SCPLOWIn the geniculostriate pathway of the human visual system, neuronal projections carry signals from a particular retinal locus in parallel from one anatomical area to the next. Imprecision in the fidelity of these projections would place constraints on the ability of the system to perform tasks requiring positional information. We investigated the impact that "spatial scrambling" between stages would have on visual performance. We consider two stages in a simple canonical model of the early visual cortex where scrambling might occur: either the input to the first orientation-tuned mechanisms (analogous to V1 simple cells), or the output from those mechanisms. These are referred as "subcortical" (SCS) and "cortical scrambling" (CS). We developed a wavelet decomposition and resynthesis algorithm to mimic these effects, and measured human performance in letter identification affected by the two types of scrambling. Our results showed SCS and CS have distinguishable effects on both perceived noisiness of letters and letter identification threshold. Comparing human performance against a suite of pre-trained and custom convolutional neural networks (CNNs) that were trained on the scrambled stimuli, relative efficiency (calculated from the ratio of human:CNN thresholds) is higher for CS than SCS. However, in modelling human inefficiency by reducing the proportion of wavelets available to the CNNs, humans are less efficient in CS than SCS. These differences in efficiencies show humans are better at processing orientation redundant stimuli (CS) than orientation noisy stimuli (SCS). We hypothesize this reflects differences in integration properties at the input and output stages of simple cells in the cortex. Author SummaryThe brain makes sense of the input from our eyes through a system where features are extracted and combined in successive stages. Our study concerns the spatial fidelity of the connections between visual areas. Previous behavioural and physiological evidence has suggested a scrambling of neuronal projections is present in biological visual systems. In our study, we investigate the ability of the human visual system to perform letter identification with stimuli affected by different types of on-screen distortions. These distortions simulate internal scrambling occurring at two early stages in the visual hierarchy. We used convolutional neural network (CNN) models as a benchmark, against which we compared human performance to find human efficiency in handling the distortions. We found that the type of scrambling in which humans were determined to have greater "efficiency" (relative to the CNNs) depended on the analysis used. The threshold magnitude of scrambling at which the letters could no longer be identified was greater for letters scrambled after the oriented features were extracted. Conversely, when efficiency was calculated by starving the CNNs of samples until their performance declined to the human level we instead found that the effective "number of samples" used by our humans was much higher for stimuli simulating scrambling before the oriented feature stage. These differences reflect how information is pooled and combined for these two stages.

We developed a high content screening to investigate how Alzheimer disease (AD) genetic risk factors may affect synaptic mechanisms in rat primary neuronal cultures. Out of the target genes identified, we found that Plcg2 downregulation in mouse dentate gyrus neurons consistently disrupted dendritic morphology and synaptic function. In human neuronal cultures (hNCs), PLCG2 downregulation also impaired synaptic function and increased A{beta} levels and Tau phosphorylation. Very rare PLCG2 loss-of-function (LoF) variants were associated with a 10-fold increased AD risk. PLCG2 LoF carriers exhibit low mRNA/protein PLCG2/PLC{gamma}2 levels and the R953* LoF mutation compromised synaptic function and increased AD hallmarks in hNCs. Single nuclei RNAseq analyses confirmed that the downregulation of PLCG2 impacted pathways related to synaptic and neuronal functions, potentially through neurexin in neurons. In conclusion, PLC{gamma}2 downregulation could increase AD risk by impairing synaptic functions and increasing the A{beta} levels and Tau phosphorylation in neurons.

BackgroundOne of the major challenges in addressing multiple sclerosis is to understand its progression trajectory. The pathological process transitions from acute phases predominantly driven by inflammation to progressive clinical profiles where neurodegeneration takes precedence. It is known that sex plays a crucial role in this heterogeneity; females are two to three times more likely to suffer from multiple sclerosis, while males suffer from more rapid neurodegeneration with greater severity. ResultsTo gain insight into the sex-based molecular differences, we processed single cell datasets from the central nervous system and the peripheral blood, covering the different courses of multiple sclerosis. We generated cell-type specific landscapes, including gene signatures from differentially expressed genes, functional profiling, pathway activation, and cell-cell communication networks for females, males, and their sex differential profiles. Among our findings, we revealed that female neurons may exhibit protective mechanisms against neurodegeneration. In the inflammatory-predominant forms, female immune cells present an inflammatory core driven by the AP-1 transcription factor, while male adaptive immune cells exhibit higher mitochondrial impairment. Conversely, larger differences are reported in CD8+ T cells progressive forms, with males exhibiting cytolytic profiles that may promote neurodegeneration. Complete results can be explored in the interactive webtool https://bioinfo.cipf.es/cbl-atlas-ms/. ConclusionsWe identified cell-type specific sex differences in brain and immune cells that vary in the spectrum of multiple sclerosis. We consider this molecular description a valuable resource to promote future targeted approaches considering the sex of the individual.

Childhood and adolescence are marked by protracted developmental remodeling of cortico-cortical structural connectivity. However, the spatiotemporal variability of white matter connectivity development across the human connectome and its relevance to cognition and psychopathology remains unclear. Using diffusion MRI data from three independent developmental cohorts spanning youth, we identified a robust divergence in structural connectivity maturation along a predefined sensorimotor-association (S-A) connectional axis during youth (http://connectcharts.cibr.ac.cn). This developmental continuum ranged from early childhood increases in sensorimotor-sensorimotor connectivity strength to late adolescent increases in association-association connectivity strength, with the transition occurring around age 15. The S-A connectional axis also captured spatial variations in the associations between structural connectivity and both higher-order cognition and general psychopathology. Moreover, group-level developmental trajectories of structural connectivity differed by cognitive and psychopathological levels, with psychopathological effects predominantly observed in association connections. These findings delineate a spatiotemporal continuum of structural connectivity development during youth, providing a normative reference for quantifying developmental variability in psychiatric disorders.

Humans are the only species with the ability to systematically combine words to convey an unbounded number of complex meanings. This process is guided by combinatorial processes whose underlying neural mechanisms remain obscured by inherent limitations of non-invasive brain measures and a near total focus on comprehension paradigms. Here, we address these limitations with high-resolution neurosurgical recordings (electrocorticography) and a controlled sentence production experiment. We uncover distinct cortical networks encoding word-level and higher-order information. These networks exhibited a hybrid spatial organization: broadly distributed across traditional language areas, but with focal concentrations of sensitivity to semantic and structural contrasts in canonical language regions. In contrast to previous comprehension-based findings, we find that these networks are largely non-overlapping. Most strikingly, our data re-veal an unexpected property of higher-order linguistic information: it is encoded independent of neural activity levels. These results show that activity magnitude and information content are dissociable, with important implications for studying the neurobiology of language. Teaser"Brain recordings during speech reveal complex linguistic information throughout cortex, independent of neural activity levels."

Schwann cells (SCs) transition into a Repair state after peripheral nerve injury; however, the early SC injury response preceding this transition remains poorly understood. We demonstrate that Sarm1, a key regulator of axon degeneration, is expressed and upregulated in SCs after nerve injury. Cell-type-specific Sarm1 knockout SCs exhibit enhanced axon protection in vitro, and SC- and glia-specific Sarm1 deletion confers axon protection in mouse sciatic nerve and Drosophila wing injury models. Single-nucleus RNA sequencing revealed that Sarm1-deficient SCs are enriched in a distinct cluster expressing genes with developmental roles in axon and myelin protection, with increased oxidative phosphorylation gene expression across all injured SC states. We propose that Sarm1 gates the transition from a Protection-Associated Schwann Cell (PASC) state to a Repair SC state, establishing Sarm1 as a multi-functional regulator with implications for peripheral neuropathies and neurodegenerative diseases.

Modular organization, the division of the cerebral cortex into functionally distinct subregions, is well established in the primate sensorimotor cortex, but debated in the cognitive association cortex, including the prefrontal cortex (PFC). Here, we obtained microelectrode recordings with broad spatial coverage from the lateral PFC of two rhesus monkeys performing a working memory task with distractors. We found that neighboring electrodes shared task-related oscillatory neural dynamics that were stable across recording sessions and formed spatially continuous, mesoscale clusters that also segregated by local and long-range frontoparietal connectivity, spiking activity, involvement in working memory processing stages and influence on behavioral accuracy. Remarkably, the degree of parcellation reflected the animals individual mnemonic abilities and strategies. Our findings support functional organization of the PFC by cognitive control operations rather than by the type of processed information, indicating that modularity may be a fundamental architectural principle across the primate cortex.

From overt emotional displays to a subtle eyebrow raise during speech, facial expressions are key cues for social interaction. How these inherently dynamic facial signals encode emotion across non-verbal expression and speech remains only partially understood. In Study 1 we recorded participants facial movements signalling happy, sad and angry emotions in Expression-only and Emotive-speech conditions. We employed a data-driven pipeline integrating facial motion quantification, spatiotemporal classification and clustering to investigate the structure and function of facial dynamics in signalling emotion. Results reveal that a few spatiotemporal patterns reliably differentiated emotion in non-verbal expressions and emotive speech facial signals. Furthermore, we identified transient substates - or dynamic phases - that are diagnostic of emotion intent and conditions. A perceptual validation with naive observers (Study 2) showed that the low-dimensional spatiotemporal structure captures meaningful cues that closely predict human emotion categorisations. We discuss theoretical implications of a low-dimensional spatiotemporal structure for optimal transmission and perception of dynamic facial emotion signals and face-to-face interaction. This work also provides a framework for modelling dynamic social cues and insights for the design of expressive emotive capabilities in social agents.

Alzheimer's disease (AD), the most common cause of dementia, represents one of the main clinical challenges of the century as the number of patients is predicted to triple by 2050. Despite the recent approval of three monoclonal antibodies targeting amyloid beta (A{beta}) aggregates by the Food and Drug Administration (FDA), immunotherapies still face challenges due to the difficulty of antibodies crossing the blood-brain barrier (BBB). This necessitates administering large doses of drugs to achieve their therapeutic effects, which is associated with significant side effects. In this context, low-intensity focused ultrasound (LiFUS) appears as an innovative and non-invasive method which, in association with intravenous injection of microbubbles (MB), leads to a transient BBB opening. This innovative strategy has been extensively studied in different preclinical models and more recently in human clinical trials, particularly in the context of AD. LiFUS+MB increases the inflammatory response at short-term, but the time course of this response is not consistent between studies, certainly due to the discrepancy between LiFUS protocols used. Moreover, the impact at longer term is understudied and the mechanisms underlying this effect are still not well understood. In our study, we therefore used the TgF344-AD rat model of AD to investigate the effect of a single or multiple exposures to LiFUS+MB in a large volume of the brain on inflammatory response, tauopathy and amyloid load, at both early and advanced stages. The ultrasound attenuation through the skull was corrected to apply a peak negative acoustic pressure of 450 kPa in all treated animals. At an advanced disease stage, single LiFUS+MB exposure induces a slight astrocyte and microglial response 24 hours post-treatment whereas chronic LiFUS treatment is associated with a transient inflammatory response predominantly affecting microglial cells, which is no longer detectable 6 weeks post-treatment. At an early stage of pathology, LiFUS seems to induce microglial reprogramming, leading to the adaptation of gene expression related to key functions such as inflammatory response, mitochondrial and energetic metabolism. In our rat model and LiFUS+MB protocol conditions, a single LiFUS exposure reduced significantly highly aggregated A{beta}42 peptide concentration. Surprisingly, multiple exposures had this opposite effect at short-term but not at longer term.

Engaging in prosocial behavior requires effort, yet people are often averse to exerting effort for others benefit. However, it remains unclear how effort exertion affects subsequent reward evaluation during prosocial acts. Here, we combined high-temporal-resolution electroencephalography with a paradigm that independently manipulated effort and reward for self and others to elucidate the neural mechanisms underlying the reward after-effect of prosocial effort expenditure. We found dissociable reward after-effects for self-benefiting and other-benefiting effort. For self-benefiting rewards, the reward positivity (RewP) increased with effort demand, suggesting an effort-enhancement effect. In contrast, for other-benefiting rewards, the RewP decreased as effort increased, demonstrating an effort-discounting effect. Critically, this dissociation was contingent upon high reward magnitude and modulated by individual differences in effort discounting, yet remained distinct from performance evaluation. Our findings reveal distinct neural computations for self- and other-benefiting efforts, offering new insights into how prior effort expenditure shapes reward evaluation during prosocial behavior.

The hypothalamic changes that occur after the loss of ovarian estrogen remain poorly characterized. Here, we performed a comprehensive temporal characterization of the mouse hypothalamus following ovariectomy (OVX), combining physiological measurements with bulk RNA-sequencing of the posterior hypothalamus (PH) and preoptic area (POA) at short-term (14 days) and long-term (4 months) post-OVX. Serum LH levels rose progressively and then declined, while core temperature peaked early and subsequently normalized, recapitulating the endocrine and thermoregulatory dynamics of reproductive aging in humans. Transcriptomic analysis revealed time-dependent activation of inflammatory pathways, glial markers, and KNDy neuron-related gene networks, with the most pronounced changes emerging at 4 months post-OVX, particularly in the PH. Immunofluorescence confirmed increased NKB release, declining KNDy neuronal activity, and heightened astrocytic reactivity in the arcuate nucleus after prolonged estrogen withdrawal. To contextualize these findings, we analyzed publicly available human hypothalamic RNA-seq data across chronological age. Age-related transcriptomic patterns in women, including progressive inflammatory signaling, glial activation, and altered KNDy gene expression, showed significant correlation with the OVX mouse model, particularly at the pathway level. These findings establish a temporal framework for hypothalamic molecular changes after estrogen withdrawal, identify conserved neuroinflammatory signatures across species, and provide a preclinical platform for testing interventions targeting menopausal-associated hypothalamic dysfunction.

Core body temperature (Tb) is defended within narrow limits through thermoregulatory behaviors like huddling, nesting, and physical activity as well as autonomic responses like brown fat thermogenesis. While Tb displays regulated fluctuations across different behavioral states and rest/arousal cycles, the neural control of these transitions is poorly understood. Here, we investigate the relationship between oxytocin neurons of the paraventricular hypothalamus (PVNOT) and behavioral and autonomic thermoeffector pathways across physiological states in mice. First, we show that PVNOT neurons are activated during social thermoregulation. We then demonstrate that in vivo PVNOT calcium dynamics align with transitions from rest to thermogenesis and behavioral arousal. Counter to our initial hypothesis, these dynamics were observed in both social and non-social contexts. Using a computer vision model to track thermoeffector pathways, we demonstrate that precisely timed stimulation of PVNOT neurons during low-Tb resting states increases thermogenesis followed by behavioral arousal. We therefore suggest a model in which PVNOT neurons facilitate homeostatic state-dependent transitions in thermo-behavioral states.

One of the most distinctive features of the mammalian cerebral cortex is its laminar structure. Of all cortical layers, layer 6b (L6b) is by far the least-studied, despite exhibiting direct sensitivity to orexin and having widespread connectivity, suggesting an important role in regulating cortical oscillations and brain state. We performed chronic electroencephalogram (EEG) recordings in mice in which a subset of L6b neurons was conditionally "silenced", during undisturbed conditions, after sleep deprivation (SD), and after intracerebroventricular (ICV) administration of orexin. While the total amount of waking and sleep or the response to SD were not altered, L6b-silenced mice showed a slowing of theta frequency (6-9 Hz) during wake and REM sleep, and a marked reduction of total EEG power, especially in NREM sleep. The infusion of orexin A increased wakefulness in both genotypes, but subsequent levels of EEG slow-wave activity during NREM sleep were lower in L6b-silenced animals in the occipital derivation. In summary, these results demonstrate a role for cortical L6b in state-dependent brain oscillations and in the response to orexinergic neurotransmission. Our findings provide new insights in functions of L6b neurons and could inform the understanding of abnormal regulation of brain states in neurodevelopmental and psychiatric disorders.

Language impairments across both structural components and pragmatic use are frequently observed in individuals with autism spectrum disorder (ASD). These difficulties are thought to stem from atypical brain development and abnormal network interactions, yet an integrative network-level model accounting for such impairments remains lacking. To bridge this gap, we applied the dynamic meta-networking framework of language, a theoretical model capturing domain-segregation dynamics during rest, to examine age-related changes (5-60 years) in cortical language networks in individuals with ASD. To further probe the biological underpinnings of these dynamics, we quantified spatial correspondences between network state hubs and gene co-expression modules as well as neurotransmitter receptor distributions. We identified distinct language meta-states characterized by domain-segregation connectivity patterns, which exhibited spatial alignment with gene co-expression modules and neurotransmitter systems. Individuals with ASD showed state-dependent developmental trajectories marked by age-related hypo- and hyper-connectivity. Critically, these network alterations strongly predicted verbal IQ and communicative difficulties, but were unrelated to social functioning or stereotyped behaviors. Our findings provide novel evidence that language-related network dynamics in ASD are developmentally altered, biologically grounded, and selectively linked to verbal and communicative impairments. These results advance a network-level model of language dysfunction in ASD and highlight potential mechanistic pathways for targeted interventions. Lay SummaryLanguage challenges are common in autism and can affect both learning language and using it in everyday conversations. In people aged 5-60, we found distinct, age-changing patterns in how the brains language areas connect at rest; these patterns align with basic biology (genes and brain chemicals) and strongly relate to verbal ability and daily communication, but not to social difficulties or repetitive behaviors. These results suggest clear, brain-based targets for earlier and more tailored support for language problems in autism.

Maladaptive reward learning and decision-making circuity are key factors in the onset and progression of alcohol use disorder and have therefore emerged as key targets for neuropsychological and pharmacological interventions. Probabilistic reversal learning studies have consistently reported impaired learning in recently detoxified alcohol dependent (AD) participants. However, the neural and behavioural changes associated with reward learning which occur throughout abstinence remain unexplored. Here, we show that AD participants, with mean abstinence of 20 months, exhibit intact behavioural performance within an electroencephalography (EEG) probabilistic reversal learning task. Reinforcement learning modelling reveals reward and punishment related learning rates and exploration rates are comparable between AD and healthy control (HC) participants, suggesting recovery of even the nuanced aspects of learning in longer term abstinence. However, EEG analysis indicates that AD, compared to HC participants, show globally elevated event-related potential (ERP) feedback related negativity (FRN) following reward valuation. Furthermore, Feedback-P3 valence prediction error signal is negatively associated with abstinence duration indicating a potential state marker of AD recovery. We then employ unsupervised machine learning (canonical polyadic tensor decomposition) to identify spatiotemporal EEG patterns of reward valuation in a purely data-driven manner. Classification analysis shows these tensor components can predict group membership with 80.4% accuracy. By probing group differences in tensor components, we discover early hyperfunctioning in centro-frontal regions linked to alcohol dependence and associated with early abstinence. The clinically meaningful EEG biomarkers presented here could guide the development of more targeted treatments and support big data approaches to objective patient monitoring.

MicroRNAs are key regulators of brain gene expression, with miR-29 family notably upregulated from development to adulthood and in aging, and showing links to cognitive decline. However, the extent to which miR-29 levels influence learning and memory processes, and its molecular mediators, remains to be determined. Here, we down- and up-regulated miR-29 levels in the dorsal hippocampus of adult mice to reveal miR-29 role in memory. Inhibition of miR-29 enhanced trace fear memory stability, increased Dnmt3a levels, and promoted DNA methylation in a DNMT3a-dependent manner. In contrast, increasing miR-29 impaired memory performances and decreased Dnmt3a levels, suggesting a destabilization of memory processes. Proteomic and transcriptomic analysis demonstrated that miR-29 antagonism upregulated RNA-binding and synaptic proteins and downregulated inflammation and myelin associated proteins. These results underscore miR-29s pivotal role in memory persistence, plasticity, and cognitive aging, suggesting that miR-29 modulation could offer potential strategies for cognitive enhancement and age-related memory decline.

Microtubules play a crucial role in neuronal structure and function, with their stability and dynamics regulated by posttranslational modifications (PTMs) such as polyglutamylation. In Alzheimer disease (AD), the microtubule-associated protein TAU becomes mislocalized into the somatodendritic compartment (TAU missorting), dissociates from microtubules, aggregates into neurofibrillary tangles, and contributes to microtubule destabilization and neuronal death. Here, we investigated the role of Tubulin-Tyrosine-Ligase-Like proteins (TTLLs) in TAU missorting and microtubule dysregulation using human induced pluripotent stem cell (hiPSC)-derived cortical neurons treated with oligomeric amyloid-beta (oA{beta}) to replicate AD-like conditions. TTLL1, TTLL4, TTLL6 were selectively knocked down (KD) to assess their impact on TAU missorting and microtubule stability. Fluorescence resonance energy transfer (FRET) microscopy was used to examine interactions between TAU and TTLL proteins. We observed TAU missorting, increased tubulin polyglutamylation, decreased microtubule stability, and synaptic declustering in oA{beta}-treated neurons. TTLL1 KD significantly reduced TAU missorting, tubulin polyglutamylation, and synaptic disintegration, while TTLL4 KD showed moderate effects, and TTLL6 KD restored microtubule acetylation. Importantly, TTLL KD did not impair neuritic networks, dendritic complexity, or neuronal activity. FRET microscopy revealed a potential interaction between TAU and TTLL1, but not other TTLLs, suggesting a direct role of TTLL1 in TAU-mediated toxicity. Our findings indicate that targeting TTLL1, either alone or in combination with other TTLLs, may be a promising therapeutic strategy to counteract microtubule and synaptic dysfunction in AD and related neurodegenerative disorders.

A key question in human neuroscience is to understand how individual differences in brain function relate to cognitive differences. However, the optimal condition of brain function to study between-person differences in cognition remains unclear. While many studies have developed objective biomarkers to accurately predict intelligence and general cognition, consensus on domain-specific markers has not yet emerged. Brain age has been proposed as a potential candidate, but recent research suggests that brain age offers minimal additional information on cognitive decline beyond what chronological age provides, prompting a shift toward approaches focused directly on cognitive prediction. Using a deep learning approach, we evaluated the predictive power of the functional connectome during various states (resting state, movie-watching, and n-back) on episodic memory and working memory performance. Our findings show that while connectomes during task, especially during movie watching, better predict both episodic and working memory, resting state connectomes are equally effective in predicting episodic memory. Furthermore, individuals with a negative brain-cognition gap (where brain predictions underestimate actual performance) exhibited lower physical activity and higher cardiovascular risk compared to those with a positive gap. This shows that knowledge of the brain-cognition gap provides insights into factors contributing to cognitive resilience. Further lower PET-derived measures of dopamine binding were linked to a greater brain-cognition gap, mediated by regional functional variability. Together, our findings highlight the importance of brain state in connectome-based cognitive prediction and introduce the brain cognitive gap as a potentially informative, dopamine-modulated marker of vulnerability to compromise brain function.

Parkinsons disease (PD) is commonly associated with the loss of dopaminergic neurons in the substantia nigra, but many other cell types are affected even before neuron loss occurs. Recent studies have linked oligodendrocytes to early stages of PD, though their precise role is still unclear. PINK1 is mutated in familial PD, and through unbiased single-cell sequencing of the entire brain of Drosophila Pink1 models, we observed significant gene deregulation in ensheathing glia (EG); cells that share functional similarities with oligodendrocytes. We found that the loss of Pink1 leads to abnormalities in EG, similar to the reactive response of EG seen upon nerve injury. Using cell-type-specific transcriptomics, we identified deregulated genes in EG as potential functional modifiers. Specifically downregulating two trafficking factors in EG, Vps35 and Vps13, also mutated in PD, was sufficient to rescue neuronal function and protect against dopaminergic synapse loss. Our findings demonstrate that Pink1 loss in neurons triggers an injury-like response in EG, and that Pink1 loss in EG in turn disrupts neuronal function. Vesicle trafficking components, which may regulate membrane interactions between organelles in EG, seem to play a role in maintaining neuronal health and ultimately preventing dopaminergic synapse loss. Our work highlights the essential role of glial support cells in the pathogenesis of PD and identifies vesicle trafficking within these cells in disease progression.

Parkinsons disease (PD) is commonly associated with the loss of dopaminergic neurons in the substantia nigra, but many other cell types are affected even before neuron loss occurs. Recent studies have linked oligodendrocytes to early stages of PD, though their precise role is still unclear. PINK1 is mutated in familial PD, and through unbiased single-cell sequencing of the entire brain of Drosophila Pink1 models, we observed significant gene deregulation in ensheathing glia (EG); cells that share functional similarities with oligodendrocytes. We found that the loss of Pink1 leads to abnormalities in EG, similar to the reactive response of EG seen upon nerve injury. Using cell-type-specific transcriptomics, we identified deregulated genes in EG as potential functional modifiers. Specifically downregulating two trafficking factors in EG, Vps35 and Vps13, also mutated in PD, was sufficient to rescue neuronal function and protect against dopaminergic synapse loss. Our findings demonstrate that Pink1 loss in neurons triggers an injury-like response in EG, and that Pink1 loss in EG in turn disrupts neuronal function. Vesicle trafficking components, which may regulate membrane interactions between organelles in EG, seem to play a role in maintaining neuronal health and ultimately preventing dopaminergic synapse loss. Our work highlights the essential role of glial support cells in the pathogenesis of PD and identifies vesicle trafficking within these cells in disease progression.

The emergence of abstract object representations in the mammalian ventral visual stream remains a central challenge for biologically plausible learning theories. While deep artificial networks trained via backpropagation achieve high performance, the algorithm lacks biological realism and conflicts with the staggered timeline of critical periods observed in cortical development. Here, we present a hierarchical model of the visual stream that learns invariant representations using only local synaptic plasticity rules modulated by lateral predictive signals. We demonstrate that imposing staggered critical periods -- where plasticity windows open and close sequentially from V1 to inferotemporal cortex -- significantly enhances representation quality for local learning rules, whereas it degrades performance in backpropagation-based networks. Furthermore, this sequential regime improves the learning efficiency in terms of number of synaptic updates, suggesting a metabolic advantage consistent with evolutionary constraints. We validate the functional utility of these acquired representations through reinforcement learning agents that successfully solve navigation and visual discrimination tasks without further fine-tuning of the visual encoder. These findings suggest that staggered critical periods are not merely a developmental constraint but a functional mechanism that enables efficient, local, and metabolically economical learning in hierarchical neural systems.

Abundant evidence supports the significant impact of biological sex on various aspects of Parkinson Disease (PD), including incidence, progression, symptoms or response to treatment. The incidence and prevalence of the disease is higher in males, while its age of onset is earlier than in females. There are also sex differences in the symptomatology, both motor and non-motor. In female PD, tremor, pain, depression and dysphagia are predominant, whereas in male PD, freezing of gait, camptocormia, cognitive impairment and urinary dysfunction are more common. Likewise, there are sex differences in the pathophysiology of the disease, related to most of the pathological processes of PD, as is the case of the greater activation of microglia in males or the lower oxidative stress in females. All these findings support the idea that different molecular mechanisms may be involved in PD depending on the sex of the patient. Some explanations for these events are related to biological, genetic, hormonal or environmental factors, such as the possible anti-inflammatory and neuroprotective effect of estrogens. However, the underlying molecular mechanisms have not yet been fully described. Our results show sex differences in gene expression, cell-cell communication and pathway activation in all major brain cell types, highlighting the presence of greater neuroinflammation in men and greater neurodegeneration in the SNpc in men, with the latter appearing to be inverted between sexes when observed in the cortical zone. Finally, we have made all the results available in a publicly accessible webtool, in order to allow the exploration of results to other researchers and to broaden the molecular-level understanding of PD sex differences.

Hyperalignment aligns individual brain activity and functional connectivity patterns to a common, high-dimensional model space, resolving idiosyncrasies in functional-anatomical correspondence and revealing shared information encoded in fine-grained spatial patterns. Given that the brain undergoes significant developmental and functional changes over the lifespan, it is likely that certain features in brain functional organization are more prominent in certain age groups than others. In this study, we examined whether age-specific functional templates, as compared to a canonical template, could enhance alignment accuracy across diverse age groups. We used the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) dataset (18 to 87 yo) to build age-specific templates and tested their performance for analyzing data in young and old brains in both the Cam-CAN dataset and the Dallas Lifespan Brain Study (DLBS) dataset (20 to 90 yo). We found the congruent age-specific template outperforms the incongruent template for various analyses, including inter-subject correlation of hyperaligned connectivity profiles and predicting individualized connectomes and brain responses to the movie using the template. The results are consistent across both datasets. This work enhances our understanding of age-related differences in brain function, highlights the benefits of creating age-specific templates to refine hyperalignment model performance, and may contribute to the development of age-sensitive diagnostic tools and interventions for neurological disorders.

The cortex generates diverse neural dynamics, ranging from broadband fluctuations to narrowband oscillations at specific frequencies. Here, we investigated whether broadband and oscillatory dynamics play different roles in the encoding and transmission of visual information. We used information-theoretical measures to dissociate neural signals sharing common information (i.e., redundancy) from signals encoding complementary information (i.e., synergy). We analyzed electrocorticography (ECoG) and local field potentials (LFP) in the visual cortex of human and non-human primates (macaque) to investigate the extent to which broadband signals (BB) and narrowband gamma (NBG) oscillations conveyed synergistic or redundant information about images. In both species, the information conveyed by BB signals was highly synergistic within and between visual areas. By contrast, the information carried by NBG was primarily redundant within and between the same visual areas. Finally, the information conveyed by BB signals emerged early after stimulus onset, while NBG sustained information at later time points. These results suggest a potential dual role of BB and NBG cortical dynamics in visual processing, with broadband dynamics supporting nonlinear pattern recognition and oscillations facilitating information maintenance across the cortex.

Dementia is a global public health challenge, with obesity emerging as an important modifiable risk factor. Here, we examined whether lifestyle interventions can mitigate the effects of diet-induced obesity on body weight, behaviour, and brain anatomy in mouse models. Using a longitudinal design, wild-type and triple-transgenic (3xTgAD) mouse models of Alzheimers disease were exposed to a high-fat diet and assigned to one of three interventions: voluntary physical activity, a low-fat diet, and their combination. A high-fat diet significantly increased body weight and induced widespread neuroanatomical changes, with effects modulated by sex and genotype. The combined intervention led to significant weight loss in males of both genotypes. Neuroanatomical analyses revealed that a high-fat diet significantly reduced hippocampal and cerebellar volumes in wild-type mice but had a less pronounced effect on 3xTgAD mice; nevertheless, interventions, particularly the combined approach, increased localized brain volumes in these regions regardless of genotype. Multivariate integration of behavioural and neuroanatomical measures identified a brain pattern linking hippocampal and cerebellar volumes to intervention and behavioural performance. Spatial gene enrichment analysis of this pattern identified biological processes, including glucose homeostasis, as potential biological mechanisms underlying intervention effects. Overall, these findings suggest that voluntary physical activity and a low-fat diet can modulate brain structure and behaviour, partially counteracting the effects of a high-fat diet, and potentially recruiting biological processes that may support brain health.

The retina provides a unique opportunity to develop a complete and precise model of a computational module in the central nervous system. Deep learning has recently vastly advanced efforts towards this goal, yet decades of data, code, and analysis practices remain fragmented between labs --- limiting reproducibility, comparison, and cumulative progress. We argue that an open, collaborative modelling ecosystem is now essential to move the field from isolated studies toward a unified, quantitative account of retinal computation. To this end, we present openretina, a modular Python package built on PyTorch that provides a standardised framework for training, evaluating, and interpreting neural network models of the retina. The package implements a shared "Core+Readout" model architecture with a reproducible training pipeline, a common data format based on HDF5, unified evaluation metrics, and in silico analysis techniques from the literature. In its initial release, openretina integrates five publicly available datasets spanning various species and recording modalities. For each dataset, we provide curated preprocessing, standardised data loaders, and pre-trained model checkpoints that serve as reproducible baselines for benchmarking new approaches. We demonstrate the platform's utility through example use cases: first, a gradient field analysis linking the instability of optimal stimuli to spatial contrast encoding in ON-OFF retinal ganglion cells; second, systematic benchmarking of architectures within and across datasets, revealing that substantial explainable variance remains uncaptured by current models. By making research tools interoperable across laboratories, openretina lays the groundwork for closing this gap collectively.

What neural events precede conscious reports? Hemisphere-asymmetric attentional networks are causally related to conscious perception (Bartolomeo et al., 2025; Kaufmann et al., 2024), but their spectrotemporal dynamics remain unclear. Here, we used magnetoencephalography to examine brain oscillations occurring in human participants (male and female) before a near-threshold target during the cue-target period. In 67% of trials, a supra-threshold visual cue appeared near the target placeholder box, indicating that the target would appear at that location (valid condition). In the remaining 33% of trials, the target appeared at the opposite location (invalid condition). We analyzed brain oscillations, coherence, and theta-gamma phase-amplitude (PAC) coupling in 18 regions of interest involved in attentional and perception (Martin-Signes et al., 2024). Results revealed that: (1) Report of validly cued targets was preceded by early ([~]58 ms post-cue) beta-band activity in the right-hemisphere superior parietal lobule. (2) Report of invalidly cued targets was preceded by late ([~]166 ms post-cue) beta-band activity in the right temporo-occipital (TO) region, PAC in the right lateral visual cortex, and low gamma coherence between this region and the left temporo-parietal junction, (3) Unreported invalidly cued targets were preceded by PAC in the right TO, and by high gamma coherence between this region and the right middle frontal gyrus suggesting a pre-target bias. We show that conscious report is preceded by temporally dissociable, frequency-specific reconfigurations of right-lateralized attentional networks, with an early parietal beta-mediated orienting window and a later ventral beta- and gamma-mediated window that predict conscious reports before target onset. Significance statementConscious perception depends not only on sensory signals, but also on how attentional networks prepare the brain in advance. Using MEG and a spatial cueing task with near-threshold targets, we show distinct right-hemisphere beta- and gamma-band dynamics predicting whether an upcoming stimulus will be reported or missed. Validly cued reports rely on early beta activity in the right superior parietal lobule, whereas invalid reports and omission errors are linked to later beta activity in the right temporo-occipital region, early theta-gamma coupling between this region and the right middle frontal gyrus, and theta-gamma phase-amplitude coupling. These findings reveal hemisphere-asymmetric spectrotemporal signatures by which attention biases predictive processing and shapes the conscious report of future stimuli, informing theories of conscious perception.

This article elucidates a methodological pitfall of cross-validation for evaluating predictive models applied to naturalistic neuroimaging data---namely, "stimulus-driven leakage." While this problem has been well known as "leakage in training examples" in machine learning, it may be difficult to detect in practice due to conventions in neuroscience. Stimulus-driven leakage can occur when predictive modelling is applied to data from a conventional neuroscientific design, characterized by a limited set of stimuli repeated across trials and/or participants. It results in spurious predictive performance due to overfitting to repeated signals, even in the presence of independent noise. Through comprehensive simulations and real-world examples, following a theoretical formulation, the article underscores how such data leakage can occur and how severely it can compromise results and conclusions when combined with widely spread informal reverse inference. The article concludes with practical recommendations for researchers to avoid stimulus-driven leakage in their experimental design and analysis.

Biophysical modeling provides mechanistic insights into brain function, spanning single-neuron dynamics to large-scale circuit models. These models are governed by biologically meaningful parameters, many of which can be experimentally measured. Some parameters are unknown, and optimizing them improves fit to experimental data, enhancing biological plausibility. However, existing methods require repeated, computationally expensive numerical integration of differential equations, limiting scalability to population-level datasets. Here, we introduce DELSSOME (DEep Learning for Surrogate Statistics Optimization in MEan field modeling), a framework that bypasses numerical integration by directly predicting whether parameter sets produce realistic brain dynamics. Across three large-scale circuit models, DELSSOME achieves a 1500-8000x speedup over numerical integration in predicting model realism. When embedded within an evolutionary optimization strategy, DELSSOME enables 50-100x faster parameter estimation without sacrificing agreement with numerical integration. Because of computational constraints, most studies simulate large-scale circuit models only at the group level. DELSSOME enables efficient individual-level optimization of the feedback inhibition control model. By collating 12,005 individuals across 14 datasets, we derive - for the first time - normative trajectories of cortical E/I ratio across the lifespan, revealing new insights into sex differences and network-specific patterns. This acceleration enables population-scale mechanistic modeling and unlocks new opportunities for understanding brain function.

Biophysical modeling provides mechanistic insights into brain function, spanning single-neuron dynamics to large-scale circuit models. These models are governed by biologically meaningful parameters, many of which can be experimentally measured. Some parameters are unknown, and optimizing them improves fit to experimental data, enhancing biological plausibility. However, existing methods require repeated, computationally expensive numerical integration of differential equations, limiting scalability to population-level datasets. Here, we introduce DELSSOME (DEep Learning for Surrogate Statistics Optimization in MEan field modeling), a framework that bypasses numerical integration by directly predicting whether parameter sets produce realistic brain dynamics. Across three large-scale circuit models, DELSSOME achieves a 1500-8000x speedup over numerical integration in predicting model realism. When embedded within an evolutionary optimization strategy, DELSSOME enables 50-100x faster parameter estimation without sacrificing agreement with numerical integration. Because of computational constraints, most studies simulate large-scale circuit models only at the group level. DELSSOME enables efficient individual-level optimization of the feedback inhibition control model. By collating 12,005 individuals across 14 datasets, we derive - for the first time - normative trajectories of cortical E/I ratio across the lifespan, revealing new insights into sex differences and network-specific patterns. This acceleration enables population-scale mechanistic modeling and unlocks new opportunities for understanding brain function.

Visible light is widely used in neuroscience, yet its direct effects on neuronal activity in the absence of optogenetic manipulation remain incompletely understood. Here, we investigated whether light stimulation can induce sustained changes in neuronal excitability. Using ex vivo electrophysiological recordings, we show that repeated pulses of blue light (5 s, 430-495 nm, 19 mW) produce a robust and persistent reduction in evoked firing activity in cortical neurons from both male and female mice, with an average decrease of [~]60% relative to baseline. This inhibitory effect persisted for more than 20 minutes following stimulation and was associated with changes in both passive membrane properties and active ion channel conductance. In human cortical neurons, responses were more heterogeneous. While a subset of neurons exhibited similar inhibitory effects, others showed increased excitability, with this response occurring more frequently in neurons from female patients, suggesting a potential sex-dependent effect. In addition, a transient depolarizing response to light was observed in a minority of human neurons but not in mice. These findings indicate that visible light, independently of exogenous opsins, can induce long-lasting modulation of neuronal activity without evidence of acute cytotoxicity under the conditions tested. This raises the possibility that visible light may provide a previously underappreciated, opsin-independent mechanism for modulating neuronal activity, with potential relevance for disorders characterized by neuronal hyperexcitability. We outline a framework for future investigations, including validation in human systems, in vivo studies, optimization of stimulation parameters, and assessment of therapeutic potential in pathological models.

Most purposeful movements require the coordinated control of both hands, yet motor adaptation studies rely on highly constrained tasks that bear little resemblance to everyday bimanual actions. Here, we investigated how task demands shape control strategies during adaptation in a naturalistic bimanual object manipulation task. We tested 73 participants who lifted a virtual plate while we systematically distorted visual feedback of their right hand's movement, creating a sensory conflict between arms. Compared to unimanual, bimanual lifting shifted learning away from feedforward adaptation toward use of feedback control--participants moved more slowly with gradual speed scaling, developed compensatory hand adjustments, and showed smaller aftereffects. Relaxing precision demands improved success and reduced feedback reliance, while minimizing interlimb sensory conflict diminished compensatory adjustments and restored plate aftereffects to unimanual levels. Bimanual contexts create distinct learning environments where precision demands and interlimb sensory conflict independently shape control strategy; this may inform bimanual training protocols.

Excitatory synaptic scaling regulates network dynamics by proportionally adjusting excitatory synaptic strengths after sensory perturbations. During associative learning, blocking excitatory scaling in conditioned taste aversion paradigms prolongs generalized aversive responses and delays memory specificity. Recent evidence also implicates inhibitory synaptic scaling in the regulation of network dynamics. Specifically, parvalbumin (PV)-expressing inhibitory neurons, targeting perisomatic regions of excitatory (E) pyramidal neurons, and somatostatin (SST)-expressing neurons, targeting distal dendrites, exhibit distinct scaling responses. This leaves open the question of how complex plasticity mechanisms regulate recurrent excitatory-inhibitory circuit dynamics in associative learning. Using computational approaches, we demonstrate that Hebbian plasticity drives memory generalization to novel stimuli not presented during conditioning. Following conditioning, diverse synaptic scaling mechanisms progressively induce memory specificity, which can be regulated by top-down inputs. Our results reveal that, in the absence of excitatory scaling, PV-to-E scaling can effectively compensate and rescue memory specificity, highlighting the presence of degenerate mechanisms in the brain. Notably, in the process of establishing memory specificity, excitatory scaling and PV-to-E scaling function synergistically, while concurrently opposing SST-to-E scaling. The synergistic and antagonistic plasticity mechanisms are orchestrated to shape the temporal evolution of memory representations, from generalized to precise. Significance statementAssociative learning is a fundamental brain function that allows us to link experiences, adapt behavior, and form lasting memories. During this process, memory representations are shaped by synaptic scaling, a homeostatic plasticity mechanism that provides slow, negative feedback to regulate synaptic strengths and adjust network excitability. Operating at the synapses of diverse excitatory and inhibitory cell types, multiple forms of homeostatic plasticity influence the dynamics of associative learning. Here, we demonstrate that synergistic and antagonistic cell-type-specific synaptic scaling mechanisms operate at different types of inhibitory synapses to jointly govern the temporal evolution of memory representations. Through their interaction, they guide the transition from generalized to precise memories.

Homeostatic plasticity preserves neuronal activity against perturbations. Recently, somatic action potential broadening was proposed as a key homeostatic adaptation to chronic inactivity in neocortical neurons. Since action potential shape critically controls calcium entry and neuronal function, broadening provides an attractive homeostatic feedback mechanism to regulate activity. Here, we report that chronic inactivity induced by sodium channel block does not broaden action potentials in neocortical neurons under a wide range of conditions. In contrast, action potentials were broadened in CA3 neurons of organotypic hippocampal cultures by chronic sodium channel block and in hippocampal dissociated cultures by chronic synaptic block. Mechanistically, BK-type potassium channels were proposed to underly inactivity-induced action potential broadening. However, BK channels did not affect action potential duration in our recordings. Our results indicate that action potential broadening can occur in specific neurons and conditions but is not a general mechanism of homeostatic plasticity in cultured neurons.

Whether the primary visual cortex (V1) is essential for visual working memory (vWM) remains a topic of scientific debate. The current study expanded upon previous findings by examining whether idiosyncratic architectural properties of V1, particularly those underlying visual field inhomogeneities such as polar angle asymmetries, predict interindividual differences in vWM performance. A total of 292 participants underwent quantitative MRI (qMRI) using a multiparametric mapping sequence to generate four microstructural maps per participant: magnetization transfer (MT), proton density (PD), longitudinal relaxation rate (R1), and transverse relaxation rate (R2*). In a separate session, the participants completed a vWM task designed to probe visual field inhomogeneities. Behavioral results are consistent with previously reported asymmetries in vWM, particularly the inverted polarity of the vertical meridian asymmetry (VMA). Quantitative MRI analysis revealed significant associations between VMA and multiple qMRI parameters within V1, indicating that V1 microarchitecture contributes to variability in vWM performance. Additionally, cortical thickness measures linked V3 to left-right asymmetry, suggesting that structural variability in the early visual cortex beyond V1 also shapes vWM performance. These findings are consistent with the sensory recruitment hypothesis and demonstrate that fine-grained architectural characteristics of early visual areas constrain vWM performance.

AO_SCPLOWBSTRACTC_SCPLOWTemporal lobe epilepsy (TLE), the most common pharmaco-resistant epilepsy in adults, has been linked to structural brain changes extending beyond the mesiotemporal areas. While not traditionally viewed as a neurodegenerative disorder, recent ex-vivo studies have shown elevated levels of misfolded tau protein in TLE. This study investigated tau deposition in TLE patients using the in-vivo PET tracer [18F]MK-6240 combined with ex vivo tau immunohistochemistry (IHC). We studied 28 TLE patients and 28 healthy controls to assess tau uptake and its relationship with brain connectivity, clinical variables, and cognitive function alongside post-surgical tissue from a subset of patients. Compared to controls, TLE patients exhibited markedly increased [18F]MK-6240 uptake in bilateral superior and medial temporal regions and the parietal cortex, with tau accumulation following regional functional and structural connectivity and cognitive impairment. IHC revealed phosphorylated tau in 6/7 cases, including subpial, neuritic, and neuronal inclusions. These findings suggest that tau accumulation contributes to cognitive decline observed in TLE, supporting a potential role of tau in epilepsy-related neurodegeneration.

Hirschsprung disease (HSCR) is a deadly congenital disorder where the enteric nervous system (ENS) is absent from the distal bowel. Current surgical treatment is generally life-saving but is often accompanied by long-term bowel problems and comorbidities. As alternative, we are developing a regenerative therapy based on rectal administration of Glial cell-derived neurotrophic factor (GDNF). We previously showed that administering GDNF enemas to HSCR mice soon after birth is sufficient to permanently induce a new ENS from tissue-resident neural progenitors. Here, we elucidate the underlying mechanism using single-cell transcriptomics, signal transduction inhibitors and genetic cell lineage tracing tools. We found that the neurogenic effect of GDNF is mediated by NCAM1 (Neural cell adhesion molecule 1), rather than by its canonical signaling receptor RET (Rearranged during transfection). We also unveiled the existence of multiple neuronal differentiation pathways that involve a larger than expected repertoire of tissue-resident neural progenitors, including a surprising one not derived from the usual neural crest. These data support feasibility of GDNF-based therapy in most human patients, even those bearing a RET variant. This work also has far-reaching implications for the choice of ENS progenitor source to use when developing cell transplantation-based therapeutic approaches.

Different situations may require radically different information updating speeds (i.e., learning rates). Some demand fast learning rates, while others benefit from using slower ones. To adjust learning rates, people could rely on either global, meta-learned differences between environments, or faster but transient adaptations to locally experienced prediction errors. Here, we introduce a new paradigm that allows researchers to measure and empirically disentangle both forms of adaptations. Participants performed short blocks of trials of a continuous estimation task (fishing for crabs) on six different islands that required different optimal (initial) learning rates. Across two experiments, participants showed fast adaptations in learning rate within a block. Critically, participants also learned global environment-specific learning rates over the time course of the experiment, as evidenced by computational modelling and by the learning rates calculated on the very first trial when revisiting an environment (i.e., unconfounded by transient adaptations). Using representational similarity analyses of fMRI data, we found that differences in voxel pattern responses in the central orbitofrontal cortex correlated with differences in these global environment-specific learning rates. Our findings show that humans adapt learning rates at both slow and fast time scales, and that the central orbitofrontal cortex may support meta-learning by representing environment-specific task-relevant features such as learning rates.

Single-neuron morphology mapping is fundamental for deciphering brain architecture and function, yet in vertebrates it remains limited in spatial coverage and cell-type information. Here we present a nervous system-wide single-neuron morphology atlas of larval zebrafish with annotated excitatory/inhibitory identity and dendrite-axon polarity. The atlas comprises >20,000 reconstructed neurons from >13,400 animals, spanning the central and peripheral nervous system and representing [~]24.5% of the total excitatory and inhibitory neurons in the brain, all integrated into a common physical space with neuroanatomical parcellations. We define >500 excitatory and inhibitory neuronal morphotypes and construct putative inter-cell-type and interregional connectomes. Projection and morphotype analyses reveal distinct laterality and directionality biases and modular innervation patterns in excitatory and inhibitory neurons, while network analyses uncover fundamental connectivity motifs, hubs, and sensorimotor pathways. Accessible through custom-built interactive platform ZExplorer, this atlas provides a foundational resource for multimodal data integration, circuit analysis, computational modeling, and hypothesis-driven research.

Multiple lines of research have studied how complex brain dynamics emerge from underlying connectivity by using Ising models as simplified neural mass models. However, limitations on parameter estimation have prevented their use with individual, high-resolution human neuroimaging data. Furthermore, most studies focus only on connectivity, ignoring node heterogeneity, even though real brain regions have different structural and dynamical properties. Here we present an improved approach to fitting Ising models to 360-region functional MRI data: derivation of an initial guess model from group data, optimization of simulation temperature, and two stages of Boltzmann learning, first with group data, then with individual data. Our implementation uses GPU acceleration to mitigate the high computational cost of this approach. We then analyze how data binarization threshold affects goodness-of-fit, the role of the external field in model behavior, consistency among models fitted to different scans of the same individual, and correlations between model parameters and features from structural MRI, including measures of myelination and cortical folding. We find that binarizing fMRI data at higher thresholds decreases correlation between model and data functional connectivity but increases the heterogeneity of node external fields and their correlations with structural features. A choice of threshold that achieves both goodness-of-fit and intrinsic heterogeneity of regions results in a model that better reflects the reality of the brain as a network of intrinsically heterogeneous nodes. By enabling personalized, biophysically interpretable modeling of structure-function mapping across the whole brain, this approach can aid understanding of individual differences in brain network organization and bridge the gap between the network-focused methodology of connectomics and the region-focused paradigm typical of translational research.

Single-cell transcriptomics has uncovered the vast heterogeneity of cell types that compose each region of the mammalian brain, but describing how such diverse types connect to form functional circuits has remained challenging. Current methods for measuring the presence and strength of synaptic connections principally rely on low-throughput whole-cell recording approaches. However, the development of optical tools for perturbing and observing neural activity - now notably including genetically encoded voltage indicators - presents an exciting opportunity to vastly increase the throughput of physiological connectivity mapping. Here, we combine massively parallel optical measurements of synaptic strength with a novel pipeline for thick-tissue spatial transcriptomics to assay synaptic connectivity motifs with high sensitivity, high throughput, and cell-type specificity. We apply this approach in the motor cortex to describe new cell-type-specific synaptic innervation patterns for long-range thalamic and contralateral input onto more than 1000 motor cortical neurons.

Endoplasmic reticulum (ER) stress contributes to the pathogenesis of neurodegenerative and age-associated diseases, motivating the search for compounds that enhance ER-stress resilience. Modulation of ER-redox pathways, including those associated with the oxidase ERO1A, can attenuate maladaptive unfolded protein response (UPR) signaling and improve cellular stress tolerance. Here we developed an integrative discovery strategy to identify natural compounds that mitigate ER-stress-associated phenotypes across cellular and organismal models. Structure-informed virtual screening guided by ERO1A biology prioritized the pyrazolopyridine alkaloid S88. In human SH-SY5Y-derived neurons, S88 improved survival and reduced tunicamycin-induced ER-stress markers. In Drosophila, S88 ameliorated neuromuscular and locomotor phenotypes in a UBQLN2-associated ALS model and improved aging-related outcomes. Biochemical assays did not detect inhibition of ERO1A or radical scavenging activity by S88, indicating that its molecular target remains to be identified. Together, these findings identify S88 as a natural-product scaffold that enhances ER-stress resilience across neuronal and in vivo models. Graphical abstract Structure-informed screening guided by ERO1A prioritized five natural products for functional validation across cellular and Drosophila models. The pyrazolopyridine alkaloid S88 consistently reduced ER-stress markers, improved neuronal survival, rescued locomotor and neuromuscular defects in an ALS model, and ameliorated aging phenotypes. The direct molecular target of S88 remains to be defined. Generated with assistance from the AI-based visualization tool NotebookLM and refined by the authors. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=185 SRC="FIGDIR/small/664722v2_ufig1.gif" ALT="Figure 1"> View larger version (104K): org.highwire.dtl.DTLVardef@8b97c0org.highwire.dtl.DTLVardef@97de54org.highwire.dtl.DTLVardef@857ce6org.highwire.dtl.DTLVardef@1cb1398_HPS_FORMAT_FIGEXP M_FIG C_FIG

The sensory/neural Temporal Sampling (TS) theory of developmental language disorder (DLD) is based on the sensory and linguistic impairments in rhythm processing that are found in children with both developmental dyslexia (DD) and DLD. These sensory/linguistic impairments include decreased sensitivity to amplitude rise times (ARTs, the sensory triggers related to automatic cortical speech tracking), syllable stress patterns and speech rhythm. At the neural level TS theory predicts impairments in the cortical tracking of different rates of amplitude modulation (AM) in the speech signal <10Hz. To date, the accuracy of low-frequency cortical tracking in natural continuous speech has not been measured in children with DLD. Here, EEG was recorded during story listening from children with and without DLD aged around 9 years, and decoding analyses in the delta, theta and alpha (control) bands were carried out. EEG power was computed in the delta, theta and gamma bands, and phase-amplitude coupling and phase-phase coupling (PAC, PPC) were also computed between bands. Whole-brain analyses showed that the accuracy of low-frequency decoding (delta, theta) did not differ between groups. However, region-specific analyses revealed significantly reduced delta-band speech tracking in the right temporal cortex in the children with DLD. PAC and PPC dynamics did not differ between groups. The data suggest that low-frequency cortical tracking impairments in DLD may be spatially constrained to the right hemisphere rather than globally present as in DD. The data are discussed using TS theory. HighlightsO_LICortical tracking of natural speech is measured in children with and without DLD C_LIO_LIDelta-band tracking is impaired in right temporal regions in children with DLD C_LIO_LICross-frequency coupling dynamics (PAC, PPC) did not differ between groups C_LI

Color discrimination thresholds--the smallest detectable color differences--provide a benchmark for models of color vision, enable quantitative evaluation of eye diseases, and inform the design of display technologies. Despite their importance, a comprehensive characterization of these thresholds has long been considered intractable due to the psychophysical curse of dimensionality. Here, we address this challenge using a novel semi-parametric Wishart Process Psychophysical Model (WPPM), which leverages the feature that the internal noise limiting color discrimination varies smoothly across stimulus space. The model was fit to data collected with a non-parametric adaptive trial-placement procedure, enabling efficient stimulus selection. Together, through the combination of adaptive trial placement and post hoc WPPM fitting, we achieved a comprehensive characterization of color discrimination in the isoluminant plane with only [~]6,000 trials per participant (N = 8). Once fit, the WPPM allows readouts of discrimination performance for any stimulus pair. We validated these readouts against 25 probe psychometric functions, measured with an additional 6,000 trials per participant held out from model fitting. In conclusion, our study provides a foundational dataset for color vision, and our approach generalizes beyond color to any domain in which the internal noise limiting performance varies smoothly across stimulus space, offering a powerful and efficient method for comprehensively characterizing various perceptual discrimination thresholds.

Psilocybin has profound therapeutic potential for various mental health disorders, but its mechanisms of action are unknown. Functional MRI studies have reported the effects of psilocybin on brain activity and connectivity; however, these measurements rely on neurovascular coupling to infer neural activity changes and assume that blood flow responses to neural activity are not altered by psilocybin. Using two-photon excited fluorescence imaging in the visual cortex of awake mice to simultaneously measure neural activity and capillary blood flow dynamics, we found that psilocybin administration prolonged the increase in visual stimulus-evoked capillary blood flow - an effect which was reduced by pretreatment with a 5-HT2AR antagonist - despite not causing changes in the stimulus-evoked neural response. Multi-modal widefield imaging also showed that psilocybin extends the stimulus-evoked vascular responses in surface vessels with no observed effect on the population neural response. Computational simulation with a whole-brain neural mass model showed that prolonged neurovascular coupling responses can lead to spurious increases in BOLD-based measures of functional connectivity. Together, these findings demonstrate that psilocybin broadens neurovascular responses in the brain and highlights the importance of accounting for these effects when interpreting human neuroimaging data of psychedelic drug action.

Functional asymmetries in the medial prefrontal cortex (mPFC) are significant attributes of this brain area, implicated in its role in emotional processing and executive function. Evidence suggests that, under normal conditions, there is a tonic inhibition of the right (R) mPFC by the left (L) mPFC, and a dysregulation of this hemispheric functional lateralization is implicated in detrimental chronic stress effects. Considering the wide interhemispheric connection and the inhibitory tone from the LmPFC to the RmPFC, we hypothesize that alterations in the activity of the direct projections between the mPFC hemispheres during stressful situations are related to stress vulnerability. To address this question, we used a chemogenetic approach to modulate the activity of L-to-R dorsomedial prefrontal cortex (dmPFC) monosynaptic projections during psychosocial stress (PSS) exposure in mice. We found that activating LdmPFC projections during a repeated PSS protocol prevents stress-induced apathy-like behavior in females and males and social avoidance in male mice. On the other hand, inhibiting such projections during a single session of PSS increases vulnerability to stress effects in male mice, increasing social avoidance and anxiety-like behaviors. Both glutamatergic and GABAergic cells compose the projecting interhemispheric neurons in the dmPFC. However, the LdmPFC showed a higher density of glutamatergic projections to the RdmPFC than the opposite. In conclusion, our results revealed an involvement of the monosynaptic projections from the LdmPFC to RdmPFC in the vulnerability to the behavioral alterations induced by PSS in female and male mice.

The anterior temporal lobes (ATLs) are known to support semantic cognition, but theories about their precise representational coding vary. We collected 7T-fMRI data with a novel acquisition sequence designed to improve signal quality in the ATLs, then employed a pioneering analytical approach (comparative multivariate decoding) to adjudicate between theories. Specifically, we applied multiple decoding methods, each making different assumptions about the content, nature or location of representations within the ATLs, then used the pattern of results across methods to adjudicate competing hypotheses. The results suggest that the ATLs represent domain-general semantic information via a multidimensional vector-space code that is anatomically clustered within and across individuals, and that posterior temporal and occipitotemporal regions utilize a similar domain-general, vector-space code. More generally, the comparative multivariate analytical framework utilized here has the potential to reveal how the brain represents, not just semantic knowledge, but any kind of information.

The end-stage pathology of Parkinson's disease (PD) involves the loss of dopamine-producing neurons in the substantia nigra pars compacta (SNc). However, synaptic deregulation of these neurons begins much earlier. Understanding the mechanisms behind synaptic deficits is crucial for early therapeutic intervention, yet these remain largely unknown. In the SNc, different dopamine neuron subtypes show varying susceptibility patterns to PD, complicating our understanding. This study uses intersectional genetic mouse models to uncover synaptic perturbations in vulnerable dopamine neurons, focusing on the LRRK2 kinase, a protein closely linked to PD. Through a combination of immunofluorescence and advanced proximity labeling methods, we found higher LRRK2 expression in the most vulnerable dopamine neuron subclusters. High-resolution imaging revealed that pathogenic LRRK2 disrupts release sites in vulnerable dopamine axons, leading to decreased in vivo evoked striatal dopamine release in mice with LRRK2 mutations. Proteomic and biochemical analyses indicate that mutant LRRK2 increases the phosphorylation of RAB3 proteins, reducing their interactions with RIM1/2 effector proteins and impacting their synaptic functions. Overall, this research highlights the cell-autonomous dysfunctions caused by mutant LRRK2 in the neurons that are primarily affected by the disease. It also provides a framework for therapeutic strategies for early nigrostriatal synaptic deficits in PD.

Despite its profound influence on human emotion and memory, and its critical importance in animal behaviour, olfaction has historically been understudied compared to other sensory modalities. Contributing to this relative neglect may be challenges inherent to odour delivery: unlike visual or auditory stimuli, odorants must be vaporised, transported, and actively cleared, requiring specialised equipment and creating temporal delays and contamination risks. While commercial olfactometers provide reliable solutions, they can be expensive and, due to proprietary software, may be difficult to customise. Existing custom designs, though excellent, often require specialized technical skills and/or access to engineering workshops. Thus, to help widen access to well-controlled odour delivery, we developed a low-cost, fully open-source olfactometer that can be assembled without specialised facilities or engineering skills and customised according to experimental needs. Our design prioritises affordability, accessibility, and versatility while maintaining temporal precision and stimulus control across applications from rodent behaviour to human psychophysics. This methods articles provides full design specifications, assembly details, and behavioural validation across both rodents and humans with the aim of reducing barriers and enabling more laboratories to study this crucial sensory system.

Dendritic spine dysfunction may contribute to the etiology and symptom expression of neuropsychiatric disorders. The intimate relationship between spine morphology and function suggests that decoding disease-related abnormalities from spine morphology can aid in developing synapse-targeted interventions. Here, we describe a population analysis of dendritic spine nanostructure applied to the objective grouping of multiple mouse models of neuropsychiatric disorders. This method has identified two major groups of spine phenotypes linked to schizophrenia and autism spectrum disorder (ASD). An increase in spine subpopulation with small volumes characterized the spines of schizophrenia-associated mouse models, whereas a spine subset with large volumes increased in ASD models. Schizophrenia-associated mouse models showed higher similarity in spine morphology, driven by reduced size and growth of nascent spines. The expression of Ecrg4, a gene encoding small secretory peptides, was increased in schizophrenia-associated mouse models, and functional studies confirmed its critical involvement in impaired spine dynamics and shape. These results suggest that population-level spine analysis provides rich insights into heterogeneous spine pathology, facilitating the identification of new molecular targets related to core synaptic dysfunction.

Binocular vision fuses compatible inputs from the two eyes into a single percept, whereas incompatible inputs can produce rivalry, lustre, or diplopia. We measured neural responses to binocular stimuli with different phase relationships to test predictions from contemporary binocular combination models. Steady-State Visually Evoked Potentials (SSVEPs) were recorded from 15 observers in response to monocular and binocular stimulation at 3 Hz, using either On/Off or counterphase flicker with varied spatial and temporal phase relationships. On/Off flicker elicited responses at the fundamental frequency (3 Hz), and its integer harmonics, while counterphase flicker generated responses at the even integer harmonics (6Hz, 12Hz, 18Hz). Manipulating phase relationships modulated these response patterns, including a reduction in the fundamental amplitude for On/Off flicker. The data were modelled with a series of binocular combination algorithms, ranging in complexity from a simple linear sum to a two-stage binocular gain-control model with parallel monocular and binocular phase-selective channels. The model required parallel monocular channels to account for our data, whereas phase selectivity was not essential. Overall, the two-stage contrast gain-control model remains a powerful and flexible framework for describing binocular combinations across various experimental conditions and modalities.

Amplitude-modulation (AM) is critical for the perception of complex sounds, and transformations in AM encoding may underlie primate-specific aspects of complex sound perception. The nonhuman primate model provides an opportunity to understand what circuit mechanisms generate hierarchical and interhemispheric transformations of AM encoding in different circuits across the cortical hierarchy. To address this, here we report the encoding of AM signals as a function of cortical layer and hemisphere in primary area A1 and the tertiary parabelt (PB) area of five NHPs. We presented AM noise and click trains to awake NHPs while recording from linear array multielectrodes spanning cortical layers. A1 typically encoded all AM frequencies (1.6-200 Hz) with high ( > 90%) classification accuracy, while the PB encoded lower (~1.6-25 Hz) frequencies. The laminar gradient observed in A1 (Granular > Infragranular > Supragranular was inverted in PB (Supragranular > Infragranular > Granular), consistent with differences in thalamocortical input. Both areas displayed enhanced AM encoding in the left hemisphere, restricted to the supragranular layers. These results represent the first analysis of AM encoding in the PB, in which we identify circuits differing in their temporal sensitivity across the hierarchy, and suggest local supragranular neuronal populations contribute to hemispheric specialization.

Arousal is essential for survival, and maladaptive arousal processing leads to an inability to focus, anxiety-like behavior, and dysregulated affective states. Norepinephrine (NE) is known to regulate anxiety, arousal, and learning through locus coeruleus (LC) projections throughout the brain. Evidence for co-release of the NE precursor and neurotransmitter dopamine (DA) from LC neurons has been accumulating for years, yet definitive measures of DA release across regions, stimulus paradigms, and behaviors associated with the LC-NE system remain controversial. Here, we identified the physiological and behavioral properties that evoke DA release from LC axon terminals. Using concomitant approaches, we inhibited the LC and ventral tegmental area (VTA) to selectively isolate the contributions of LC-derived DA release. Together these findings establish the constraints by which LC neurons release DA in a modality-dependent manner.

A substantial fraction of amyotrophic lateral sclerosis (ALS)-associated proteins remain poorly characterized, in part because of the limited availability of validated research antibodies. We established knockout (KO)-based antibody characterization workflows and demonstrated that widely used antibodies against the major ALS-associated protein C9orf72 lacked specificity (Laflamme et al., 2019). We subsequently scaled this framework to systematically benchmark research antibodies, revealing that up to 61% fail to perform as recommended by manufacturers (Ayoubi et al., 2023). Here, we extend this approach by establishing the ALS-Reproducible Antibody Platform (ALS-RAP), a comprehensive effort to generate a publicly available dataset of KO-validated antibodies targeting proteins encoded by ALS risk genes. In total, we characterized 303 antibodies against 33 ALS-associated proteins to identify high-quality reagents for use in western blot, immunoprecipitation, and immunofluorescence. Using these antibodies, we profiled protein levels across human induced pluripotent stem cell (iPSC)-derived and primary neurological cell types. These analyses revealed diverse cellular distributions and higher levels of several ALS-associated proteins in glial populations, consistent with emerging evidence for immune contributions to ALS. Together, ALS-RAP provides a validated antibody toolbox and protein expression resource to support the study of ALS-associated proteins.

Decades of studies implicating GluN3A N-methyl-D-aspartate receptor (NMDAR) subunits in physiological and pathological function have largely been interpreted through direct regulation of conventional glutamatergic NMDARs. However, emerging evidence indicates that GluN3A frequently assembles with GluN1 forming unconventional glutamate-insensitive NMDARs that operate as native excitatory glycine receptors (eGlyRs). Here we demonstrate that hippocampal somatostatin and neurogliaform interneurons (Sst-INs and NGFCs) express functional eGlyRs from early postnatal through adult ages. In the developing hippocampus eGlyR-mediated excitation of NGFCs with ambient glycine dramatically increases GABAergic tone, with consequences for the generation of giant depolarizing potentials (GDPs). In the mature hippocampus, eGlyR- mediated excitation of Sst-INs regulates sharp wave ripples (SWRs). Finally, we reveal evolutionary conservation of hippocampal Sst-IN eGlyRs and eGlyR- mediated SWR regulation in non-human primates confirming functional eGlyR availability for therapeutic potential in higher species. Our findings underscore that eGlyR mediated regulation of cell and circuit excitability through both cell autonomous and cell non-autonomous mechanisms must be considered to understand GluN3A roles in brain development, plasticity, and disease.

The brains representations are encoded in the collective activity of neural populations, whose non-monotonic tuning properties define the population code. Adaptive behavior calls for flexible retuning of this code as stimuli statistics change across contexts. Yet whether and how such adaptation occurs is unknown. Using fMRI during a numerosity-estimation task with variable number ranges, we show that number representations in human parietal cortex dynamically recalibrate to context, enabling context-sensitive behavioral accuracy. The tuning properties of neural populations collectively shift and rescale with the range. This distributed range adaptation achieves efficient coding in real time: neural precision scales with the range and predicts corresponding changes in behavioral precision. Individuals with stronger neural adaptation show larger behavioral adjustments. These findings extend static sensory efficient coding to adaptive representations of abstract magnitudes. Such flexible population tuning may constitute a canonical mechanism of encoding networks that enables the brain to sustain precise, adaptive behavior.

Synaptic neurotransmission imposes high demands on membrane turnover, metabolism, and the remodeling of presynaptic molecular composition. While the impact of autophagy on neurotransmission has been firmly established, evidence for activity-dependent synaptic induction of autophagy remains surprisingly limited. Here, we demonstrate that amphisomes containing BDNF/TrkB are formed at presynaptic boutons following sustained synaptic activation. Activity-dependent bulk endocytosis serves as a membrane source for amphisome biogenesis, while key autophagy proteins are recruited to the active zone, and autophagy initiation is triggered locally by the energy-sensing kinase AMPK. BDNF/TrkB-containing amphisomes contribute to the turnover of key presynaptic cytoskeletal proteins involved in synaptic vesicle clustering. The formation of amphisomes following sustained synaptic activity facilitates both the degradation of these proteins and their replenishment through local translation of their mRNAs at presynaptic boutons. We propose that activity-induced synaptic autophagy largely reflects amphisome formation, which in turn is required for the replacement of proteins within the local presynaptic cytomatrix.

Alpha-band neural oscillations (8-13 Hz) are theorized to phasically inhibit visual processing based, in part, on results showing that pre-stimulus alpha phase predicts detection (i.e., hit rates). However, recent failures to replicate and a lack of a mechanistic understanding regarding how alpha impacts detection have called this theory into question. We recorded EEG while six observers (6,020 trials each) detected near-threshold Gabor targets embedded in noise. Using signal detection theory (SDT) and reverse correlation, we observed an effect of occipital and frontal pre-stimulus alpha phase on sensitivity (d), not criterion. Hit and false alarm rates were counterphased, consistent with a reduction in internal noise during optimal alpha phases. Perceptual reports were also more consistent when two identical stimuli were presented during the optimal phase, suggesting a decrease in internal noise rather than signal amplification. Classification images revealed sharper spatial frequency and orientation tuning during the optimal alpha phase, implying that alpha phase shapes sensitivity by modulating sensory tuning towards relevant stimulus features.

During sustained activity, voltage-gated sodium (Nav) channels enter a slow-inactivated state to limit cellular hyperexcitability. Disruption of this regulatory process has been implicated in skeletal, cardiac and neurological disorders. While the kinetics of this process are well characterized, its endogenous modulators remain unclear. Here, we identify Proline-Rich Transmembrane Protein 2 (PRRT2) as a native regulator of Nav channel slow inactivation. We show that PRRT2 facilitates the entry of Nav channels into the slow-inactivated state and delays their recovery, a regulatory effect conserved from zebrafish to humans. PRRT2 forms molecular complexes with Nav channels both in vitro and in vivo. In the mouse cortex, PRRT2 deficiency impairs the slow inactivation of Nav channels in neuronal axons, leading to reduced cortical resilience in response to hyperexcitable challenges. Together, these findings establish PRRT2 as a physiological modulator of Nav channel slow inactivation and reveal a mechanism that supports cortical resilience to pathological perturbations.

Understanding the brain requires integrating molecular, structural, and functional information across multiple scales. Despite the rapid expansion of multimodal, multiscale brain atlases in various species, integrative analysis remains challenging. Here, we present iBrAVE, an open-source platform for 3D interactive, integrative analysis of brain atlas datasets across modalities and scales within a common reference space. iBrAVE unifies heterogeneous datasets into five core representations, enabling source-independent analyses from insects to primates. At the single-modality level, it features spatially resolved quantification, as exemplified by single-neuron morphology analyses spanning geometry, topology, projection, clustering, and putative wiring. Across modalities, it links gene expression and neuronal activity with morphologically defined neurons and putative circuits via establishing spatial correspondence. Across scales, it enables bidirectional inference of neuronal identity and synaptic connectivity between light- and electron-microscopy reconstructions via neuronal morphology matching. Thus, iBrAVE provides a unified framework for integrative brain atlas analyses, facilitating data-driven discovery in neuroscience.

Brain-derived neurotrophic factor (BDNF) promotes neuronal plasticity through retrograde signaling from axon terminals to the nucleus, activating CREB-dependent transcription. While this relies on signaling endosomes, the molecular mechanisms enabling their axonal transport remain poorly understood. Using compartmentalized cultures of mouse cortical neurons, we show that axonal BDNF activates mTOR signaling and stimulates local protein synthesis. Translation inhibitors blocked both BDNF-enhanced retrograde transport and nuclear CREB phosphorylation, indicating that axonal protein synthesis is required for long-distance signaling. Among locally synthesized proteins, we identified Rab5, a master regulator of endosomal trafficking. BDNF increased axonal Rab5 levels through TrkB- and mTOR-dependent mechanisms, confirmed by puromycin-PLA for Rab5 and soma-free axon preparations. Axon-specific Rab5 knockdown abolished BDNF-induced retrograde transport and CREB activation, demonstrating that local axonal translation of Rab5 mRNA is essential for neurotrophin signaling propagation. Remarkably, even basal retrograde transport depended on ongoing axonal Rab5 synthesis, revealing a constitutive role for local translation in maintaining axonal trafficking capacity. These findings establish that local axonal translation of trafficking regulators is a prerequisite for axon-to-nucleus neurotrophin signaling, positioning on-demand protein synthesis as a central node in long-distance neuronal communication.

Adolescence is a window of heightened vulnerability to the neurotoxic effects of binge ethanol exposure. Adolescent intermittent ethanol (AIE) exposure has been shown to induce long lasting cognitive and behavioral impairments in patients and rodent models that increase the risk of developing alcohol use disorder (AUD). Our previous work shows that these behavioral deficits coincide with persistent dysfunction of astrocytes. Here, we aim to understand how astrocyte synaptic structural and functional crosstalk are disrupted following AIE to provide better mechanistic understanding of why behavioral impairments persist into adulthood. Male Sprague Dawley rats received AIE, a variety of adeno-associated viruses encoding astrocyte specific sensors, and fiber implantation in the dorsal hippocampal (dHipp) for in vivo photometry. A subset of rats received hM3D(Gq) to chemogenetically activate astrocytes. Following AIE and a forced abstinence period that allowed growth into adulthood, rats underwent assessment in the contextual fear conditioning (CFC) task with simultaneous fiber photometry recordings. By combining immunohistochemistry (IHC), Stimulated Emission Depletion (STED) microscopy, fiber photometry, chemogenetics, and slice physiology, we show that AIE induces structural and functional decoupling of astrocytes from synapses and astrocyte dysregulation that persists into adulthood. Remarkably, stimulating astrocytic calcium signaling via chemogenetic activation attenuates heightened fear responding and restores gliotransmitter availability. These findings highlight a critical role for astrocyte synaptic crosstalk in regulating fear learning and underscore the untapped therapeutic potential of targeting astrocytes to improve behavioral outcomes following substance use.

Notch filters can alter color contrasts by selectively filtering different spectral bands of the stimulus and have been developed to enhance reddish-greenish contrasts for color-deficient observers with anomalous trichromacy. We examined the effects of such filters on color salience for normal trichromats, using a visual search paradigm where the task was to locate a color target superimposed on a variegated chromatic background, similar to foraging for fruits among foliage. Background colors varied along a bluish-yellowish or purpliish to yellow-green (short-wave cone isolating) axis, roughly spanning the range of dominant color variations in arid or lush environments. Target colors sampled a wide range of hue angles and contrasts. Testing was conducted on a computer monitor, with the filter effects simulated by calculating corresponding chromaticities with or without the filter for naturalistic (Munsell) reflectances. The filter evaluated (Enchroma SuperX glasses) was designed to increase color contrast along a magenta-green axis. Consistent with this, search times for targets on the blue-yellow background were significantly faster for the filter condition, because the filter increased the target-background color difference. Alternatively, overall differences in search times were not observed for the S-cone background. The differences on the two backgrounds could be qualitatively accounted for by the relative salience of the stimuli predicted by a perceptual color space (CIELAB). Our results demonstrate the efficacy of the filters for enhancing visual performance for normal trichromats and naturalistic tasks, and illustrate how these effects depend on the potential color characteristics of the environment.

Detecting salient visual objects and orienting toward them are commonplace tasks for animals, yet the underlying neural circuits remain poorly understood. The fruit fly is an ideal model for a comprehensive analysis of feature detection mechanisms given its complete synaptic wiring diagrams, robust behavioral assays, and cell-type-specific gene expression datasets. We previously showed that columnar T3 neurons are required for saccadic orientation toward landscape features during flight. Here, we examine how signals downstream of T3 are processed in the central brain. We identify LC17 visual projection neurons as key postsynaptic targets: they receive strong excitatory input from T3, project to premotor brain regions, and are thus positioned to support visual approach. Using in vivo optical physiology and virtual reality behavior, we demonstrate that LC17 neurons are indeed necessary for object tracking during flight. Furthermore, we find that electrical synapses in LC17 are also required for tracking behavior. We show that the innexin Shaking B (shakB) is highly expressed in LC17 and localized to its dendrites, and genetic perturbations confirm its essential role for electrical coupling in this circuit. Our findings reveal mechanisms underlying visual approach, and highlight the interplay between electrical and chemical neurotransmission for rapid object detection and action selection.

Early synaptic dysfunction is a hallmark of Alzheimers disease (AD), yet the astrocytic mechanisms underlying these alterations remain poorly defined. Here, we identify astrocyte perisynaptic processes (PAPs) as subcellular hotspots of early translational dysregulation in AD. Soluble A{beta} rapidly enhanced global and local protein synthesis in primary astrocytes. In 5.5-month-old APP/PS1 dE9 (APP) mice, translating ribosome affinity purification (TRAP) revealed widespread remodeling of the PAP translatome, while whole-astrocyte translation remained largely unchanged. Dysregulated mRNAs were linked to neuroinflammation, synaptic remodeling, and endoplasmic reticulum stress, and alterations emerged prior to amyloid plaque deposition. Among them, Serpina3n exhibited increased mRNA abundance in PAPs, uncovering spatially restricted translational control. Mechanistically, early Serpina3n upregulation was partially driven by JAK STAT3 signaling, with preferential effects in astrocyte processes. These findings reveal that local translation in astrocyte PAPs is an early and compartment-specific mechanism that may contribute to synaptic dysfunction and disease initiation in AD.

Neural lateralization is well recognized in the control of contralateral somatic movement, yet its relevance to visceral organ regulation remains poorly understood. This study aimed to determine whether the central nervous system exerts lateralized control over hepatic glucose metabolism and to localize the site of peripheral sympathetic crossover to the liver. Pseudorabies virus (PRV) tracing revealed bilateral projections from the lateral paragigantocellular nucleus (LPGi) with preferential innervation of the contralateral hepatic lobes. Unilateral LPGi activation elevated systemic glucose by enhancing glycogenolysis and gluconeogenesis specifically in contralateral lobes, whereas bilateral activation produced additive effects. Following unilateral hepatic denervation, contralateral LPGi activation induced metabolic compensation in the remaining innervated lobes, characterized by increased norepinephrine release, glucose production, and glycogen depletion. Whole-mount tissue clearing and dual viral tracing localized the sympathetic crossover to the porta hepatis. Developmental analysis showed that lobar-specific innervation along the vasculature emerges by postnatal week 2. These findings demonstrate that the brainstem can exert lobe-specific, lateralized control of hepatic glucose metabolism via bilaterally projecting brain-liver sympathetic pathways. This contralateral regulation arises from a peripheral decussation at the porta hepatis, and the compensatory activation observed after denervation reveals an intrinsic neuroadaptive mechanism that helps safeguard systemic glucose homeostasis.

Deciding when to act in the absence of external cues is essential for exploration, learning, and survival. Yet the neural mechanisms underlying such decisions remain controversial, with current views favoring either deterministic or stochastic underpinnings. We simultaneously recorded from large neuronal populations in cortical, thalamic, pallidal, and cerebellar regions as mice self-initiated voluntary actions. Action onset timing was predictable from firing patterns up to several seconds in advance with predictions correlated across regions, demonstrating a prominent deterministic drive that spans regions. Computational modeling indicated that this drive has an initial value and rate that vary trial-by-trial, and the rate increases within trials. Although the deterministic drive is sufficient to trigger action, noise within trials also contributes to setting action timing. Therefore, discrete (across-trial) and continuous (within-trial) sources of variability synergize to time self-initiated actions. This synergy is observed brain-wide, suggesting a distributed decision-making process rather than a hierarchical, modular one.

The unfolding argument in the neuroscience of consciousness posits that causal structure cannot account for consciousness because any recurrent neural network (RNN) can be "unfolded" into a functionally equivalent feedforward neural network (FNN) with identical input-output behavior. Subsequent debate has focused on dynamical properties and philosophy of science critiques. We examine a boundary condition on the unfolding argument for RNN systems with rapid plasticity in their connection weights. We demonstrate through rigorous mathematical proofs that rapid plasticity negates the functional equivalence between RNN and FNN. Our proofs address history-dependent plasticity, dynamical systems analysis, information-theoretic considerations, perturbational stability, complexity growth, and resource limitations. We demonstrate that neuronal systems that possess properties such as plasticity, history-dependence, and complex temporal information encoding have features that cannot be captured by a static FNN. We show that plasticity is a concrete instance of lenient dependency between behavioral and internal observables, restoring empirical testability to theories that incorporate plasticity on perception-relevant timescales. Our results do not establish that recurrence, plasticity, or process are necessary for consciousness; they establish that the unfolding argument does not preclude empirical investigation of whether these properties matter.

Adult neurogenesis of olfactory sensory neurons (OSNs) provides the unique opportunity to understand how new neurons functionally integrate into existing circuitry and contribute to behaviors. Previous studies have shown that immature OSNs express odorant receptors, form dendritic knobs with short cilia, and project their axons into the olfactory bulb (OB) to form functional synapses. Furthermore, a previous study found that immature OSNs respond selectively to odorants and exhibit graded responses in a higher odorant concentration range than mature OSNs. Finally, this study also showed that, in mice that lack mature OSNs, sensory input from immature OSNs can mediate odor detection and discrimination. What remains unknown is how these immature OSNs contribute to odor-guided behavior in the healthy, intact olfactory system. Here we show that chemogenetically silencing immature OSNs impairs odor detection ability in a buried food assay. Furthermore, immature OSN silencing reduces the amplitude of odor-evoked dendritic calcium responses in OB neurons in vivo. Together, these findings suggest that immature OSNs provide distinct odor input that complements mature OSN input to contribute to odor-guided behaviors in the healthy, intact olfactory system.

PKM{zeta}, a persistently active atypical PKC (aPKC) isoform, is thought to maintain late-phase long-term potentiation (late-LTP) and long-term memory. However, PKM{zeta}-knockout mice still exhibit hippocampal LTP and spatial memory while lacking neocortical LTP, questioning whether this kinase is fundamental to enduring synaptic potentiation and memory. Tsokas et al. (2016) showed the other aPKC, PKC{iota}/{lambda}, likely compensates for PKM{zeta} during maintenance in the hippocampus of PKM{zeta}-null mice. In wild-type mice, PKC{iota}/{lambda} drives early-LTP and short-term memory, while PKM{zeta} compensates for PKC{iota}/{lambda} knockout by supporting both early- and late-phase processes. Here we show PKC{iota}/{lambda} persistently increases during maintenance in two mouse models: PKM{zeta}-conditional knockout (cKO) mice, and double-knockout mice carrying both conditional deletion of PKC{iota}/{lambda} and constitutive loss of PKM{zeta}. In the double-knockout mice, PKC{iota}/{lambda} was measured while the kinase was still present, prior to its inducible ablation, to characterize its compensatory upregulation in late-LTP before removal. To test whether this compensation was functional, we ablated PKC{iota}/{lambda} in the hippocampus of the double-knockout mice. The double-knockout eliminated late-LTP, whereas individual knockout of either aPKC alone showed normal-appearing LTP. Double-knockout also abolished spatial long-term memory without affecting short-term memory. Thus, when PKM{zeta} is absent, PKC{iota}/{lambda} persists to maintain hippocampal late-LTP and long-term memory.

ObjectiveRepeated alcohol-cue pairings with rewarding experiences establish automatic response tendencies that bias instrumental behavior through Pavlovian-to-instrumental transfer (PIT). How individual differences in approach and avoidance tendencies shape PIT and intervention responsiveness remains poorly understood. This study examined whether automatic tendencies differentially modulate PIT, and whether counterconditioning (CC) combined with retrieval cues can attenuate approach biases and cue-driven instrumental interference. MethodThirty-nine male alcohol users completed an Alcohol Approach-Avoidance Task and PIT task before and after CC, classified into approach or avoidance groups based on their baseline Alcohol Approach Index. Alcohol cues were paired with monetary loss during CC, with retrieval cues introduced to facilitate reactivation of newly formed aversive associations. Right frontal N2 and centroparietal P3 were examined as indices of early evaluative and attentional processing. ResultsDespite comparable behavioral PIT performance, approach-oriented individuals showed attenuated right frontal N2 during push actions at baseline, reflecting reduced frontal regulatory engagement during cue-incongruent responding. CC selectively reduced approach biases in the approach group, with retrieval cues producing additional reductions, accompanied by N2 and P3 restoration. CC recalibrated PIT interference by reducing push and increasing pull interference, particularly with retrieval cues. CC-induced changes in approach bias did not predict PIT interference, suggesting modulation through partially dissociable pathways. ConclusionsCC with retrieval cues selectively reduced approach biases and recalibrated cue-driven instrumental interference in approach-oriented individuals, providing proof-of-concept for retrieval cue-integrated CC as a targeted associative intervention and highlighting the importance of individual tendency profiles in intervention responsiveness.

Vertebrate early neurogenesis is a highly conserved process fundamental to brain function and the emergence of intelligence. However, the cellular dynamics bridging gastrulation and organogenesis remain elusive due to observational challenges. We developed a live-cell imaging platform for transgenic zebrafish that provides, for the first time, a continuous reconstruction of early neurogenesis across subcellular to organismal scales. Our analysis reveals that neurogenesis is a precisely orchestrated process. Neuronal cell bodies initially coalesce into discrete, linearly arranged clusters extending from the brain along the spinal cord. From these hubs, axons radiate outward to innervate the central nervous system and peripheral tissues, including the yolk sac surface. A primary pioneer neuron projects from the brain, coursing ventrally in parallel to the body axis. Secondary neurons then interconnect, forming a pervasive network that is subsequently refined through selective axonal apoptosis. The emergence of frequent Ca{superscript 2} flashes only after structural maturation indicates that functionality is contingent upon an established scaffold. We also observe concurrent material transport and a slow, directional flow of Ca{superscript 2} along axons, suggesting complementary signaling modalities. Furthermore, neurogenesis exhibits precise spatiotemporal coupling with histogenesis, particularly with the developing lateral line and vasculature. Our work, with refined spatial and time resolution, defines the kinetic pathway of early neurogenesis and underscores the critical interplay of subsystems in embryogenesis, offering fundamental insights for neural health and bio-inspired intelligence.

External landmarks anchor internal spatial representations. The neural mechanisms underlying this process and the sources of landmark signals remain unknown. We recorded neurons across five parahippocampal regions while rats navigated in a virtual reality apparatus, inducing conflict between self-motion and landmark cues. Area 29e, a parahippocampal field putatively homologous to primate area prostriata, maintained firing coupled to landmarks even when other regions decoupled from the landmarks. This decoupling was preceded by a decline of gamma-band influence from 29e to MEC and a concomitant decline of theta-modulated feedback from MEC to 29e. Area 29e also displayed weak theta modulation, strong gamma rhythmicity, strong egocentric head-direction tuning, and enhanced landmark contrast sensitivity. These findings provide strong evidence that 29e serves as a specialized visuospatial hub that provides landmark signals for anchoring parahippocampal spatial representations to the external world.

Long-Stokes-shift fluorophores enable high sensitivity and multiplexed imaging with single-wavelength excitation. Under single-photon illumination ATTO 490LS exhibits a 165-nm Stokes shift, but its two-photon properties remain uncharacterised. Emission and excitation spectral analyses of ATTO 490LS in ex vivo Drosophila melanogaster brains identified two-photon excitation sensitivity at 940 nm, with peak emission at 640 nm. We demonstrate successful duplexed imaging of ATTO 490LS alongside Alexa Fluor 488 using a single 920-nm fibre laser and dual photomultiplier tubes, enabling distinct measurement of red and green fluorescence signals. These findings establish ATTO 490LS as suitable for multicolour two-photon microscopy with single-laser systems.

Verbal short-term memory includes resources for maintaining semantic and phonological information. These resources are complementary and often activated simultaneously, making their anatomical bases difficult to determine. One way to distinguish them may be to study the resolution of interference from distractor words that are semantically or phonologically related to a planned sentence. We recorded magnetoencephalography (MEG) data while participants rehearsed short formulaic 5-word sentences like "The mouse ate the cheese." During a memory delay period, participants exhibited bilateral temporofrontal event-related desynchronization (ERD, power decrease) in the alpha and beta bands (8-30 Hz). During the memory delay, participants also heard an auditory distractor word that could be unrelated to the sentence, semantically related to one of the words in the rehearsed sentence (e.g. "rat" or "butter"), or phonologically related to one of the words in the sentence (e.g. "mountain" or "cheat"). Relative to unrelated words, related words induced a greater degree of ERD immediately following their presentation. Effects of semantic distractors were exclusively in the temporal lobe, largely in the left middle temporal gyrus but also in bilateral medial temporal regions. Effects of phonological distractors were far more widespread in temporal, frontal, and parietal regions, and were largely left-lateralized, although they also overlapped with the temporal regions showing semantic effects. As no behavioural effects were observed in cued sentence repetition, it seems that auditory distractors produce short-lasting interference with a verbal memory trace that is ultimately resolved, but useful for mapping regions involved in maintaining distinct aspects of the sentence content.

Intense injury induces long-term changes in the spinal nociceptive system, which increases pain in magnitude and duration. We investigated whether activation of G protein-coupled receptor 37 (GPR37) at the spinal level can erase this nociceptive system sensitization and resolve long-lasting, enhanced pain using two animal models: the capsaicin model and the hyperalgesic priming model. Without altering normal mechanical and heat nociception, a single intrathecal (i.th.) administration of two GPR37 agonists, TX14A and protectin D1 (PD1), dose-dependently inhibited capsaicin-induced increase in nociception not only acutely but also long-term. In the hyperalgesic priming model, a single i.th. injection of either GPR37 agonist after an initial injury-induced priming dose-dependently prevented increased nociception following a subsequent inflammatory insult, indicating an unpriming effect. Global GPR37 knockout or conditional knockout of GPR37 in TRPV1-lineage sensory neurons abolished the long-term inhibitory effect and unpriming effect of i.th. TX14A, confirming that GPR37 in this specific cellular population mediates these effects. Ex vivo Ca2+ imaging revealed that i.th. TX14A, given in vivo to the capsaicin model a week before imaging, had rescued dorsal horn excitatory and inhibitory interneurons from long-term potentiation and depression of responsiveness to afferent inputs, respectively, suggesting the erasure of capsaicin-induced nociceptive system sensitization. Conditioned place preference tests indicated no obvious abuse liability for centrally administered GPR37 agonists. These findings suggest that spinally targeting GPR37 in TRPV1-expressing sensory neurons represents a promising therapeutic strategy for resolving persistent pain by erasing nociceptive system sensitization.

Chronic stress induces neural circuit remodeling, yet the computational link between circuit changes and behavioral rigidity remains unclear. By analyzing in vivo GCaMP8s recordings from amygdala-striatal pathways, we identified distinct recovery dynamics in BLA-DMS and CeA-DMS circuits following acute perturbations. To resolve how these differences emerge, we developed a nonlinear dynamical model integrated with an adaptive neural network. Our framework utilizes a unified stability-constrained loss function, with model parameters autonomously mapped from the statistical features of neural ensembles. The simulation successfully replicates experimental outcomes, demonstrating that chronic stress is computationally equivalent to a pathological gain shift that favors the stabilizing CeA-DMS pathway at the cost of BLA-mediated flexibility. Furthermore, robust tests (10 seeds) revealed a functional-structural decoupling--where rigid dynamical attractors are maintained despite high variability in coupling weights (CV {approx} 40%)--providing a mechanistic framework for stress-induced circuit dysfunction.

SignificanceHabituation is an early-developing cognitive process linked to learning, typically reflected in functional near-infrared spectroscopy (fNIRS) studies as a reduction in evoked hemodynamic response amplitude. Conventional fNIRS analyses rely on linear time-invariance assumptions, potentially limiting insight into how responses evolve across repeated stimulus presentations. AimTo determine whether functional change point (FCPt) detection can characterize trial-specific changes in the infant hemodynamic response and reveal developmental differences in habituation timing. ApproachFunctional data analysis (FDA) treats entire response curves as statistical objects. Within this framework, FCPt detection identifies statistically significant structural shifts in the mean response across trials. FCPt detection with wild binary segmentation was applied to infant fNIRS data (n = 204) collected from infants living in rural Gambia at 5-, 8-, and 12-months of age during a habituation and novelty detection paradigm. ResultsSignificant changes were identified within auditory cortical regions. A high proportion of detected change points corresponded to decreases in response magnitude at 8- and 12-months. Ordinal regression revealed an age-related shift toward earlier occurrence of decreasing change points, indicating that older infants completed habituation sooner within the trial sequence. ConclusionFCPt detection provides temporal information on the infant hemodynamic response unavailable to conventional analysis. This additional information has revealed a previously overlooked developmental change in the habituation response during the first year of infancy.

The pupillary light response was once considered a brainstem reflex, but newer findings indicate that pupil dilation can also reflect content held 'in mind' with working memory (WM). This suggests that WM may recruit even the earliest sensorimotor apparatus for maintenance. Here, we tested two boundaries of this pupillary WM response: whether it generalizes beyond low-level stimuli and whether it adapts to changing behavioral goals. Namely, we tested whether the pupils reflect remembered brightness for real-world scene images, and whether the effect varies when different features dimensions are emphasized for the memory test (i.e., visual detail vs. semantic category). We found a feature-specific pupillary WM effect for remembering natural scenes, but only when the task encouraged a visual maintenance strategy. Rather than a retrospective echo of sensory-evoked stimulus features, the pupillary WM response prospectively adapts to how the memory content will be used.

Hyperthermia (HT) is recognized across various medical disciplines for its capacity to modulate specific protein expressions. In efforts to improve Alzheimer's disease (AD), HT has the potential to regulate heat shock proteins (HSPs) and antioxidant enzymes, which helps decrease the aberrant accumulation of {beta}-amyloid (A{beta}) protein and oxidative stress. Nonetheless, the precise delivery of mild hyperthermia to the brain remains a significant challenge. To apply mild hyperthermia targeted to the brain and evaluate its impact on cognitive improvement, this study used focused ultrasound (FUS) to administer localized mild hyperthermia to the brains of AD mouse induced by intracerebroventricular (i.c.v.) injection of A{beta}25-35. For considerations of safety and therapeutic efficacy, a thermal cycling-hyperthermia (TC-HT) protocol was adapted into a focused ultrasound-mediated thermal cycling stimulation (FUS-TCS), which was compared with the continuous focused ultrasound-mediated hyperthermia stimulation (FUS-HTS). The findings revealed that the FUS-TCS treatment group exhibited a significant improvement in cognitive performance, as evidenced by enhanced outcomes in the Y-maze and novel object recognition (NOR) tests. Furthermore, this group demonstrated increased expression of A{beta}-degrading enzymes and antioxidant proteins, including heat shock protein 70 (HSP70), neprilysin (NEP), insulin degrading enzyme (IDE), sirtuin 1 (SIRT1), and superoxide dismutase 2 (SOD2). These results suggest that localized mild hyperthermia targeting the brain using FUS-TCS treatment represents a promising strategy for ameliorating cognitive deficits associated with AD.

The visual system can flexibly adjust attentional deployment to match task demands, but whether observers can proactively modulate the spatial scope of attention based on expectations about upcoming search difficulty remains unclear. According to the zoom lens model, attention can narrow or broaden its spatial extent, with narrower focus enhancing processing efficiency, a mechanism that would benefit target discrimination in crowded displays. We tested whether observers adjust attentional scope when expecting sparse versus dense search arrays by combining spatial cueing with block-wise manipulations of display density expectations. Participants performed a visual search task in which endogenous cues predicted target location, while blocks predominantly contained either sparse (1 target, 3 distractors) or dense (1 target, 7 distractors) displays. We applied inverted encoding models to broadband EEG data to reconstruct spatial channel tuning functions, enabling precise characterization of both the locus and breadth of attentional deployment. Behaviorally, expecting difficult searches selectively improved accuracy at cued locations without costs elsewhere. Consistent with this selective benefit, neural measurements revealed that expectancy enhanced the amplitude of spatially selective responses at the attended location but did not alter tuning width. These findings demonstrate that expectations about search difficulty modulate attention through gain-based signal enhancement rather than adjustments to spatial scope, revealing that preparatory attentional control operates via amplitude modulation within a stable spatial focus. This mechanism complements reactive attentional adjustments and provides an efficient means for the visual system to optimize processing under predictable task demands.

Both active movement profiles and robust circadian rhythms are linked to improved health outcomes, yet the underlying mechanisms remain partially understood. We investigated this relationship in young adults (n = 169, aged 18-30 years) under real-world conditions using actigraphy data. We performed k-means clustering on 12 accelerometer-based features capturing magnitude, duration, frequency, and intensity distribution to derive movement behavior profiles. As a proxy of circadian rhythms integrity we computed the Circadian Function Index (CFI), which combines intradaily variability, interdaily stability, and relative amplitude. We also assessed circadian phase and sleep quality parameters. Additionally, we quantified light exposure and physical activity over 3-hour daily intervals. The unsupervised algorithm identified two non-overlapping profiles among participants, the More Active (MA) and the Less Active (LA) profiles. MA exhibited a higher CFI (0.81 {+/-} 0.06 vs. 0.69 {+/-} 0.06, p <0.001), which was also positively associated with early-evening physical activity, but not with light exposure. MA also showed an earlier circadian phase, estimated as the midpoint of the five least active hours (L5c, 04:30 {+/-} 01:03 vs. 04:59 {+/-} 01:15, p adj. = 0.04), which was inversely associated with early-morning physical activity and late-morning light exposure. We found no differences in sleep quality between MA and LA. Our results underscore the association between movement behavior and overall circadian rhythms integrity. Importantly, these findings reinforce actigraphy as a multidimensional tool for both health research and clinical applications.

Generalization is a fundamental criterion for evaluating learning effectiveness, a domain where biological intelligence excels yet artificial intelligence continues to face challenges. In biological learning and memory, the well-documented spacing effect shows that appropriately spaced intervals between learning trials can significantly improve behavioral performance. While multiple theories have been proposed to explain its underlying mechanisms, one compelling hypothesis is that spaced training promotes integration of input and innate variations, thereby enhancing generalization to novel but related scenarios. Here we examine this hypothesis by introducing a bio-inspired spacing effect into artificial neural networks, integrating input and innate variations across spaced intervals at the neuronal, synaptic, and network levels. These spaced ensemble strategies yield significant performance gains across various benchmark datasets and network architectures. Biological experiments on Drosophila further validate the complementary effect of appropriate variations and spaced intervals in improving generalization, which together reveal a convergent computational principle shared by biological learning and machine learning.

Brainstem arousal systems including the locus coeruleus noradrenaline system, re-spond transiently to behaviorally relevant events. Locus coeruleus activity also drives dilations of the pupil, which are often observed during cognitive tasks. The strength of pupil responses during encoding of stimulus material predicts the success of its later retrieval, which might reflect the impact of noradrenaline on synaptic plasticity and memory formation. The pupil also dilates in response to task-irrelevant sounds, which could therefore serve as a valuable tool for investigating causal effects of phasic, pupil-linked arousal on cognition. Here, we evaluated whether task-irrelevant white noise sounds affect memory formation and memory-based decisions. These sounds were played before, during or after the presentation of memoranda (images or spoken words). Memory success was measured in recognition and free recall tasks the day after. Trial-to-trial variations in the amplitude of pupil dilations during word encoding without task-irrelevant sounds predicted memory success. Task-irrelevant white-noise sounds also robustly dilated the pupil but did not improve memory formation for the words or the images. We conclude that pupil-linked arousal processes triggered by task-irrelevant sounds differ from those recruited endogenously during memory for-mation, for example in states of increased emotionality or attention.

Understanding how neural circuits compute requires capturing voltage dynamics across large neuronal populations with millisecond resolution in vivo. However, two-photon voltage imaging remains fundamentally limited by a trade-off among imaging speed, field of view, and excitation efficiency. We introduce HS2PM, a hybrid scanning two-photon microscope that overcomes this bottleneck, enabling kilohertz-rate imaging over a 650x524 m2 field of view at single-cell resolution while preserving the photon efficiency of single-point excitation. HS2PM stably records deep-layer membrane potentials from over 160 neurons simultaneously, with minimal photobleaching and phototoxicity. It resolves both spikes and subthreshold voltage dynamics in vivo, revealing how these jointly shape sensory adaptation and population coding. Beyond voltage imaging, HS2PM supports high-speed fluorescence lifetime and vascular flow imaging, establishing a multimodal platform for dissecting fast circuit dynamics with precision previously inaccessible to optical methods.

The ability to recall learned movements and rapidly adapt to environmental changes, known as locomotor savings, is crucial for mobility in community-dwelling older adults. However, the influence of aging on locomotor savings and the underlying mechanisms remains poorly understood. Attentional compensation is a particularly relevant mechanism because the control of automatic motor behaviors like walking tend to recruit more attentional/executive resources with aging. We hypothesize that locomotor savings is diminished with age and relies on attentional rather than automatic control of walking. To test this, we compared savings of a novel walking pattern learned on a split-belt treadmill, where each leg moves at a different speed, across multiple days in 21 older and 21 younger adults. Attentional control of walking was assessed by overground dual-task walking while prefrontal cortex (PFC) activity was recorded using functional near-infrared spectroscopy (fNIRS). We found that older adults exhibited less locomotor savings than younger adults after practice. Older adults also relied more on attentional resources during dual-task walking. Importantly, greater locomotor savings was associated with higher attentional control of walking in older adults, suggesting that the use of attentional resources during challenging walking facilitates the recall of previously learned movements. These results indicate that cognitive compensation strategies utilizing attentional resources are important neural mechanisms modulating locomotor savings. Understanding the role of cognitive compensation in locomotor savings may inform rehabilitation design to enhance mobility in older adults ensuring movement corrections practiced in clinical settings are saved for long-term benefit in daily life.

Polyglutamine diseases are incurable genetic neurodegenerative disorders characterized by the accumulation of extended polyglutamine fragments-containing mutant proteins, which are prone to the formation of poorly soluble aggregates. The adequate cellular model is crucial in uncovering the pathological mechanisms responsible for neurotoxicity in HD, screening for therapeutic molecules and elucidation of the molecular mechanisms impacted by particular compound. In the present study, genetic constructs based on the Sleeping Beauty system were created for the stable inducible expression of full-length normal and mutant huntingtin (Htt) in eukaryotic cells. These constructs were then employed to develop model neuronal cells using Neuro-2a cell line. The expression of Htt as well as the accumulation of Htt immunopositive intracellular aggregates (most characteristic features of HD) was demonstrated, and these aggregates showed colocalization with the proteasome. The activation of the proteasome, as well as changes in the expression of proteasome regulators, components of the autophagy system, and the neuronal proteases cathepsins B and D, reflect the versatility of cellular responses to the mutant pathological forms of Htt.

Tactile sensitivity is temporally modulated on a moving limb. Yet the neural mechanisms underlying this modulation remain unclear. Using electroencephalography, we examined the temporal dynamics of early somatosensory processing during goal-directed reaching. Participants reached for their unseen left hand while brief vibrations were applied to the moving right index finger in different movement phases. Psychophysical results revealed overall tactile suppression during reaching, with sensitivity transiently improving around maximum speed relative to the late movement phase. Consistent with the psychophysical data, the short-latency P45 component, originating in primary somatosensory cortex, was suppressed during reaching but recovered around maximum speed. Reduced P45 amplitudes were associated with stronger tactile suppression measured behaviorally, linking early cortical activity to perceptual changes. This temporally specific modulation of tactile perception, associated with early cortical processing, suggests that the somatosensory system dynamically adapts its sensitivity to facilitate sensorimotor control in goal-directed actions. Significance statementThe perception of touch on a moving hand varies across different movement phases, depending on the importance of sensory feedback for guiding the hand. Our results show that these changes in perception are linked to modulations in early brain activity, indicating that the central nervous system adjusts touch processing in a time-sensitive manner at early processing stages to facilitate control of goal-directed actions.

Individuals with borderline personality disorder (BPD) show alterations in empathic abilities, potentially involving automatic simulation processes supported by mirror-like mechanisms in the somatosensory domain. Within the tactile mirror system (TaMS), observing touch on another persons body activates cortical regions involved in tactile perception, including the primary somatosensory cortex (S1). Although mirror-like alterations have been suggested in BPD, the underlying mechanisms of plasticity remain underexplored. Here, we used a cross-modal paired associative stimulation (cm-PAS) protocol to investigate the plasticity mechanisms of TaMS functioning in BPD. Twenty-four individuals with BPD and 24 healthy controls (HCs) were included. Empathic abilities were assessed using self-report questionnaires. Participants performed tactile acuity and visuo-tactile spatial congruity (VTSC) tasks before and after a cm-PAS protocol. During cm-PAS, images of a hand being touched were paired with transcranial magnetic stimulation over the S1. The effects of cm-PAS were assessed on tactile acuity, as an index of S1 activity, and VTSC performance, as an index of TaMS functioning. Preregistered analyses revealed that patients with BPD tended to have lower cognitive empathy than HCs, with no significant cm-PAS effects on tactile acuity or VTSC performance in HCs, precluding between-group comparisons of plasticity effects. Exploratory analyses were conducted to further investigate potential sources of variability in the effects of cm-PAS, as well as the relationship between cognitive empathy and visuo-tactile processing as measure of TaMS functioning.

Light drives processes that include perception and the regulation of circadian rhythms, sleep, metabolism, and development. These processes are initiated by photopigment molecules, each preferentially absorbing particular wavelengths. Light of a given spectrum stimulates an animals set of photopigments in a specific profile. Natural skylight and its variations produce stimulation profiles that promote normal physiology. To mimic these profiles using artificial light, we consider the thermally stable, photoconvertible states of relevant photopigments: ground states of rhodopsin and cone photopigments, and three states of melanopsin. This gives a relatively high-dimensional representation of illumination. Nevertheless, we find that two wavelengths suffice to closely mimic the effects of natural light for mammals, including humans and mice. Adjusting the wavelength ratio allows mimicry of natural lights variations, such as those from twilight to noon. Ratio adjustments also compensate for lights filtering by elements like the eyes optics and laboratory cages. Adding a third wavelength makes natural light mimicry nearly perfect. By contrast, common artificial lighting--designed for low-dimensional, human color space--stimulates photopigments in unnatural proportions. We conclude by providing species-specific maps of photopigment stimulation profiles under natural and artificial illumination, which make our observations intuitive while providing insight into the diverse visual ecologies of mammals. SIGNIFICANCE STATEMENTHumans sense light for vital processes like sight and physiological regulation. These processes are normal under natural skylight, where they evolved. However, much of modern life is spent in artificial light, which is unlike natural light in many of its biological effects. This disparity has been linked to disorders that range from cardiovascular disease to cancer. This manuscript introduces simple forms of artificial lighting that replicate the effects of natural skylight on photoreceptors of humans and other species. It also demonstrates how the biological effects of natural and artificial lights can be captured in simple maps, facilitating the choice and further design of illumination that is beneficial.

Primate vision has exceptionally high spatial acuity and contrast sensitivity. This performance originates in specialized photoreceptors of the fovea. These cones transduce light into electrical signals in the outer segment, and convey these signals to the presynaptic terminal for transmission. Backpropagating signals are also possible, as the terminal receives inputs. Such signals could influence phototransduction itself. To test this idea, we recorded electrophysiologically from both ends of single cones dissociated from the macaque fovea. We found that backpropagation was effective despite the extreme slenderness and length of these cells. Backpropagation was also effective in a passive compartmental model, indicating that amplification by voltage-gated channels is not required. We then modeled foveal cones receiving terminal inputs from retinal networks. Despite faithful backpropagation of these inputs, they appear unlikely to influence phototransduction. Thus, even though foveal cones exhibit effective backpropagation, their encoding of visual information may remain compartmentalized.

IntroductionNoninvasive brain stimulation can help clarify the neural basis of reward processing and potentially inform treatments for disorders involving reward dysfunction. However, widely used methods such as transcranial magnetic and electrical stimulation cannot directly stimulate deep-brain regions like the striatum. Here, we tested whether stimulating the ventrolateral prefrontal cortex (VLPFC)--a cortical region strongly connected to the striatum-- could indirectly influence reward-related neural and physiological responses. MethodsIn a within-subjects design, participants performed a card-guessing task involving monetary rewards for correct guesses and punishments for incorrect guesses. During the task, participants underwent functional magnetic resonance imaging (fMRI) and pupillometry while receiving concurrent 10 Hz transcranial alternating current stimulation (-tACS). Stimulation targeted either the VLPFC or a control region (temporoparietal junction). We measured pupil dilation, brain activation (BOLD signal), and functional connectivity between the ventral striatum and dorsal anterior cingulate cortex (VS-dACC). ResultsVLPFC stimulation increased pupil size during reward and punishment outcomes, indicating greater physiological arousal. At the neural level, -tACS enhanced VLPFC activation during reward and suppressed its responses during punishment. Stimulation also changed VS- dACC connectivity in a context-dependent manner. Importantly, stimulation-driven increases in pupil size during reward correlated positively with stimulation-induced changes in VS-dACC connectivity. Exploratory moderated mediation analyses suggested that stimulation influenced the degree to which striatal responses mediated the relationship between task outcomes and pupil size changes. ConclusionsTargeting VLPFC with -tACS modulates local cortical activity and corticostriatal networks during reward processing, providing a promising noninvasive approach to influence reward circuitry. HighlightsO_LI-tACS over VLPFC increases pupil responses to reward and punishment. C_LIO_LIStimulation alters reward-related VLPFC activity without enhancing striatal BOLD. C_LIO_LI-tACS modulates ventral striatum-dACC connectivity in a task-dependent manner. C_LIO_LIConnectivity changes predict pupil dilation, linking brain and autonomic responses. C_LI

Synapses are fundamental building blocks of cortical circuits, yet their geometry is typically regarded as a local property, independent of mesoscale architecture. The prevailing assumption is that synaptic clefts are isotropically oriented in space. Here, we test this assumption by analyzing approximately 117 million synaptic clefts from two independent 1 mm3 electron microscopy datasets: the human H01 middle temporal gyrus and the mouse MICrONS primary visual cortex, using three independent cleft-extraction methods. Across both volumes, we observe that synaptic cleft orientations are not randomly distributed, but instead show statistically significant and spatially coherent directional biases across cortical layers. This mesoscale anisotropy is conserved across species, yet is stronger and more consistent in human association cortex than in mouse sensory cortex, a difference that may reflect the expanded dendritic arbors and greater integrative demands of human pyramidal neurons. We propose that cleft orientation bias is a geometric consequence of the axonal and dendritic architecture that shapes synapse formation, representing a new candidate organizational feature of cortical microarchitecture with potential implications for circuit computation and neuromodulation. These findings motivate targeted physiological studies to determine whether synaptic orientation contributes causally to cortical function.

Self-reflection is central to human cognition and is arguably a defining feature of human consciousness. Yet, the mechanisms enabling our mind to reflect upon itself and to construct a conceptual sense of self remain poorly understood. This study brings empirical traction to the puzzle of self-reflection by studying human infants, across the period when a conceptual self is believed to emerge, from 12 to 18 months of age. Using a gaze-contingent match-to-sample paradigm with concurrent eye-tracking and EEG recordings, we find evidence of self-reflective capacities in 12-month-old infants: they exhibit a signature neural response of error-tracking (error-related negativity, ERN) after making incorrect as opposed to correct choices, and before receiving feedback. Remarkably, the magnitude of the ERN at 12 months developmentally predicted which infants will evidence a conceptual self-representation (mirror-self-recognition) 6 months later. This relationship was specific to internal error-monitoring (ERN), and not external feedback processing (FRN), and could not be explained by infants' age or general cognitive development. Furthermore, we show that only the group of infants, who later evidenced self-representation, exhibited an ERN, while FRN was evidenced in both groups. Moreover, the same group of infants who evidenced self-representation and internal error monitoring also adapted their behaviour post-error, by slowing their decisions and increasing visual exploration following mistakes. Thus, error-detection, if available, can be utilised for adaptive information-seeking and decision-making as early as 12 months of age. The finding that internal error-monitoring not only precedes but developmentally predicts the emergence of self-representation strongly supports the proposal that infants' error-monitoring and behavioural adjustments index rudimentary forms of metacognition. Moreover, these results point to the possibility that internal error-monitoring is functionally involved in building a conceptual self, thereby raising questions regarding possible factors modulating individuals' sensitivity to own errors and consequently their conceptual representation of themselves as distinct epistemic agents.

Bad channels in electroencephalography (EEG) recordings can substantially degrade downstream analyses, particularly in high-density datasets where localized hardware or motionrelated artifacts may affect groups of electrodes in a structured manner. We introduce a MATLAB Module for bad-channel quality control that emphasizes interpretability, relational structure, and human-in-the-loop validation rather than fully automated rejection. The method operates on multichannel EEG data and combines complementary channel-level features, including time-dependent neighbor dissimilarity and amplitude- and variance-based statistics to score and pre-label channels as good, suspicious, or bad. To expose shared artifactual structure, channels are additionally grouped using a similarity measure derived from the co-occurrence of robustly detected high-amplitude transients, allowing channels to be reviewed together. Importantly, clustering is used as an exploratory tool to reveal co-artifactual patterns rather than to impose final class labels, which are confirmed through an interactive review interface supported by summary visualizations and grouped channel displays. This Module is released as a publicly available codebase with documentation, example work-flows, and a supporting dataset. This Module is designed as a quality-control step preceding ICA and does not replace end-to-end data cleaning pipelines, which typically involve additional steps such as interpolation of known bad channels.

How does the visual system recognize objects in noisy natural environments? Several psychophysical techniques, including critical-band masking, have established that human object recognition is mediated by a narrow 1.5-octave spatial-frequency band (a "channel"). The narrow band has been linked to the robustness of human recognition. Here we investigate its physiological basis. Along the ventral stream, from V1 to V2 to V3 to V4 to ventral temporal cortex (VTC), we used fMRI to measure BOLD responses to bandpass noise and to natural images perturbed by that noise. Along this stream, the BOLD signal is sensitive to noise across an increasingly wide range of stimulus spatial frequencies, from 2 octaves in V1 to 5 octaves in VTC. However, when we assess the effect of the same noise on the accuracy of decoding scene images from the BOLD response, we obtain a different result: Recognition bandwidth is conserved along the ventral stream at about 2 octaves, close to the 1.5-octave behavioral channel. Though the recognition band is conserved, its noise tolerance increases steadily along the ventral stream, approaching behavioral levels in VTC. These findings suggest that V1 sets the bandwidth of the object-recognition channel, while downstream areas progressively denoise the signal, setting the channels noise tolerance.

We present the most comprehensive sampling of the macaque and human brain with diffusion MRI to date. As part of the BRAIN CONNECTS center for Large-scale Imaging of Neural Circuits, we leverage ultra-high-gradient MRI systems, including the first-of-its-kind Connectome 2.0, for post-mortem acquisitions. Each sample is imaged for ~250 hours at multiple spatial resolutions down to 0.25 mm isotropic for whole macaque brains and 0.4 mm isotropic for human hemispheres. Our optimized protocols allow us to sample both species across ~50 diffusion shells varying in b-value, diffusion time, and echo time, reaching ultra-high b-values up to 64000 s/mm^2 with high signal-to-noise ratio. We demonstrate that these multi-dimensional data resolve not only white matter connectional architecture but also cortical and subcortical cytoarchitectonic boundaries, at a level of detail previously inaccessible in whole-brain noninvasive imaging. As such, these data are an important resource for both technical development and basic and clinical neuroscience.

We studied the effects of prioritization in a two-step retrocuing task in which male and female humans hold two items in working memory, and the item not cued by the first cue cannot be dropped because it may be prioritized by the second cue. In Experiment 1, using a dense sampling procedure, recall performance oscillated at 15 Hz in the prioritization task, in comparison to 20 Hz in a matched neutral-cue task. Furthermore, the prioritized item was shielded from bias exerted by the uncued item, as well as by items from the previous trial. In Experiment 2, we recorded the EEG while participants performed variants of the two tasks. The prioritization cue uniquely triggered a phase reset at 15 Hz and an increase in oscillatory peaks at this frequency. Burst analysis ruled out bursting as a possible underlying factor. Time-resolved representational similarity analysis (RSA) revealed that the prioritization cue triggered representational transformations that were larger for the uncued item. The shielding effects of prioritization may arise from the transformation of the not-prioritized item into an "unprioritized" state that is implemented and maintained by a mechanism that cycles at 15 Hz. Significance statementWhen multiple items are held in working memory, the brain must prioritize the information currently needed to guide action while also managing the other information that remains potentially relevant for future actions. Through behavior and electroencephalography, we show that prioritizing one item in working memory shields it from interference from the not-prioritized item and that this shielding is implemented by transforming the representational state of the unprioritized item. Behavioral signatures of this transformation and the underlying neural dynamics both cycle at a frequency in the low-beta band ([~]15 Hz). These findings suggest that the brain uses an oscillatory mechanism--distinct from previously described beta-bursting inhibitory control--to organize and protect the contents of working memory from inter-item competition.

A much-replicated finding in human brain imaging is a distributed 'multiple-demand' or MD system, increasing in activity for many kinds of cognitive demand, and centrally involved in cognitive control. MD regions are proposed to encode a distributed mental model of critical task events, bound together in the roles and relationships needed to direct action selection. Though previous data hint at a corresponding network in the macaque, there has been no direct comparison to human data. Here we used functional magnetic resonance imaging to measure whole brain activation in a multi-step saccadic maze task, compared to a control requiring similar moves but without goal-based decisions. Human data were a close match to the canonical MD network, extended to include adjacent regions and in particular much of the canonical dorsal attention network. Monkey data suggested correspondences in dorsomedial frontal, lateral and medial parietal, insula/orbitofrontal and posterior temporal cortex. In lateral frontal cortex there was just a single, largely dorsal activation patch, in contrast to multiple distinct human patches. In macaque as in human, together with previous data, our findings suggest an extended and strongly interconnected brain network recruited by increased cognitive challenge.

Nucleus accumbens (NAc) dopamine 2 receptor expressing medium spiny neurons (D2-MSNs) are involved in stress and aversive learning, where repeated stress increases excitatory spine density. Whether this plasticity reflects cue-specific learning or generalized stress response remains unknown. Using Pavlovian fear conditioning in Tac1-Cre/Tdtomato mice, we dissociated associative plasticity from the effects of foot shock stress. Acute fear conditioning produced distinct physiological outcomes between stress in the presence or absence of a cue. Conditioning for 7 days consolidated cue learning and increased excitatory transmission frequency via an increase in the total spine density. However, repeated exposure to foot shock did not lead to this synaptic remodeling. Our results suggest that morphological changes supporting synaptic plasticity on NAc D2-MSNs are due to cue-dependent learning, but not foot shock stress alone. We propose that NAc D2-MSNs encode learning and response to threat cues, which may heighten later stress responsivity.

According to theories of the brain as a predictive network, perceptual decisions result from integrating incoming sensory inputs with prior experience. A neuronal population implementing this form of computation must not only retain information about past events, but also combine this information with current sensory evidence. To examine how this integration occurs, we recorded extracellular activity from both primary sensory cortex and a target frontal region in rats performing stimulus categorization. Psychophysical analysis showed that judgments were history-dependent. Sensory cortex represented the current stimulus largely independently of prior stimuli and failed to account for the history-dependence seen in behavior. By contrast, frontal cortex embedded current input within a representation of prior sensory information through collinearity in coding dimensions. This mechanism - predominantly mediated by fast-spiking neurons - explained trial-to-trial variability in decisions. Our findings argue for distinct roles of cortical regions in predictive processing, and identify a frontal stage where current and prior sensory information converge to inform decisions.

Postmortem human brains stored in brain banks are important research resources to study the mechanisms underlying normal brain functions as well as various neurodegenerative disorders. Immunohistochemical (IHC) and histochemical (HC) staining have been used to examine human brains fixed in neutral-buffered formalin (NBF) for months, years, and even decades. As such, it is essential to establish the effects of prolonged fixation in NBF on both IHC and HC stains. Previously, we found that prolonged NBF fixation resulted in differential effects on IHC and HC staining on postmortem brains. In this study, we further examined the effects of prolonged fixation on IHC stains targeting 6 antigens and 2 HC stains of known biomarkers of cerebrovascular diseases in prefrontal cortex of human brains fixed for 1, 5, 10, 15, and 20 years. The IHC targets included microvasculature markers of the blood brain barrier (Collagen-IV and Claudin-5), a type III intermediate filament marker (Vimentin), an activated microglia marker (CD68), a biomarker for oligodendrocytic myelin proteolipid protein (PLP) and a marker for iron accumulation (Ferritin). The HC included Massons Trichrome Stain (MTS) and Bielschowsky silver stain (BSS). We found that staining intensities of Ferritin, Vimentin, Collagen-IV and BSS decreased with prolonged fixation, while no significant differences were observed in the staining intensity of other markers. Hence, these differential alterations should be taken into consideration when interpreting the results from processed tissues with prolonged fixation. We recommend performing IHC and HC staining for human brains with the same fixation times to offset any impact on downstream neuropathological analyses, as well as adding the fixation duration as a covariate in the analysis.

AO_SCPLOWBSTRACTC_SCPLOWThe hippocampus receives convergent input from multiple sensory systems, yet in humans it has been studied almost exclusively through vision. Here we examine how the hippocampus contributes to sensory processing beyond the visual modality and to the multisensory integration of visual information with these other modalities. Participants were exposed to multiple repetitions of short naturalistic movie clips, each presented in four formats: auditory only, visual only, congruent audiovisual, and incongruent audiovisual (audio and video from different movies). Using high-resolution fMRI, we measured univariate activation and multivariate representations across the subfields and longitudinal axis of the human hippocampus. Whereas univariate analyses detected only visual responses across hippocampal subfields, with no activation for auditory stimuli and no benefit of congruent stimuli, multivariate analyses revealed robust representations of both auditory and visual scenes. The posterior hippocampus showed enhanced pattern similarity for congruent stimuli relative to unisensory stimuli, demonstrating multisensory facilitation. The anterior hippocampus showed crossmodal decoding between auditory and visual versions of the same clip, suggesting a more abstract representation. Finally, whole-brain searchlight analyses revealed parallel effects in cortical regions known to support multisensory integration. These findings advance understanding of auditory and multisensory coding in the human hippocampus, including the discovery of a functional dissociation along its longitudinal axis, from facilitation in posterior to generalization in anterior.

How intelligence emerges from the brains complex microscopic physical system is a central question for neuroscience and artificial intelligence. Constrained by the genomic bottleneck that precludes synapse-by-synapse specification, we propose and validate a microscopic structure-function concise-constraint sufficiency hypothesis. We develop the Neuro-Informed Generative Connectome (NIGC) framework, and show that connectomes generated under a concise set of biophysical constraints (geometric embedding, node propensity modulation, a global energy budget and maximum-entropy selection) closely match the structural statistics of a measured mouse V1 microcircuit (similarities, 0.997). In parallel, using the generated connectome as the fixed reservoir of an echo state network (ESN), training only a linear readout achieves 90% accuracy on an auditory multi-classification task. Moreover, multidimensional biologically consistent functional phenotypes, such as hierarchical transmission delays and low-dimensional spatiotemporal trajectories, are obtained without fitting functional matrices or time courses. Further, by combining single-constraint ablations, pathological perturbations and cross-modal validation, we clarify how specific structural constraints map onto functional consequences. Together, these results delineate sufficient conditions for computational intelligence emergence at the microscopic scale, and provide an auditable benchmark for first-principles understanding of brain construction.

TECPR2-related disorder is a rare, autosomal recessive neurodevelopmental and neurodegenerative disease characterized by early-onset motor dysfunction, sensory- and autonomic neuropathy, and progressive neurological decline with early mortality. Currently, there are no effective treatments for individuals affected by this debilitating condition. To advance our understanding of disease mechanisms and explore therapeutic strategies, we developed and then characterized a knock-in (KI) mouse model carrying the human TECPR2 c.1319delC frameshift mutation. TECPR2-KI mice exhibit a subset of disease-relevant phenotypes, most prominently abnormal gait, along with reduced body weight and altered tactile sensitivity. We additionally observe a reduction in acoustic startle responses, consistent with dysfunction of brainstem-associated sensorimotor pathways. Histopathological analyses reveal progressive accumulation of axonal spheroids in the dorsal column nuclei, together with abnormalities in autophagy-related markers, features previously reported in individuals with TECPR2-related disorder.To assess the therapeutic potential of gene replacement, we delivered TECPR2 via intracisternal infusion of AAV9/TECPR2 in neonatal KI mice. Gene therapy restored mechanosensory function, normalized gait and startle responses, maintain autophagic homeostasis, and partially reduced axonal pathology. These findings demonstrate that TECPR2-associated deficits are not only replicable in this new mouse model but are also amenable to postnatal intervention. Our study introduces a genetically accurate murine model of TECPR2 deficiency, identifies brainstem-associated phenotypes, and provides preliminary evidence supporting the feasibility of AAV9-mediated TECPR2 gene delivery, establishing a foundation for future translational research in a currently untreatable disease.

Psychedelics profoundly alter conscious experience, yet how they reshape the relationship between brain anatomy and function remains unclear. In particular, it is unknown whether psychedelic states reflect a global disruption of structure-function organization or a frequency- and network-specific reconfiguration of neural dynamics relative to the structural connectome. Here we address this question using source-localized magnetoencephalography mapped onto connectome harmonics to quantify structure-function coupling in humans under lysergic acid diethylamide (LSD) and placebo. LSD induces a robust decoupling of low-frequency (theta, alpha and beta) activity from anatomical constraints, indicating a global loosening of structure-aligned large-scale dynamics. In contrast, high-frequency gamma activity shows selective reorganization rather than uniform disruption. Greater gamma-band decoupling within core default-mode network regions predicts the intensity of ego dissolution across individuals, demonstrating that while LSD broadly alters large-scale dynamics, subjective loss of self may be specifically linked to frequency-selective reorganization of the default-mode network. Functional decoding reveals that LSD does not produce indiscriminate disintegration but instead drives system-specific rebalancing, with preferential decoupling of visual and attentional systems and strengthened coupling within auditory networks. Together, these findings provide electrophysiological evidence that psychedelic states emerge from a frequency-dependent relaxation of structural constraints on brain activity and identify default-mode reorganization as a neural correlate of ego dissolution. These results offer a mechanistic framework for understanding how LSD may exert therapeutic effects by transiently relaxing rigid structural constraints and enhancing dynamical flexibility within networks involved in self-related processing.

Hexadirectional modulation is widely treated as a proxy for population-level grid-cell activity in humans. Here we show that this interpretation is generally not supported by the statistics of grid-cell firing. Conventional analyses test symmetric sixfold modulation of the mean response, whereas grid-cell firing predicts a dominant sixfold modulation of cell-level variance, rather than population-level mean. Using analytical deduction, simulations and a large-scale rodent dataset, we show that the previously reported mean hexadirectional effect is not a principal consequence of grid-cell activity. Among current hypotheses, a signal compatible with empirical rodent MEC cell population characteristics can emerge only with a second-order nonlinearity, and only under restricted conditions. Even then, the expected population-level mean modulation is small, approximately 2%. These findings suggest that the existing human literature targets a weak, indirect signature rather than a diagnostic readout of grid-cell population coding. Moreover, many reported hexadirectional effects may arise from testing a single sixfold component without establishing the full spectral response is robust against an appropriate null distribution. We provide a more comprehensive framework for testing hexadirectional symmetry in future studies.

Aging selectively degrades neuronal structure and function, yet the signals that actively preserve neuronal integrity over adult life remain incompletely defined. In Caenorhabditis elegans, the PVD sensory neuron develops progressive excessive higher-order dendritic branching during normal aging that correlates with declines in proprioceptive locomotion. Using this system as a quantitative in vivo readout of neuronal healthspan, we identify the cholecystokinin-like neuropeptide NLP-12 as a protective signal that preserves PVD homeostasis across adulthood. nlp-12 loss-of-function animals show early-onset excessive branching and earlier declines in proprioceptive function, whereas nlp-12 overexpression reduces excessive branching in aged adults without extending lifespan, indicating a neuron-focused effect on healthspan. Using an NLP-12::mKate reporter and coelomocyte uptake as an in vivo proxy for secretion, we find that aging is associated with reduced extracellular delivery of NLP-12 and increased retention within the soma of the DVA interneuron, where nlp-12 is predominantly expressed. Consistent with a requirement for secretory trafficking, disrupting the NLP-12 signal peptide abolishes the rescue effects of nlp-12 reintroduction in nlp-12 mutants. Additionally, histamine-gated silencing of DVA during adulthood similarly accelerates PVD excessive branching, supporting an ongoing, adult-stage requirement for this pathway. Receptor genetics further show that the ckr-1/GPCR is required for nlp-12 overexpression-mediated neuroprotection in aged animals. Finally, human cholecystokinin can rescue the branching phenotype in nlp-12 mutants, supporting evolutionary conservation. Together, these findings implicate conserved cholecystokinin-like neuropeptide signaling as an adult maintenance mechanism that buffers age-associated decline in neuronal resilience.

Lucid dreaming (LD), during which the dreamer is aware that they are dreaming, is frequently induced in laboratory settings by delivering sensory cues during rapid eye movement (REM) sleep. These cues should be incorporated into ongoing dreams and can trigger reflective awareness. This approach relies on the continuity between waking experiences and dream content. In sleep laboratories, participants often dream of the experimental setting itself (lab dreaming), providing a predictable context in which lucidity may emerge. The present studies leveraged this phenomenon by explicitly training participants to associate the sleep laboratory with reflective awareness prior to sleep. Across three studies (total N = 101), participants completed a morning nap following verbal LD instructions and presleep audio designed to prime recognition of the laboratory context in dreams. In addition, conditions included immersive virtual reality (VR) rehearsal of the laboratory environment, VR combined with haptic stimulation (HS) during REM sleep, or VR containing subtle fake system errors intended to prompt reflective checking. LD frequency was assessed through external ratings of signal-verified LD (SVLD) dream reports. Lucidity rates were high across all conditions, with approximately 40-45% of dreams externally rated as lucid and 11%-32% SVLDs occurring in every group. However, neither VR rehearsal, haptic stimulation, nor implicit VR errors increased lucidity relative to the baseline laboratory induction procedure. Exploratory analyses investigated the overlap between laboratory dreaming, false awakenings (FAs), and lucidity. These findings suggest that explicit training focused on the predictable context of the sleep laboratory may already provide a powerful pathway to lucidity, with additional technological manipulations offering limited benefit under a single-nap protocol.

Background: To understand the neurobiology underlying psychopathology, we need valid measurements of brain function. Group atlases for brain functional connectivity (FC) allow for efficient comparisons, but they fail to account for inter-individual variability in network topography, a problem that personalized methods address. We assess the validity and predictive utility of group and personalized approaches of quantifying FC by 1) comparing effect sizes of associations with clinical metrics; and 2) accounting for spatial features of brain networks when examining the association between FC and clinical metrics. Methods: 324 teens ages 13-16 participated. Personalized networks were estimated using a hierarchical Bayesian model. Effect size comparisons were done by comparing the correlations between FC and clinical metrics (depression, ruminative coping style, and sensitivity to punishment/reward) with Steigler's Z-test. We also conducted regressions, with clinical metrics as the dependent variables. Those models included FC and spatial features, together and alone. Results: The effect size comparisons did not survive FDR correction. However, exploratory permutation tests show that 1) the magnitude of the correlations with depression are larger on average for the intersection estimates of FC than the group estimates; and 2) the magnitude of the correlations with a ruminative coping style are larger on average for the intersection estimates of FC than the personalized estimate. The other comparisons conducted using permutation tests are not significant. Multiple regression analyses demonstrated that only spatial features of networks, not FC, are associated with sensitivity to reward. Discussion: These results imply that the intersection estimates are more valid than the group estimates, and that the intersection estimates have greater predictive utility than personalized estimates. Further, spatial features of functions networks may be useful in and of themselves in certain contexts. Therefore, researchers in psychiatry should take into consideration functional network topography in order to gain a better understanding of the neurobiology underlying psychopathology.

Presynaptic homeostatic plasticity (PHP) is a potent form of homeostatic plasticity that has been documented at synapses as diverse as the glutamatergic Drosophila neuromuscular junction (NMJ), cholinergic mammalian NMJ (including human), and glutamatergic synapses in the mammalian brain. Published experimental evidence in favor of PHP in adult hippocampus and cerebellum includes patch-clamp electrophysiology, presynaptic capacitance measurement, calcium imaging, optical reporters of vesicle release and correlated three-dimensional electron microscopy. These studies are grounded in newly optimized experimental protocols that differ substantively from those typically used to study activity-dependent plasticity in neonatal and juvenile slice preparations. Here, we elaborate and extend our assays and methodologies for the study of PHP in the adult mammalian brain. Our assays are designed to optimize synapse, cell and tissue health and minimize the incorporation of unintended adverse experimental conditions that may interfere with the induction and/or expression of PHP. In addition, we provide benchmark criteria for assessment of cell health, necessary for analysis of PHP and, in so doing, advance our understanding of postsynaptic conditions necessary for PHP induction in the adult brain. Our data underscore why PHP may have been previously overlooked, inclusive of a recent manuscript challenging the robust expression of PHP in the mammalian brain (Dou et al., 2026 BioRxiv [preprint]).

Background and ObjectivesHerpes simplex virus type 1 (HSV-1) is a neurotropic pathogen capable of invading the central nervous system (CNS) and increasingly associated with chronic neuroinflammation, cognitive impairment, and neurodegenerative disease. While microglia orchestrate the initial immune response to HSV-1, the molecular mechanisms that regulate their sustained neuroinflammatory activity in vivo remain poorly understood. MethodsTo define the transcriptional and epigenetic mechanisms that shape microglial responses during acute HSV-1 infection in vivo, we have, for the first time, integrated single-nucleus RNA sequencing, chromatin accessibility profiling, and spatial transcriptomics in a physiologically relevant intranasal HSV-1 infection model. ResultsSingle-cell multiome analysis of CD11b nuclei identified transcriptionally and epigenetically distinct microglial and macrophage populations. HSV-1 infection redistributed monocyte-lineage states, with a marked overrepresentation of interferon (IFN)-responsive microglia and macrophage-associated populations. These states exhibited amplification of STAT1/2-, IRF1-, and CEBPB-centered regulons, distinguishing IFN-responsive microglia from macrophage-enriched populations rather than reflecting uniform activation. Homeostatic microglial gene signatures (e.g., ApoE, Cst3) were reduced in response to HSV-1 infection. Spatial transcriptomics localized HSV-1 antigen to discrete brainstem regions, which were enriched for predicted STAT-, IRF-, and CEBPB-regulated targets identified through single-nuclei analysis. DiscussionUsing a multiomic framework, we demonstrate that HSV-1 infection drives transcriptional and epigenetic remodeling of microglial populations, characterized by a dominance of IFN-responsive states and a loss of homeostatic signatures. These findings provide mechanistic insight into how localized viral infection can reprogram microglial regulatory landscapes to maintain persistent HSV-1-associated neuroinflammation, contributing to long-term neurological vulnerability and neurodegenerative disease risk.

BACKGROUNDWith few exceptions, pathological progression in ischemic stroke is presumed to occur uniformly within the ischemic core region. These exceptions include edema formation, brain tissue [Na+] increase, and the qualitative visually observed decrease of brain tissue [K+], [K+]br, all of which occur in peripheral regions of the ischemic core. We hypothesize that [K+]br depletion and egress occur heterogeneously in the peripheral compared to the central ischemic core and this heterogeneity is not associated with neuronal degradation. METHODSPermanent focal ischemia was produced in 13 rats for 2.5-5 h. Brain sections were quantitatively stained for K+ to assess variations in [K+]br depletion and egress between the peripheral and central ischemic core. Reflective change and microtubule-associated protein 2 (MAP2) stained sections were used to identify the ischemic region and relate neuronal pathology to [K+]br variations. RESULTSThe mean value of normal cortex [K+]br was 96 mEq/kg and of K+-egress in all ischemic regions over time was 12.2 mEq/kg/h, consistent with measurements from other studies. Significant differences in exaggerated K+-depletion (p<0.001) and egress (p=0.010) occurred in 56% of the peripheral compared to central ischemic core regions suggesting accelerated K+-egress from 0 to 2.5 h. Unlike [K+]br, there was no difference between the MAP2 immunoreactivity in K+-depleted and non-K+-depleted peripheral ischemic core regions (p=0.83, p=0.16, respectively). CONCLUSIONSWhile confirming previous results of quantitative losses of [K+]br in the ischemic core, we additionally show using quantitative imaging that K+ dynamics within and between the peripheral and the central ischemic core are heterogeneous and not related to MAP2-assessed neuronal structural integrity. Insufficient K+ in K+-depleted peripheral ischemic core regions might limit spreading depolarization-mediated infarct expansion and not allow restoration of the parenchymal membrane potential even if the functionality of the Na+,K+-ATPase is restored. Further study of differing K+-dynamics within the ischemic core might lead to a better understanding of ischemic stroke pathophysiology.

BackgroundMachine learning methods employing neuroimaging data are useful for monitoring the activation of neural representations. Specifically, they can be used to discern the brain networks engaged in processing specific categories of items. This approach has been used predominantly with functional magnetic resonance imaging data, and more rarely with electroencephalography (EEG) data. New methodHere, we present a task, an analytical pipeline, and a stimulus dataset for investigating category representations using EEG. Participants (N = 30) viewed a series of images and words of objects belonging to five categories (Animals, Tools, Food, Scenes, and Vehicles) and responded when items from the same category were presented consecutively. ResultsWe trained support vector machines on EEG data within participants and found that both image trials and word trials yielded significant category classification accuracy, with image trials achieving higher accuracy than word trials. When comparing categories in a pair-wise fashion, all pairs were statistically distinguishable for image trials, whereas only one pair was distinguishable for word trials. Parietal and Left Temporal electrodes contributed more to image classification than Frontal and Right Temporal electrodes. Category-specific activity patterns also generalized across participants for image trials. Comparison with existing methodsOur data and analytic pipeline yielded high classification accuracies, primarily for image trials, providing support for the utility of EEG data for neural decoding. ConclusionsThese methods can be instrumental for exploring the activation and reactivation of neural representations at the category level during wakefulness and, potentially, during offline states.

In this study, we investigate the simultaneous recording of electrical and chemical signals within both the cortical surface and deep regions of the brain. This is made possible through the utilization of an innovative carbon based three-dimensional multi-functional neural probe. Our primary objectives are to explore in-depth the mechanisms of signal propagation among neuronal cells particularly within a three-dimensional framework and demonstrate initial progress in elucidating the interplay between electrical and chemical signals and their responsiveness to external stimuli variability.

Postnatal mouse retinal development is a multi-faceted process involving the coordinated interaction of spontaneous neural activity as retinal waves, vascular plexus growth, and programmed cell death. While these processes are known to interact at a coarse scale, the specific mechanisms integrating them have remained elusive. Using large-scale, widefield calcium imaging, high-density multielectrode array recordings, single cell RNA-seq, and immunohistochemistry, we characterise a tightly aligned centrifugal expansion pattern during retinal development. This pattern is common to stage II retinal wave onsets, vascular development, Heme oxygenase-1 (Hmox1) expressing microglia, apoptotic cell markers, and a novel set of auto-fluorescent cluster complexes (ACCs) identified in this study. Apoptotic cells are known to upregulate functional Pannexin1 (PANX1) hemichannels. These voltage-gated channels release purinergic molecules which act as "eat me" signals to neighbouring microglia. PANX1 hemichannel blockade with the drug probenecid results in a profound decrease in spontaneous wave frequency and strength, suggesting that retinal waves are indeed triggered by these apoptotic cells. Taken together, our observations suggest that spontaneous waves are initially triggered in hotspots by hyperactive apoptotic RGCs in unvascularised retinal areas. These apoptotic cells release purinergic molecules via PANX1 hemichannels, leading to wave generation. This hyperactivity leads to local hypoxic conditions, which, coupled with high extracellular ATP concentrations, promotes angiogenesis. Once blood vessels reach a particular hotspot, ATP release activates Hmox1 positive microglia, which engulf the dying RGCs, creating the auto-fluorescent clusters. We suggest that these early occurring events may be universal in the developing CNS, causally linking early neural activity, programmed cell death and angiogenesis.

Tauopathies are characterised by progressive deterioration of brain regions due to abnormal accumulation of the microtubule-associated protein tau (MAPT). Alternative splicing of MAPT pre-mRNA results in six tau isoforms, which are classified into two groups depending on the number of microtubule-binding domain repeats (3R vs 4R). Although many tauopathies are 3R or 4R-specific, the relative contributions of individual isoforms to neurotoxicity remain incompletely understood. To systematically characterise differences in tau isoform toxicity, we created a novel set of Drosophila lines expressing equivalent amounts of the six human tau isoforms (hTau) at levels sufficient to induce visible phenotypes. Using a variety of assays including survival, negative geotaxis and tissue-level or cell-type-specific degeneration, we found that hTau isoform toxicity is not uniform across different biological contexts. Despite generally higher toxicity of 4R isoforms compared to 3R, the effects of individual hTau isoforms varied with the temporal window of expression, tissue type, and neuronal identity. Restricting hTau expression to small homogeneous neuronal populations enabled detailed analysis of isoform-specific degeneration. Neurons previously observed to be vulnerable or resilient to hTau toxicity exhibited differences in the onset and progression of degeneration, suggesting that resilience may be an early and transitory state, with most or all neurons eventually succumbing to tau toxicity over time. Notably, these differences in toxicity were not readily explained by variations in hTau abundance and phosphorylation. Together, our findings demonstrate that tau toxicity is highly context-dependent, clearly isoform-specific, and shaped by interactions between tau and its cellular environment.

Human development unfolds in continuous, multimodal environments across seconds, days, and years, yet most developmental datasets capture sparse, context-limited samples of everyday life. We introduce the First 1,000 Days (1kD) Project, an initiative designed to collect ultra-dense, longitudinal, child-centered data that capture developmental trajectories within their full ecological context. Fifteen U.S. homes with 17 infants were recorded 12-14 hours per day over a median of 944 days, yielding [~]1.18 million hours of raw audiovisual data. We present an end-to-end framework for large-scale longitudinal naturalistic measurement and a scalable analysis pipeline of the collected data. In a case study, we describe how we utilized our pipeline to isolate child-centered speech, resulting in the collection of 2,000 to 6,000 hours of transcribed speech for each infant. We demonstrate that dense sampling within the home environment reveals a stable, household-specific lexical structure, which sparse sampling methods consistently fail to capture. The 1kD project offers a blueprint for teams aiming to collect and analyze natural behavior at scale in real-world settings.

Consistent, high-quality data is key to the success of fMRI studies given the many confounding factors and undesired signals that contaminate these data. Several quality assurance (QA) metrics exist for fMRI (e.g., temporal signal-to-noise ratio (TSNR), percent ghosting, motion estimates), but none of them leverage relationships between echoes that are part of multi-echo (ME) fMRI acquisitions. Here, we fill this gap by proposing a new QA metric for for ME-fMRI that quantifies the likelihood a given ME scan is dominated by BOLD (Blood Oxygenation Level-Dependent) fluctuations. We refer to this metric as pBOLD; the probability of the signal change being primarily BOLD contrast-dominated. Having an estimate of overall BOLD weighting - both before and after preprocessing - is meaningful because BOLD is the intrinsic contrast mechanism used in fMRI to infer neural activity. We introduce pBOLD to the neuroimaging community by first describing the theoretical principles supporting the metric. Next, we validate pBOLD efficacy using a small dataset (N=7 scans) of constant- and cardiac-gated scans that have distinct levels of contributing BOLD fluctuations. Third, we apply pBOLD to a larger publicly available ME dataset (N=439 scans), to evaluate six different pre-processing pipelines, and show how pBOLD provides complementary information to TSNR. Our results show that ME-based denoising increases both pBOLD and TSNR relative to basic denoising; however, including the global signal (GS) as a regressor only improves TSNR, but worsens pBOLD. Further analyses looking at the BOLD-like characteristics of the GS and its relationship to cardiac and respiratory traces suggest that the observed decrease in pBOLD is likely due to a decrease in BOLD fluctuations of neural origin contributing to the GS, and not due to contributions from other physiological BOLD fluctuations (i.e., respiratory and cardiac function). Finally, we also demonstrate how pBOLD can be applied as a data quality metric, by showing how higher pBOLD results in better ability to predict phenotypes based on whole-brain functional connectivity matrices.

Retinal degenerative diseases progressively erode the cone photoreceptor mosaic, reducing the retinas spatial sampling power, yet visual acuity is remarkably resilient to cone loss. Prior work has shown that clinically normal visual acuity (20/25 or better) can persist despite up to 50% of cone cells being lost (Ratnam et al. 2013, Foote et al. 2018). However, studies on individuals with retinal degeneration are limited by patient recruitment and cannot control for patients stage of disease progression, creating the need for an experimental paradigm that can mimic these diseases in healthy subjects. The Oz Vision system creates visual percepts through programmable, per-cell stimulation of thousands of cone cells. We reprogram this system to emulate cone loss in healthy eyes by withholding stimulation from a subset of randomly-selected cones, rendering them inactive, in a method we term "cone dropout." Using this approach, we characterize the visual systems robustness to cone loss, showing that visual acuity declines nonlinearly with increasing cone dropout. Importantly, we uncover the compensatory benefit that eye motion provides under cone-deprived conditions, finding that at the highest level of dropout, a visual system with eye motion has an equivalent acuity to a static dropout condition with nearly twice as many sampling elements. Through analysis of eye motion and stimulation data, we find that this benefit arises from the additional information accumulated by "surviving" cones as they sample more of the letter through fixational eye motion.

Quantifying feeding behavior with high temporal and spatial precision is critical for understanding how internal state, sensory cues, and neural activity shape food intake and dietary choice. Here, we describe a detailed protocol for performing consumption and dietary choice assays in Drosophila using the flyPAD/optoPAD system. This method enables simultaneous measurement of feeding events across multiple arenas while allowing precise control of gustatory stimuli and optogenetic stimulation. We provide step-by-step instructions for assay food preparation, flyPAD arena setup, data acquisition, and downstream data organization with suggested analyses. This approach is suitable for studying consumption, nutrient preference, learning, and state-dependent modulation of feeding behaviors, and can be readily adapted for optogenetic manipulations and comparative choice assays.

Quantifying feeding behavior with high temporal and spatial precision is critical for understanding how internal state, sensory cues, and neural activity shape food intake and dietary choice. Here, we describe a detailed protocol for performing consumption and dietary choice assays in Drosophila using the flyPAD/optoPAD system. This method enables simultaneous measurement of feeding events across multiple arenas while allowing precise control of gustatory stimuli and optogenetic stimulation. We provide step-by-step instructions for assay food preparation, flyPAD arena setup, data acquisition, and downstream data organization with suggested analyses. This approach is suitable for studying consumption, nutrient preference, learning, and state-dependent modulation of feeding behaviors, and can be readily adapted for optogenetic manipulations and comparative choice assays.

CRX is a transcription factor essential for photoreceptor differentiation and functional development. Two missense mutations in CRX homeodomain, CRXE80A and CRXK88N, are linked to early-onset dominant retinopathies. Molecular studies have revealed distinct profiles of perturbed gene expression in differentiating photoreceptors of knock-in mouse models, resulting from altered DNA binding activities of mutant CRX proteins. This study characterizes concurrent retinal and vascular alterations in knock-in mouse models. Fated cones are present in heterozygous and homozygous CrxE80A and CrxK88N mutants at birth, but subsequent cone differentiation is rapidly compromised. Expression of rod marker rhodopsin (RHO) is absent in CrxK88N/Nretinae but present in other mutants through adulthood. Notably, as compared to wildtype controls, RHO expression is prematurely activated in neonatal CrxE80A mutants. Among tested mutants, only CrxE80A/+retinae elaborate rod outer segments but still lose visual function by young adulthood. The presence of irregular retinal rosettes is a striking pathological phenotype in all mutants. Retinal rosettes displace the localization of inner neurons without affecting their cell numbers during retinal development. Retinal vessels develop close contact with rosette structures. In summary, disrupted photoreceptor differentiation leads to the loss of visual function and formation of retinal rosettes. The presence of retinal rosettes secondarily impairs the localization of inner neurons and vasculature. A deeper understanding of these cellular underpinnings will inform pathogenesis of CRX homeodomain mutations.

BackgroundNeonatal global hypoxic-ischemic cerebral injury is a leading cause of infant mortality and lifelong disability. Current rodent models do not replicate neonatal global cerebral ischemia (nGCI) and reperfusion injury. Here, we developed and characterized a rodent model of cardiac arrest and cardiopulmonary reperfusion (CA/CPR) to induce nGCI, producing acute systemic ischemia, mild neuronal injury, white matter alterations, and motor and memory deficits. MethodsRat pups underwent CA/CPR or sham procedure on postnatal day 9-11. CA/CPR in rat pups was performed under anesthesia while intubated. Asystole was induced with intravenous (IV) KCl and maintained for 10-14 minutes. Resuscitation included oxygen ventilation, chest compressions, and IV epinephrine. ResultsTwelve minutes of asystole provided an optimal balance between survival and systemic injury. Behavioral testing on postoperative day (POD) 7 revealed memory impairments. Despite the absence of overt neuronal death in the hippocampus or cerebellum, we observed evidence of glial activation and white matter alterations. ConclusionThis novel rodent model of nGCI addresses limitations in existing models while offering clinically relevant features to support future mechanistic and translational research. ImpactO_LIThis study validates cardiac arrest and cardiopulmonary resuscitation (CA/CPR) as a novel model for neonatal global cerebral ischemia (nGCI), complementing existing rodent models of unilateral and permanent injury by enabling investigation of both global ischemia and reperfusion injury. C_LIO_LInGCI results in memory impairment in the absence of overt neuronal cell death. Functional deficits are associated with neuroinflammatory responses in the hippocampus, white matter, and cerebellum. C_LIO_LINeonatal CA/CPR induces global cerebral ischemia which uniquely allows investigation of hindbrain structures, such as cerebellum, which are typically spared in existing rodent models of neonatal hypoxia-ischemia. C_LI

Soluble oligomers and transmembrane channels formed by the 42-residue variant of amyloid beta (A{beta}42) play key roles in Alzheimers disease. Unfortunately, detailed structures of these assemblies have not been determined. Our group addresses this problem by developing atomic scale models. Previously we proposed that both soluble A{beta}42 oligomers and transmembrane channels have symmetric concentric {beta}-barrel structures. Here we expand this hypothesis to include GM1 gangliosides and sometimes cholesterol and lattice models of channel assemblies. The presence of GM1 gangliosides increases the toxicity of A{beta}42, enhances its ability to penetrate liposome membranes, and facilitates interactions between adjacent liposomes. Although the conformations of numerous model assemblies vary, in these models the carboxyl group of GM1 always binds to side-chains of histidine 13 and/or histidine 14. Our soluble oligomer models are consistent with electron microscopy images of beaded annular protofibrils. Our models of membrane-bound assemblies are consistent with the following: freeze-fracture and atomic force microscopy images of A{beta}42 in lipid bilayers, secondary structure results, the calcium hypothesis of Alzheimers Disease, effects of lithium depletion on AD, established {beta}-barrel theory, and energetic criteria.

Chemotherapy-induced neuropathic pain (CINP) is a frequent and debilitating adverse effect of anti-tumor therapies, for which current treatments are largely non-specific and offer limited efficacy. Identifying molecular mechanisms that drive CINP may enable the development of targeted therapeutic strategies. Here, we demonstrate that paclitaxel-induced mechanical pain hypersensitivity in mice occurs independently of classical Nav1.8+ nociceptors but critically depends on TrkB+ sensory neurons. Transcriptomic analysis of TrkB+ sensory neurons revealed selective expression of Scn5a, which encodes the voltage-gated sodium channel Nav1.5, a channel classically associated with cardiac excitability. Importantly, SCN5A expression was also detected in human primary sensory neurons, indicating potential translational relevance. Functional studies further showed that Scn5a knockdown, using small interfering RNA, significantly attenuates paclitaxel-induced mechanical pain hypersensitivity. Together, these findings identify TrkB+ sensory neurons as key drivers of CINP and reveal Nav1.5 as a previously unrecognized contributor to chemotherapy-induced neuropathic pain. Targeting Nav1.5 in TrkB+ sensory neurons may therefore represent a novel therapeutic strategy for the treatment of CINP.

Dexterous hand function underlies many essential human activities, from tool use to expression through gestures. Coordinated digit movements are enabled by the intricate musculature of the hand and forearm, which also imposes mechanical coupling between the digits and wrist, constraining their independent control. It remains unclear whether motor cortex inherits these constraints in its activity or encodes digit and wrist independently. To address this problem, we asked individuals with intracortical microelectrode arrays implanted in motor cortex to attempt flexion and extension of individual digits, either in isolation or in combination with attempted wrist movements. We could accurately decode which digit was moving based on cortical recordings, and channels selective for digit identity were arranged somatotopically across the recording arrays. Nevertheless, the activity during flexion or extension overlapped between digits, and movement direction of a given digit could be reliably inferred by a decoder trained on movements of other digits. This directional signal was largely invariant to the digits initial posture. The population axis describing digit movement direction was aligned with the axes associated with wrist flexion-extension or pronation-supination. This alignment persisted during simultaneous wrist and digit movements, which complicated efforts to control them individually. However, by decoding wrist and digit motion from activity orthogonal to the shared direction axis, a participant was able to achieve continuous control of virtual hand movements with improved speed and reduced unintended movements. Together, the results identify both a code for digit identity and a low-dimensional flexion-extension signal which is shared across the digits and wrist. This arrangement is consistent with muscle-like biomechanical constraints on motor cortical activity, which must be accounted for to improve coordinated BCI control.

Dexterous hand function underlies many essential human activities, from tool use to expression through gestures. Coordinated digit movements are enabled by the intricate musculature of the hand and forearm, which also imposes mechanical coupling between the digits and wrist, constraining their independent control. It remains unclear whether motor cortex inherits these constraints in its activity or encodes digit and wrist independently. To address this problem, we asked individuals with intracortical microelectrode arrays implanted in motor cortex to attempt flexion and extension of individual digits, either in isolation or in combination with attempted wrist movements. We could accurately decode which digit was moving based on cortical recordings, and channels selective for digit identity were arranged somatotopically across the recording arrays. Nevertheless, the activity during flexion or extension overlapped between digits, and movement direction of a given digit could be reliably inferred by a decoder trained on movements of other digits. This directional signal was largely invariant to the digits initial posture. The population axis describing digit movement direction was aligned with the axes associated with wrist flexion-extension or pronation-supination. This alignment persisted during simultaneous wrist and digit movements, which complicated efforts to control them individually. However, by decoding wrist and digit motion from activity orthogonal to the shared direction axis, a participant was able to achieve continuous control of virtual hand movements with improved speed and reduced unintended movements. Together, the results identify both a code for digit identity and a low-dimensional flexion-extension signal which is shared across the digits and wrist. This arrangement is consistent with muscle-like biomechanical constraints on motor cortical activity, which must be accounted for to improve coordinated BCI control.

Only a subset of heroin users develop addiction, characterized by binge-like heroin use and preference for heroin over other rewards, including social rewards. We recently established a rat model of these features. We trained rats to lever-press for social interaction and heroin (or saline, control) infusions and then tested heroin- and social-seeking and heroin-vs.-social choice. During 3-5 abstinence weeks, we used 2-deoxy-2-[{superscript 1}F]fluoro-D-glucose (FDG) PET imaging to assess regional brain metabolic activity at rest (homecage) and during heroin and social seeking. We assessed regional differences in FDG uptake using unbiased voxel-wise analysis and statistical parametric mapping, and correlated FDG uptake with principle-component-analysis-derived addiction severity score incorporating heroin intake, binge-like episodes, and heroin preference. Compared with saline-trained rats, heroin-trained rats showed overall higher FDG uptake across multiple brain regions at rest and during both reward-seeking tests. Comparison of heroin-vs.-social-seeking in heroin-trained rats showed higher uptake in claustrum/lateral striatum and auditory cortex during social seeking. Analysis of individual differences showed that addiction severity was primarily associated with metabolic alterations under resting conditions rather than during heroin- or social-seeking. At rest, higher addiction severity was associated with lower uptake in piriform cortex and higher uptake in ventral hippocampus, whereas during heroin-seeking, addiction severity was associated with lower uptake in post-subiculum and cerebellum. Addiction severity was not associated with differences in social seeking or FDG uptake during social seeking. These findings identify neurometabolic features of social and heroin seeking and heroin addiction vulnerability that can potentially serve as brain biomarkers and targets for neuromodulation. Significance StatementHeroin addiction develops in only a subset of users, yet the determinants of vulnerability versus resilience to addiction remain largely unknown. We combined a rat model capturing key features of heroin addiction, including binge-like heroin intake and preference for heroin over social interaction, with behavioral heroin- and social-seeking assays and longitudinal whole-brain metabolic imaging using FDG-PET. We identified distinct patterns of neurometabolic alterations associated with heroin self-administration and addiction severity at rest and in the context of heroin seeking. In contrast, heroin self-administration and addiction severity were not significantly associated with neurometabolic alterations during social seeking. These findings highlight brain-wide neurometabolic features of vulnerability to heroin addiction that can serve as brain biomarkers and targets for neuromodulation.

The neural bases of long-lasting childhood olfactory memory carrying positive emotions, such as the one evoked by Prousts madeleine, remain poorly understood. To address this, we modeled childhood olfactory memory in mice based on a human survey indicating that our earliest olfactory memory arises from repeated positive experiences paired with a pleasant odorant. Accordingly, mice were exposed during childhood to a pleasant odorant in a playful environment. In adulthood, memory recall relied on neonatal-born granule cells in the olfactory bulb, as their optogenetic silencing impaired retrieval, and on increased functional connectivity in the reward system. With age, memory persistence depended on re-exposure to the childhood odorant and was associated with the disengagement of neonatal-born granule cells, alongside with strengthened limbic functional connectivity. Together, these findings identify neonatal neurons as a key substrate for encoding childhood olfactory memory and reveal dynamic reorganization of brain networks supporting its long-term significance.

Serotonergic psychedelics have attracted considerable interest as promising therapeutic agents. However, the molecular mechanisms linking their acute hallucinogenic-like effects to longer-lasting neuroplastic responses remain incompletely understood, partly because of the scarcity of native neural models suitable for mechanistic studies. Here, we developed a neural stem cell-derived in vitro model capable of differentiating into neuronal and glial lineages and, after characterization, used it to investigate the molecular pharmacology of serotonergic psychedelics. A panel comprising tryptamines, phenethylamines and ergolines, including psychedelic compounds and selected non-psychedelic analogues, was evaluated alongside ketamine and TrkB agonists. Endpoints included dendritogenesis, synaptogenesis, immediate-early gene induction, BDNF expression and lactate production. TrkB silencing abolished dendritogenic responses to serotonergic psychedelics, ketamine and TrkB agonists, whereas 5-HT2A receptor silencing selectively impaired serotonergic psychedelic-induced plasticity and altered TrkB-dependent responses. Most serotonergic compounds also increased synaptogenesis and induced c-Fos and Egr-2 expression, although ligand-specific differences were evident, particularly for psilocin and the phenethylamines DOI and Ariadne. Uncoupling of Gq/11 or Gi/o protein-dependent signaling differentially modified neuroplastic and transcriptional responses, indicating a ligand and endpoint dependent contribution of both pathways. Serotonergic psychedelics further induced a 5-HT2A receptor dependent lactate response that was generally sensitive to disruption of either Gq/11 or Gi/o protein coupling. Taken together, these findings support a model in which serotonergic psychedelics recruit an integrated 5-HT2A-TrkB signaling network with distinct structural, transcriptional and metabolic outputs, and establish this neural stem cell-derived system as a valuable platform for screening and dissecting the signaling basis of psychedelic action.

Receptive fields provide a concise description of the stimulus selectivity of visual neurons. But this stimulus selectivity is neither static nor linear, and these nonlinear effects are not well captured by standard linear or pseudo-linear receptive field models. At the same time, receptive field models incorporating nonlinear effects are largely empirical, and are not easily interpreted in terms of underlying cellular and synaptic mechanisms. Here we show that two nonlinear mechanisms in the primate outer retina shape neural responses and that these contribute significantly to responses to natural stimuli and to the retinal output signals. Incorporating these outer retinal nonlinearities into models for visual function will improve our ability to identify the mechanistic origin of specific features of downstream visual responses.

Motion artifacts remain a barrier to in vivo calcium imaging in Drosophila melanogaster larvae. Here, we evaluate a multimodal immobilization approach that combines a Pluronic F-127 (PF-127) hydrogel with brief diethyl ether vapor exposure (5 minutes, 25{degrees}C) and compare it against hydrogel-only immobilization using custom MATLAB-based analysis software that performs NoRMCorre rigid motion correction. In wide-field GFP recordings at 1 Hz over approximately 60 minutes (N = 15 per group), the multimodal condition significantly reduced motion across all three core metrics after FDR correction (all q < 0.001), with large effect sizes for mean speed (Hedges g = -1.18) and median step size (g = -1.36). In a secondary analysis of the first 30 minutes, uniformly large effect sizes (|g| = 1.10-1.51) were observed, consistent with stronger initial chemical immobilization that partially wanes over the recording period. We implemented a dual-flag quality control system that distinguishes motion data reliability from ROI detection eligibility. Control calcium recordings (33.33 Hz, [~]5 minutes; N = 23) yielded 368 ROIs with a mean SNR 30.4 {+/-} 16.9 and an event rate of 0.228 {+/-} 0.113 Hz. Experimental recordings (N = 21) yielded 295 ROIs with SNR 18.0 {+/-} 10.6 and event rate 0.309 {+/-} 0.188 Hz. SNR was higher in controls (Cliffs{delta} = 0.50, p < 0.001), while event rate was modestly higher in the experimental group at the ROI level ({delta} = -0.22, p < 0.001), though this difference did not reach significance at the sample level, suggesting altered but not suppressed calcium dynamics. These results support a practical, accessible immobilization workflow for larval calcium imaging. HighlightsO_LIBrief ether + hydrogel approach reduces larval motion 85-91% vs. hydrogel alone C_LIO_LIDual-flag QC system separates motion reliability from calcium ROI eligibility C_LIO_LICalcium event rates not suppressed under multimodal immobilization C_LIO_LIComplete MATLAB pipeline for motion analysis and calcium imaging provided C_LIO_LIAccessible protocol requires only standard laboratory supplies C_LI

Reaction time is a measure of the speed of our response to stimuli in the environment. Even for a well-trained task, a subjects reaction time varies. One source of this variability is internal state fluctuations (such as changes in arousal). There are few studies that systematically quantify the extent to which reaction time varies across different timescales and link this to measures of systemic physiology associated with arousal. In much of the literature, it is assumed but not demonstrated that behavioral and systemic measurements associated with arousal will be consistently linked because both estimate a common underlying arousal process. In this work, we examined this assumption by simultaneously measuring reaction time, heart rate, and pupil diameter in rhesus macaque monkeys performing several visual tasks over hours and across hundreds of sessions. We found a portion of the variability in reaction time could be linked to systemic physiological signatures of arousal on fast timescales from second to second and slower timescales from minute to minute. This link between reaction time and systemic physiology was also present for different biomarkers of arousal (heart rate and pupil). However, the strength of this relationship varied depending on the arousal biomarker. Our findings support the conclusion that there are multiple arousal mechanisms that act simultaneously to influence behavior and multiple timescales at which they operate.

Behaviour is adaptive: To survive, organisms must continuously adjust their actions to their physiological needs. Yet, core behavioural dimensions such as impulse control and motivation are often treated as enduring traits, overlooking their dynamical regulation by physiological states. Here, we investigated how short-term energy deficits induced by fasting interact with longer-term energy reserves to shape human behavioural control. In healthy participants, fasting increased impulsivity selectively for food rewards, an effect attenuated by body fat percentage. Fasting also robustly increased effort expenditure across reward domains, indicating a domain-general motivational effect best predicted by relative energy deficit. Neither effect was explained by changes in subjective valuation. While self-report questionnaires of motivational, impulsivity, and eating-related traits captured stable behavioural tendencies and their association with body composition, they failed to account for state-dependent fluctuations. Together, these findings demonstrate that impulse control and motivation are flexibly regulated by the interaction of transient with sustained energy states, challenging trait-based accounts of human decision-making and highlighting its adaptive, state-dependent nature.

Male parenting behavior is highly conserved and activated only after offspring are born. Here we show that the behavioral switch from infanticide in virgin male mice to caregiving in wild-type sires is associated with enhanced expression and activation of Transient receptor potential channel 5 (Trpc5) in estrogen receptor (Esr1)-expressing neurons in the hypothalamic medial preoptic area (MPOA). While selective deletion of Trpc5 from Esr1MPOA neurons diminishes paternal behavior in sires, overexpression of Trpc5 in these neurons converts the otherwise infanticidal virgin males to exhibit care to pups. Mechanistically, Trpc5-dependent changes in neuronal excitability underlie fatherhood-associated Esr1MPOA neuron plasticity. Notably, Trpc5 overexpression also enhances escape behavior and elicits exploratory diving behavior, suggesting that these neurons control a broader adaptive parenting response in males. These findings establish a Trpc5-dependent MPOA neural signal as a critical regulator of paternal behavior.

SCN2A-related neurodevelopmental disorders comprise a genetically and mechanistically diverse group of early-onset brain conditions. Loss-of-function (LoF) variants in SCN2A represent one of the strongest genetic risk factors for autism spectrum disorder and intellectual disability, yet the molecular cascade linking reduced NaV1.2 dosage to neuronal dysfunction remains poorly understood. Here, we combine deep isoform-resolved transcriptomics, high-content imaging, and high-content cellular phenotyping in human hiPSC-derived neurons from three unrelated individuals carrying pathogenic SCN2A LoF variants and three independent healthy donor lines to delineate the multi-layered consequences of NaV1.2 insufficiency. We show that SCN2A LoF activates the nonsense-mediated decay (NMD) mechanism, selectively depleting canonical SCN2A isoforms and modifying the cells RNA processing. These molecular deficits translate into robust structural phenotypes, including axon initial segment shortening, reduced sodium channel density, and simplified dendritic arborization. Transcriptomic analysis converged on remodeling of synaptic and axonal pathways. RNA-seq identified coordinated alterations in gene programs linked to synaptic signaling, ion channel activity, and neuronal projection development, consistent with the structural and functional phenotypes observed. Transcript-level analysis further uncovered extensive perturbation of long non-coding RNA (lncRNA) networks, including lncRNAs strongly correlated with SYN1 and ANK3 isoforms. Together, these findings reveal that SCN2A haploinsufficiency induces a phenotype spanning NMD activation, isoform-specific dysregulation, axon initial segment destabilization and lncRNA-dependent regulatory shifts. This multiscale framework clarifies how reduced NaV1.2 disrupts neuronal development and highlights isoform-level restoration and modulation of post-transcriptional control as promising therapeutic avenues for SCN2A-related neurodevelopmental disorders.

Functional near infrared spectroscopy (fNIRS) is increasingly used in hearing and communication research, with advantages such as robustness to movement artifacts, improved spatial resolution, and flexibility of contexts in which it can be applied. At the same time, the field is progressively moving towards more continuous, naturalistic listening paradigms resulting in the widespread adoption of speech tracking analyses such as temporal response functions (TRFs) in electroencephalography (EEG) and magnetoencephalography (MEG) studies. However, it remains unclear whether these analyses can be applied to slower haemodynamic signals measured by fNIRS. In the present study, we investigated whether a TRF framework can similarly be applied to fNIRS data recorded during continuous speech perception. Eight participants listened to speech simultaneously while fNIRS signals were acquired in a hyperscanning setup. Speech features were regressed onto the haemodynamic responses to test the feasibility and interpretability of fNIRS-based TRFs. Prediction correlations between observed and modelled fNIRS signals across speech features were higher than those typically reported for EEG- and comparable to those reported for MEG-TRF studies. Moreover, these correlations did not overlap with a null distribution generated from triallJmismatched fNIRS data, confirming statistical significance and were slightly greater than those obtained from a conventional GLM approach. Our findings support that TRF estimation method can yield meaningful and statistically significant responses from fNIRS data. HighlightsO_LITRF modelling can be meaningfully applied to fNIRS data acquired during speech listening tasks. C_LIO_LIPrediction correlations between actual and modelled fNIRS signals were above chance level, with values comparable to previous EEG/MEG studies. C_LIO_LITRFs explained more fNIRS variance than a conventional GLM approach. C_LI

Across brain regions and behaviors, neural population activity unfolds as temporally structured sequences that underlie perception, memory, and precisely timed actions1-10. However, how neural circuits transform continuous information streams into transient patterns of activity over time remains poorly understood. A long-standing hypothesis for cerebellar learning posits that the granule cell (GC) layer segments sensory and motor information arriving via mossy fibers (MFs) into temporal basis sets that enable precisely timed motor and cognitive commands11-15. Measurements of such basis sets have been elusive. Using high-speed multiphoton calcium imaging of MF and GC responses to whisker air puff stimulation, we show that prolonged MF activity is transformed into temporally sharpened GC responses that form a sparse population sequence tiling the sensory event in time. Temporal sparsity of GC sequences varied between cerebellar regions. By combining in vivo glutamate imaging with ex vivo synaptic recordings, we identify heterogeneous MF-GC synaptic strength and short-term plasticity as the mechanisms underlying region-specific temporal sparsification. Mathematical modeling predicted that region-specific MF-GC synaptic dynamics generate temporally sparse GC sequences with distinct statistics specifically suited for learning across different timescales. Thus, heterogeneous synaptic dynamics provide a biological substrate for shaping population activity in time, setting the temporal precision of sensorimotor associations underlying adaptive behavior. One-sentence summaryDiverse short-term synaptic dynamics transform input activity patterns into temporally sparse neural sequences in the cerebellar cortex, providing a mechanistic basis for precise temporal learning.

The human brain varies from person to person in ways that shape behaviors and vulnerabilities, yet the cellular and molecular bases for inter-individual variation are largely unknown. Here we describe an analysis of cellular and gene-expression variation in four key structures of the striatum complex - the caudate, putamen, nucleus accumbens, and internal capsule - as well as the prefrontal cortex, from single-nucleus RNA-seq analysis of 3.9 million nuclei from 178 adult brain donors. We found that people with more astrocytes in any one brain region tended to have this property in all brain regions sampled; the same was true of striatal interneurons, microglia, and oligodendrocyte precursor cells (OPCs). OPCs showed attrition with age, declining in numbers by approximately 40% between age 30 and age 80 in both gray matter and white matter regions. We identified thousands of age-associated (but few sex-associated) variations in gene expression; the vast majority of these effects of age were cell-type-specific. Aging most strongly affected gene expression in projection neurons - especially striatal medium spiny neurons (MSNs/SPNs) - and had a much smaller effect on gene expression in interneurons. Individuals ages could be predicted to within about five years based on RNA-expression patterns from any of the striatal cell types. Common genetic variants detectably affected the expression levels of some ten thousand genes; the great majority of these effects were cell-type-specific. These data will provide a foundation for exploring natural inter-individual variation, aging, and tissue-based studies of human brain vulnerabilities.

The coupling between brain excitatory activity and positive blood oxygen level-dependent (BOLD) responses is well-established. Although often associated with inhibition, negative BOLD remains partially understood. Moving away from neurovascular coupling, apparent diffusion coefficient (ADC)-fMRI provides a more direct measure of excitatory activity, possibly mediated by transient cellular deformations. While decreases in ADC align with positive BOLD, the possible translation of negative BOLD into positive ADC has not been investigated in humans. Diffusion-weighted fMRI (dfMRI) combines vascular and microstructural contributions. Using interleaved subthreshold transcranial magnetic stimulation (TMS)-fMRI on the primary motor cortex (M1), we induced negative BOLD responses in contralateral M1 and primary somatosensory cortex (S1). This was accompanied by a negative dfMRI response, but no ADC-fMRI response, indicating minimal microstructural fluctuations. In ipsilateral M1/S1, no BOLD response was detected while dfMRI revealed a positive cluster, suggesting sensitivity to subtle neural activity. These findings provide new insights into vascular and neuronal responses underlying subthreshold TMS and negative BOLD.

AO_SCPLOWBSTRACTC_SCPLOWMastering a perceptual skill requires maintaining high-fidelity information in the cortex to support task-relevant behavior. Yet it remains unclear how sensory and higher-order cortices jointly support this maintenance, and how experience reshapes their respective contributions. To address these questions, we trained participants on visual motion discrimination and measured sensory and mnemonic neural codes using a delayed discrimination paradigm. After learning, fMRI activation patterns in V1 exhibited enhanced sensory fidelity during the retention period, which predicted individual learning effect. In contrast, mnemonic information in the intraparietal sulcus (IPS) decreased after learning. Moreover, learning aligned the temporal dynamics between the sensory and mnemonic representations in V1. These results suggest that perceptual learning reallocates mnemonic resources from higher-order parietal regions toward high-fidelity sensory maintenance in early visual cortex, thereby optimizing the cortical implementation of visual working memory.

Some images are consistently remembered better than others, suggesting that memorability reflects intrinsic image properties. We tested whether within-category distinctiveness underlies this effect. Across three experiments (N = 477), participants categorized indoor scenes previously rated for subjective typicality and then completed recognition memory tests. Typical scenes were categorized faster and more accurately, but were remembered worse and showed a more liberal response bias than atypical scenes. These opposing effects were robust across categories. To link subjective typicality to visual representations, we quantified image distinctiveness using a convolutional neural network (CNN). Across layers, CNN-derived distinctiveness closely tracked human typicality judgments and predicted both categorization speed and memorability, with strongest effects in higher, semantic layers. Critically, the memory advantage for atypical scenes persisted even when most images were atypical, ruling out rarity within the experimental context. Together, the results show that intrinsic scene memorability reflects an images position within a category-specific representational space.

IntroductionThe exploration of alternative strategies for neural tissue regeneration and repair is giving rise to a novel paradigm in neurosurgery: fusogenic therapy. This approach promises rapid restoration of peripheral nerve and spinal cord function by circumventing Wallerian degeneration and eliminating the delay associated with axonal regrowth. Its potential stems from the capacity of fusogens to induce axonal fusion and achieve immediate membrane sealing, complemented by their pronounced neuroprotective properties. However, experimental data on fusogens and their effects are inconsistent, often contentious, and derived using heterogeneous methodologies. MethodsWe present the first comprehensive systematic review covering nearly four decades of research on fusogens for axonal membrane repair and 26 years of their experimental and clinical application in mammalian and human models for peripheral and central nervous system restoration. The review includes a meta-analysis of fusogen efficacy following traumatic spinal cord and peripheral nerve injuries. ResultsConducted in accordance with the PRISMA 2020 flow protocol and PICO criteria, our analysis incorporates 86 sources, 20 of which were included in the meta-analysis. DiscussionIn summary, we have systematized the prevailing approaches and methods for fusogen application, delineated key contentious issues, and identified promising directions for the development of axonal fusion technology.

More than 30% of stroke survivors develop post-stroke cognitive impairment (PSCI), for which current neuron-centric therapies not only lack cellular specificity but also carry risks of adverse effects such as epilepsy. Here, we explore the therapeutic potential of astrocytes by chemogenetically activating Gq signaling in hippocampal astrocytes, which rescues memory deficits and synaptic plasticity impairments in a mouse model of ischemic stroke. Gq activation restores dendritic complexity, spine density, and long-term potentiation in hippocampal CA1 neurons. Fiber photometry further reveals that astrocytic Ca2+ signals precede neuronal activity by 600 ms during novel environment exploration, indicating that astrocytes prime memory encoding. In contrast, Gi pathway activation induces pathological neuronal hyperactivity without cognitive improvement. These findings establish that astrocytes regulate post-stroke recovery through pathway-specific calcium signaling and uncover a previously unknown temporal hierarchy in astrocyte-neuron communication during memory processing, offering a new glia-targeted strategy to overcome the limitations of current neuromodulation approaches for PSCI. TeaserTargeting astrocyte calcium signaling rescues memory deficits after stroke by restoring synaptic plasticity and revealing astrocytes priming role in memory encoding.

Amyotrophic lateral sclerosis (ALS) is a motor neuron (MN) disease characterized by profound alterations in energy metabolism and progressive degeneration of MNs. Evidence from patients and model systems point to MN hyperexcitability as an early hallmark of ALS. How altered electrical activity intersects with energy metabolism, however, remains largely unexplored. To directly examine this relationship, we performed long-term longitudinal recordings of neuronal firing and mitochondrial function in patient-derived MNs harboring the pathogenic TDP-43 mutation A382T, together with their isogenic controls. A382T MNs displayed an early, transient phase of hyperexcitability peaking around 35 days in culture, which was also observed in MNs carrying a different TDP-43 disease variant (M337V). This hyperexcitable phase coincided with elevated mitochondrial function (hyperpolarized membrane potential and accelerated electron flow across respiratory complexes) and was ultra-sensitive to mild Fo/F1 ATPase inhibition, revealing near maximal mitochondrial output to meet increased energy demands. This phase was followed by a sharp decline in A382T MN firing frequency, mitochondrial depolarization, and the loss of approximately 50% of firing-competent neurons. Acute bidirectional manipulations of MN firing rates elicited homeostatic mitochondrial responses, further demonstrating tight coupling between neuronal activity and mitochondrial metabolism. Together, these findings uncover a pathological trajectory in which early hyperexcitability drives mitochondrial hypermetabolism, with progressive erosion of mitochondrial capacity, ultimately leading to late-stage MN failure.

Amyotrophic lateral sclerosis (ALS) is a motor neuron (MN) disease characterized by profound alterations in energy metabolism and progressive degeneration of MNs. Evidence from patients and model systems point to MN hyperexcitability as an early hallmark of ALS. How altered electrical activity intersects with energy metabolism, however, remains largely unexplored. To directly examine this relationship, we performed long-term longitudinal recordings of neuronal firing and mitochondrial function in patient-derived MNs harboring the pathogenic TDP-43 mutation A382T, together with their isogenic controls. A382T MNs displayed an early, transient phase of hyperexcitability peaking around 35 days in culture, which was also observed in MNs carrying a different TDP-43 disease variant (M337V). This hyperexcitable phase coincided with elevated mitochondrial function (hyperpolarized membrane potential and accelerated electron flow across respiratory complexes) and was ultra-sensitive to mild Fo/F1 ATPase inhibition, revealing near maximal mitochondrial output to meet increased energy demands. This phase was followed by a sharp decline in A382T MN firing frequency, mitochondrial depolarization, and the loss of approximately 50% of firing-competent neurons. Acute bidirectional manipulations of MN firing rates elicited homeostatic mitochondrial responses, further demonstrating tight coupling between neuronal activity and mitochondrial metabolism. Together, these findings uncover a pathological trajectory in which early hyperexcitability drives mitochondrial hypermetabolism, with progressive erosion of mitochondrial capacity, ultimately leading to late-stage MN failure.

A widely used framework for studying the computational mechanisms of decision making is the Drift Diffusion Model (DDM). To account for the presence of both fast and slow errors in empirical data, the DDM incorporates across-trial variability in parameters such as the drift rate and the starting point. Although these variability parameters enable the model to reproduce both fast and slow errors, they rely on the assumption that over trials each parameter is independently sampled. As a result, the DDM effectively predicts that errors-- whether fast or slow--occur randomly over time. However, in empirical data this assumption is violated, as error responses are often temporally clustered. To address this limitation, we introduce the autocorrelated DDM, in which trial-to-trial fluctuations in drift rate, starting point, and boundary evolve according to first-order autoregressive (AR1) processes. Using simulations, we demonstrate that, unlike the across-trial variability DDM, the autocorrelated DDM naturally accounts for temporal clustering of errors. We further show that model parameters can be reliably recovered using Amortized Bayesian Inference, even with as few as 500 trials. Finally, fits to empirical data indicate that the autocorrelated DDM provides the best account of error clustering, highlighting that computational parameters fluctuate over time, despite typically being estimated as fixed across trials.

Modeling individual brain dynamics from resting-state fMRI (rs-fMRI) remains challenging due to substantial inter-subject variability, measurement noise, and limited data length per subject. Here, we systematically evaluate a hierarchical dynamical systems framework based on shallow piecewise-linear recurrent neural networks (shPLRNNs) for individualized modeling of rs-fMRI data, with a particular focus on reproducing subject-specific functional connectivity (FC). We applied the framework to 1,423 rs-fMRI samples from healthy participants of the Marburg-Munster Affective Disorders Cohort Study (MACS). Simulated rs-fMRI data robustly reproduced empirical FC patterns, with comparable reconstruction accuracy on training and independent validation sets. Generalization to unseen individuals was heterogeneous and strongly depended on how typical a subjects connectivity pattern was relative to the training cohort, with template similarity explaining 37% of variance in reconstruction accuracy. Learned subject-specific parameters exhibited significant test-retest stability and higher within-subject than between-subject similarity on longitudinal data from two different timepoints, supporting their interpretation as individualized dynamical markers. Associations between individual parameters and demographic or cognitive variables were statistically significant but modest in effect size, and predictive performance remained below that obtained using empirical rs-fMRI features directly. Together, these results demonstrate that hierarchical shPLRNNs can extract meaningful and stable individual-specific dynamical structure from rs-fMRI data, while highlighting current limitations in capturing fine-grained individual differences. The findings delineate key trade-offs between model expressivity, generalization and subject specificity, and point to directions for future methodological refinement in individualized brain modeling.

The nuclear receptor Nurr1 (NR4A2) is an essential transcription factor that governs the differentiation, maturation, and long-term maintenance of midbrain dopaminergic (mDA) neurons in the substantia nigra. Reduced Nurr1 expression has been closely linked to age-related dopaminergic neuronal loss and the pathogenesis of Parkinsons disease. However, the molecular mechanisms regulating Nurr1 expression and protein stability in the aging midbrain remain poorly understood. Here, we identify Janus kinase 2 (JAK2) as a previously unrecognized regulator of Nurr1 in mDA neurons. In the substantia nigra of aged mice (12-and 18-month-old), JAK2 was robustly expressed in Nurr1-positive mDA neurons, whereas its expression was minimal in young adult mice. In SK-N-BE(2)C neuroblastoma cells, overexpression of JAK2 modestly enhanced Nurr1 transcriptional activity, while the constitutively active mutant JAK2V617F markedly increased it. Notably, this effect was not blocked by pharmacological inhibition of STAT, PI3K, or Akt signaling pathways, indicating that JAK2 regulates Nurr1 independently of canonical JAK/STAT or PI3K/Akt signaling. Mechanistically, JAK2 did not promote tyrosine phosphorylation of Nurr1 but instead physically interacted with Nurr1, leading to enhanced nuclear stability of the Nurr1 protein. Consistent with this mechanism, expression of JAK2V617F increased Nurr1 protein levels without altering its mRNA expression. Functionally, co-expression of JAK2V617F and Nurr1 attenuated oxidative stress-induced cytotoxicity and reduced reactive oxygen species accumulation. Together, these findings reveal a phosphorylation-independent mechanism by which JAK2 stabilizes Nurr1 protein and enhances its transcriptional activity. Our results further suggest that age-associated induction of JAK2 in dopaminergic neurons may promote neuronal resilience by maintaining Nurr1 protein stability during aging.

Central pacemaker neurons use a combination of external stimuli and neuropeptide signaling to synchronize molecular oscillations leading to circadian behaviors. The clock network structure and signaling between these pacemaker neuron groups have been well described, but how these pacemakers communicate with specific brain output regions remains poorly understood. Here, we identified how "core" clock neurons in Drosophila, the ventrolateral neurons (LNvs), signal to the proto-hypothalamic region, the pars intercerebralis (PI). Previously thought to communicate with the PI only indirectly, we provide evidence to show that LNvs functionally modulate insulin-producing cells (IPCs) of the PI in a time-of-day-dependent manner. This functional connectivity relies on neuropeptidergic signaling of two classical clock neuropeptides: pigment dispersing factor (PDF) and short Neuropeptide F (sNPF). Connectomic analysis does not identify any direct synaptic inputs from clock neurons to IPCs. Small ventrolateral clock neurons, which secrete both PDF and sNPF are 15-20 m away from IPCs, suggesting that volume transmission across these distances may be possible in the fly dorsal protocerebrum. Peptide application with functional imaging of IPCs provides insight into how these two neuropeptides may act synergistically via their receptors to signal to IPCs. Our findings indicate that LNvs can signal directly to IPCs by volume transmission and also form indirect multisynaptic circuits with IPCs, which may model more broadly how circadian clock peptides communicate with other clock output regions. Author SummaryCircadian clocks in the brains of animals from flies to humans allow animals to anticipate daily environmental changes and temporally coordinate internal processes. The central clock in the brain serves as a master pacemaker that sets the pace of circadian clocks in all other tissues. Fruit flies have been an essential model system for discovering the genetic and cellular underpinnings of circadian rhythms, with work in flies being awarded the 2017 Nobel Prize in Physiology or Medicine. Brain clocks in flies and mammals use classical synaptic communication and neuromodulatory peptides to signal between the neurons that make up the brain clock. Our study asks whether the neuropeptides that signal between clock neurons also signal from clock to non-clock neurons. We found that the signature fly clock neuropeptide pigment dispersing factor signals outside the brain clock to insulin producing cells of the brain. There are no synaptic connections from clock neurons to insulin producing cells, instead signaling occurs by diffusion of peptide signals across tens of microns, termed volume transmission. Our findings point to the possibility that neuropeptide volume transmission may be a general feature not only of intra-clock signaling but also of brain clock output signaling to non-clock neurons.

Exploration allows animals to gather information and adapt to changing conditions. Yet, it also exposes them to potential threats, requiring neural systems that weigh uncertainty and regulate behavioral transitions between cautious and exploratory states. These computations are distributed across cortical and subcortical networks, including the basal ganglia, which integrate sensory, motivational, and contextual information to shape action-selection behaviors. Within this circuitry, the globus pallidus externa (GPe) occupies a central but underappreciated role. Once viewed as a relay between striatum and downstream nuclei, the GPe is gaining recognition as a dynamic regulator that integrates diverse inputs and exerts bidirectional control over motor and cognitive processes. Here, we examine arkypallidal NPAS1-expressing GPe (GPeNPAS1) neurons, which form preferential inhibitory projections to the striatal matrix. Chemogenetic manipulations and in vivo calcium measurement reveal that GPeNPAS1 activity modulates and encodes risk-taking behavior sequences, identifying a circuit mechanism by which the GPe can regulate adaptive decision-making in risky contexts.

Subcellular localization of mTOR is thought to be key for regulating cell size and growth, but the relative contributions of mRNA versus protein localization are unclear. We used reporter mRNA localization assays to identify two distinct mTOR Localizing Sequences (MLS) in its 5UTR, in addition to the localization activity already reported for the 3UTR. Gene-edited mice with deletion of both 5UTR MLS are mTOR hypomorphs with reduced body weight and brain size. In contrast, a mouse line lacking the second 5UTR MLS and the 3UTR retains near normal overall mTOR expression levels with specific subcellular perturbation of mTOR localization to neuronal axons. This subcellular mTOR deficit affects axonal local protein synthesis and neuronal growth. Thus, mTOR transcripts are localized by multiple UTR sequences, and subcellular localization of mTOR mRNA regulates local protein synthesis and neuronal growth.

Hierarchy in the brain emerges across spatial and temporal scales, enabling transformations from rapid sensory encoding to sustained cognitive control. Hierarchical gradients are well established in sensory systems. In contrast, the hierarchical organization of the primate motor cortex remains debated, partly due to its agranular architecture and the absence of clear laminar input-output projections, that obscures the distinction between feedforward and feedback pathways. In particular, the relative hierarchical position of the dorsal premotor cortex (PMd) and the primary motor cortex (M1) cannot be resolved from anatomy alone. To investigate their relative organization, we here adopted a multimodal approach using intrinsic timescales derived from both single-unit spiking activity (SUA) and local field potentials (LFPs) in macaques performing a delayed-match-to-sample reaching task. We found convergent evidence for inter-areal temporal hierarchy, with longer spiking timescales and smaller LFP aperiodic spectral exponents in M1. Across cortical depth, however, temporal organization depended on signal modality. LFP spectral exponents were significantly smaller in deep than superficial layers in both areas, and LFP-autocorrelation timescales were longer in deep layers in M1. In contrast, spiking activity did not show significant laminar differences in intrinsic timescales. Functionally, neurons with longer timescales exhibited more stable representations of the planned movement direction during motor preparation in PMd and slower temporal evolution of movement encoding during execution in both areas. In conclusion, multimodal temporal measures converge on the same hierarchical organization across these two motor areas, with M1 placed higher than PMd. Our study provides the first characterization of intrinsic spiking timescales across cortical layers in any cortical area and shows that laminar temporal organization depends on the neural signal analyzed. This divergence likely reflects their distinct physiological origins. Spikes capture neuronal output, whereas LFPs primarily reflect synaptic and dendritic population activity, potentially integrating differential contributions from apical and basal dendritic inputs.

Cerebellar ataxias are a rare group of disorders manifesting with motor incoordination and cognitive-affective deficits of variable severity. Although neurogenetic has revealed multiple mutations, the study of ataxias still relies on clinical evaluation, while the underlying neural network changes remain unclear. It has been argued that the less severe symptoms in congenital (like Joubert syndrome, JS) than in slowly progressive (SP) ataxias reflect a different interplay of alteration and compensation but direct evidence is still lacking. Moreover, it is unclear why, in front of a wide heterogeneity of molecular alterations, SPs show common clinical symptoms. To address these questions, we created brain digital twins for each participant by combining volumetry, graph theory analysis of structural and functional connectivity, and dynamical simulations using the virtual brain. We studied 8 JS (3 females, 21{+/-}6years), 8 SP (3 females, 20{+/-}5years) and 11 healthy controls (HC; 5 females, 21{+/-}2years).Volumetry quantified atrophy, graph metrics (centrality, segregation and integration) characterized topology, and neural dynamical simulations estimated excitation/inhibition balance, providing anatomo-physiological parameters within the somatomotor (SMN) and ventral attention (VAN) networks. Anatomo-physiological parameters were correlated with clinical/neuropsychological scores, and unsupervised clustering was applied to assess whether network features can discriminate between JS and SP beyond clinical classification. MRI morphometry confirmed selective vermis reduction in JS and a widespread cerebellar atrophy in SP compared to HC. In both ataxia groups, SMN and VAN showed reduced volume and structural connectivity but with different patterns of topological and dynamical alterations. In the SMN of SP, reduced centrality and excitation/inhibition balance depressed information transfer through the network. In the VAN of JS, reduced centrality, segregation, and integration, were detrimental but coexisted with a higher number of functional core nodes and an increased large-scale excitatory coupling, supporting compensatory reorganisation in extracerebellar nodes. Clustering confirmed that SMN better differentiates SP, whereas VAN better clusters JS. Importantly, anatomo-physiological parameters of network volume, topology, and dynamics correlated with patients motor and cognitive performance. In conclusion, primary cerebellar damage secondarily impacts large-scale brain networks, altered in both ataxia groups but compensated only in JS. Similar clinical symptoms in SP reflects the similarity of network changes, while differential involvement of SMN and VAN in JS and SP reflects the connectivity pattern of the lesioned areas inside these large-scale brain circuits. Importantly, anatomo-physiological parameters are sufficient to explain individual motor and cognitive performance, offering a basis for improved patient profiling and personalized therapies.

Many functional magnetic resonance imaging (fMRI) studies conclude that two conditions engage "overlapping, yet partly distinct" patterns of activation. Yet, there is currently no commonly accepted method for determining the extent of this overlap. While correlations between activation patterns can serve as a measure of their correspondence, empirical correlations are strongly biased towards zero due to measurement noise, preventing their use in testing hypotheses about the actual degree of pattern correspondence. In this paper, we derive the maximum-likelihood estimate for the correlation of the true (noise-less) activation patterns and examine its behavior in the low signal-to-noise regime that is typical for fMRI studies. We show that although the maximum-likelihood estimate corrects for much of the influence of measurement noise, it is ultimately biased. We examine different ways of drawing inferences about the size of the underlying true correlations. We find that a subject-wise bootstrap on the maximum-likelihood group estimate performs best over the tested conditions. We extend the proposed method to test more general hypotheses about the representational geometry of activation patterns for more conditions, and highlight best practices, as well as common pitfalls and problems, in testing such hypotheses.

Many functional magnetic resonance imaging (fMRI) studies conclude that two conditions engage "overlapping, yet partly distinct" patterns of activation. Yet, there is currently no commonly accepted method for determining the extent of this overlap. While correlations between activation patterns can serve as a measure of their correspondence, empirical correlations are strongly biased towards zero due to measurement noise, preventing their use in testing hypotheses about the actual degree of pattern correspondence. In this paper, we derive the maximum-likelihood estimate for the correlation of the true (noise-less) activation patterns and examine its behavior in the low signal-to-noise regime that is typical for fMRI studies. We show that although the maximum-likelihood estimate corrects for much of the influence of measurement noise, it is ultimately biased. We examine different ways of drawing inferences about the size of the underlying true correlations. We find that a subject-wise bootstrap on the maximum-likelihood group estimate performs best over the tested conditions. We extend the proposed method to test more general hypotheses about the representational geometry of activation patterns for more conditions, and highlight best practices, as well as common pitfalls and problems, in testing such hypotheses.

Hippocampal pyramidal neurons function as place cells, showing location-specific activity during navigation, to form an internal spatial map of the environment. They are hypothesized to be the neural substrate of episodic memory. However, place cell receptive fields tend to drift or have poor tuning in low demand tasks, lacking operant goals such as random foraging, or in sensory context-deprived environments. Through chronic two-photon calcium imaging of hippocampal area CA1, we directly compare stability in a low versus a high demand task within the same animals over the course of learning and recall in the same environment. We find that compared to random foraging, an odor-context based navigational task stabilizes place cell representations and increases place cell quality and quantity. To investigate the circuit mechanism that may support this stability, we manipulated the activity of lateral entorhinal cortex (LEC) excitatory neurons, which provide both indirect and direct multisensory inputs about context, odor, and time to CA1. We chemogenetically suppressed activity of excitatory neurons in LEC during recall of the odor-context based navigation task and found that context discrimination is impaired at both the behavioral and neural level. With LEC silencing, mice had lower behavioral performance, less stable population activity, and greater similarity between opposing trial types. Our study finds that increasing task demand increases CA1 stability and that this stability is partially supported by LEC.

ObjectiveImpaired blood flow has recently been recognized as a critical contributor to cognitive impairment and dementia. It was reported that cerebral distal arterial flow measured from Simultaneous Non-contrast Angiography and Intraplaque Hemorrhage (SNAP) MRI is associated with post-treatment cognitive function improvement in carotid atherosclerosis patients. In this study, we aim to evaluate the value of SNAP-based measurements in assessing cerebrovascular function in an aging population. Materials and MethodsNeurovascular MRI data were collected on 36 aging participants (22 cognitively unimpaired and 14 impaired; 9 mild cognitive impairment (MCI) and 5 Alzheimers Disease (AD)). Neurovascular MRI measurements, including white matter hyperintensities (WMH) volumes, cerebral blood flow (CBF), and SNAP-based distal cerebral arterial flow (dCAF) index, were quantified. Cognitive function was assessed using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). ResultsSignificant differences in the dCAF index were observed between cognitively unimpaired and impaired groups, and the dCAF index was significantly correlated with the RBANS total score. While CBF was significantly associated with dCAF index, there is no significant correlation of CBF or WMH with the RBANS score in this population. ConclusionOur findings suggest that the dCAF measured with SNAP MRI is valuable for evaluating the cognition-related cerebrovascular condition in an aging population.

ObjectiveImpaired blood flow has recently been recognized as a critical contributor to cognitive impairment and dementia. It was reported that cerebral distal arterial flow measured from Simultaneous Non-contrast Angiography and Intraplaque Hemorrhage (SNAP) MRI is associated with post-treatment cognitive function improvement in carotid atherosclerosis patients. In this study, we aim to evaluate the value of SNAP-based measurements in assessing cerebrovascular function in an aging population. Materials and MethodsNeurovascular MRI data were collected on 36 aging participants (22 cognitively unimpaired and 14 impaired; 9 mild cognitive impairment (MCI) and 5 Alzheimers Disease (AD)). Neurovascular MRI measurements, including white matter hyperintensities (WMH) volumes, cerebral blood flow (CBF), and SNAP-based distal cerebral arterial flow (dCAF) index, were quantified. Cognitive function was assessed using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). ResultsSignificant differences in the dCAF index were observed between cognitively unimpaired and impaired groups, and the dCAF index was significantly correlated with the RBANS total score. While CBF was significantly associated with dCAF index, there is no significant correlation of CBF or WMH with the RBANS score in this population. ConclusionOur findings suggest that the dCAF measured with SNAP MRI is valuable for evaluating the cognition-related cerebrovascular condition in an aging population.

The muscarinic acetylcholine receptor 1 (mAChR1, M1) has been identified as a primary target for Alzheimers disease (AD) and better understanding of the receptor biology, especially in regard to biased signalling of the receptor, will allow for the development of improved drugs targeting cholinergic dysfunction in AD. The aim of this study was to determine the contribution of phosphorylation of M1 to the learning and memory (LM) effects of M1 agonism. The contribution of M1 phosphorylation dependent signalling in LM was assessed using the mAChR1 positive allosteric modulator, VU0486846, in a scopolamine (1.5 mg/kg) induced LM deficit model in mice expressing HA-tagged M1 (M1-WT), phosphorylation deficient HA-tagged M1 (M1-PD), or mice deficient in M1 (M1-KO). LM was assessed using a fear conditioning (FC) testing paradigm where context and cued memory retrieval was measured 24 hrs after training and a higher level of freezing indicated intact memory. Results demonstrated that scopolamine induced a significant LM deficit in both context and cued retrieval in M1-WT mice which was partially rescued by VU0486846 confirming a contribution of M1 signalling in LM. The scopolamine induced deficit in contextual retrieval in M1-KO mice was not rescued by VU0486846, which is an M1 selective ligand, while scopolamine did not induce a deficit in cued retrieval in M1-KO mice. In M1-PD mice, scopolamine induced a LM deficit in contextual retrieval, however this was also not rescued by VU0486846 treatment. Similarly to M1-KO animals, M1-PD mice did not display a scopolamine induced deficit in cued retrieval. When freezing responses were compared across strains, M1-PD mice displayed a deficit compared to M1-WT and M1-KO mice in contextual retrieval, while both M1-PD and M1-KO mice displayed a deficit compared to M1-WT mice in cued retrieval. These results demonstrate that although M1 agonism can restore a LM deficit in both contextual and cued testing paradigms, only the cued retrieval response is dependent on the M1. Additionally, biased Gq M1 signalling is not sufficient to restore contextual memory and requires phosphorylation of the receptor. Furthermore, biased M1 signalling results in LM deficits not seen with KO of the receptor. Overall, these results reiterate the importance of considering the bias of ligands when developing M1 agonists for dementia in the future.

Sensory-perceptual differences are widely reported in autism, yet their underlying mechanisms remain unclear. We tested preregistered hypotheses using stacked encoding models applied to naturalistic movie-viewing fMRI from children and adolescents with and without an autism diagnosis from the Healthy Brain Network. We mapped cortical responsiveness to low- and high-level auditory and visual feature spaces. Contrary to enhanced perceptual functioning predictions, autism was not associated with increased low-level encoding in primary sensory cortices. Instead, autistic children and adolescents had reduced high-level visual representations and a relative shift toward low-level over high-level feature encoding in integration and social brain regions including the pSTS and adjacent face/social areas. In pSTS, this high-low weighting tracked Social Responsiveness Scale (SRS) scores. By contrast, audio-visual modality preference and sensory dominance were broadly conserved across groups. Developmentally, encoding exhibited strong, lateralized, modality-congruent age effects. Together, these findings favor weak central coherence accounts over early sensory enhancement, constrain mechanisms to altered visual feature weighting within social/multisensory networks, and demonstrate the value of naturalistic stimuli and encoding models for characterizing sensory-perceptual neurodevelopmental differences.

G Protein coupled receptors (GPCRs) are the largest class of clinically validated drug targets with nearly 35% of all approved therapeutic agents acting on these receptors. To further explore the potential of this class of receptors for the development of circuit-specific and mechanism-based therapeutic strategies for neurological disorders, we focused on GPCRs with no known endogenous ligand, orphan GPCRs (oGPCRs), because knowledge of their functions in the human brain remains rudimentary. Here, we utilized fluorescence activated nuclear sorting and sequencing (FANSseq) to generate deep molecular profiles of cell type specific nuclei isolated from post-mortem brains to generate an atlas of oGPCR expression across multiple regions of the human brain. We identified 22 oGPCRs that displayed selective cell-type enrichment both in RNA transcript expression and chromatin accessibility. We further validated each of these targets for cell-type specific expression in human brains and developed an open-source web atlas of all oGPCR expression in the human brain to serve as a neuro-resource for the broader scientific community. These studies reveal novel cell-type specific expression patterns of several oGPCRs, suggest potential endogenous roles for these receptors, and identify validated candidates for cell-type specific neuromodulation of the human brain. One Sentence SummaryThis study presents an atlas of orphan GPCR expression across the human brain for translational targeting.

The active zone scaffold RIM is canonically viewed as an obligate, universal pillar of the neurotransmitter release machinery. However, whether RIM is strictly required across diverse synapse subtypes with distinct release probabilities has remained an important unresolved question. Here, we report a fundamental revision of this model: RIM is not a constitutive necessity for baseline transmission, but rather a specialized "gain factor" selectively deployed to empower high-release synapses. Utilizing botulinum neurotoxin-based silencing to isolate convergent inputs at the Drosophila neuromuscular junction, we demonstrate that while RIM is essential for high-fidelity transmission at phasic (MN-Is) synapses, it is largely dispensable at low-release tonic (MN-Ib) synapses. This input specificity extends into plasticity: RIM is required for acute presynaptic homeostatic potentiation (PHP) at phasic inputs but is dispensable for the chronic maintenance of PHP at tonic inputs. Mechanistically, super-resolution imaging reveals that RIM is positioned significantly closer to CaV2 Ca2+ channel nanodomains at phasic synapses. During acute plasticity, RIM coordinates the homeostatic compaction of CaV2 channel clusters and drives the rapid expansion of the readily releasable vesicle pool. Our results revise the canonical view of active zone architecture, demonstrating that rather than serving as a static, uniform structural anchor, RIM functions as a tunable, dynamic module deployed to shape the performance and plasticity of high-demand synaptic connections.

Building a simple model that precisely and functionally characterizes a neuron is a challenging and important task to select the best concise and computationally efficient model. However, this type of work has only been done for subthreshold properties of neurons. Here, we take a different perspective and suggest a method to obtain point-neuron models from morphologically-detailed models with dendrites. To do this, we focus on the functional characterization of the neuron response under in vivo conditions, and compute the transfer function of the detailed model. The parameters of this transfer function, in terms of mean voltage, voltage standard deviation and correlation time, can be used to compute the "best" point-neuron model that generates a transfer function very close to that of the morphologically-detailed model. We illustrate this approach for two very different neuronal morphologies, one from Drosophila larvae and one from mammals. In conclusion, this approach provides a tool to generate point-neuron models from detailed models, based on a functional characterization of the neuron response. Significance StatementThis study provides a new computational method to reduce morphological models into point-neuron models. To do so, we calculate the transfer function parameters, ie the voltage standard deviation, the mean voltage and the correlation time, of the morphological model and fit a point neuron-model onto this data. Here, we successfully apply this approach for two very different neuron morphologies, a drosophila neuron and a rat motoneuron.

Animal intelligence is not purely a product of abstract computation in the brain, but emerges from dynamic interactions between the nervous system and the body. New connectome datasets and musculoskeletal models now enable integrated, closed-loop simulations of the neural and biomechanical systems of the fruit fly Drosophila, an ideal model organism to investigate embodied intelligence. However, many biological parameters of the nervous system and the body, as well as how they interface, remain unknown. To fill such gaps, researchers are turning to deep reinforcement learning (DRL), a data-driven optimization framework, to create virtual animals that imitate the behavior of real animals. Here, we provide a cautionary tale about the interpretation of such models. We constructed a virtual chimera of two phylogenetically distant species: a connectome of the C. elegans nematode worm and a biomechanical model of the fly body. The worm connectome receives sensory information from the fly body, and an artificial neural network is trained with DRL to map worm motor neuron activations to the flys leg actuators. The resulting digital sphinx produces highly realistic fly walking--yet it is biologically meaningless. This exercise teaches us nothing about either animal and exposes a core peril of connectome-body models: behavioral fidelity is achievable without biological fidelity, making such models easy to overinterpret. Done carefully, virtual animals can be powerful partners to biological experiments, but only if their components and interfaces are grounded in biology.

Fear learning and extinction unfold as time-dependent processes. Herein, we examined how fear learning dynamically reorganizes brain activity immediately after learning, and whether such reorganization can be modulated with TMS application during extinction learning to prospectively predict extinction-memory expression. Eighty-seven healthy adults completed a three-day Pavlovian threat-learning protocol with resting-state fMRI acquired before and after conditioning (Day 1), dorsolateral prefrontal cortex (DLPFC) transcranial magnetic stimulation (TMS) applied during extinction learning (Day 2), and fMRI during extinction recall and renewal (Day 3). Using coactivation pattern analysis with a hidden Markov model within a 24-nodes threat-circuit parcellation, we identified a fear-learning-induced brain state characterized by global threat-circuit coactivation with heightened engagement and transition uncertainty post conditioning, and a progressive increase in engagement across post-conditioning. Critically, conditioning-induced functional connectivity reorganization within this state predicted individual differences in extinction recall- and renewal-related brain activation under TMS-modulated extinction (cross-validated; recall r = 0.47, p = 0.001; renewal r = 0.37, p = 0.01; permutation-tested), but not under natural extinction. Similar associations were observed between neural features and behavioral expression. These findings demonstrate that fear learning reshapes spontaneous brain-state dynamics and that such learning-induced reorganization serves as an interpretable biomarker for neuromodulation-linked extinction-memory expression.

Practice enhances motor acuity, enabling movement execution with greater speed and accuracy. However, the learning principles underlying improvements in speed, accuracy, and efficiency remain less understood than those supporting motor skill acquisition and adaptation. Here, we examined motor execution in a skill-based practice task to characterize learning, retention, and generalization of motor acuity. Using a gamified two-dimensional racing task, right-handed participants controlled a stylus-driven car along a curved track as quickly and accurately as possible. Across two studies (N = 83 total, 54 females), participants completed 300 training laps on Session 1 and returned for Session 2 to assess retention and generalization to novel track configurations: one with altered spatial configuration (rotated track) and one requiring movement in the opposite direction of training (reverse track). Movement speed improved rapidly and showed robust, though incomplete, retention across sessions. Speed improvements generalized substantially to both novel tracks. Accuracy was high at training onset and showed strong retention. However, we do not observe offline gains between sessions. Notably, accuracy declined transiently for the novel track configurations, suggesting interference from prior training. Movement efficiency, indexed by path length, was retained and generalized to the rotated track. However, reversing movement direction impaired efficiency, revealing a movement direction effect. This effect persisted when training direction was reversed in a second study, with counterclockwise movements remaining slower and less efficient than clockwise movements. These findings show that practice produces durable and broadly transferable motor execution improvements, while inherent movement direction biases constrain how improvements generalize across contexts. New & NoteworthyThe learning principles underlying improvements in motor acuity remain less well understood than those governing other forms of motor learning. Prior work suggests that motor execution improvements show limited generalization. In contrast, the present findings demonstrate that execution-based practice can produce robust, transferable gains, while also revealing a key constraint: inherent movement direction biases that limit generalization. By characterizing learning, retention, and generalization, this work provides new insight into how motor acuity improvements compare with skill acquisition and adaptation.

This study aimed to examine whether Humanin-G (HNG), a mitochondrial derived peptide with cytoprotective properties, could improve the retinal function and gene expression profiles after intraperitoneal injections to Royal College of Surgeons (RCS) rats with Retinal Pigment Epithelium (RPE) dysfunction and retinal degeneration. Starting at postnatal day 21 (p21), RCS rats received twice a week intraperitoneal injections of either Low Dose HNG (0.4 mg/kg), High Dose HNG (4mg/kg), or sham-saline for 1 or 4 weeks. Visual function was tested with full field scotopic & photopic electroretinography (ERG) and optokinetic testing (OKT) 1 and 4 weeks after first injection (WAFI). The rats were euthanized after the ERG and OKT (1 or 4 WAFI) and the dissected retinas and RPE were collected for RNA, cDNA and Quantitative Real-time PCR (qRT-PCR) analysis. The results of our study showed that high dose (4mg/kg) HNG at 4 WAFI was associated with the largest change in gene expression in the RPE and retina of treated animals, altering expression of genes involved in apoptosis, oxidative stress, inflammation and retinal/RPE function. Analysis of a and b waves from scotopic and photopic ERG showed no difference between either low or high dose of HNG and sham injection at 4 WAFI. However, at 4 WAFI, the visual acuity in rats treated with high dose HNG showed significant improvement as compared to the rats treated with low dose of HNG or saline. Most significantly, our findings support that HNG administered IP can modulate RPE/neuroretina cells and improve vision, thus may be a potential treatment for retinal degeneration diseases.

Capsaicin, the principal agonist of the heat-sensitive transient receptor potential vanilloid 1 (TRPV1) channel, triggers profound hypothermia by suppressing thermogenesis and promoting heat loss. While TRPV1 has been extensively characterized as a molecular sensor of heat and inflammatory mediators, the neural circuits through which capsaicin drives body cooling remain poorly defined. Emerging work suggests that peripheral TRPV1 activation modulates afferent input to central thermoregulatory networks, yet how --and where-- these signals are integrated within the central nervous system to induce hypothermia has remained unresolved. Intriguingly, optogenetic or chemogenetic activation of specific neuronal populations in the preoptic area (POA) of the hypothalamus has been shown to evoke deep hypothermia, raising the possibility that capsaicin engages overlapping thermoregulatory circuits. However, whether capsaicin-driven hypothermia depends on these POA neuron populations has not been directly tested. Here, we address this question by selectively and permanently silencing defined POA neuronal subtypes and assessing their contribution to capsaicin-evoked hypothermia. Silencing VMPOLepR or POAVgat neurons attenuated the hypothermic response but did not abolish it, whereas silencing POAVglut2 neurons nearly eliminated capsaicin-induced hypothermia. These findings identify POAVglut2 neurons as a critical central node through which peripheral TRPV1 activation drives body cooling. Together, our results demonstrate that capsaicin induces hypothermia via afferent sensory pathways that converge onto hypothalamic preoptic thermoregulatory neurons, revealing a direct circuit-level link between peripheral TRPV1 signalling and central control of body temperature.

Post-traumatic stress disorder (PTSD) is a debilitating condition that affects millions of veterans. A recent observational study in 30 veterans showed that a single dose of the atypical psychedelic ibogaine can be highly effective at treating PTSD up to twelve months later. Although a prior study demonstrated that ibogaine transiently alters electroencephalography (EEG) power in various frequency bands, the long-term, network-level neural mechanisms targeted by ibogaine are unclear. Here, we investigated whether ibogaine-related clinical improvements are associated with the reorganization of certain brain networks. We applied a novel framework, FREQuency-resolved brain Network Estimation via Source Separation (FREQ-NESS), to identify frequency-specific brain networks in resting-state EEG data acquired at baseline, three to four days after treatment (immediate-post), and one month after ibogaine. At both the immediate-post and one month-post timepoints, high-beta (24 and 25 Hz) networks shifted away from frontal areas and towards posterior regions, an effect that was replicated in an independent EEG dataset on ibogaine treatment for opioid use disorder. This posterior shift was significantly correlated with improvements in PTSD symptoms at both timepoints. Neural field modeling demonstrated that these posterior high-beta shifts are associated with increases in corticocortical, but not corticothalamic, connectivity. Our results are consistent with prior evidence implicating aberrant frontal beta-band activity in PTSD. Overall, we demonstrate that the reconfiguration of high-beta brain networks could be a robust biomarker for ibogaines therapeutic effects.

Cochlear implant (CI) users typically experience difficulties perceiving musical harmony due to a restricted spectro-temporal resolution at the electrode-nerve interface, resulting in limited pitch perception. We investigated how stimulus parameters affect discrimination of complex-tone triads (three-voice chords), aiming to identify conditions that maximize perceptual sensitivity. Six post-lingually deafened CI listeners completed a same/different task with harmonic complex tones, while spectral complexity, voice(s) containing a pitch change, and temporal synchrony (simultaneous vs. sequential triad presentation) were manipulated. CI listeners discriminated harmonically relevant one-semitone pitch changes within triads when spectral complexity was reduced to three or five components per voice, with significantly better performance for three-component compared to nine-component tones. Sensitivity was observed for pitch changes in the high voice or in both high and low voices, but not for changes in only the low voice. Single-voice sensitivity predicted simultaneous-triad sensitivity when controlling for spectral complexity and voice with pitch change. Contrary to expectations, sequential triad presentation did not improve discrimination. An analysis of processor pulse patterns suggests that difference-frequency cues encoded in the temporal envelope rather than place-of-excitation cues underlie perceptual triad sensitivity. These findings support reducing spectral complexity to enhance chord discrimination for CI users based on temporal cues.

Mental fatigue is known to impair cognitive and motor performance, but its impact on motor learning remains unclear. This study examined how mental fatigue affects skill acquisition in a sequential finger-tapping task. Twenty-eight participants were assigned to either a mental fatigue group, which completed a thirty-minute Stroop task, or a control group, which watched a documentary of equivalent duration. Both groups then trained on the finger-tapping task across multiple practice blocks with brief rest periods. Overall motor skill improved similarly in both groups. However, mental fatigue altered the pattern of acquisition: participants in the fatigue group showed decreased performance during practice blocks, which was compensated by larger gains during inter-block rest periods. A strong negative correlation was observed between online decrements and offline improvements, indicating that greater declines during practice were associated with larger gains during rest. This study highlights the critical role of rest periods in maintaining learning under cognitively demanding conditions and provides insight into how internal states, such as mental fatigue, can selectively influence the expression of performance without compromising overall learning.

The biophysical mechanisms by which circadian clock neurons integrate temporal coding signals to regulate sleep remain elusive. Here, using Drosophila, we identify Rabphilin (Rph) in DN1p clock neurons as a key stabilizer of the metaplasticity setpoint governing circadian regulation of sleep. Rph protein levels are elevated at night relative to daytime and modulate stochastic process of DN1p membrane potential dynamics linked to variability in synaptic activity at connections between DN1p neurons and their downstream postsynaptic partners. We find that Rph acts as a bidirectional regulator of synaptic plasticity thresholds. Under dim nocturnal light stimulation, Rph knockdown permits synaptic potentiation, whereas synthesized Rph introduction induces synaptic depression. In contrast, under optogenetic manipulation mimicking daytime spiking in DN1p neurons, these effects are reversed. We further show that spike-timing-dependent plasticity emerges when postsynaptic spiking is engaged, with nocturnal dim light conditions determining the direction of plasticity. Together, these findings establish a mechanistic link between microscale circadian neural dynamics and hierarchical metaplastic regulation, demonstrating how circadian regulation of sleep dynamically balances stability and adaptive flexibility through circadian setpoints and environmental nocturnal light interactions. Significance StatementWe show that circadian metaplasticity regulates sleep through membrane potential dynamics. Circadian clock neurons implement flexible metaplasticity, whereby the direction can be determined by internal circadian setpoints and interactions with nocturnal environmental light. This mechanism engages spike-timing-dependent plasticity to determine plasticity polarity. Our findings identify membrane potential dynamics as a computational substrate for physiological state control, linking molecular mechanisms to circuit-level circadian regulation of sleep. Together, they reframe sleep regulation as an active metaplastic process that hierarchically integrates microscale circadian neural dynamics to optimize circuit function.

Adeno-associated viral (AAV)-mediated overexpression of human wildtype -synuclein (-syn) in the substantia nigra (SN) is a widely used approach to model Parkinsons disease (PD) in rodents. However, variability in the ability of AAV-based systems to induce nigrostriatal pathology and motor deficits has limited reproducibility across studies, especially in mice. Here, we systematically optimized key vector features - AAV serotype, promoter, viral titer - to establish a highly efficient and reliable mouse model of PD. We compared the tropism and expression efficiency of mixed AAV2/1 and AAV2/rh10 serotypes combined with three promoters - CMV enhancer/chicken {beta}-actin (CBA), human Synapsin (hSYN), and rat Tyrosine Hydroxylase (TH) - to drive human -syn gene (SNCA) expression in nigral dopaminergic neurons. The AAV.TH.SNCA vector, delivered at an optimized titer, achieved selective and sustained -syn overexpression in nigral neurons, resulting in nigro-striatal neurochemical changes and progressive motor deficits preceding overt neuronal loss. Fine tuning -syn expression proved critical for detecting early disease processes: lower AAV.TH.SNCA titer induced early pathological signatures, including -syn hyperphosphorylation and neuroinflammation, whereas higher titers produced robust nigrostriatal degeneration not achieved with other promoter constructs. Notably, we demonstrate that motor and neurochemical impairments can occur prior to dopaminergic cell death, implicating microglial activation and -syn pathology as primary drivers of dysfunction. This observation is consistent with human genetic evidence showing that triplication of the wild-type SNCA gene alone can cause Parkinsonian pathology, highlighting that our model enables the use of a single experimental reagent to investigate the molecular, cellular, and behavioral consequences of controlled increases in -syn expression. This novel AAV.TH.SNCA model provides a powerful and versatile platform for investigating mechanisms of a -syn-mediated neurotoxicity and for evaluating disease modifying interventions targeting early, pre-degenerative stages of PD. HighlightsO_LITitrated -syn expression uncouples early dysfunction from dopaminergic neuron loss C_LIO_LIAAV2/rh10-TH-SNCA model captures prodromal and degenerative PD stages C_LIO_LIMotor deficits arise from -syn pathology and nigral molecular changes before neurodegeneration. C_LI

The nucleus accumbens (NAc) and its excitatory input from the medial prefrontal cortex (mPFC) form a critical circuit underlying drug-induced plasticity associated with addiction-related behaviors. However, baseline differences in excitatory signaling across NAc subcircuits and sex-specific neuroadaptations following opioid self-administration remain poorly understood. Here, we examined synaptic signaling in mPFC-NAc pathways in drug-naive mice and after abstinence from remifentanil self-administration. Under drug-naive conditions, AMPA receptor- mediated glutamatergic signaling was generally elevated in D2 medium spiny neurons (MSNs) of both the NAc core and shell across sexes, while females exhibited greater excitatory signaling in D1 MSNs of the NAc core compared with males. Pathway-specific analyses revealed that prelimbic cortex (PL) inputs to NAc core D2 MSNs displayed enhanced calcium-permeable AMPA receptor (CP-AMPAR) signaling and increased presynaptic release relative to D1 MSNs. Following abstinence from remifentanil self-administration, miniature excitatory postsynaptic current analyses showed increased excitatory drive at D1 MSNs and decreased drive at D2 MSNs, largely restricted to the NAc core. At PL-Core D1 MSN synapses, remifentanil reduced AMPA/NMDA ratios, consistent with increased CP-AMPAR incorporation in males and females, while increasing presynaptic signaling exclusively in males. In contrast, PL-Core D2 MSN synapses showed a reduction in presynaptic signaling across sex, while ostensibly weakening postsynaptic signaling selectively in males through reductions in CP-AMPAR signaling. At infralimbic cortex (IL)-shell inputs, a reduction in AMPAR rectification indices at D1 MSN synapses was produced by remifentanil, while release probability was decreased at D2 MSN synapses in males only. Together, these findings reveal sex- and pathway-specific synaptic adaptations within mPFC-NAc circuits that may be obscured by global measures of excitatory transmission and identify baseline circuit differences that may shape opioid-induced plasticity.

Voltage perturbations to a repetitively firing Hodgkin-Huxley (HH) model of neuronal spiking in the bistable regime with coexisting limit cycle and stable steady node can either lead to the spikes phase resetting or collapse to the stable steady state. The latter describes a non-firing hyperpolarized quiescent state of the neuron despite the presence of constant external current. Using asymptotic phase response curve (PRC), the impact of voltage perturbations on a repetitively firing HH model is studied here while it is diffusively coupled to another HH model under identical external stimulation. It is observed that the pre-perturbation state of synchronization and the coupling strength critically determine the PRC response of the perturbed HH dynamics. Higher coupling strengths of perfectly in-phase (anti-phase) synchronized HH models shrink (expand) the combinatorial space of perturbation strengths and the oscillation phases causing collapse to the quiescent state. This indicates reduced (enlarged) basin of attraction, viz. the null space, associated with the steady state in the HH phase space. The findings bear important implications to the spiking dynamics of diverse interneurons, as well as special cases of pyramidal neurons, coupled through electrical synapses via. gap junctions, and suggest the role of gap junction plasticity in tuning vulnerability to quiescent state in the presence of biological noise and spikelets.

Neuroscience needs observation. Observation lets us evaluate data quality, judge whether models are biologically realistic, and generate new hypotheses. However, high-dimensional behavioral and neural data are too complex to be easily displayed and eye-tested. Computational methods can reduce the dimensionality of data and reveal statistically robust dynamical structure but often yield results that are difficult to relate back to the underlying biology. In addition, the choice of what parameters to quantify may not capture unexpectedly relevant aspects of the data. To supplement quantification with enhanced qualitative observation, we developed Visualization and Sonification of NeuroData (ViSoND), an open-source approach for displaying multiple data streams using video and sonification. Sonification is nothing new to neuroscience. Scientists have sonified their physiological preparations since Lord Adrians earliest recordings. We extend this tradition by mapping multiple physiological datastreams to musical notes using MIDI. Synchronizing MIDI to video provides an opportunity to watch an animals movement while listening to physiological signals such as action potentials. Here we provide two demonstrations of this approach. First, we used ViSoND to interpret behavioral structure revealed by a computational model trained on the breathing rhythms of freely behaving mice. Second, ViSoND revealed patterns of neural activity in mouse visual cortex corresponding to eye blinks, events that were previously filtered out of analysis. These use cases show that ViSoND can supplement quantitative rigor with observational interpretability. Additionally, ViSoND provides an accessible way to display data which may broaden the audience for communication of neuroscientific findings.

ObjectiveConvolutional neural networks (CNNs) have shown promise in decoding neural drive from high-density surface electromyography (HD-sEMG) signals. However, the effects of convolutional kernel dimensionality on the generalizability and computational efficiency of CNN-based neural drive decoding remain unclear. This study systematically examined how the dimensionality of convolutional kernels (1D, 2D, and 3D) affects both the generalizability and computational efficiency of CNN-based neural drive decoding. ApproachThree CNN architectures differing only in the dimensionality of their convolutional kernels were implemented to extract temporal (1D), spatial (2D), or spatiotemporal (3D) features from HD-sEMG signals of isometric knee extension, ankle plantarflexion at three intensities. Each CNN was repeatedly trained using subsets of a pooled training dataset with varying sizes. Cross-intensity and cross-muscle generalizability were assessed by the correlation coefficient between neural drive from deep CNN and that from golden standard blind source separation (BSS) algorithms. Computational efficiency was assessed by measuring inference time on both CPU and GPU platforms. Main ResultsAll CNN architectures demonstrated generalizability across contraction intensities and muscles. For cross contraction intensities, the 1D, 2D, and 3D CNNs achieved mean correlation coefficients of 0.986 {+/-} 0.009, 0.987 {+/-} 0.010, and 0.987 {+/-} 0.010, respectively. For cross-muscle generalizability, the corresponding correlation coefficients were 0.961 {+/-} 0.051, 0.965 {+/-} 0.049, and 0.968 {+/-} 0.046. In terms of efficiency, the 3D CNN was the least computationally efficient, with inference times of 4.1 ms per sample on the CPU and 1.2 ms per sample on the GPU. SignificanceThese findings demonstrate that increased CNN architectural complexity does not necessarily yield superior generalizability in neural drive decoding from HD-sEMG signals. The results provide practical guidance for balancing decoding performance and computational efficiency in HD-sEMG-based neural-machine interfaces.

During brain development, dynamic remodeling of membrane lipid composition accompanies the maturation of inhibitory neurotransmission and the progressive establishment of low intracellular chloride levels. Central to this developmental transition is the neuronal K-Cl- cotransporter KCC2, whose stabilization at the plasma membrane enables the emergence of hyperpolarizing GABAergic signaling. Although KCC2 regulation by protein partners has been extensively characterized, whether lipid remodeling actively contributes to its membrane organization and chloride transport remains unclear. Here we identify the ganglioside GM1, a complex lipid abundant in plasma membrane of neurons, as a developmentally regulated lipid determinant of KCC2 membrane localization and function. We show that KCC2 interacts with GM1 within plasma membrane lipid rafts and that this interaction increases during postnatal brain maturation. Molecular modeling identified a conserved ganglioside-binding domain (GBD) in KCC2 centered on tryptophan 318 (W318). Biophysical analyses revealed a specific and saturable interaction between this domain and GM1 that is abolished by the epilepsy-associated W318S mutation. Disruption of KCC2-GM1 interactions, either by W318S mutation or by pharmacological depletion of GM1, excludes KCC2 from lipid rafts, alters its membrane diffusion and clustering, and reduces its surface stability. Functionally, these perturbations impair KCC2-mediated chloride extrusion and disrupt the somato-dendritic chloride gradient in hippocampal neurons. Consistent with these cellular effects, GM1-deficient (St3gal5-/-) mice exhibit selective reduced hippocampal KCC2 expression. Together, these findings reveal a lipid-protein mechanism that links developmental membrane remodeling to KCC2 stabilization and chloride homeostasis, highlighting membrane lipids as active regulators of transporter maturation and inhibitory circuit development.

Communication between gut microbiota and immune cells within the brain is essential for neurotypical development. Specifically, microglia are known to play a key role in regulating and supporting neural progenitor stem cell production during brain development, and are sensitive to changes in the maternal gut microbial composition during perinatal development. Here, we employed a germ-free (GF) porcine paradigm to examine how the absence of the microbiome affects microglial dynamics during a key epoch of brain development. We utilized automated software to evaluate microglial density and morphology across three developmentally significant regions: the ventricular/subventricular zone (VZ/SVZ), the prefrontal subcortical white matter (PFCSWM), and layers II/III of the prefrontal cortex (PFCII-III). We found no significant differences in microglial morphology or density in the VZ/SVZ or PFCSWM. In contrast, the PFCII-III of P16 piglets exhibited an increase in microglia density paired with morphologies indicative of an activated/reactive functional state. Notably, these effects were identified with no overall changes in microglial density in any of the regions assessed. Transcriptomics on RNA isolated from the PFCII-III revealed a significant upregulation of genes related to neuroinflammation, in agreement with a region-specific microglial and immune response in the absence of microbial colonization during postnatal development. Together, these findings build on the limited knowledge available on how microbiota influence brain development in large animal model organisms with high similarities to human brain anatomy and developmental trajectories. Significance StatementThe prefrontal cortex of porcine display unique, ramified microglia which are sensitive to germ-free conditions whereby they display alterations in morphology with a more transcriptionally reactive signature. These findings indicate that microglia are regionally sensitive to stimuli in the periphery, and studies in lissencephalic mammalian models may not be directly correlative to other higher-order species. The neuroanatomical heterogeneity of microglia across species is informative and understudied, but necessary, to draw conclusions on the array of perturbations spanning neurodevelopmental trajectories in health and disease.

Healthy energy balance relies on an equilibrated trade-off between the respective drives for food and exercise. However, the motivation circuitry underlying the choice between these two rewards remains unknown. Here, we developed a neuroeconomic model wherein mice living in operant chambers needed to choose between standard food and wheel running under increasing effort demands. Reward seeking resistance to increasing costs was then quantified using feeding and exercise essential values (EVs). Through conditional genetics and viral approaches, we show that cannabinoid type-1 receptors (CB1Rs) located on GABAergic neurons gate in necessary and sufficient manners exercise EV, exercise preference over feeding and exercise duration per rewarded sequence. Further, we report that these GABAergic neurons are located in the ventromedial striatum in males, but not females. CB1R deletion from medium spiny neurons did not impact exercise motivation, revealing an unforeseen role for ventromedial striatal GABAergic interneurons in effort-based decision-making between food and exercise.

Neurofibromin 1 (NF1) is a critical negative regulator of the RAS-RAF-ERK pathway, mutations in which have been clinically implicated in various neurodevelopmental disorders. However, the lack of a high-resolution spatiotemporal map has obscured the understanding of why specific cell populations and developmental processes are uniquely vulnerable to NF1 loss. In this study, we present a comprehensive atlas of NF1 expression in the developing mouse brain. Using in situ hybridization and immunohistochemistry, we characterized NF1 distribution from early embryonic stages through postnatal maturation. We further integrated these findings with single-nuclei RNA-sequencing (snRNA-seq) datasets from adult mouse brain to achieve higher resolution. Our results reveal a previously undocumented graded expression pattern of NF1 across various brain regions and lineages. This comprehensive study will not only help in understanding the fundamental role of NF1 during brain development but will also be pivotal in providing a framework to study NF1-associated brain disorders.

How does the human brain represent the meaning of abstract symbols? Some theories postulate the existence of semantic spaces where concepts occupy positions that reflect their conceptual relationships. In the number domain, psychological evidence suggests that integers are represented along a mental number line which, with education, integrates higher-level number concepts such as fractions. To test this hypothesis, we recorded whole-brain 7T fMRI responses to integer and fraction symbols during a magnitude comparison task. Consistent with predictions, we found both behavioral and neural numerical distance effects. Activation vectors in intraparietal, inferior temporal, prefrontal, hippocampal, and parahippocampal cortices formed a two-dimensional semantic space organized by numerical magnitude and domain (fractions versus integers). Gaussian fits revealed a topographic map of numerical preferences in the anterior inferior parietal cortex, common to both domains. Our results suggest that, in educated adults, a joint semantic map integrates fractions and integers and supports symbolic magnitude representation and comparison.

Mitochondria engage in extensive communication with other organelles through membrane contacts. Perturbed mitochondria-organelle interactions are indicated in a variety of neurodegenerative diseases, but the underlying mechanisms remain poorly understood. Here, we report a new class of mitochondria-organelle communication: autophagosome/autophagic vacuole (AV)-mitochondria (Mito) contact, which exhibits hyper-tethering in tauopathy neurons, consequently hampering AV retrograde transport. Such defects are attributed to accelerated turnover of the contact release factor TBC1D15, triggered by mitochondrial bioenergetic deficit-induced hyperactivity of the AMP-activated protein kinase (AMPK). Increasing TBC1D15 levels or repressing AMPK activity normalizes AV-Mito contact release and restores retrograde transport of AVs, thereby increasing autophagic cargo clearance and reducing tau burden in tauopathy axons. Furthermore, overexpression of TBC1D15 enhances autophagic clearance and attenuates tau pathology, alleviating neurodegeneration and cognitive dysfunction in tauopathy mice. Taken together, our study provides new insights into AV-Mito contact dysregulation in tauopathy-related autophagy failure, laying the groundwork for the development of potential therapeutics to combat tauopathy diseases.

Spinal motoneuron (MN) pools behave as linear systems that transmit common synaptic input to muscles. However, MNs are biophysically heterogeneous and intrinsically nonlinear. How different MN subpopulations integrate and transmit high-frequency inputs remains poorly understood, partly because conventional analyses treat the MN pool as a single functional system rather than examining subpools with different firing rates. Here, we addressed this gap using a combination of computational simulations and human MN recordings. Simulations of MNs receiving a common synaptic input at varying frequencies showed that MNs firings become phase-locked to input oscillations when the input frequency approximates the neurons firing rate or its harmonics. We refer to this frequency-dependent synchronization as entrainment. Importantly, this subpool-specific effect was masked when MN activity was analysed at the whole-pool level. Because entrained MNs effectively sample the input at their firing instants, we developed a MN-firing locked method that uses individual MN firings as endogenous triggering events for peristimulus frequencygrams across the pool. In simulations, this method revealed entrainment-driven firing rate modulations across MN subpools. We then applied this MN-firing locked method to MNs decomposed from high-density surface electromyography recordings obtained during isometric contractions in healthy individuals. We found that faster-firing MNs exhibited larger transient firing rate increases, time-locked to slower MN activity. Furthermore, these modulations correlated with common input in the alpha and beta bands implicating high frequency common input as the driving source. Together, these findings demonstrate that MN nonlinearities generate heterogeneous, frequency-dependent dynamics that remain hidden in conventional pool-level analyses.

Human language depends on highly specialized left-hemispheric brain networks. Damage to these networks causes severe language impairments (aphasia), one of the most common, debilitating and costly consequences of left-hemispheric brain injury, especially stroke. The limited recovery of aphasia despite intensive rehabilitation efforts emphasizes the need to understand the basis of residual language abilities at the single-neuron level, which has remained unexplored so far. Here, we report large-scale microelectrode recordings with single-unit resolution over a period of ten months from the right-hemispheric prefrontal and parietal association cortex of an individual with stroke-induced chronic non-fluent aphasia. Single neurons exhibited regionally specific responses during comprehension, retrieval and articulation of words, the core operations of language. Distinct subpopulations encoded linguistic information in a task-specific manner, despite correlated firing patterns across tasks. Both single-neuron activity and temporally coordinated population dynamics were predicted by semantic and phonological embeddings derived from large language models (LLMs), revealing a regional dissociation in which semantic features preferentially accounted for prefrontal activity and phonological features for parietal activity. Our findings suggest that right-hemispheric circuits, homotopic to the left language network, can support language processing through structured, functionally organised activity at the level of single neurons. This study opens an avenue for developing mechanistically specific neurorehabilitation and neurorestorative strategies for aphasia, such as brain-computer interfaces (BCIs), that leverage right-hemispheric language resources.

In Alzheimers disease (AD) astrocytes become reactive, displaying hypertrophic morphology, increased expression of intermediate filament proteins GFAP and Vimentin and impaired homeostatic support to neurons. However, the contribution of reactive astrocytes to AD progression, particularly the role of cytoskeletal hypertrophy, remains unclear. Here, we investigate whether astrocyte intermediate filaments actively contribute to early AD progression. We show that astrogliosis appears as early as at 3 months in APP/PS1 mice, preceding amyloid-{beta} plaque deposition, and is characterized by a strong upregulation of GFAP and Vimentin. Genetic ablation of GFAP and Vimentin attenuated astrogliosis, as evidenced by the absence of hypertrophy of astrocyte processes and restored expression of glutamine synthetase and other proteins altered in reactive astrocytes in AD. Importantly, GFAP and Vimentin deletion prevented cognitive decline in 4-month old male and female mice, independently of amyloid plaque pathology or microglial reactivity. Mass-spectrometry based proteomics of the dorsal hippocampus revealed a downregulation of synaptic proteins and dysregulation of ribosomal and RNA-binding proteins in APP/PS1 mice, both of which were rescued by GFAP and Vimentin deletion. Using astrocyte-specific CRISPR-Cas9-mediated knockout of GFAP and Vimentin, we further demonstrate translation impairments in AD astrocytes, and that GFAP and Vimentin deletion restores this impaired astrocytic translation. Together, our findings identify intermediate filament proteins GFAP and Vimentin as active regulators of astrocyte protein synthesis, and reveal a previously unrecognized mechanism by which reactive astrocytes contribute to early cognitive dysfunction in AD. This highlights these astrocyte intermediate filaments as promising therapeutic targets to counteract reactive astrocyte-driven cognitive decline in the early stages of Alzheimers disease.

Several neurodevelopmental disorders (NDDs) are characterized by impairments in social behavior and affective dysregulation. Converging evidence implicates the endocannabinoid system in the control of both behaviors. However, the brain region-specific contribution of cannabinoid receptor type 1 (CB1R) signaling to these NDD-relevant phenotypes remains unclear. The anterior insular cortex (aINS) is a key integrative hub involved in socio-emotional processing and social novelty recognition. Whether CB1Rs within this region are sufficient to regulate behavioral domains disrupted in NDDs remains unclear. Here, we employed a Cre-dependent viral strategy to selectively restore CB1R mRNA expression in the aINS of global CB1R-deficient mice. Region-specific rescue of CB1R in the aINS normalized social novelty discrimination and reduced anxiety-like behavior as compared to mice lacking CB1R, while leaving basal sociability and locomotor activity unaffected. In addition, insular CB1R re-expression modulated repetitive-like behaviors without broadly altering other behavioral domains. These effects were observed in the absence of off-target expression, supporting the specificity of the genetic manipulation. Our findings demonstrate that CB1R mRNA expression within the aINS is sufficient to regulate distinct socio-emotional and repetitive behavioral domains. These results identify the aINS as a critical CB1-dependent modulatory node and provide mechanistic insight into how region-specific endocannabinoid signaling contributes to behavioral phenotypes relevant to NDDs.

Oligodendrocyte precursor cells (OPCs) are unique glial cells that communicate bidirectionally with neurons. Neuronal inputs drive various OPC behaviors, including proliferation and differentiation, immunomodulation, blood brain barrier regulation, synapse engulfment and axonal remodeling. OPCs are implicated in numerous stress and pain conditions, where their involvement is likely driven by neuronal activity (ie. neurotransmitter and neuropeptide signaling). One neuropeptide causally involved in chronic pain and stress conditions is calcitonin gene-related peptide (CGRP). Here, we tested the hypothesis that OPCs receive direct inputs from CGRP-containing neurons in the adult brain. Using RNAscope, immunofluorescence and analysis of single-cell datasets, we find that OPCs express receptors for CGRP and we identify close spatial contacts between CGRP and OPCs, with nearly half of CGRP puncta occurring within 1 {micro}m of an OPC. Some of these contacts appear to be synaptic, with CGRP-OPC contacts colocalizing with the presynaptic protein Bassoon and the postsynaptic protein PSD-95. This work suggests the presence of both diffuse and more direct forms of CGRP signaling to OPCs, raising the importance of future experiments to identify both the mode of CGRP release onto OPCs and the functional effects of these different contact types.

The medial prefrontal cortex (mPFC) and ventral tegmental area (VTA) form a highly interconnected circuit involved in emotional regulation, stress reactivity, and cognitive processing. While prior research has established the anatomical and functional interactions between these regions, the precise organization and molecular identity of VTA neurons involved in unidirectional and bidirectional mPFC connectivity remains poorly defined, particularly under stress. We combined dual anterograde and retrograde viral tracing in male and female mice to label VTA neurons according to their connectivity with the mPFC. This approach identified three distinct subpopulations including mPFC-projecting, mPFC-receiving, and bidirectionally-connected neurons which accounted for nearly half of the labelled VTA population. Each group displayed molecular heterogeneity, with most cells expressing dopaminergic (TH) and glutamatergic (VGLUT2) transcripts rather than single dopaminergic or GABAergic (GAD1) markers. Acute and chronic stress exposure revealed sex- and circuit-specific patterns of c-Fos activation. In males, acute and chronic stress generated opposing rostrocaudally organized activation profiles, whereas females showed a more uniform increase in activity. Spatial clustering analyses further revealed that stress induces distinct hotspot organization within the VTA, with chronic stress promoting cohesive hotspot organization and consistent local enrichment of bidirectionally connected neurons despite a limited global activation. Together, these findings uncover a molecularly diverse mPFC-VTA circuitry with bidirectional connectivity that undergoes sex-dependent spatial and functional rearrangement under stress, providing new insights on circuit-level mechanisms of stress-related disorders.

Speech production requires orchestration of multiple brain systems, including cortical and subcortical areas that support the unfolding of the spoken message across hierarchical linguistic levels, such as phonemes, syllables, words or phrases. Transitions between levels are critical for fluent speech, yet the neural dynamics of, for example, syllable-level and word-level transitions remain unknown. In this electroencephalography (EEG) study, we use time-frequency analysis and source localization to determine differences associated with word-boundary vs. within-word syllable transitions. To this end, pseudoword pairs comprising six consonant-vowel (CV) syllables with different word-boundary positions were used. Fluent human adults produced the utterances at the rhythm of a learned visual metronome (i.e., syllable-by-syllable), such that each syllable was uttered at matching times independently of its relative word position. Accordingly, a target syllable could be either a within-word syllabic transition or a between-word transition, while other linguistic properties, including articulation, stress pattern, co-articulation or prosody, were matched. EEG time-frequency analyses of neural sources successfully revealed sensitivity to hierarchical structure. Neural sources in left and right inferior frontal lobes, as well as left superior temporal lobe were differentially recruited when producing the same exact syllables, in the same exact utterance position, but under different word boundary contexts. A right inferior frontal source showed a robust time-frequency modulation in word transitions that included elevated event-related synchronization in the theta and beta range. Interestingly, despite our efforts to control speech pace across conditions using metronome-based guidance, small, albeit significant timing delays emerged, confirming higher cognitive demands at word boundaries.

White matter structural connectivity constrains large-scale brain communication, yet most network models do not account for biologically meaningful differences between connections. Although axonal diameter and myelination influence neural signaling at the microscale, how these features shape systems-level functional connectivity remains unclear. Here, we test whether structural connectomes weighted by white matter microstructure give rise to distinct communication regimes that differentially predict multimodal functional connectivity. Combining quantitative MRI and advanced diffusion modeling, we constructed whole-brain networks weighted by tract caliber and multiple myelin-sensitive measures. To these, we applied routing- and diffusion-based communication models and used the resulting communication metrics to predict haemodynamic and frequency-resolved electromagnetic connectivity. Myelin-weighted networks preferentially enhanced long-range communication efficiency and redistributed spectral energy toward globally integrative topological eigenmodes. In contrast, caliber-weighted networks emphasized mesoscale organization and short-range communication. Across nested regression models controlling for geometric embedding and network topology, myelin-sensitive communication explained unique variance in functional connectivity with effects varying systematically across cortical systems and frequency bands. The strongest coupling was observed for alpha-band connectivity in association and attentional networks, consistent with a role for myelin-dependent communication delays in supporting long-range alpha synchrony. These findings demonstrate how distinct white matter microstructural features give rise to heterogeneous large-scale communication regimes: tract caliber and myelin bias communication toward locally specialized and globally integrative architectures, respectively. By integrating biologically informed connectomics with communication modeling and multimodal functional data, this work advances a mechanistic account of how white matter microstructure shapes macroscale brain dynamics.

In everyday vision, animals routinely extract from the same visual stimulus both object identity and continuous identity-independent variables such as position and size. It has been shown that linear decoding performance of both kinds of information increases along the ventral stream, suggesting that inferior temporal cortex may be implementing a joint code for object category and category-independent features. A central open question is whether such a code can indeed exist within a single representation and, if so, what geometric properties enable it. Here, we show that convolutional neural networks can develop such a code. We then derive a theory of regression on category manifolds, identifying the key manifold-geometry measures that enable accurate readout of category-independent features, and showing how they can be optimized while preserving manifold properties known to support classification performance. We further characterize how common experimental constraints, such as subsampling neural units and using a limited number of categories, affect the empirical estimation of regression performance. Our findings thus provide a principled understanding of the geometry underlying joint codes and yield testable predictions for future neural recordings probing the joint-code hypothesis in the ventral stream.

Speech comprehension involves the inference of abstract information from continuous acoustic signals. Prior work suggests that electrophysiological activity is synchronized with abstract linguistic structures (phrases and sentences) during the processing of isochronous syllable sequences. It is yet unclear whether this prior evidence generalizes to natural speech comprehension, which requires the flexible processing of continuous speech, where syllables and other types of linguistic units are anisochronous. Our magnetoencephalography experiment investigated neural synchronization to acoustic (syllables) and abstract units (phrases and sentences) using continuous speech ranging from artificial isochronous to more natural anisochronous. We find that neural synchronization to phrases and sentences, but not syllables, is resilient to naturalistic anisochrony. This suggests that linguistic structure processing reflects endogenous inferences that are fundamentally distinct from the exogenous processing of syllables driven by speech acoustics. Lateralization and linear regression results extend this functional dissociation as hemispheric asymmetry: stimulus-independent leftward lateralization for linguistic structure processing but stimulus-driven rightward lateralization (or bilaterality) for both syllable and acoustic processing. Our findings provide a more realistic characterization of the flexible neural mechanisms supporting the efficient comprehension of natural speech.

Transcranial focused ultrasound (tFUS) can noninvasively modulate sensory pathways, but the cell-type-specific mechanisms underlying excitatory or inhibitory effects remain unclear. Here, we investigate how tFUS applied to the somatosensory cortex (S1) influences S1 and posterior medial thalamic nucleus (POm) responses to hind paw vibration-tactile stimulation and which neuronal populations mediate these effects. Vibration-tactile stimulation evoked potentials (TEPs) and multi-unit activities (MUA) in S1 and POm were recorded from male rats. Optogenetic tagging was used to identify S1 CaMKII-positive, PV-positive, and SST-positive neurons, while waveform features were used to classify putative excitatory (i.e., regular-spiking units - RSUs) and inhibitory neurons (i.e., fast-spiking units - FSUs) in POm. We found that only S1 CaMKII-positive neurons and POm RSUs responded robustly to tactile stimulation. When tFUS was applied to S1, high pulse repetition frequency (PRF), high duty cycle, and high-pressure stimulation (etFUS) produced excitatory modulation of the sensory pathway, whereas low PRF, low duty cycle, and low-pressure stimulation (itFUS) induced inhibitory effects. Further analyses revealed that excitatory modulation was mediated by activation of S1 CaMKII-positive neurons, while the inhibitory effect arose from their deactivation. These findings demonstrate that tFUS exerts bidirectional, parameter-dependent modulation of a sensory pathway and highlight the critical role of CaMKII-positive neurons in mediating these effects. This study provides mechanistic insight into cell-type-specific neuromodulation by tFUS, particularly in bidirectional modulation of a sensory pathway, and informs the optimization of stimulation parameters for targeted therapeutic interventions.

Aesthetic preference is a primary driver of social behavior in the digital era, yet the extent to which these preferences remain consistent across disparate domains remains poorly understood. We hypothesize that aesthetic judgment is governed by a domain-invariant latent structure, such that individuals who exhibit similar preferences in one category will demonstrate comparable alignment in seemingly unrelated domains. To test this, we recruited 37 participants to evaluate stimuli across three distinct aesthetic domains: art, faces (male and female), and scenes. We developed a novel computational framework that reformulates cross-domain preference as a user-based collaborative filtering problem, encoding individual profiles through inter-subject similarity matrices. Our model successfully predicted participant responses in a target domain based on their similarity to the cohort in a separate source domain. These results demonstrate robust cross-domain consistency, suggesting that aesthetic evaluation is mediated by an abstract, domain-general mechanism rather than being purely stimulus-dependent. We propose that this consistency is rooted in a shared neurophysiological pathway, likely involving the orbitofrontal cortex (OFC) and the Default Mode Network (DMN), and discuss how these findings provide a foundation for more sophisticated, cross-modal recommendation systems and the study of individual social identity.

ObjectiveTo determine whether non-axon optic nerve morphometric features correlate with clinical visual function as strongly as the traditional axon count gold standard. DesignCross-sectional histological analysis with longitudinal clinical correlation. SubjectsEighteen mice from three strains: C57BL/6J (n=6), BXD51 (n=6), and DBA/2J (n=6). MethodsLeft eye (OS) optic nerves from mice euthanized at 12 months of age were resin-embedded and stained with p-phenylenediamine. Bright-field cross-sectional images were segmented using an AxonDeepSeg-based workflow to generate axon, myelin, whole nerve, and glial coverage masks for morphometric quantification. Seven morphometrics were extracted: axon count (nAx), axon density (AxDen), glial coverage area ratio (GliaR), mean solidity (Sol), mean axon diameter (AxDiam), mean myelin area (MyArea), and mean axon-myelin area (AxMyArea). Morphometrics were correlated with longitudinal clinical data collected at 1, 3, 6, 9, and 12 months, including visual acuity (VA), contrast threshold, intraocular pressure (IOP), and pattern electroretinography P50 and N95 amplitudes (PERG P50 and N95). Main Outcome MeasuresPearson correlation coefficients were used to assess associations between morphometric features and clinical measures, and Fisher z-transformed meta-analytic correlations were used to aggregate these associations across ages. ResultsVA and contrast threshold demonstrated strong correlations with GliaR that matched or exceeded nAx. Meta-analysis across ages revealed GliaR correlated with VA (r = -0.84, p = 4.49 x 10-21) and contrast threshold (r = 0.86, p=7.55 x 10-23), comparable to nAx correlations with VA (r = 0.80, p=8.13x10-17) and contrast threshold (r = -0.80, p= 1.74x10-16). Structure-function relationships shifted with age: at 6 months, GliaR had the strongest correlation with contrast threshold (r = 0.96), while at 12 months, AxDiam became the dominant correlate of both VA (r = 0.77) and contrast threshhold (r = -0.74). IOP, PERG P50, and PERG N95 exhibited weak correlations with all morphometrics (|r| < 0.27). ConclusionsNon-axon morphometrics, particularly glial coverage area ratio, correlate with visual function as strongly as traditional axon count. Automated optic nerve assessment should incorporate glial and other non-axon features. Further, stage-aware biomarker selection may better capture structure-function relationships in glaucoma.

The blood-brain barrier (BBB) poses a major obstacle to the delivery of therapeutics into the central nervous system (CNS) due to its highly restrictive permeability. Here, we introduce glycan-targeted delivery vehicles, or GlycoShuttles, that traverse the BBB by harnessing the cerebrovascular glycocalyx, a carbohydrate-rich layer lining the BBB lumen. We discover that mucin-domain glycoproteins within this structure serve as novel entry portals for brain delivery and engineer mucin-binding protein shuttles that enable efficient transport of diverse molecular cargo across the BBB into multiple key brain cell types. This modular platform facilitates enhanced brain delivery of a variety of payloads, including antibodies and lysosomal proteins, and demonstrates therapeutic efficacy in mouse models of dementia. Our findings establish mucin-targeted GlycoShuttles as a versatile platform for noninvasive brain delivery of therapeutics, opening new avenues for the treatment of CNS diseases.

Brain decoding from fMRI data using artificial neural networks traditionally operates at the regional level, identifying which brain areas activate during tasks but ignoring how these regions interact through structural networks. While Graph Neural Networks can capture connectivity, they require prohibitively large datasets for typical neuroscience studies. We introduce a message-passing mechanism that allows a shallow neural network to incorporate structural connectivity, enabling network-level interpretation from limited data. Using motor task data from 30 Human Connectome Project subjects, we evaluate seven structural connectivity matrices derived from deterministic and probabilistic tractography. Our approach achieves 83.0% classification accuracy while revealing functional network organization. We demonstrate that sparser, anatomy-driven connectivity matrices outperform dense alternatives, and that normalizing for network size improves model performance. Critically, our method is capable of exposing structural pathways contributing towards classification, distinguishing between complete network recruitment and selective regional activation. This approach bridges the gap between high-performance brain decoding and biological fidelity of the model, enhancing neuroscientific understanding, with implications for analyzing network dysfunctions in neurological disorders such as Alzheimers disease (AD), attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder, mild cognitive impairment (MCI), and schizophrenia.

Wolfram syndrome is a rare autosomal recessive disorder characterized by antibody-negative early-onset diabetes mellitus, optic atrophy, sensorineural hearing loss, arginine-vasopressin deficiency, and progressive neurodegeneration of the brainstem and cerebellum. It is caused primarily by pathogenic variants in the WFS1 gene, which encodes a transmembrane endoplasmic reticulum-resident protein involved in the unfolded protein response and cellular calcium homeostasis. Although multiple rodent models of Wolfram syndrome have been developed and shown to exhibit visual defects, some studies have reported significant vision loss prior to any detectable axonal degeneration or myelin abnormalities, and the mechanisms underlying these early visual deficits remain poorly understood. Recent in vitro studies have demonstrated altered synaptic contacts and aberrant neurite morphology in WFS1-deficient cerebral organoids and human iPSC-derived neurons, respectively. These findings prompted us to investigate, for the first time in vivo, whether synaptic and dendritic abnormalities occur in the retina of Wfs1 knockout mice. Using confocal microscopy, we examined retinal and optic nerve histology in Wfs1 knockout mice at 4 and 7 months of age. Our analysis reveals progressive synaptic alterations in the inner plexiform layer, driven by early presynaptic compartment failure. These changes represent the earliest detectable phenotype associated with vision loss in this model and precede overt axonal degeneration.

Synapses are evolutionarily conserved structures that form the fundamental units of neural communication. In the adult mouse cerebral cortex, most synapses are enveloped by glial protrusions from astrocytes and microglia, forming multi-partite synapses. Despite their prevalence, quantitative tools to systematically analyse these multi-cellular structures are limited to two or at most three markers. Here, we present Synapse Thresholding Image Analyser (SynThIA), an open-source, Python-based pipeline for high-throughput and accurate quantification of synapses, including multi-partite synapses. SynThIA enables multichannel analysis of up to four markers, providing detailed measurements of synaptic composition and distribution. The pipeline features an intuitive graphical interface allowing for users with minimal programming experience and a modular design that allows customization for advanced users. By combining accessibility and precision, SynThIA addresses a key methodological gap in multi-partite synaptic image analysis and provides a robust platform for studying synaptic organization in both in situ and ex situ preparation.

Predictive coding has influenced many conceptual accounts of delusions, the bizarre and distressing beliefs that accompany a range of neuropsychiatric conditions. However, these explanations remain incomplete and have rarely been tested directly using formal modelling. Here, we present a formal account of delusional beliefs based on hybrid predictive coding, which sheds light on the computational mechanisms underpinning the core features of delusions: thematic recurrence and imperviousness to contradictory evidence. In simulation experiments, we demonstrate that a combination of contextually inadequate initialisation of beliefs and excessive certainty (a hallmark of psychosis), triggers a reorganisation of the generative model relating observed events to hidden causes. This reorganisation enables the maintenance of delusional beliefs that are thematically stable, internally consistent with external inputs, and impervious to contradictory evidence, all without an increase in prediction error. Overall, our results suggest that delusions may arise not from faulty inference, as previously argued, but as an adaptive consequence of generative models learned under atypical conditions. These findings provide mechanistic insights into the computations underpinning delusions and have important implications for a novel therapeutic strategy in terms of re-training generative models.

Large-scale electrical perturbation of the human brain provides a unique model for understanding how multiscale biological constraints shape behaviorally relevant reorganization. Here, we integrate longitudinal neuroimaging coordinates from 148 experiments ({approx}2,300 subjects) with normative connectomics, chemoarchitecture, intrinsic electrophysiology, and transcriptomics to identify cross-scale principles governing human brain reconfiguration under strong perturbation. Convergent hubs of structural and functional plasticity embed within default-mode and salience systems and show complementary coupling to visual networks, linking perturbation-induced change to large-scale circuits supporting affective regulation, memory, interoception, and psychosis-relevant processes. These macroscopic patterns align with intrinsic cortical dynamics and chemoarchitectural gradients dominated by 5-HT1A receptors, with additional contributions from D2, -opioid and GABAA systems, and are enriched for astrocytic and microglial gene expression, implicating glial plasticity in systems-level reorganization. Finally, in a separate intervention dataset, regularized statistical-learning models demonstrate that this multiscale signature tracks behaviorally relevant symptom change specifically under strong electrical perturbation. Together, these results outline general organizing principles linking molecular, cellular and network-level constraints to human behavioral adaptation, providing a computational framework for understanding how large-scale perturbations reshape brain systems across levels of biological organization.

We explored processes within and orthogonal to the solution space (uncontrolled manifold, UCM) as superposition of fast random walk (RW) and slow drifts during multi-finger force production. Healthy participants performed two-hand (using the index and middle fingers per hand) accurate total force production task with different initial sharing of the force between the hand. After 5 s, visual feedback was manipulated - kept for both force and sharing, for only one of those variables, or turned off. The subjects tried to continue "doing what they have been doing" for 55 s. Trajectories both along and orthogonal to the UCM for total force showed fast RW and slow drifts. The diffusion plots confirmed persistent RW within the first 0.2 s and anti-persistent RW after 0.5 s. Persistent RW was similar across visual feedback conditions and larger orthogonal to the UCM. Its Hurst index correlated between the UCM and orthogonal to the UCM direction across participants. Anti-persistent RW depended strongly on visual feedback. Drift magnitude and characteristic time depended strongly on visual feedback, being similar along and orthogonal to the UCM. We conclude that RW destabilizes the state of the system thus encouraging exploration of nearby states over short time intervals and contributes to its stability over larger time intervals. Visual feedback plays a more important role in structuring stability of performance compared to the explicit task formulation. RW exploration promises new insights into the organization of stability in abundant systems and a potential biomarker for clinical studies. HighlightsO_LIStability during a multi-element action is structured in a feedback-specific way; C_LIO_LIRandom walk and drift characteristics of force depend not on the task but on salient feedback; C_LIO_LIRandom walk destabilizes steady state within a short range and stabilizes it within a long range; C_LIO_LIThe control of an action encourages exploration but limits its range. C_LI

Muller glia are instrumental macroglia of the vertebrate retina, once thought to be a homogeneous population. Now Muller glia are generally accepted as transcriptionally heterogeneous, and new evidence suggests functional diversity may exist in the way these cells respond to retinal injury. It remains unclear, however, whether this functional heterogeneity is limited to a transient phenotype that stems from injury or a fundamental feature of the healthy retina. Here, we investigate Muller glia heterogeneity in the uninjured zebrafish retina across development and adulthood using a comprehensive single-cell transcriptomic atlas of the 5 days post-fertilization (dpf) eye, validated in vivo and integrated with 9 dpf and adult datasets. We reveal that Muller glia are partitioned into three constitutive subpopulations that persist from early larval stages into adulthood: 1) a proliferative and immature population in both the peripheral and central retina; 2) a novel cohort of neuron-associated Muller glia that express coherent transcriptional programs specific to distinct neuronal subtypes, including retinal ganglion, amacrine and horizontal cells; and 3) spatially distinct Muller glia subsets that define a dorso-ventral axis of retinoic acid metabolism, bisected by a novel cyp26c1-expressing equatorial domain. Finally, cross-species analysis reveals that while neuron-associated programs are evolutionarily conserved in mammals, the spatial patterning of morphogens in adult retinae may be specific to the teleost lineage. Collectively, these findings provide robust evidence for intrinsic functional heterogeneity in the uninjured vertebrate retina, reframing Muller glia from a general support population to a specialized cellular network that actively maintains retinal geography and function. Main pointsO_LIZebrafish Muller glia are heterogeneous at 5dpf. C_LIO_LIZebrafish Muller glia subtypes define a spatial axis of retinoic acid metabolism. C_LIO_LINeuron-associated glial programs identified in Zebrafish Muller glia are evolutionarily conserved in mammals. C_LI

A central question in neuroscience is how neural processing generates or encodes behavior. Caenorhabditis elegans is well suited to addressing this question, given its compact nervous system and near-complete structural connectome. Despite this, findings from previous studies remain inconclusive. While some have shown that the connectome can robustly encode specific behaviors such as locomotion, others report that functional connectivity can be reconfigured across behaviors. We aim to understand the relationship between structural connectivity, functional connectivity and biological behavior in silico by using an experimentally motivated computational model leveraging the structural connectome. Stimulation of specific neurons in the model induces oscillatory neural responses, enabling us to infer neuronal functional connectivity. Functional connectivity is found to be stronger among some neurons, allowing us to identify functional communities. We find that electrical synapses play a critical role in determining functional communities, and the resulting mesoscale functional architecture is predominantly gap junctionally assortative. Furthermore, comparison with behavioral circuits shows that locomotion circuits are largely segregated into distinct functional communities while other circuits are more distributed across multiple functional communities. We also observe that stimulation of neurons belonging to these distributed circuits elicits a more synchronized neuronal response compared to stimulation of neurons within the more segregated circuits. This is consistent with the presence of behavioral patterns that originate in one circuit and terminate in another (e.g., chemosensation leading to locomotion), such that stimulation of one circuit can activate the other and eventually result in a synchronized response. We also find a large repertoire of chimera-like synchronization patterns upon stimulation of certain behavioral circuits (chemosensation, mechanosensation) indicating high dynamical flexibility. Overall, our results demonstrate that while certain behaviors are governed by functionally segregated circuits, others emerge from the synchronization of multiple functional communities, which are, to begin with, influenced by the underlying structural connectivity. Author summaryAnimals constantly transform sensory inputs into actions, but it is still unclear how this mapping from neural activity to behavior is implemented in a real nervous system. Caenorhabditis elegans offers a unique testbed for this question because its entire wiring diagram is nearly completely mapped. Yet, previous works have reached mixed conclusions about how well this anatomical circuit diagram predicts actual patterns of activity and behavior. Here, we use a biologically inspired computational model of the C. elegans nervous system to bridge this gap between structure, function, and behavior. By virtually stimulating individual neurons and observing the resulting network-wide oscillations, we infer how strongly different pairs and groups of neurons interact in functional terms. We then use network analysis tools to identify groups of neurons that tend to co-activate, and relate these functional communities to known behavioral circuits for locomotion and sensory processing. We find that gap junctions play a key role in shaping functional communities, and that locomotion-related neurons are more functionally segregated than neurons involved in other behaviors, which are more functionally distributed. Our results suggest that some behaviors rely on specialized, functionally isolated circuits, whereas others emerge from the coordinated activity of multiple functional communities.

Developing a reliable detection of olfactory performance for early Alzheimers disease (AD) diagnosis remains challenging. Existing methods, such as psychophysical and event-related potential approaches, provide limited consistency in quantifying olfactory function. This study introduces a novel and objective framework that analyzes olfactory-stimulus-evoked EEG synchronizations of the subjects for AD diagnosis. We calculated the time-resolved wavelet coherence between EEG signals and then determined the timings (i.e., latency and duration) that describe when olfactory-stimulus-induced EEG channel interactions begin and end for each channel and frequency band. These timings, as well as the mean synchronization values in these segments, were used as features for diagnosis. Our framework, when cross-correntropy was used as a synchronization measure, exhibited a notable diagnostic accuracy in mild AD detection. The most discriminating feature between mild AD and healthy subjects was found to be the latency of synchronization between Fp1 and Fz in the low{theta} band, which showed significantly high correlation with clinical test scores. Furthermore, our framework achieved 100% diagnosis accuracy when EEG features and clinical test scores were used together. Our findings show that inter-channel short-lived synchronization timings serve as useful and complementary metrics about subjects olfactory performance and their neurological conditions.

SARM1 and NMNAT2 are two well described players in the Programmed Axon Death (PAxD) pathway. However, less is known about their transcriptional regulation, especially in humans, despite evidence that their expression levels influence axon vulnerability and thus modulation of expression presents a potential therapeutic target. Here, we used in-cell luciferase assays to functionally study the promoter regions of the human NMNAT2 and SARM1 genes. We find that human NMNAT2 expression can be driven by cAMP, acting through one cAMP response element (CRE), compared to two in mice. Naturally occurring single-nucleotide variants exist within the CRE, some of which lower NMNAT2 promoter activity by more than 50%. We also report an ultra-rare single nucleotide variant in the NMNAT2 promoter in an ALS patient in Project MinE. This variant demonstrates pathogenic potential by lowering NMNAT2 promoter activity in our assay. Project MinE also reveals a common SARM1 promoter variant that significantly increases SARM1 promoter activity in our assay. Thus, several single nucleotide changes in the NMNAT2 and SARM1 promoters modify transcription levels in the direction that would predict an increase in susceptibility to PAxD. These promoter variants refine our understanding of regulatory mechanisms affecting NMNAT2 and SARM1 expression and, together with previously reported coding variants for these genes, expand the catalogue of functionally relevant variants for future association studies in neurodegenerative diseases, including peripheral neuropathies and motor nerve disorders.

The brain coordinates animal physiology and behavior via neuronal circuits. To understand and simulate brain functions, it is essential to delineate the synaptic connectivity between neurons. Transsynaptic tracers serve as powerful tools for such purposes. In response to the demand for anterograde tracers for circuit mapping and functional interrogation, we developed WTR, a fusion protein of mammalian codon-optimized WGA, TEV-protease cleavage sequence, and Recombinase. WTR expressed via AAV vectors in cell-type-specific starter neurons reaches their postsynaptic neurons and releases Cre/Flpo upon exposure to TEV-protease expressed in downstream neurons. Accompanied by Cre/Flpo-dependent expression of EGFP, GCaMP7s, or ChR2, the toolkit enables labeling, recording, or manipulation of downstream neurons. We utilized WTR to characterize downstream neurons of either glutamatergic or GABAergic neurons in the preoptic area of anterior hypothalamus for their differential actions in thermoregulation or stress responses, respectively. These results establish WTR as a versatile platform for functional anterograde circuit mapping.

The brain coordinates animal physiology and behavior via neuronal circuits. To understand and simulate brain functions, it is essential to delineate the synaptic connectivity between neurons. Transsynaptic tracers serve as powerful tools for such purposes. In response to the demand for anterograde tracers for circuit mapping and functional interrogation, we developed WTR, a fusion protein of mammalian codon-optimized WGA, TEV-protease cleavage sequence, and Recombinase. WTR expressed via AAV vectors in cell-type-specific starter neurons reaches their postsynaptic neurons and releases Cre/Flpo upon exposure to TEV-protease expressed in downstream neurons. Accompanied by Cre/Flpo-dependent expression of EGFP, GCaMP7s, or ChR2, the toolkit enables labeling, recording, or manipulation of downstream neurons. We utilized WTR to characterize downstream neurons of either glutamatergic or GABAergic neurons in the preoptic area of anterior hypothalamus for their differential actions in thermoregulation or stress responses, respectively. These results establish WTR as a versatile platform for functional anterograde circuit mapping.

Cells release signaling molecules such as neurotransmitters that diffuse through the extracellular space and bind to receptors. These signaling molecules can be detected by fluorescent sensors/probes to provide images of the signaling process. Such images are not equivalent to a concentration because diffusion and sensor kinetics affect (convolute) them. Therefore, computational approaches are necessary to disentangle these contributions and allow interpretation of fluorescent sensor-based images. Here, we present a kinetic Monte Carlo framework (FLuorescence Imaging Kinetic Simulation, FLIKS) that simulates signaling molecules undergoing cellular release, stochastic diffusion and reversible binding to sensors in realistic cellular (2D or 3D) geometries. We apply it to model neurotransmitter (dopamine) release in synaptic clefts and for paracrine signaling by immune cells. We also show how sensor location, sensor kinetics and release location affect fluorescence images. For example, we show how sensor sensitivity depends on the distance from the synaptic cleft and changes when dopamine transporters (DAT) clear dopamine. The approach also allows to compare the performance of membrane bound (genetically encoded) sensors versus artificial sensors such as nanosensors placed outside under or around the cells. As an example, we also demonstrate how the images of catecholamine release by immune cells can be modeled and compared to experimental data to better understand the release pattern. This framework provides a quantitative basis for analyzing and interpreting fluorescent sensor imaging data.

Vestibular schwannomas (VS) cause vestibular function loss by mechanisms still poorly understood. We evaluated the vestibulo-ocular reflex by the video-assisted Head Impulse Test (vHIT) in patients with planned tumour resection by a trans-labyrinthine approach. The vestibular sensory epithelia were collected and processed by immunofluorescent labelling for confocal microscopy analysis of sensory hair cell subtypes (type I, HCI, and type ll, HCll), calyx endings of the pure-calyx afferents, and the calyceal junction normally found between HCI and the calyx (n=23). Comparing Normofunction and Hypofunction patients, we concluded that worse vestibular function associates with decreased HCI and HCll counts in the sensory epithelia and with increased proportion of damaged calyces. A decrease in the number of HCI and calyx endings of the pure-calyx afferents was recorded to associate with age increase. Partial least squares regression (PLSR) models indicated that VS and age had independent, additive effects on vestibular function. Correlation analyses indicated that lower vHIT gains associate with lower numbers of HCI and increased percentages of damaged calyces. These data support the hypothesis that the deleterious effect of VS on vestibular function is mediated, at least in part, by its damaging impact on the vestibular sensory epithelium. They also provide further evidence for the dependency of the vestibulo-ocular reflex on HCI function and for the calyceal junction pathology as a common response of the sensory epithelium to HC stress.

Vestibular schwannomas (VS) cause vestibular function loss by mechanisms still poorly understood. We evaluated the vestibulo-ocular reflex by the video-assisted Head Impulse Test (vHIT) in patients with planned tumour resection by a trans-labyrinthine approach. The vestibular sensory epithelia were collected and processed by immunofluorescent labelling for confocal microscopy analysis of sensory hair cell subtypes (type I, HCI, and type ll, HCll), calyx endings of the pure-calyx afferents, and the calyceal junction normally found between HCI and the calyx (n=23). Comparing Normofunction and Hypofunction patients, we concluded that worse vestibular function associates with decreased HCI and HCll counts in the sensory epithelia and with increased proportion of damaged calyces. A decrease in the number of HCI and calyx endings of the pure-calyx afferents was recorded to associate with age increase. Partial least squares regression (PLSR) models indicated that VS and age had independent, additive effects on vestibular function. Correlation analyses indicated that lower vHIT gains associate with lower numbers of HCI and increased percentages of damaged calyces. These data support the hypothesis that the deleterious effect of VS on vestibular function is mediated, at least in part, by its damaging impact on the vestibular sensory epithelium. They also provide further evidence for the dependency of the vestibulo-ocular reflex on HCI function and for the calyceal junction pathology as a common response of the sensory epithelium to HC stress.

One major distinction between artificial neural networks and biological brains is the prevalence of extensive, long-range feedback connections in biological systems. Here we investigate unique contributions of these hierarchical feedback signals beyond feedforward processing and local recurrence by exploring their mechanistic role in resolving visual ambiguity caused by occlusion. Both empirical fMRI and EEG experiments and computational modeling show that when sensory evidence for faces became insufficient, the ventrolateral prefrontal cortex (vlPFC) sustained a low-dimensional belief state (e.g., animate vs. inanimate objects) and transmitted this abstract information back to the animacy map in the ventral temporal cortex (VTC) encompassing face-selective representations. Critically, in the hierarchical vision model inspired by this finding, this frontal feedback did not reshape the attractor geometry of the VTC; instead, it provided guidance to reroute ongoing neural dynamics away from ambiguous pseudo-states toward face attractor basins in the energy representational landscape. This control-based mechanism of feedback signals thus enabled perceptual completion by reconstructing missing facial features with temporal costs verified through EEG. Together, this multimodal study bridges analysis-by-synthesis theories of vision and dynamical-systems perspectives on long-range feedback as state-space control, and offers inspiration for the design of hierarchical AI architectures incorporating feedforward, recurrent, and feedback connections.

AO_SCPLOWBSTRACTC_SCPLOWAuditory-motor learning is critical in mastering the production of complex sounds, such as speaking and playing music. It is anchored upon internal models of interactions between actions and their sensory consequences, which are fine-tuned by minimizing the errors between the predicted and received sound. Here, we applied the concept of surprisal to a piano-playing task to probe the neural dynamics of sensorimotor learning. Specifically, during play, the key-pitch map was changed unpredictably among three map configurations: normal, inverted, and shifted-inverted. At the change boundaries, a signature of violated motor-to-auditory predictions was found in the auditory evoked responses at N100 which could not be attributed to either purely auditory surprisals or motor execution errors. This surprisal is modulated by short-term context, with greater surprise following longer periods of no map change, indicating that the brain continuously tracks short-term map contexts and rapidly adapts to them. In contrast, 30 minutes of extended goal-directed training on a single map modulated P50 amplitude only for that map, which can be explained by a slow, persistent modulation of motor predictions from the auditory signals. Hence, while auditory predictions from motor actions are rapidly and implicitly learned within short-term contexts, the complementary process of adjusting motor inferences from auditory inputs requires targeted training sustained over time. Our approach of studying auditory-motor surprisal in time-varying sequences reveals that auditory-motor learning is fast, context-sensitive, and shaped by both short- and long-term experience. Significance statementUnderstanding how the brain links motor actions with their sensory consequences is key to explaining how complex skills are acquired and how they adapt to changing environments. Prior work has shown that short-term sensory feedback supports rapid adaptation. Yet, the neural mechanisms underpinning the evolution of internal sensorimotor associations across different stages of learning remain to be elucidated. We address this challenge by extending the concept of surprisal, traditionally used in studies of perception, to the sensorimotor domain. Results show that surprisal responses are modulated by both short-term sensory feedback and longer-term training, suggestive of two distinct neural mechanisms underlying sensorimotor learning. These findings advance our understanding of the neural dynamics of sensorimotor learning and inform development of technologies that interface with sensorimotor systems, such as virtual reality and brain-machine interfaces.

This electroencephalography (EEG) study elucidates how expectations shape visually evoked brain responses over time by revealing a biphasic temporal mechanism: an initial enhancement of encoding for expected image components, followed by a later prioritization of unexpected components. This temporal dissociation suggests that the brain first combines sensory input with prior expectations in a Bayesian manner before shifting to emphasize surprising information, supporting both efficient recognition and adaptive model updating.

BackgroundSpinal cord injury (SCI) triggers persistent neuroinflammation, gliosis, neuronal loss, and demyelination, leading to motor deficits and neuropathic pain. Botulinum neurotoxin type A (BoNT/A) has shown anti-inflammatory and neuroprotective effects in acute SCI, but its potential in the chronic phase remains unclear. This study investigates whether combining BoNT/A with electrical muscle stimulation (EMS) enhances recovery in chronic SCI. MethodsAdult mice with severe thoracic SCI (paraplegic) underwent EMS (30 min/day for 10 non-consecutive days starting 3 days post-injury) or no stimulation. Fifteen days after SCI, animals received a single intrathecal injection of BoNT/A (15 pg/5 L) or saline. Functional recovery was assessed up to 60 days as well as in moderate and mild SCI mice, neuropathic pain onset and maintenance were evaluated. Spinal cord tissue was analysed for astrocytic and microglial morphology, neuronal and oligodendroglia survival, myelin protein expression, and in vitro effects on oligodendrocyte precursor cells (OPCs). The phenotype of hindlimb muscles was evaluated through morphological and gene expression analyses. ResultsEMS was able to counteract muscle atrophy and fibrosis, and when combined with BoNT/A, also denervation. Moreover, the combination restored hindlimb motor function in chronic SCI, whereas BoNT/A or EMS alone were ineffective. Neuropathic pain, a common comorbidity associated with SCI, was mitigated by BoNT/A treatment even when administered in the chronic phase. BoNT/A reduced astrocytic hypertrophy and excitatory synapse association and was associated with a morphology-based redistribution of microglial profiles toward a resting-like classification, decreased apoptosis, and increased neuronal and oligodendroglia survival. Myelin basic protein expression was significantly elevated in vivo. In vitro, BoNT/A promoted OPC differentiation into myelinating oligodendrocytes, increased process complexity, and upregulated Myelin basic protein, galactocerebroside C, proteolipid protein, and myelin oligodendrocyte glycoprotein under both proliferative and differentiating conditions. Cleaved SNAP25 colocalization with OPC confirmed direct BoNT/A internalization and activity. ConclusionsBoNT/A exerts multi-cellular neuroprotective actions in chronic SCI, supporting neuronal and oligodendroglia survival, reducing neuroinflammation, enhancing remyelination and the combination with EMS promotes substantial recovery of muscle homeostasis within a permissive microenvironment shaped by early stimulation. Its efficacy depends on a permissive microenvironment achieved through EMS. These results provide strong rationale for the clinical evaluation of BoNT/A as a therapeutic strategy for chronic SCI.

Riluzole is the most commonly prescribed among the limited approved therapies for amyotrophic lateral sclerosis (ALS), a neurodegenerative disorder characterized by progressive motoneuron loss and paralysis. It is thought to act by suppressing motoneuron excitability and glutamate release, but its clinical benefits are modest and often diminish over time. We previously showed that homeostatic mechanisms in the SOD1G93A (mSOD1) mouse model of ALS are hyperactive and prone to overcompensation. Here, we tested whether such dysregulated homeostasis antagonizes the effects of riluzole. Wild-type (WT) and presymptomatic mSOD1 mice received therapeutic doses of riluzole in drinking water for 10 days, with untreated littermates of both genotypes serving as controls. Motoneuron excitability and synaptic inputs were then examined using intracellular recordings from the isolated sacral spinal cord. The data showed that chronic riluzole treatment increased motoneuron excitability and polysynaptic inputs in mSOD1 mice but produced no detectable changes in WT motoneurons. These results suggest that hyperactive homeostatic mechanisms in ALS counteract the suppressive effects of riluzole. Notably, mSOD1 motoneurons exhibited larger membrane capacitance than WT, consistent with their increased cell size at this disease stage. Riluzole treatment reduced motoneuron membrane capacitance in mSOD1 mice to the range observed in WT animals, indicating normalization of cell size and potentially reduction in metabolic demand. Together, these findings help explain the limited clinical efficacy of riluzole while revealing a previously unrecognized neuroprotective mechanism of the drug in ALS.

While goal-driven artificial neural networks (ANNs) have successfully modeled important aspects of the primate ventral stream, their efficacy for the dorsal stream remains unclear. Here, we investigated how computational objectives and architectural constraints influence the neural alignment to MSTd, a dorsal area that demonstrates selectivity to complex optic flow patterns and is linked to self-motion perception. We systematically evaluated the neural alignment between 54 ANNs and Non-negative Matrix Factorization (NNMF) against key neurophysiological optic flow tuning properties of MSTd. We optimized these models on either a supervised self-motion estimation task (accuracy-optimized) or an unsupervised input reconstruction task (autoencoding) using both raw optic flow and model MT-encoded signals. Interestingly, accuracy on the self-motion task does not predict neural alignment. Instead, model performance bifurcates based on both objective and input encoding: autoencoders utilizing MT-like input signals consistently achieve superior correspondence with MSTd tuning preferences. Explicitly enforcing sparsity or non-negativity does not improve alignment; rather, these constraints often degrade the match to biological data. Furthermore, we demonstrate that neural alignment remains largely unaffected even when the pressure to generate an efficient code with few units is eased, suggesting that dimensionality reduction may not be a primary driver of MSTd-like tuning. Taken together, our results indicate that the tuning properties of MSTd are better explained by an unsupervised reconstruction-based objective than by supervised task optimization, suggesting a fundamental difference in the computational principles that govern the dorsal and ventral streams. Significance StatementGoal-driven neural networks have revolutionized our understanding of the ventral visual stream, yet their effectiveness in modeling the dorsal stream remains less clear. We systematically evaluated 54 neural network models to identify the computational principles that drive neural-like optic flow tuning in dorsal stream area MSTd. Surprisingly, we find that accuracy-optimized models fail to replicate biological tuning. Instead, models that reconstruct motion inputs from a biologically plausible MT-like representation achieve the highest consistency with MSTd neurons. These findings suggest that the organizational principles of dorsal stream area MSTd may be better explained by an unsupervised, reconstruction-based objective rather than one focused on the accuracy of self-motion estimation, suggesting a fundamental difference in the computational objectives of the two visual streams.

Air pollution has been increasingly linked to adverse neurodevelopmental and neurodegenerative outcomes. While experimental and preclinical studies suggest that exposure to particulate matter (PM), particularly during gestation, may disrupt cognitive development, the impact of short-term PM exposure on cognitive and behavioral functioning in healthy young populations remains insufficiently explored in Spain. Moreover, few studies have incorporated individualized dosimetry models to estimate exposure more accurately. This study included 186 healthy young adults (mean age = 20.4 years) recruited from three Spanish cities (Teruel, Almeria, and Talavera) characterized by different pollution levels. Ambient fine and coarse PM concentrations were recorded 8, 15, and 30 days prior to psychological assessment. Instead of relying solely on raw in situ environmental measurements, individualized PM deposition was estimated using the Multiple-Path Particle Dosimetry Model (MPPD), allowing a more biologically meaningful exposure approximation. Psychological outcomes were assessed using validated questionnaires: DASS-21 (depression, anxiety, stress), BIS-11 (impulsivity), UCLA Loneliness Scale, and SWLS (life satisfaction). Behavioral performance was evaluated using computerized versions of the Attentional Network Task (ANT) and the Stroop Task. Blood NRF2 concentrations were analyzed as a biomarker potentially related to oxidative stress mechanisms. In situ data indicated that Talavera presented the highest pollution levels, followed by Almeria and Teruel. Linear regression analyses showed that coarse PM exposure across 8-, 15-, and 30-day windows significantly predicted poorer Executive Control Index performance in the ANT. Additionally, 15-day coarse PM and 30-day fine PM exposure were associated with greater cognitive interference. Oxidative stress markers were significantly associated with PM exposure levels. These findings support emerging evidence that short-term PM exposure may negatively affect executive and attentional processes even in healthy young adults. Further longitudinal research incorporating individualized exposure modeling is warranted to clarify causal pathways and underlying biological mechanisms. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/713644v1_ufig1.gif" ALT="Figure 1"> View larger version (79K): org.highwire.dtl.DTLVardef@1a0ac13org.highwire.dtl.DTLVardef@1812accorg.highwire.dtl.DTLVardef@120bf07org.highwire.dtl.DTLVardef@dd9a7c_HPS_FORMAT_FIGEXP M_FIG C_FIG

Neuron connectivity and signal processing rely on a complex, dynamic morphology regulated by the cytoskeleton. The membrane-associated periodic skeleton (MPS), a 190-nm periodic actin-spectrin lattice, is a conserved feature of neurons. Here, we show that the dendritic MPS is built from a dual {beta}-spectrin system in which {beta}II- and {beta}III-spectrins are co-expressed and interleaved at the nanoscale in shafts and spine necks. 3D MINFLUX nanoscopy suggests that these paralogues form both homotypic ({beta}II- or {beta}III-only) and heterotypic ({beta}II/{beta}III) tetramers with an approximately 100-nm radial periodicity. Either paralogue alone is sufficient to maintain lattice architecture, whereas their combined loss disrupts MPS integrity. Using targeted mutagenesis, we show that actin binding is required to stabilize both paralogues within the MPS, whereas {beta}III-spectrin additionally depends on phosphoinositide interactions. Our findings reveal that, unlike the axonal MPS, the dendritic MPS is a composite scaffold in which structural redundancy coexists with paralogue-specific regulatory mechanisms, with potential consequences for synaptic function.

The accumulation of A{beta} plaques and hyperphosphorylation of Tau neuropathologically characterize Alzheimers disease (AD). Synaptic dysfunction and endoplasmic reticulum (ER) stress precede overt neuropathology. ER stress is characterized by the accumulation of unfolded/misfolded proteins, which leads to activation of the adaptive signaling pathway, the unfolded protein response (UPR). Chronic or unresolved ER stress, as in disease, is maladaptive and triggers the integrated stress response (ISR). We hypothesize that targeted attenuation of ISR activation would mitigate the early cognitive deficits and molecular pathology in the triple transgenic (3xTg) mouse model of AD. To test this hypothesis, we used an adeno-associated viral (AAV) vector to overexpress BiP, the key ER chaperone and UPR regulator, in the hippocampi of young 3xTg mice. BiP overexpression reduced phosphorylated PERK (pPERK), a marker of ISR activation, and increased synaptic proteins BDNF, PSD95, and choline acetyltransferase marker (ChAT). Hippocampal-dependent working memory, social memory, long-term spatial memory, and REM theta power were improved without changes in locomotion. BiP overexpression reduced neuroinflammation, as evidenced by a decrease in the astrocyte marker GFAP. Additionally, A{beta} and A{beta}42 levels were reduced in the hippocampus and cortex. Collectively, these findings indicate that modulation of ER stress via BiP overexpression ameliorates early cognitive and molecular alterations associated with AD.

Coordinated signaling among neurons, glia, and the vasculature is essential for the formation of a functional nervous system, yet how these relationships emerge during development remains unclear. Here, we investigated the developmental interplay between neural activity, Muller glia, and the retina vasculature in mice. Using quantitative confocal imaging from postnatal day 5 to eye-opening, we mapped the emergence of the superficial, intermediate, and deep vasculature layers and found that they emerged normally in mice lacking the {beta}2-containing nicotinic acetylcholine receptors, despite a dramatic reduction in cholinergic signaling. Tip cell density and overall vessel growth were unchanged, indicating cholinergic wave activity is not required for the emergence of retinal vasculature. We next defined the developmental timeline of Muller glia-vascular interactions. Sparse labeling and immunohistochemistry revealed that Muller glial lateral processes closely associate with endothelial tip cells during intermediate- and deep-layer angiogenesis and establish Aquaporin-4-enriched endfeet at vascular contact sites from the earliest stages of growth, even when vessel trajectories are perturbed. Finally, two-photon calcium imaging combined with simultaneous electrophysiology demonstrated that Muller glial endfeet exhibit robust, compartmentalized calcium transients during development. Although a subset of events was temporally correlated with retinal waves, enhancing neurotransmitter spillover selectively increased wave-associated activity in glial stalks but not endfeet. These findings indicate that calcium signaling at the glial-vascular interface is largely independent of spontaneous neuronal activity. Together, our results support a model in which Muller glia engage growing vessels through an activity-independent, parallel developmental program that may provide instructive cues for retinal angiogenesis.

Coordinated signaling among neurons, glia, and the vasculature is essential for the formation of a functional nervous system, yet how these relationships emerge during development remains unclear. Here, we investigated the developmental interplay between neural activity, Muller glia, and the retina vasculature in mice. Using quantitative confocal imaging from postnatal day 5 to eye-opening, we mapped the emergence of the superficial, intermediate, and deep vasculature layers and found that they emerged normally in mice lacking the {beta}2-containing nicotinic acetylcholine receptors, despite a dramatic reduction in cholinergic signaling. Tip cell density and overall vessel growth were unchanged, indicating cholinergic wave activity is not required for the emergence of retinal vasculature. We next defined the developmental timeline of Muller glia-vascular interactions. Sparse labeling and immunohistochemistry revealed that Muller glial lateral processes closely associate with endothelial tip cells during intermediate- and deep-layer angiogenesis and establish Aquaporin-4-enriched endfeet at vascular contact sites from the earliest stages of growth, even when vessel trajectories are perturbed. Finally, two-photon calcium imaging combined with simultaneous electrophysiology demonstrated that Muller glial endfeet exhibit robust, compartmentalized calcium transients during development. Although a subset of events was temporally correlated with retinal waves, enhancing neurotransmitter spillover selectively increased wave-associated activity in glial stalks but not endfeet. These findings indicate that calcium signaling at the glial-vascular interface is largely independent of spontaneous neuronal activity. Together, our results support a model in which Muller glia engage growing vessels through an activity-independent, parallel developmental program that may provide instructive cues for retinal angiogenesis.

Current evidence suggests that older adults perform worse at tasks involving spatial memory and navigation, yet the underlying reasons remain unclear. Here, we tested the hypothesis that age-related declines in spatial memory stem from difficulties in recognizing spatial environments from rotated perspectives. Young and older adults underwent fMRI as they encoded virtual scenes which were later viewed either from the same or rotated perspective. Older adults were worse at identifying changes in these scenes, although the age effect was equally robust across perspective conditions. Neural specificity of scene representations was examined with the phenomenon of fMRI repetition adaptation. We predicted that young adults would show significant fMRI adaptation to the same but not rotated perspective, indicative of intact viewpoint specificity, while older adults show would adaptation effects to both. While analyses of raw fMRI BOLD produced results consistent with these predictions, follow-up analyses revealed a general attenuation of activity in older adults across both perspective conditions. Additionally, although older adults showed both lower fMRI BOLD and worse spatial memory, lower trial-wise BOLD was associated with better performance independent of age. This suggests that the variance associated with fMRI adaptation is reflective of two independent sources of variance: age and cognition. Our results suggest that age differences in spatial memory may manifest due to cognitive and neural factors that are shared across same and rotated perspectives, and thus they cannot be explained by a selective deficit in allocentric (viewpoint-independent) processing. Significance StatementIncreasing age is often associated with reduced spatial memory and navigation. Prior research suggests that age differences in spatial memory could be exacerbated by changes in perspective, possibly due to increased difficulties in the ability to construct allocentric (viewpoint-independent) representations from previously encoded egocentric perspectives. Here, we demonstrate that older adults are equally disadvantaged when recognizing layouts across same and rotated perspectives. FMRI analyses indicate that older age is associated with reduced fMRI BOLD in higher-level visual cortex across both perspective conditions, as opposed to altered specificity of perspective coding. Consequently, the present study challenges the notion that aging is associated with a selective decline in allocentric spatial memory and instead supports a more general age-related difficulty with scene processing.

Continuous invasive brain-computer interfaces (BCIs) translate neural activity into continuous control signals. During ongoing control, fluctuations in these signals can reflect either transient execution noise or genuine changes in user intent, yet most BCI control systems do not explicitly distinguish between these possibilities. Assistive controllers must therefore determine whether variability should be stabilized as noise or expressed as intentional changes in movement. Here we evaluate a confidence-modulated shared-control framework that adaptively integrates decoded neural commands with a temporal prior to balance stabilization and responsiveness. Using macaque BCI navigation tasks that impose opposing control demands, we show that shared control nearly eliminates execution failures in obstacle-avoidance tasks while preserving the directional structure of commands. When goals change abruptly, however, the same temporal prior introduces transient inertia. Resetting the prior restores baseline performance, revealing a fundamental stabilization-responsiveness trade-off imposed by temporal priors during continuous arbitration.

Interpersonal neural synchrony (INS) in mother-child dyads is often interpreted as a neural marker of relational quality and sensitive caregiving, yet findings on its predictors remain heterogeneous. One possible source of this variability is the diversity of interactional paradigms used in hyperscanning research. This study examined how maternal personality, child temperament, and affective states relate to INS across interaction contexts varying in social interactivity. Thirty-three mother-child dyads (n = 20 female children) participated in a functional near-infrared spectroscopy hyperscanning experiment involving passive video co-exposure, a structured cooperative task, and free interaction. Fronto-temporal activity was recorded simultaneously, and INS was computed using wavelet transform coherence. Above-chance levels of INS emerged in inter-brain region combinations primarily involving the mothers left inferior frontal gyrus (IFG) and the childs right IFG (adjusted ps < 0.030, Cohens d range = 0.14-0.31). Maternal neuroticism was the only significant predictor of INS, with higher levels associated with increased synchrony during passive video co-exposure (adjusted p = 0.012) and free interaction (adjusted p = 0.021), but not during the structured game. These findings indicate that maternal dispositional traits shape INS in a context-dependent manner. Notably, the positive association between neuroticism and INS suggests that heightened neural synchrony may reflect over-attunement in more anxious caregivers, rather than optimal coordination. Excessive synchrony may therefore index tightly coupled, over-monitoring interaction dynamics, consistent with models of affiliative vigilance in anxious parenting. Overall, INS may follow a non-linear pattern in which moderate levels are most adaptive, highlighting its flexible, dynamic, and context-sensitive nature.

Human brain assembloids offer a powerful platform for modeling neurological diseases, yet comprehensive methods for analyzing their complex network dynamics are lacking. Here, we developed a time-resolved network analysis pipeline that extracts quantitative biomarkers from two-photon calcium imaging, enabling the detection of subtle differences between disease and control models. We applied this pipeline to assembloids containing a pathogenic MAPT p.R406W variant--clinically associated with an Alzheimers disease-like phenotype--and their isogenic controls. Our analysis revealed that mutant networks exhibit significantly increased degree variance and clustering. This indicates a "hub-like", interconnected topology prone to hypersynchrony, a finding that parallels the network hyperexcitability and seizure-like features observed in in-vivo models of Alzheimers disease. Furthermore, a Random Forest classifier trained on these dynamic network features distinguished between diseased and control states with high accuracy (F1 score = 0.90). These results establish that dynamic network properties can serve as potent biomarkers for identifying pathological states in assembloid models, providing a quantitative framework to investigate disease mechanisms and potential therapeutic interventions.

Working memory (WM) supports the temporary maintenance of goal-relevant information and is disrupted across many neuropsychiatric disorders. We examined whether scalp electroencephalography (EEG) data features beyond spectral power, including waveform shape, broadband spectral structure, and signal complexity, provide complementary information for predicting cognitive and clinical outcomes. EEG was recorded from 200 adults spanning a broad range of neuropsychiatric symptom severity while they completed three WM task paradigms: Sternberg spatial WM (SWM), delayed face recognition (DFR), and dot pattern expectancy (DPX). Separate machine learning models were trained on EEG features from the encoding, delay, and probe phase of each task to predict participants' task accuracy, reaction time (RT) variability, WM capacity, and psychopathology scores (Brief Psychiatric Rating Scale). A split-half analytic framework was used, with cross-validated model development in an exploratory dataset (N=100) and evaluation of statistically significant models in a held-out validation dataset (N=100). In the exploratory dataset, SWM task data best predicted WM capacity, DPX task data predicted RT variability, and DFR task data predicted psychopathology, suggesting that these three WM paradigms engage distinct neural processes relevant to different outcomes. No models reliably predicted task accuracy. Models incorporating features beyond spectral power generally outperformed power-only models, and task-derived features outperformed resting-state-derived features. However, only those models predicting WM capacity and RT variability generalized to the validation dataset; models predicting psychopathology did not. These findings demonstrate functional heterogeneity across WM paradigms, show that complementary EEG features enhance predictive modeling, and highlight the importance of rigorous validation for identifying robust brain-behavior relationships.

Dopamine (DA) neurons of the midbrain project throughout the striatum, including the nucleus accumbens core (NAc) and are thought to co-release ATP with DA from vesicles. The mechanisms of evoked NAc ATP release and clearance and their relationship to exocytotic DA transmission are largely unexplored and the focus of the present work. Using fast scan cyclic voltammetry (FSCV), we measured simultaneous ATP and DA transmission in response to pharmacological manipulations of release and reuptake cellular machinery. ATP transmission is tightly coupled to that of DA, though ATP release concentrations are typically smaller. Manipulations that increase DA transmission (increased release via 4-aminopyridine Kv channel blockade or decreased uptake via cocaine) also increase ATP transmission, though to a smaller extent. Blocking DA vesicular packaging (reserpine) or action potentials (lidocaine), results in attenuated DA and ATP release. Interestingly, reserpine or lidocaine can result in completely abolished DA release, but not a complete prevention in ATP release, suggesting a secondary source for ATP transmission thats not dependent on DA terminals. Both transmitters were reduced to a similar extent following nAChR blockade, demonstrating that nAChR activation regulates ATP in addition to DA. Surprisingly, cocaine inhibition of DATs reduced clearance for both ATP and DA, which correlated with one another when cocaine concentration was highest. There was also a strong relationship between the effect of cocaine on release of ATP and DA. As the first FSCV study to examine evoked NAc ATP release, this paper bridges prior work to confirm the strong association between ATP and DA in the mesolimbic circuit and identifies unexpected overlap in mechanisms regulating their transmission. Our results contribute novel evidence of both vesicular and non-vesicular ATP release in the NAc and demonstrate that extracellular ATP is a modulator of DA terminal function.

How the human brain organizes complex cognitive functions remains unresolved, particularly regarding the debate between localized and distributed architectures. Here, we show that the language network undergoes a non-linear developmental reorganization that reconciles these views. Using multimodal neuroimaging and behavioral measures, we identify a three-stage trajectory: early localization, a transiently distributed state during adolescence marked by a connectivity dip, and a return to refined localization in adulthood. This adolescent dip is behaviorally meaningful and contributes to integrative network architecture. Convergent shifts in functional connectivity and brain-behavior relationships identify adolescence as a critical window for large-scale network remodeling. Our findings provide a unifying framework for language network development and suggest that transient redistribution may represent a general principle of human brain maturation.

Information about eye movements is necessary for linking auditory and visual information across space. Recent work has suggested that such signals are incorporated into processing at the level of the ear itself (Gruters, Murphy et al. 2018). Here we report confirmation that the eye movement signals that reach the ear can produce perceptual consequences, via a case report of an unusual participant with tensor tympani myoclonus who hears sounds when she moves her eyes. The sounds she hears could be recorded with a microphone in the ear in which she hears them (left), and occurred for large leftward eye movements to extreme orbital positions of the eyes. The sounds elicited by this participants eye movements were reminiscent of eye movement-related eardrum oscillations (EMREOs, (Gruters, Murphy et al. 2018, Brohl and Kayser 2023, King, Lovich et al. 2023, Lovich, King et al. 2023, Lovich, King et al. 2023, Abbasi, King et al. 2025, Sotero Silva, Kayser et al. 2025, King and Groh 2026, Leon, Ramos et al. 2026, Sotero Silva, Brohl et al. 2026)), but were larger and longer lasting than classical EMREOs, helping to explain why they were audible to her. Overall, the observations from this patient help establish that (a) eye movement-related signals specifically reach the tensor tympani muscle and that (b) when there is an abnormality involving that muscle, such signals can lead to actual audible percepts. Given that the tensor tympani contributes to the regulation of sound transmission in the middle ear, these findings support that eye movement signals reaching the ear have functional consequences for auditory perception. The findings also expand the types of medical conditions that produce gaze-evoked tinnitus, to date most commonly observed in connection with acoustic neuromas.

Sensory cortices filter repeated inputs through rapid adaptation over seconds and experience-driven learning over days. Although these forms of plasticity occur simultaneously, it is not known how they interact within cortical circuits. We combined two-photon calcium imaging, data-driven circuit modelling and optogenetics to investigate how short-term adaptation in layer 2/3 of mouse V1 is shaped by stimulus familiarity and reward association. Habituation reduced the fraction of pyramidal cells responsive to a visual stimulus, whereas reward association maintained overall responsivity. In contrast, both forms of learning shifted pyramidal cell adaptation from depression toward sensitization, but through distinct circuit mechanisms. Habituation reduced disinhibition through the VIP[->]SST[->]PC pathway by weakening feedback activation of VIPs and VIP[->]SST connections. Reward association counteracted this effect by increasing disinhibition through the SST[->]PV[->]PC pathway, strengthening SST[->]PV connections while reducing SST[->]PC inputs. Despite engaging distinct disinhibitory circuits and producing divergent effects on pyramidal cell responsivity, both forms of learning converged on a reduced PV:SST input ratio to pyramidal cells, thereby biasing V1 toward sensitizing adaptation. These results identify changes in cortical circuits that link the plasticity of fast adaptation to simple forms of learning.

Elucidating the neural computations underlying natural, complex movement remains a fundamental challenge in neuroscience. Bat flight presents a formidable motor control challenge, requiring the use of hand-like wings whose many degrees of freedom must be precisely coordinated to enable rapid three-dimensional maneuvers. Here we performed large-scale wireless recordings of neuronal ensembles from the wing motor cortex of freely flying bats using Neuropixels probes, alongside detailed 3D pose tracking of wing kinematics. Despite the complexity of flight control, bats repeatedly executed highly accurate flights through precise adjustments of individual wingbeats. Surprisingly, motor cortical activity was not dominated by the global wingbeat cycle. Instead, individual neurons were sparsely active, exhibiting mixed selectivity for specific flight kinematics combined with variable entrainment to the wingbeat phase reaching millisecond-scale precision. This yielded a high-dimensional population regime driven by low shared variance across wingbeats, with successive wingbeats occupying distinct neural population states. Our findings reveal that during complex natural behavior the mammalian motor cortex operates in a high-dimensional computational regime that challenges prevailing views of motor cortical computation and underscores the importance of studying ethologically relevant behaviors to uncover neural principles governing brain function.

Elucidating the neural computations underlying natural, complex movement remains a fundamental challenge in neuroscience. Bat flight presents a formidable motor control challenge, requiring the use of hand-like wings whose many degrees of freedom must be precisely coordinated to enable rapid three-dimensional maneuvers. Here we performed large-scale wireless recordings of neuronal ensembles from the wing motor cortex of freely flying bats using Neuropixels probes, alongside detailed 3D pose tracking of wing kinematics. Despite the complexity of flight control, bats repeatedly executed highly accurate flights through precise adjustments of individual wingbeats. Surprisingly, motor cortical activity was not dominated by the global wingbeat cycle. Instead, individual neurons were sparsely active, exhibiting mixed selectivity for specific flight kinematics combined with variable entrainment to the wingbeat phase reaching millisecond-scale precision. This yielded a high-dimensional population regime driven by low shared variance across wingbeats, with successive wingbeats occupying distinct neural population states. Our findings reveal that during complex natural behavior the mammalian motor cortex operates in a high-dimensional computational regime that challenges prevailing views of motor cortical computation and underscores the importance of studying ethologically relevant behaviors to uncover neural principles governing brain function.

Early childhood development is scaffolded by rapid maturation of brain white matter structure, believed to support the emergence of cognitive and socioemotional functions. Previous whole-tract studies have suggested patterns of white matter development occurring along posterior-anterior, deep-superficial and inferior-superior axes. However, little is known as to whether these patterns are evident within tracts. Using longitudinal diffusion imaging data from 133 children (4-8 years; 76 females), the present work characterizes along-tract patterns of white matter development across association, commissural and projection bundles using fixel-based analyses of microstructure and macrostructure. Within long range association bundles, faster age-related changes were observed for segments adjacent to the visual cortices relative to segments located near association regions, supporting a sensorimotor-association axis of brain development. An inferior-superior pattern was found for projection tracts, with faster age-effects observed for segments near the brainstem. Lastly, while several association and commissural bundles exhibited faster maturation within central segments; indicative of a deep-superficial axis, effects were mixed between micro- and macrostructure, underscoring the unique developmental timing of these different fiber properties. Our findings provide evidence that within-tract white matter maturation unfolds along key spatiotemporal axes and suggests that increased spatial precision can advance our understanding of early childhood brain development.

It is critical to identify which factors induce specific brain states as these large-scale patterns of coordinated neural activity drive downstream processing and behavior. The retrieval state, a brain state engaged when attempting to retrieve the past, is thought to specifically support episodic memory, remembering experiences within a spatiotemporal context, as opposed to semantic memory, remembering general knowledge. However, we hypothesize that the retrieval state reflects internal attention engaged to access stored episodic and semantic information. To test these alternatives, we recorded scalp electroencephalography while participants made episodic, semantic, or perceptual judgments, and applied an independently validated mnemonic state classifier to measure retrieval state engagement. We found that retrieval state engagement was greater for both episodic and semantic judgments compared to perceptual judgments. These findings suggest that the retrieval state reflects a domain-general internal attention process that supports not just episodic memory, but internally directed cognition.

Animals exposed to pairings of a neutral stimulus with reward acquire a conditioned response to the neutral stimulus. A prominent hypothesis, formalized in the Temporal Difference (TD) learning algorithm, is that animals learn to predict the future reward associated with the neutral stimulus ("value"). Though the TD algorithm does not explicitly specify what drives conditioned responding, a typical assumption is that it reflects the animals estimate of value. In TD learning, value estimates are updated using reward prediction error (RPE, the discrepancy between observed and predicted reward), and are thought to be signaled by the phasic activity of midbrain dopamine neurons. This hypothesis posits that dopamines effects on conditioned responding are mediated entirely by its effects on learning. However, recent experimental and theoretical evidence suggests that dopamine may play a more direct role in modulating conditioned responding. We use a combination of data analysis and computational modeling to probe the relationship between dopamine and conditioned responding. Our results suggest that dopamine directly modulates conditioned responding, in addition to its role in learning. These findings can be captured by a model in which dopamine RPE acts both indirectly (via learning) and directly on conditioned responding.

The thalamus plays a central role in cortical development, organisation and function. Thalamic nuclei acquire distinct molecular identities during gestation, with first-order relays maturing before higher-order nuclei. Thalamic afferents innervate the cortical plate with a precise order, disruptions to which alter cortical function. Recent models propose that thalamic input to primary sensory cortex constrains the development of wider cortical networks, promoting the formation of highly-connected hubs in association cortex. Here, we combine neuroimaging, post mortem gene expression data and network modelling to examine how the timing and spatial distribution of thalamocortical innervation influences the formation of cortical networks during gestation. We find that the maturation rates of thalamic nuclei align with predicted timing and distribution of afferent outgrowth. While higher order nuclei connect widely across the cortex, they do not preferentially target high-degree hubs. Instead, hubs emerge from interdependent spatiotemporal constraints imposed by both wiring distance and thalamocortical maturation.

The functional organization of the human brain is established early, yet the ontogeny of its large-scale functional gradients remains unclear. Using resting-state fMRI data from 714 neonates in the Developing Human Connectome Project, we mapped neonatal brain gradients via functional connectome harmonics (FCH). We identified adult-like sensory-to-multimodal and cognitive gradient patterns present at birth. Applying three FCH-derived metrics, entropy, power, and energy, we found that power and energy were higher in term-born compared to preterm neonates, while entropy was elevated in preterms. These metrics predicted up to ~30% of postmenstrual age, indicating their biological relevance. Our findings reveal that the neonatal brain possesses a robust gradient architecture underpinning early functional organization, offering novel biomarkers for assessing brain maturity and the impact of prematurity on neurodevelopment.

Alzheimer's disease (AD) is the most prevalent form of dementia, characterized by progressive memory loss, cognitive decline, and emotional dysregulation. Adult hippocampal neurogenesis (AHN) critically contributes to cognition and mood but undergoes precipitous decline during AD progression. Here, we investigated whether enhancing AHN through genetic expansion of endogenous neural stem cells (NSC) ameliorates AD-related phenotypes. Using lentiviral overexpression of the cell cycle regulators Cdk4 and CyclinD1 in the dentate gyrus of 3xTg-AD mouse, we show that enhancing AHN partially rescues hippocampal-specific cognitive functions, namely: spatial navigation and exploratory behavior. These findings show that endogenous NSC can be exploited to ameliorate hippocampal cognitive functions in AD, providing additional evidence for exploiting AHN as a promising therapeutic target for neurodegenerative disease.

In animal models, the primary somatosensory cortex (S1) exhibits columnar organisation, where vertically arranged neurons share functional properties. In humans, however, the thinness and folding of S1 have limited non-invasive investigations of such columnar structures. In this study, we aimed to identify columns in human S1 by delivering alternating bursts of 3 Hz and 30 Hz fingertip vibration while acquiring functional MRI time series at 7 Tesla. Using cortical surface modelling, we identified functional patterns in S1 that showed higher reliability, stronger differential responses, and greater statistical sensitivity than those observed in a frontal cortex control region (p = .001-.012 for reliability; p < .001 for differential signal; p = .004-.011 for sensitivity). Laminar analyses revealed depth-consistent frequency preferences in approximately 20-45% of S1 nodes, a pattern compatible with vertically organised functional structure. Although the relative signal difference between 3 Hz and 30 Hz was small (0.14% signal change), frequency tuning was reliably observed. Taken together, these findings reveal functional patterns in human S1 consistent with aspects of columnar-like organisation, providing non-invasive evidence of fine-scale functional architecture. TeaserfMRI reveals highly reliable but modestly selective responses in human S1, consistent with column-like functional organisation.

Auditory attention enables the selection of behaviorally relevant sounds in dynamic environments, supporting the flexible allocation of neural resources over time. Although neural entrainment has been proposed as a mechanism for temporal prediction in audition, human studies have largely emphasized changes in response strength, leaving unresolved whether attention reorganizes the temporal alignment of entrained activity across hierarchical cortical networks. Here, we introduce the Selective Temporal Alignment of Components (STAC) framework to dissociate stimulus-driven and attention-controlled dynamics using non-invasive EEG. In a series of experiments across two independent adolescent cohorts (n = 79), Reliable Components Analysis (RCA) revealed two dissociable entrained networks with distinct spatial, functional, and attentional profiles: a sensory-driven network that remained tightly stimulus-locked and a frontal-auditory network that exhibited systematic attention-dependent phase shifts. These phase dynamics were consistent across independent cohorts and stable within individuals, and critically, predicted performance on a standardized neuropsychological measure of auditory attention. Together, these findings establish selective temporal alignment as a robust and behaviorally relevant neural mechanism underlying auditory attentional control.

Background: Lactamase B (LACTB) is a mitochondrial protease associated with cancer progression and lipid metabolism. LACTB is located in an AD locus and has been associated with Alzheimers Disease (AD) in a proteomic study. Methods: We performed Mendelian randomization (MR) to evaluate the relationship between LACTB expression, succinyl-carnitine, and AD risk. We generated LACTB knock-down (KD) THP1 macrophages, LACTB knock-out (KO) iPSC-derived microglia and LACTB enzymatically-dead (ED) mice. The impact of LACTB downregulation in myeloid cells was characterized via transcriptomics, metabolomics, lipidomics, and functional assays. Finally, human LACTB KO microglia precursors were xenotransplanted into the brains of amyloid-pathology mice to assess in vivo interactions with amyloid plaques. Results: MR analyses revealed that lower LACTB expression in myeloid cells reduces AD risk and is genetically associated with increased levels of succinylcarnitine, a metabolite that independently correlates with reduced AD risk. We identified LACTB as a primary enzyme responsible for succinylcarnitine hydrolysis. Transcriptional and functional studies showed that loss of LACTB enhances OXPHOS, reduces protein synthesis, and alters lipid profiles. LACTB expression was upregulated following IFN/TNF stimulation, and its loss modified efferocytosis-related functions under inflammatory conditions. In vivo, xenotransplanted human LACTB-KO microglia exhibited enhanced association with amyloid plaques compared to controls. Conclusions: Our findings define a previously unrecognized axis linking LACTB and succinylcarnitine to myeloid cell function and AD susceptibility. Given the druggability of LACTB and the potential for succinylcarnitine to serve as a translational biomarker, this pathway represents a promising therapeutic target for modulating neuroinflammation in AD.

Perceptual learning is a temporally dynamic process involving the acquisition and integration of sensory information necessary for adaptive decision making. Resolving the neural basis of perceptual learning could uncover new therapeutic targets for schizophrenia and other neurodevelopmental disorders that implicate impaired perceptual acuity. In the present study, we developed a novel touchscreen task which utilizes orientation discrimination to assess visual perceptual learning (VPL) in male and female rats. Based on previous evidence we hypothesised that VPL would depend on inhibitory neurotransmission mediated by {gamma}-amino butyric acid (GABA). Segregating subjects based on 'poor learning' (lower tertile) and 'good learning' (upper tertile) revealed dose-dependent improvements in VPL in poor learners following the administration of a GABA-B agonist (R-baclofen) and an 5 subunit specific GABA-A (GABRA5) positive allosteric modulator (alogabat) administered early in learning. Poor VPL performance was associated with a significant reduction in GABRA5 expression in dorsal regions of the prefrontal cortex (PFC), most notably the prelimbic cortex. Reduced GABRA5 expression in this region was co-localized to somatostatin- and parvalbumin-expressing interneurons. These findings indicate that inter-individual variation in the expression of GABRA5 in selective PFC populations of inhibitory interneurons may determine the speed and acuity of VPL. Based on these findings, interventions that restore GABRA5 signalling in the PFC may hold therapeutic relevance for neuropsychiatric disorders involving deficits in perceptual learning.

Reverse correlation is a widely-used and well-established method for probing latent perceptual representations in which subjects render subjective preference responses to ambiguous stimuli. Stimuli are purposefully designed to have no direct relationship with the target representation (e.g., they are randomly-generated), a property which makes each individual stimulus minimally informative toward reconstructing the target, and often difficult to interpret for subjects. As a result, a large number of stimulus-response pairs must be gathered from a given subject in order for reconstructions to be of sufficient quality, making the task fatiguing. Recent work has demonstrated that the number of trials needed can be substantially reduced using a compressive sensing framework that incorporates the assumption that the target representation can be sparsely represented in some basis into the reconstruction process. Here, we introduce an alternative method that incorporates the sparsity assumption directly into stimulus generation, which holds promise not only for improving efficiency, but also for improving the interpretability of stimuli from subjects perspective. We develop this new method as a mathematical variation of the compressive sensing approach, before conducting one simulation study and two human subjects experiments to assess the benefits of this method to reconstruction quality, sample size efficiency, and subjective interpretability. Results show that sparse stimulus generation improves all three of these areas relative to conventional reverse correlation approaches, and also relative to compressive sensing in most conditions.

Motor adaptation is driven by sensory prediction errors, yet reinforcement feedback can alter the speed and retention of adaptive behaviors. The cerebellum is central in motor adaptation, but posterior lobules, especially Lobule VI (CB6) and Crus I (CBcrus1), also participate in reinforcement-related signaling. Serotoninergic and dopaminergic systems, key modulators of motivational processes, directly influence cerebellar activity. However, how these neuromodulatory systems contribute to cerebellar network organization and to reinforcement-based adaptation in humans remains unclear. We employed a multimodal framework (Receptor-Enriched Analysis of functional Connectivity by Targets; REACT) using PET-derived Serotonin/Dopamine Transporter (SERT/DAT) templates to enrich resting-state functional Magnetic Resonance Imaging (rs-fMRI). We estimated SERT- and DAT-enriched functional connectivity from CB6 and CBcrus1 within motor-adaptation and reinforcement-learning networks, and tested their correlations with performance in a visuomotor adaptation task completed under reward and punishment. Our findings show lobule-specific neuromodulatory organization within the cerebellum. CB6 exhibited predominantly DAT- and SERT-enriched connectivity with motor adaptation networks, while CBcrus1 showed stronger SERT-enriched communication extending to both motor and reinforcement networks. Crucially, distinct cerebello-cortical neuromodulatory networks predicted individual differences in adaptation rate. DAT-enriched CBcrus1 connectivity was linked to punishment-driven adaptation, whereas SERT-enriched cerebello-orbitofrontal connectivity predicted faster adaptation across both reward and punishment contingencies. Furthermore, we observed overlaps between SERT- and DAT-enriched networks in the medial orbitofrontal area for Crus I, which predicted retention following punishment, underscoring the role of convergent neuromodulation in stabilizing adapted movements. We conclude that partially segregated yet convergent cerebello-cortical networks support interactions between motor and motivational behaviors, with combined and opposing effects of serotonergic and dopaminergic neuromodulation accounting for the speed and retention of adaptive behaviors.

Topographic organization characterizes hippocampal circuits, yet its functional significance remains unclear. By selectively disrupting CA1-to-subiculum topographic projections in latrophilin-2 conditional knockout mice, we show that precise topography shapes the anatomical distribution of subicular spatial coding while preserving single-cell tuning. Disrupted topography also selectively impairs boundary vector coding and long-term network stability. Thus, CA1 inputs provide an indispensable scaffold for organizing subicular spatial maps and dynamics.

1Single-cell proteomics (SCP) enables direct measurement of cellular heterogeneity during dynamic biological processes. Here, we applied an SCP workflow to investigate proteome diversity during nerve growth factor (NGF)-induced differentiation of PC12 cells. Differentiated PC12 cells are highly adherent and prone to aggregation, complicating single-cell sample preparation. To address this challenge, sample handling was optimized using gentle dissociation, anti-adhesive conditions, and rapid processing immediately prior to cell isolation. Individual cells were deposited using a refined thermal inkjet (TIJ) dispensing system, enabling accurate single-cell placement with minimal sample loss. Inclusion of the mild nonionic surfactant n-dodecyl-{beta}-D-maltoside (DDM) improved recovery of membrane-associated and other low-solubility proteins. Coupled with high-sensitivity liquid chromatography-ion mobility-mass spectrometry, this workflow consistently quantified approximately 2,000-3,000 proteins per cell across differentiation stages. Single-cell proteomic profiles acquired over the differentiation time course revealed clear separation between undifferentiated and NGF-treated cells by Day 6. At later stages (Days 4-6), cells further partitioned into two distinct subpopulations with protein expression patterns not evident in bulk measurements. Dimensionality reduction and non-negative matrix factorization identified multiple proteomic states coexisting within the same differentiation stages, characterized by coordinated differences in pathways related to intracellular trafficking, protein translation, and neuronal structural organization. Together, these results show that while global proteome remodeling during PC12 differentiation is captured in both bulk and single-cell data, single-cell proteomics uniquely resolves functionally distinct cellular subpopulations that are masked in population-averaged analyses.

Developmental stuttering is a complex neurodevelopmental disorder characterized by disfluent speech. At the individual level, the behavioral manifestations of stuttering vary considerably, likely reflecting heterogeneity in underlying neural mechanisms. In this study, we examined individual-specific differences in the brains of children who stutter (CWS), by implementing normative modeling, a framework that quantifies how an individual deviates from an age- and sex-matched reference population. We applied this approach to identify individual-specific structural brain atypicalities using gray and white matter volumes. These volumes were derived from MRI scans from a large mixed-longitudinal dataset of 235 and 240 scans from CWS and fluent controls respectively, aged between 3 and 12 years. Individual deviation maps capturing these atypicalities were then used to cluster CWS into subtypes based on similarities in their neuroanatomical profiles. This analysis identified four neural subtypes with distinct neuroanatomical atypicalities relative to fluent controls. The key findings were a basal ganglia-thalamo-cerebellar subtype associated with higher stuttering severity and lower rates of recovery, and a white matter subtype characterized by mild severity and a higher likelihood of recovery. The remaining two subtypes showed cerebellar differences alongside alterations in brain regions involved in sensorimotor integration. Moreover, cerebellar volume atypicalities were present in all four subtypes, indicating that cerebellar alterations were present across otherwise distinct neural profiles and may represent a shared neuroanatomical feature of stuttering. These findings indicate that examining individual-specific neural differences and subtyping based on patterns of neural atypicalities provides valuable insight into the heterogeneity of developmental stuttering and represents a promising direction for improving our understanding of the disorder.

Cajal-Retzius neurons (CRs) are a transient cell type that populates the postnatal hippocampus. To test how the persistence of CRs shapes the maturation of hippocampal function, we used a CRs-specific transgenic mouse line combined with targeted viral delivery to selectively ablate CRs in the postnatal hippocampus. Single cell sequencing revealed that gene networks in superficial CA1 pyramidal cells were more strongly perturbed compared to deep CA1 pyramidal cells. To test if these two subpopulations were also distinctly affected in their function, we performed in vivo recordings from spatially modulated cells in CA1. Our analysis showed an impaired spatial representation specifically in superficial CA1 pyramidal cells. Additionally, we observed an increased CA3 to CA1 excitatory drive, as indicated by increased gamma oscillations, and alterations of intrinsic firing properties in superficial CA1 pyramidal neurons confirmed by in vitro electrophysiological recordings. Together, these results indicate a crucial role for CRs in the maturation of hippocampal subcircuits.

Background: Traumatic brain injury (TBI) initiates a rapidly evolving neuroinflammatory response; however, the temporal relationship between early innate immune activation, T cell polarization, and neurobehavioural recovery remains poorly understood. Here, we hypothesize that interleukin-1{beta} (IL-1{beta}) is a critical upstream mediator that polarizes T cells towards pro-inflammatory and cytotoxic effector functions following TBI. Methods: Using a controlled cortical impact model in adult male C57BL/6J mice, we mapped post-injury immune dynamics and investigated whether targeting key innate inflammatory compartments influenced subsequent T cell programming and neurological outcomes. We conducted longitudinal immune profiling by multiparameter spectral flow cytometry and quantitative polymerase chain reaction up to 10 days post-injury. Antibody-based immune depletion strategies were used to investigate neutrophil and monocyte contributions to the post-traumatic T cell response, while pharmacological inhibition of NLRP3 inflammasome by MCC950 treatment was used to investigate the contribution of IL-1{beta}. Results: TBI elicited a structured early innate immune response, marked by rapid chemokine induction, followed by temporally distinct infiltration of neutrophils, monocytes, and dendritic cells. Neutrophils and monocytes were the predominant early IL-1{beta}-producing infiltrating populations. This was followed by a delayed adaptive phase characterized by sustained recruitment of T cell subsets (CD4+, CD8+, gd+), alongside dynamic effector cytokine production (IL-17, IFN-{gamma}). Neutrophil depletion altered the early myeloid composition but did not result in durable improvements in T cell effector responses or neurobehavioral outcomes. Depletion of CCR2-dependent inflammatory monocytes reduced acute monocyte accumulation and attenuated early downstream T cell responses; however, these effects were not sustained and only resulted in modest neurobehavioural benefits. In contrast, inhibition of the NLRP3 inflammasome suppressed microglial IL-1{beta} production, without significantly altering leukocyte recruitment or subacute T cell effector phenotypes. These phenotypic changes were associated with improvements in motor and cognitive function recovery. Conclusion: We show that early monocyte IL-1{beta} signalling actively regulates downstream T cell infiltration and effector function after TBI. In addition, inhibition of NLRP3 inflammasome after TBI attenuates microglial IL-1{beta}-associated immune activation and results in behavioural improvement despite ongoing leukocyte recruitment, indicating that targeting the nature and cellular source of IL-1{beta} signalling can dissociate immune cell burden from neurological outcomes. Collectively, our findings identify myeloid IL-1{beta}-linked pathways as a viable bridge between innate and adaptive immunity post-TBI, and underscore cellular compensation as a critical design consideration for next-generation immunotherapies.

Mutations in ANXA11 cause amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), yet the mechanisms linking ANXA11 dysfunction to neurodegeneration remain poorly defined. Recent cryo-EM studies revealed heteromeric ANXA11-TDP-43 filaments in patient brains, suggesting a direct pathological connection between these two ALS-associated proteins. However, whether ANXA11 possesses intrinsic amyloidogenic properties and how its aggregation relates to TDP-43 proteinopathy remain unknown. Here, we demonstrate that ANXA11 undergoes liquid-liquid phase separation and subsequently matures into amyloid fibrils through a liquid-to-solid phase transition. ANXA11 fibrils exhibit prion-like properties, including self-templating seeding activity and intercellular propagation in human iPSC-derived neurons. Strikingly, ANXA11 fibrils induces pathological conversion of TDP-43, including hyperphosphorylation, accumulation in detergent-insoluble fractions, and formation of cytoplasmic aggregates. TurboID proximity-labeling proteomics further revealed aggregation-dependent enrichment of nuclear pore complex and nucleocytoplasmic transport factors in the ANXA11 aggregate-proximal proteome. Consistently, ANXA11 aggregation was associated with nuclear envelope abnormalities, altered nucleoporin distribution, impaired mRNA export, and progressive neuronal toxicity in iPSC-derived neurons. Together, these findings establish ANXA11 as an intrinsically amyloidogenic, phase-transition-competent protein whose seeded assemblies propagate between cells, induce TDP-43 co-pathology, and are linked to nucleocytoplasmic transport defects and neuronal injury, thereby providing a mechanistic framework for ANXA11-associated ALS/FTD pathogenesis.

Genetic defects of the gene encoding the ubiquitin ligase UBE3A cause a severe neurodevelopmental disorder, the Angelman syndrome (AS). The pathophysiology of AS remains unclear, hindering the development of effective therapies. Using AS animal models, we show here that UBE3A controls the development of excitatory and distinct subtypes of inhibitory synapses in cortical pyramidal neurons through cell-autonomous mechanisms, ultimately leading to alteration of synaptic transmission and hyperexcitability. Replacing endogenous Ube3a with individual isoforms, we demonstrate that their uneven nuclear (hUBE3A isoform 1) and cytosolic (hUBE3A isoforms 2/3) distribution is critical for regulating distinct aspects of synaptic development. We also define the molecular requirements underpinning this regulation, showing that: (i) both nuclear and cytosolic UBE3A rely on their ubiquitin ligase activity to ensure proper assembly of synapses; (ii) in addition to the nucleus, UBE3A isoform 1 is also localized in the cytosol, where it is functionally interchangeable with UBE3A isoform 3. Our findings identify a subcellular distribution-dependent mechanism by which UBE3A coordinates cortical circuit development and suggest pathogenic mechanisms of AS.

Electrical conductivity of cortical gray matter governs the magnitude and spatial distribution of electric fields generated by brain stimulation and intrinsic neuronal activity measured with M/EEG and intracortical recordings. However, reported macroscopic conductivity values vary by more than threefold, limiting the fidelity of bioelectromagnetic models and leaving unresolved whether this variability reflects measurement uncertainty or genuine structural heterogeneity of cortical tissue. Here, we present a multiscale computational framework that, for the first time, attempts to derive mesoscale conductivity maps of mouse visual cortex at 50-m resolution directly from large-volume, segmented nanometer-scale electron microscopy data. The Minnie 65 subvolume of the MICrONS dataset is accurately subdivided into 1,224 50-m cubic blocks. Each block contains, on average, 40-50 million membrane facets of a highly convoluted and dense cellular structure. Three orthogonal electrode pairs are applied to each isolated block to estimate the three principal components of the conductivity tensor. Quasistatic electric modeling is enabled by an iterative boundary-element fast multipole method (BEM-FMM) under the approximation of non-conducting membranes (DC conductivity). Spatially averaged conductivity values predicted by our framework agree well with prior low-resolution measurements in rats, validating the approach. At the same time, the resulting mesoscale maps reveal pronounced conductivity granularity at 50-100 m scales as well as significant variations in both radial and tangential directions. These results indicate that mesoscale conductivity heterogeneity could be an intrinsic structural property of the cortex. Limitations and extensions of this study are discussed in detail.

Neurosteroids are endogenous neuromodulators and emerging therapeutics, but understanding but understanding how these compounds modulate receptor signaling within defined neuronal populations and networks has been limited by an inability to deliver these molecules with receptor-level and cell-type specificity. Here, we developed a neurosteroid DART (Drug Acutely Restricted by Tethering) that combines the GABAA receptor subunit-selectivity of a neuroactive steroid (NAS) with the cell-type specificity of the DART platform. Screening of seventeen NAS analogs identified seven scaffolds suitable for further engineering, and structure-activity analysis revealed that DART linker attachment at the C11 position preserved NAS activity on GABAA receptors, whereas C2 and C17 attachment failed to exhibit activity. Functional profiling of C11-linked NAS-DARTs slowed IPSC decay kinetics and showed variable off-target modulation of NMDA and AMPA EPSCs. The most selective compound, YX85.1DART.2 potentiated GABA-evoked currents in neurons expressing pharmacogenetically isolated 4/{delta}-containing GABAA receptors but not in {gamma}2-expressing neurons. A previously validated BZP.1DART.2 produced complementary selectivity on the two receptor populations. Together, these findings establish new tools for interrogating subunit-specific NAS actions on inhibitory signaling in defined neuronal populations.

Hypoxic-ischemic injury is a major cause of olfactory dysfunction, yet the cellular and morphological mechanisms underlying this sensory loss remain poorly understood. Here, we investigated the structural, cellular, and functional effects of acute hypoxic exposure on the olfactory system of adult zebrafish (Danio rerio) of both sexes, a model organism with remarkable neuroregenerative capacity. Fish were subjected to 15 minutes of acute severe hypoxia (0.8 mg/L dissolved oxygen) and assessed at 1 and 5 days post-hypoxia (dph). We evaluated olfactory function by means of cadaverine-evoked aversive behavioral assays. Structural and morphological integrity and inflammation of the olfactory epithelium (OE) and olfactory bulb (OB) were characterized using immunohistochemistry, histological stainings, and a 2,3,5-triphenyltetrazolium chloride (TTC) colorimetric assay. Acute hypoxic exposure impaired olfactory-mediated behaviors without affecting locomotion or exploratory behavior. In the peripheral OE, hypoxia caused neurodegeneration, disruption of the nasal mucus layer, and robust leukocytic infiltration. We observed reduced mitochondrial dehydrogenase activity in the olfactory bulb (OB) along with reactive astrogliosis. Olfactory function recovered by 5 days, coinciding with full restoration of OE morphology, and supported by a strong proliferative response. These findings reveal a coordinated degenerative and regenerative response to hypoxia across the olfactory axis, with implications for understanding hypoxia-induced sensory loss and neural repair.

AbstractResting-state electroencephalography (rs-EEG) offers a cost effective and portable alternative to conventional neuroimaging for dementia screening, yet the lengthy, multichannel nature of rs-EEG makes learning robust representations challenging. Convolutional and Transformer based architectures dominate current deep learning based approaches, but often struggle with long-range dependencies and may not properly preserve channel-dependent features. In this work, we propose EEG-SSFormer, a state space model based architecture designed for the classification of mild cognitive impairment (MCI) and dementia from normal controls using raw rs-EEG signals. Our method decouples channel-wise representation learning from modeling cross-channel interactions and leverages Mamba layers for effective long-sequence modeling. We evaluate our method on the Chung-Ang University EEG dataset (CAUEEG) with 1,155 subjects, the largest public rs-EEG dataset for challenging MCI and dementia differential diagnosis. We achieve a 3-class accuracy of 57.65% using a strict subject-wise split, and relate task-specific features learned by our model as revealed by feature occlusion-based explainability techniques to clinical literature, highlighting that state space models can facilitate interpretable and scalable clinical rs-EEG screening tools for cognitive degeneration. The code for the study is publicly available at: https://github.com/HealthX-Lab/EEG-DimentiaMamba-official

AbstractResting-state electroencephalography (rs-EEG) offers a cost effective and portable alternative to conventional neuroimaging for dementia screening, yet the lengthy, multichannel nature of rs-EEG makes learning robust representations challenging. Convolutional and Transformer based architectures dominate current deep learning based approaches, but often struggle with long-range dependencies and may not properly preserve channel-dependent features. In this work, we propose EEG-SSFormer, a state space model based architecture designed for the classification of mild cognitive impairment (MCI) and dementia from normal controls using raw rs-EEG signals. Our method decouples channel-wise representation learning from modeling cross-channel interactions and leverages Mamba layers for effective long-sequence modeling. We evaluate our method on the Chung-Ang University EEG dataset (CAUEEG) with 1,155 subjects, the largest public rs-EEG dataset for challenging MCI and dementia differential diagnosis. We achieve a 3-class accuracy of 57.65% using a strict subject-wise split, and relate task-specific features learned by our model as revealed by feature occlusion-based explainability techniques to clinical literature, highlighting that state space models can facilitate interpretable and scalable clinical rs-EEG screening tools for cognitive degeneration. The code for the study is publicly available at: https://github.com/HealthX-Lab/EEG-DimentiaMamba-official

Prolonged esports play induces cognitive fatigue that is not fully captured by subjective awareness, motivating practical, non-stimulant nutritional strategies supported by objective physiological markers. We here tested whether acute milk protein intake attenuates fatigue-related physiological responses during prolonged esports play and supports subjective state, executive control, and in-game performance. In a randomized, single-blind (assessor-blind), energy-matched controlled crossover study, 15 healthy young adults with esports experience completed two sessions in which they consumed either a milk protein drink or an energy-matched apple juice control before a 3-h virtual soccer task. Physiological measures included pupillometry during gameplay, salivary cortisol, continuous interstitial glucose monitoring, and heart rate. Subjective ratings (VAS) and executive function (flanker task) were assessed across post-ingestion time points, and in-game performance metrics were aggregated within hourly gameplay blocks. Milk protein intake was associated with a coherent pattern of physiological advantages, including larger pupil diameter during gameplay, smoother interstitial glucose dynamics, and lower salivary cortisol, while heart rate showed time-dependent changes without a clear condition effect. These physiological changes co-occurred with higher enjoyment and lower hunger, improved flanker performance, and condition-dependent improvements in in-game performance, most notably higher shot success rate. Additionally, pupil diameter during gameplay was associated with inhibitory-control efficiency on the flanker task. These findings suggest that acute milk protein intake may serve as a practical, non-stimulant nutritional strategy to sustain physiological state and cognitive-behavioral performance during prolonged esports (virtual soccer) play. Highlights- Prolonged esports play models modern digital cognitive activity and cognitive fatigue. - Acute milk protein intake increases pupil diameter during prolonged esports play. - Interstitial glucose dynamics are smoother and salivary cortisol is lower with milk protein. - Enjoyment increases and hunger decreases during 3 h of virtual soccer play. - Executive function and in-game performance improve, most notably shot success rate.

Among individuals with equivalent Alzheimers pathology, cognitive outcomes can diverge by decades, a phenomenon termed cognitive reserve that remains descriptive after thirty years of research. We propose that the [~]109-to-10 bits/s gap between sensory input and behavioral output functions as error-correcting redundancy in the sense of Shannons channel coding theorem. Progressive neuronal loss maps to symbol erasure in a redundant code, and the critical damage fraction at which cognition fails is dc = 1 - k/n, where k {approx} 10 bits/s is the behavioral channel requirement and n is the effective number of coding units. We evaluate this threshold across three channel models (binary erasure, Gaussian, and Erd[o]s-Renyi percolation) and show that all produce a sharp phase transition from reliable to unreliable decoding. The framework makes four testable predictions: (i) dc scales with the measurable redundancy ratio{rho} = n/k, which accounts for clinical heterogeneity; (ii) information-theoretic redundancy from resting-state fMRI should predict time-to-conversion beyond structural atrophy; (iii) the decline trajectory near dc is sharp, consistent with the "cognitive cliff"; and (iv) motor circuits, operating at higher bandwidth, have lower reserve than cognitive circuits. Significance StatementCognitive reserve (why some brains resist dementia pathology better than others) has been described for thirty years but never given a quantitative, information-theoretic foundation. We propose that the roughly hundred-million-fold gap between sensory input ([~]109 bits/s) and behavioral output ([~]10 bits/s) functions as error-correcting redundancy in the Shannon coding-theoretic sense. This yields a closed-form critical damage threshold, dc = 1 - k/n, below which cognitive function is preserved and above which it collapses; this is consistent with the clinically observed plateau-then-cliff pattern of dementia. The framework unifies cognitive reserve with channel coding theory, accounts for individual heterogeneity in disease onset, and generates falsifiable predictions that link information-theoretic redundancy measures to time-to-clinical-conversion.

Intervertebral disc (IVD) injury is a major cause of low-back pain and can lead to structural deficits and mechanical instability. When the IVD is compromised, neuromuscular compensation by paraspinal muscles, such as the multifidus (MF) and longissimus (ML), is critical for maintaining spine stability. However, it is unknown how IVD injury and its interaction with nociception affect neuromuscular control. This study assessed the effects of IVD injury and additional muscle-derived nociception on trunk motor control during locomotion in a rat model. IVD injury was induced via needle puncture at L4/L5. One week later, hypertonic saline was injected into the lumbar MF to induce nociception. Trunk and pelvic kinematics, bilateral EMG activity of MF and ML were recorded during treadmill locomotion at baseline, one week after IVD injury, and immediately following hypertonic saline injection. Trunk and pelvic kinematics and bilateral muscle activation patterns remained largely consistent across conditions. No significant changes were found in stride duration, pelvic, lumbar and spine angle changes, variability, or movement asymmetry. MF activation was bilaterally synchronized, whereas ML showed left-right alternating activation patterns. Following IVD injury, right MF mean activation and EMG variability increased significantly compared to baseline. When muscle-derived nociception was added in the unstable spine (IVD injury) condition, left MF minimum amplitude was significantly reduced, and instability-related increases in right MF mean activation and variability were attenuated, but not fully reversed. These findings suggest that IVD injury, alone or in combination with muscle-derived nociception, elicits localized neuromuscular adaptations without disrupting the global locomotor patterns.

Succinic semialdehyde dehydrogenase deficiency (SSADHD) is a rare autosomal recessive metabolic disorder due to loss-of-function ALDH5A1 mutations impairing the catabolism of {gamma}-aminobutyric acid (GABA), the major inhibitory neurotransmitter in the brain. In SSADHD, pathologic accumulation of GABA and its metabolic by-product {gamma}-hydroxybutyrate (GHB) corresponds to a clinical syndrome dominated by developmental delay and epilepsy in half of patients with risk of sudden death in adolescence and adulthood. Brain-wide ALDH5A1 gene replacement for SSADHD is unavailable, and whether such treatment will reverse the SSADHD phenotype is unknown. We developed an inducible mouse SSADHD model, Aldh5a1lox-STOP, enabling Cre-dependent Aldh5a1 restoration to evaluate gene therapy feasibility. In the absence of SSADH, Aldh5a1lox-STOP mice exhibit hyperactivity and excessive serum GHB levels, culminating in death by ~postnatal day 22, recapitulating the severe SSADHD condition. Systemic delivery of a blood-brain barrier (BBB)-penetrating adeno-associated virus (AAV) carrying a Cre gene to Aldh5a1lox-STOP mice leads to brain-wide SSADH restoration, serum GHB level reduction, normalization of hyperactivity, and substantial increase in survival. As a step toward clinical translation, we further assessed an AAV encompassing a functional native promoter (FLnP) of ALDH5A1 tethered to its human coding sequence, namely AAV-FLnP-hALDH5A1. Aldh5a1lox-STOP mice were effectively rescued when treated with AAV-FLnP-hALDH5A1 packaged in the blood-brain barrier (BBB)-penetrating capsid PHP.eB. These findings provide preclinical proof that SSADH gene replacement therapy is feasible and potentially effective.

As social beings, humans make decisions partly based on social interaction. Observing the behavior of others can lead to learning from and about them, potentially increasing trust and prompting trust-based behavioral changes. Observation-based decision making involves different neural structures. The orbitofrontal cortex (OFC) and lateral prefrontal cortex (LPFC) are known as neural structures mainly involved in processing emotional and cognitive decision values, respectively, while the anterior cingulate cortex (ACC) plays a pivotal role as a social hub, integrating the afferent expectancy signals from OFC and LPFC. This paper presents a neurocomputational model of the interplay between observational learning and trust, as well as their role in individual decision-making. Our model elucidates and predicts the emotional and rational behavioral changes of an individual influenced by observing the action-outcome association of an alleged expert. We have modeled the neurodynamics of three cortical structures (OFC, LPFC, and ACC) and their interactions, where the neural oscillatory properties, modeled with Dynamic Bayesian Probability, represent the observer's attitude towards the expert and the decision options. As an example of an everyday behavioral situation related to climate change, we use the choice of transportation between home and work. The EEG-like simulation outputs from our model represent the presumed brain activity of an individual making such a choice, assuming the decision-maker is exposed to social information.

Age-related cognitive decline reflects progressive atrophic changes that advance through broad neural networks. There is no effective treatment. However, brain ageing is not homogenous, so treating the earliest-affected circuits may be successful in reversing and/or preventing ongoing neuronal atrophy and therefore cognitive decline. Repetitive transcranial magnetic stimulation (rTMS), a non-invasive technique that modulates cortical excitability, induces activity-dependent neuronal plasticity. Here we investigate short- and long-term effects of low intensity rTMS (LI-rTMS) on the cerebellum, which is adversely affected early during ageing. With age, cerebellar genes related to inflammation are strongly upregulated, whereas processes of synaptic-maintenance are reduced. Both abnormalities are rapidly corrected by LI-rTMS in a protocol-dependent manner. In parallel, LI-rTMS increases neuronal spine density and dendritic complexity, in association with improved spatial memory in both young adult and aged mice. These responses of the ageing cerebellum to low-intensity magnetic stimulation are extremely encouraging for treating age-related cognitive decline, but reinforce that appropriate stimulation parameters must be identified for effective treatment.

Sensory processing is continuously shaped by internal bodily states, yet the neural mechanisms underlying this interoceptive-exteroceptive integration remain poorly understood. Predictive processing theories propose that bodily states modulate perceptual inference through precision-weighting (the contextual adjustment of prediction error gain according to sensory reliability), but empirical validation with neurobiologically realistic models has been lacking. We address this gap by combining cardiac phase-locked magnetoencephalography with systematic dynamic causal modelling to test competing mechanistic hypotheses about systolic-induced sensory attenuation. Using an auditory oddball paradigm, we observed selective suppression of deviant responses during cardiac systole (200-250ms post-stimulus), affecting prediction errors from unexpected tones whilst sparing expected tones. To identify the underlying synaptic mechanisms, we implemented three methodological innovations: (1) systematic comparison across 20 architectures representing precision-weighting (via intrinsic gains and/or modulatory connections), sensory gating (via forward connections), and predictive suppression (via backward connections) hypotheses; (2) Bayesian model reduction testing all 256 parameter configurations within the winning architecture to handle distributed model evidence; and (3) sensitivity analysis quantifying both direct effects and second-order interactions across the cortical hierarchy. Model comparison decisively favoured precision-weighting implementations (>99.99% posterior probability), with Bayesian model averaging revealing distributed gain control: superficial pyramidal self-inhibition in primary auditory cortex (94%) and inferior frontal gyrus (100%), inhibitory interneuron modulation in superior temporal gyrus (99%), and top-down modulatory connections from superior temporal to primary auditory cortex (96%). Critically, sensitivity analysis demonstrated that intrinsic inhibitory mechanisms exerted order-of-magnitude larger effects than hierarchical modulatory connections, with superior temporal gyrus emerging as an integration nexus showing extensive parameter interactions. These findings provide the first empirical validation of precision-weighting mechanisms during cardiac-sensory integration, establishing that systolic attenuation operates primarily through coordinated local inhibitory gain control rather than hierarchical (expected) attentional modulation. This modelling framework bridges computational theories of interoceptive-exteroceptive integration with laminar-specific cortical mechanisms, offering a generalisable methodology for testing predictive coding hypotheses about embodied perception.

Sleep deprivation (SD) disrupts memory processes, particularly those dependent on the hippocampus. Six hours of SD after training in a hippocampus-dependent task typically induces amnesia in mice and impairs performance upon memory testing later. However, we previously demonstrated that object-location memories (OLMs) encoded under SD conditions can be recovered several days later, suggesting that these memories were not lost but suboptimally stored. Given that engrams of a specific memory are distributed across multiple functionally connected brain regions, we hypothesized that SD-induced amnesia arises from disrupted network alterations extending beyond the hippocampus. Consistent with this, brain-wide cFos mapping revealed a widespread reduction in cFos in memory associated regions during recall in SD mice and connectivity analysis identified the hippocampus as a central hub in this network. Since cGMP signaling modulates memory processes, we next tested whether the cGMP-specific PDE5 inhibitor vardenafil could restore access to these latent memories. One day after training, vardenafil reversed SD-induced OLM impairment when administered 30 minutes before testing, but this effect was lost when testing occurred several days later. To achieve persistent access to OLMs formed under SD conditions, we combined vardenafil treatment with optogenetic engram stimulation. This combined approach successfully maintained OLM retrievability for several days post-manipulation. Crucially, successful retrieval in these mice was associated with a significant increase in engram cell reactivation within the dorsal dentate gyrus compared to mice that failed to recall. Collectively, these findings provide novel insight into the molecular and network mechanisms underlying SD-induced amnesia and offer a strong rationale for developing targeted PDE5-mediated therapies to reverse SD-related memory deficits.

The rat vestibular system triggers anti-gravity responses such as the tail-lift reflex and the air-righting reflex. In a previous study in male rats, we obtained evidence that these two reflexes depend on the function of non-identical populations of vestibular sensory hair cells (HC). Here, we caused graded lesions in the vestibular system of female rats by exposing the animals to several different doses of an ototoxic chemical, 3,3'-iminodipropionitrile (IDPN). After exposure, we assessed the anti-gravity responses of the rats and then assessed the loss of type I HC (HCI) and type II HC (HCII) in the central and peripheral regions of the crista, utricle and saccule. As expected, we recorded a dose-dependent loss of vestibular function and loss of HCs. The relationship between hair cell loss and functional loss was examined using non-linear models fitted by orthogonal distance regression. The results indicated that both the tail-lift reflex and the air-righting reflexes mostly depend on HCI function. However, a different dependency was found on the epithelium triggering the reflex: while the tail-lift response deficits associated with the loss of crista or utricle HCIs, the loss of the air-righting response associated with the decrease in utricular or saccular integrity.

Reward can enhance motor performance. However, its potential to counteract motor fatigability, a reduction in motor performance during sustained movements, remains underinvestigated. This could be particularly relevant in neurological conditions such as multiple sclerosis, where increased motor fatigability is a prominent symptom. One form of motor fatigability is motor slowing, a decline in movement speed over time evoked by fast, repetitive movements. In this study, we investigated whether the possibility to earn reward attenuates motor slowing, and examined associated changes in muscle activity and pupil size, a putative marker of physical effort. Participants performed a wrist tapping task at maximal voluntary speed with or without the possibility of earning a reward. We found that wrist tapping induced motor slowing and that slowing was significantly reduced by reward. Over time, tapping became more costly as indicated by higher muscle activity and coactivation per tap. This was accompanied by a sustained pupil dilation, which could not solely be explained by tapping speed. These findings suggest that, rather than restoring efficient motor control, reward attenuates motor slowing by allowing participants to access a performance reserve and invest more resources into the task, reflected by increased muscle activation per tap and sustained pupil dilation.

Sequential experimental paradigms are fundamental to cognitive neuroscience, yet standard event-related response analysis struggles with the temporal variability inherent to these designs. Conventional epoching treats each event within a sequence as an independent response, discarding the temporal dependencies between successive events and obscuring systematic changes in neural state that accumulate across the sequence. In order to generate responses that capture the entire sequence, it necessitates alignment across trials to correct for the inherent temporal jitter that would otherwise blur averaged responses and obscure the true sequential dynamics. Existing temporal alignment methods warp observed signals directly, making them vulnerable to correlated noise and potentially disrupting multichannel temporal relationships essential for connectivity and causal analyses. Event-Related Warping (ERW) addresses these limitations by aligning template functions encoding experimental event structure rather than neural signals themselves. Templates constructed from event onsets and durations undergo smooth monotonic warping via gradient-based optimisation, then estimated trajectories are applied uniformly across all channels, preserving inter-channel timing relationships and causal structure. This design-level alignment exploits experimentally observable jitter whilst maintaining signal integrity. Simulations with known ground truth incorporating Gaussian jitter, skewed latencies, amplitude-latency coupling, and multi-parameter dependencies yielded standardised root-mean-square errors (sRMSE) of 0.27-0.38. Distance-weighted averaging, emphasising temporally consistent trials, provided 5-13% improvement when jitter exceeded 100 ms, with maximal benefit ({approx}13% reduction) under quadratic amplitude-latency coupling. Empirical validation using an auditory go/no-go dataset with cue-to-target intervals of 1.5-4.1 seconds demonstrated that ERW recovers jittered target-locked responses with comparable fidelity (sRMSE 0.24-0.51) to conventional epoching of time-locked events, whilst preserving inter-channel lag relationships (cross-covariance sRMSE 0.63-0.82). ERW thus extends standard trial averaging to scenarios where temporal variability would otherwise preclude coherent response recovery, supporting investigation of temporally extended processing in ecologically valid paradigms whilst maintaining compatibility with established ERP frameworks and downstream connectivity analyses.

The nasal epithelium is a complex tissue composed of both respiratory and olfactory tissue, and is constantly exposed to environmental insults, including toxins and pathogens. The main olfactory epithelium (MOE) serves as the critical site for olfaction, or sense of smell. Dysfunction at this critical barrier tissue can result in partial or total loss of olfactory function, resulting in significant impact to quality of life. The MOE is heterogeneous, comprised of many cell types including olfactory sensory neurons, support cells, and immune cells. It is not well understood how these diverse cell types in the MOE interact to regulate this tissue during homeostasis, and during times of injury and inflammation. We investigated how environmental olfactory exposures impact cell type specific transcriptional responses in the mouse MOE. We performed single-cell RNA sequencing (scRNA-seq) of the MOE following controlled environmental exposure to both well-known odorants and allergens. We identified major cell types and subtypes within the MOE, and identified transcriptional changes in response to the olfactory exposures. We identified transcriptional changes in OSNs, sustentacular cells, and resident immune cells to each condition. This indicated that environmental olfactory exposures drive changes to multiple cell types in the MOE. To our knowledge, this is the first study to identify effects of environmental olfactory exposures on cell-type specific transcription at homeostasis. These findings highlight the potential importance of multi-cellular interactions and communication in regulation of the olfactory epithelium.

Interpersonal communication relies on integrating facial and vocal signals to extract multidimensional communicative information. How the absence of audition reshapes the communicative system remains unclear. We compared the performance of deaf (N=136) and hearing (N=135) adults across multiple domains, facial identity, emotional expression, speech, and global motion, through a series of unisensory and audiovisual psychophysical tasks. The results showed that, in hearing individuals, reliance on facial versus vocal signals differed across domains. In deaf individuals, auditory deprivation did not produce uniform enhancement or impairment of visual processing. Instead, they exhibited reduced sensitivity to dynamic emotional expressions and global motion, preserved sensitivity to facial identity (both static and dynamic) and static expressions, and enhanced categorization of facial speech. Notably, sensitivity to dynamic facial expressions and global motion was correlated, and both were explained by variations in fluid intelligence. Our results provide a systematic characterization of visual function across domains in deaf individuals, suggesting that the consequences of hearing loss are shaped both by the functional roles of audition within each domain and by broader cognitive adaptations. These findings advance understanding of cross-modal plasticity and inform the development of targeted ecologically valid accessibility and sensory-substitution strategies.

Peripheral hearing loss can cause auditory hallucinations and is considered a risk factor for psychosis, at least in genetically vulnerable individuals. To disentangle brain abnormalities driven by hearing loss and genetic risk for psychosis, we quantified auditory cortical temporal acuity in mice with or without hearing loss and with or without a genetic risk factor for psychosis (22q11.2 deletion). We recorded cortical activity while awake mice listened to loudness-adjusted gap-in-noise stimuli with varying durations of silent gap. Both hearing loss and the 22q11.2 deletion were associated with impairments in auditory cortical temporal acuity. However, hearing loss broadly impaired temporal acuity of neural population activity, while the 22q11.2 deletion had more subtle effects, selectively impairing gap duration thresholds in regular-spiking (putative excitatory) but not fast-spiking (putative inhibitory) neurons. Results suggest that auditory cortical consequences of comorbid hearing loss and genetic risk for psychosis are at least partially dissociable.

Functional magnetic resonance imaging (fMRI) captures whole-brain activity fluctuations non-invasively in humans and animals. Beyond task/stimuli-locked responses, fMRI measures large-scale patterned activity during rest. An established method for identifying patterned activity in fMRI data, termed quasi-periodic pattern (QPP) analysis, identifies waves of activity which unfold over seconds and have consistent spatiotemporal characteristics. Notably, certain fMRI-QPPs are well-preserved across species and altered in various neuropsychiatric and neurodegenerative diseases. Yet, our collective understanding of their neural underpinnings is limited given the indirect nature of blood-oxygen-level dependent (BOLD) fMRI signals. Simultaneous measures of local field potentials have provided some affirmation that fMRI-QPPs have neural origins, but these point-measurements are limited to a handful of sites. Here, we use a unique multimodal implementation of simultaneous wide-field calcium (WF-Ca2+) imaging and fMRI to investigate the neural origins of fMRI-QPPs. We uncover a robust time-locked correlation between QPPs detected by cortex-wide fluorescent WF-Ca2+ imaging of neural activity and QPPs of BOLD-fMRI. These data validate the hypothesis that BOLD QPPs derive from preceding slow waves of neural activity with regional and temporal precision.

Spatialization in working memory refers to the spatial coding of non-spatial information along a mental horizontal line when encoding verbal material. This phenomenon is thought to support working memory by facilitating order encoding. Although it has been observed for both visually and auditorily presented stimuli, no direct comparison has yet examined whether these modalities rely on similar neural mechanisms. In this study, we investigated whether spatialization in visual and auditory modalities involves shared or distinct patterns of activity within the working-memory network. Forty-nine participants performed both a visual and an auditory working memory SPoARC task of the same verbal material, allowing to study the cortical patterns associated with distinct serial positions at both encoding and recognition across sensory modalities. Whole-brain analyses revealed similar frontoparietal networks across conditions. In addition, a representational similarity analysis (RSA) was conducted to assess the similarity of neural patterns between early and late serial positions in a sequence and across sensory modalities. This multivoxel pattern analysis revealed modality-dependent patterns distinguishing early and late positions in the inferior frontal gyrus. Additional modality-specific effects were observed in the anterior intraparietal sulcus in the visual modality and in the posterior hippocampus in the auditory modality. Drawing on the framework proposed by Bottini & Doeller (2020), we propose that order decoding in the IPS might reflect a low-dimensional spatial coding of order (e.g., along a horizontal axis), whereas order decoding in the hippocampus might reflect higher-dimensional spatial representations or temporal representations.

A key component of intraneuronal communication is the modulation of postsynaptic firing frequencies by stochastic transmitter release from presynaptic neurons. The time interval between successive postsynaptic firings is called the inter-spike interval (ISI), and understanding its statistics is integral to neural information processing. We start with a model of an excitatory chemical synapse with postsynaptic neuron firing governed as per a classical integrate-and-fire model. Using a first-passage time framework, we derive exact analytical results for the ISI statistical moments, revealing parameter regimes driving precision in postsynaptic action potential timing. Next, we extended this analysis to include both an excitatory and an inhibitory presynaptic connection onto the same postsynaptic neuron. We consider both a fixed postsynaptic-firing threshold and a threshold that adapts based on the postsynaptic membrane potential history. Our analysis shows that the latter adaptive threshold can result in scenarios where increasing the inhibitory input frequency increases the postsynaptic firing frequency. Moreover, we characterize parameter regimes where ISI noise is hypo-exponential or hyper-exponential based on its coefficient of variation being less than or higher than one, respectively.

Nav1.7 voltage-gated sodium channels are strongly expressed in human primary pain-sensing neurons (nociceptors) and selective Nav1.7 inhibitors have been developed as possible therapeutic agents for treating pain, so far with disappointing clinical results. In contrast, a selective Nav1.8 channel inhibitor (suzetrigine) has had successful clinical trials. Because nociceptors express both Nav1.7 and Nav1.8 channels, it is of interest to compare effects of Nav1.7 and Nav1.8 inhibitors on the excitability of human nociceptors. To compare with previous results with suzetrigine, we characterized the effects of a selective Nav.7 inhibitor, AM-2099, on action potential generation and repetitive firing of dissociated human dorsal root ganglion neurons, studied at 37{degrees}C. Inhibition of Nav1.7 channels by 600 nM AM-2099 generally produced a substantial depolarizing shift of action potential threshold, an increase in rheobase, a decrease in action potential upstroke velocity, decrease in action potential peak, and prolongation of refractory period. Compared to inhibition of Nav1.8 channels, inhibition of Nav1.7 channels had larger effects on threshold and maximal upstroke velocity, while action potential peak was reduced similarly by both. Nav1.8 inhibition produced much more dramatic reduction of repetitive firing than Nav1.7 inhibition. The results show that although the excitability of human DRG neurons is affected by inhibition of Nav1.7 channels, most notably by an increase in threshold and increase in refractory period, repetitive firing of the neurons in response to strong stimuli is little affected.

Central nervous system (CNS) tumor diagnosis requires comprehensive genomic profiling including DNA-methylation classification, copy-number variants (CNV), gene fusion analysis, small variant detection and MGMT promoter methylation status. Long-read sequencing platforms such as nanopore sequencing by Oxford Nanopore Technologies and SMRTseq by PacBio can capture all these in a single assay, but integrating diverse analytical tools to leverage the advantages of long-read sequencing remains complex. We present DIANA (Diagnostic Integrated Analytics of Neoplastic Alterations), a pipeline providing fully automated end-to-end processing of long-read whole-genome sequencing data from aligned sequence reads. DIANA produces a human readable report that combines methylation classification with prioritized genetic variants to support CNS tumor diagnostics and clinical decision-making.

Central nervous system (CNS) tumor diagnosis requires comprehensive genomic profiling including DNA-methylation classification, copy-number variants (CNV), gene fusion analysis, small variant detection and MGMT promoter methylation status. Long-read sequencing platforms such as nanopore sequencing by Oxford Nanopore Technologies and SMRTseq by PacBio can capture all these in a single assay, but integrating diverse analytical tools to leverage the advantages of long-read sequencing remains complex. We present DIANA (Diagnostic Integrated Analytics of Neoplastic Alterations), a pipeline providing fully automated end-to-end processing of long-read whole-genome sequencing data from aligned sequence reads. DIANA produces a human readable report that combines methylation classification with prioritized genetic variants to support CNS tumor diagnostics and clinical decision-making.

Glucose is the brain's primary fuel, but the brain can also use alternative energy substrates, especially during development or starvation. Emerging evidence suggests ketone metabolism may help the brain adapt to energy stress in neurodegenerative diseases such as Alzheimer's disease, although its role in constitutive brain function in normal aging is poorly understood. Using iPSC-derived human neurons and adult-inducible, neuron-specific Bdh1 knockout mice, we show that ketone body metabolism is essential for maximum energy production, neuronal function, and mouse survival -- even under normal nutritional conditions. Mechanistically, phenotypes of Bdh1 knockout neurons are mitigated by provision of acetoacetate, a downstream energy metabolite. Moreover, loss of neuronal ketone oxidation markedly increases mortality and memory deficits in Alzheimer's disease model mice. These findings identify ketones as critical neuronal fuels, with particular importance during neurodegeneration. While non-energetic activities of ketone bodies are increasingly appreciated, oxidation for energy provision is an essential mechanism for normal function in neurons and mice. Targeting the energetic function of ketones may thus offer new therapeutic strategies for both aging and neurodegenerative diseases such as Alzheimer's.

Objective: Nicotinic acetylcholinergic receptors (nAChRs), comprising of a and b subunits are present in the brain and whole body. The less abundant 2-subunit is a fast-acting receptor subtype and plays an important role in cognition and learning. To understand cellular functional consequences, this study evaluated glucose metabolism using [18F]FDG PET/CT in 2 knockout (2KO) and 2 hypersensitive (2HS) mice. Methods: Control (CN; 4M, 4F), 2 knockout (2KO; 4M, 4F) and 2 hypersensitive (2HS; 4M,4F), 12-16 month old mice were used. Mice were fasted and injected with [18F]FDG (3-5 MBq) while awake. After 40 minutes they underwent whole body PET/CT. On a separate day, nicotine challenge [18F]FDG studies were done. Reconstructed images were analyzed to obtain standard uptake values (SUV) of [18F]FDG in brain and interscapular brown adipose tissue (IBAT). Statistical analysis was performed. Results: The 2HS male mice exhibited the largest brain increase in [18F]FDG compared to 2KO male mice. The rank order of brain [18F]FDG uptake in the 3 groups: 2HS[male]> CN[male]> 2KO[male]> CN[female]= 2KO[female][≥]2HS[female]. Nicotine treatment reduced brain [18F]FDG uptake in all mice. Females had lower [18F]FDG uptake compared to males and were less sensitive to 2 nAChR. In the case of IBAT, 2KO mice had significantly higher baseline [18F]FDG uptake compared to the other two groups: 2KO[male]> 2KO[female]> 2HS[female]> 2HS[male]> CN[female]> CN[male]. Nicotine decreased IBAT in 2KO mice rather than increase as observed in CN and 2HS mice. Conclusions: 2 nAChRs plays a significant role in brain activation as exhibited by the increase in [18F]FDG in 2HS mice. In the absence of regulatory control by the 2 nAChR, the 2KO mice IBAT exhibited higher [18F]FDG IBAT compared to controls and 2HS mice. Female mice were less affected by nicotine compared to the male mice. Overall, 2 nAChRs played a significant role in glucose metabolism in the brain and IBAT.

Severe hypoglycemia remains a serious adverse effect of insulin therapy in individuals with diabetes and is linked to cognitive decline, yet the mechanisms by which transient metabolic stress leads to persistent neuronal dysfunction remain poorly defined. Using mouse models of acute severe hypoglycemia and integrated screening, we identified the retrosplenial cortex as a previously unrecognized brain region that is particularly vulnerable to hypoglycemia-induced neuronal damage. This injury is driven by a feedforward interaction between neuron-specific Drp1-dependent mitochondrial fission and microglial IL-1 signaling, as pharmacological or genetic targeting of either pathway suppressed the other, rescued neuronal damage, and reversed cognitive impairment. These findings identify a region-specific neuron-microglia injury circuit that links severe hypoglycemia to cognitive dysfunction and suggest a therapeutic strategy to protect brain function without compromising diabetes management.

Previous studies exploring the connection between early language development and brain anatomy have shown that cortical areas relating to individual differences in language skills are diverse and vary depending on the age of child. However, due to lack of large longitudinal samples, current literature is limited in answering the extent to which individual differences in language development prior to school age are reflected in areas of the cortex. To fill this gap, we compared gray matter density between participants that belonged to different longitudinally defined language profiles from 14 months to five years of age in a large population-based sample. Participants were 166 children from the FinnBrain Birth Cohort Study who had longitudinal language data from 14 months to five years of age and magnetic resonance imaging data at five years of age. Three groups of language development were used as per our prior study: persistent low, stable average, and stable high. Voxel-based morphometry metrics were calculated using SPM12 and the three language profile groups were compared to one another. Covariates included sex and age at brain scan. The statistics were thresholded at p < 0.01 and false discovery rate corrected at the cluster level. Of the three longitudinal language profiles, the stable high group had higher gray matter density than the persistent low group in the right superior frontal gyrus. No differences were found between the stable average and stable high groups, nor persistent low and stable average groups. The identified superior frontal cortical area belongs to executive functions neural network. This finding adds to the cumulating evidence that individual differences in language development are reflected in growth of gray matter supporting general processing ability rather than specialized language regions. The results suggest that cognitive development and early language development are linked through shared principles of neural growth, identifiable already at age five.

The brain generates diverse cognitive states while maintaining a stable functional architecture, a duality that remains difficult to reconcile. Prevailing views assume that flexible cognition necessitates correspondingly flexible architecture, in which different tasks demand distinct reconfigurations of functional networks. Here we introduce the intrinsic network flow (INF) framework as a complementary view. This framework is built on temporally coordinated signal flows across brain networks that constitute a universal scaffold, stable across diverse cognitive states and common across individuals. We show that a wide range of task-evoked activation patterns can be reconstructed by modulating only the temporal phase alignment of these flows, whose fixed structure determines functional connectivity topology, gradients, and large-scale networks, thereby preserving these properties across task states. This situates resting-state and task-state dynamics within a unified framework and suggests a generative relationship from flow-like dynamics to the full landscape of resting-state and task-state phenomena. Crucially, phase information, which neither existing brain state analyses nor eigenmode decompositions can extract, outperforms amplitude or activation-based markers in distinguishing cognitive states. These findings reframe task-evoked activation and deactivation as constructive and destructive interference among concurrent flows, rather than selective engagement or disengagement. This reconceptualization implies that the primary control variable for cognition is when intrinsic dynamics align in time, not where or how much the brain activates. Together, these results demonstrate that flexible cognition can emerge from retiming without reconfiguring functional architecture, offering a new path toward understanding the principled link between intrinsic dynamics and task-evoked cognition.

How can humans remember and imagine without vision? Mental time travel, the ability to re-experience past events and envision future ones, is widely assumed to rely on visual imagery and the construction of mental scenes. Blindness provides a critical test of this assumption. Across behavioral interviews, language analyses, and multimodal neuroimaging in congenitally blind, late-blind, and sighted individuals, we show that blind individuals, even those blind from birth, mentally time travel as vividly as sighted people, but construct their inner worlds differently. Sighted participants relied on perceptual detail and activated classic scene-processing regions, whereas blind participants emphasized thoughts and emotions and recruited reorganized occipital cortex. Connectivity analyses revealed strengthened coupling between occipital and medial temporal regions, indicating adaptive reconfiguration of the episodic system. The brain does not require images to imagine: it flexibly builds internal experiences using the representational resources available.

Moth pheromone-sensitive olfactory receptor neurons (Phe-ORNs) encode the intermittent structure of pheromone plumes through precisely timed spikes, a mechanism that is essential for odor plume tracking behavior in flying insects. However, natural olfactory scenes are composed of diverse volatile plant compounds (VPCs) with complex temporal dynamics whose effects on pheromone signal intermittency encoding remain unclear. Two lines of research, encoding of pheromone intermittency and background interference, remain largely disconnected. Here, we performed electrophysiological recordings from moth Phe-ORNs to quantify their responses to turbulent plume-like flickering pheromone stimuli in constant or fluctuating backgrounds of a diversity of VPCs. We found that some VPCs reversibly disrupted the temporal coding of various subregions of the pheromone stimulus and the trial-to-trial variability. While Phe-ORN activation by VPCs partially accounted for the decrease in coding performance, Phe-ORN gain reduction was insufficient to explain the full extent of the disruption. Some VPCs disrupt temporal coding without activating Phe-ORNs, and others activate Phe-ORNs without altering temporal coding. A continuous background noise can induce strong adaptation and limit dynamic range, whereas a fluctuating background can interfere with pheromone pulse encoding by disrupting spike timing. Altogether, these results indicate that the pheromone detection system must contend with multiple forms of background noise rather than a uniform disturbance. Timing is key for olfactory navigation, and our results raise questions regarding how downstream circuits would process noisy sensory inputs.

Background: Peri-synaptic astrocyte processes (PAPs) play a fundamental role in synapse formation and function. Central afferent synapse loss and astrocyte dysfunction greatly impede sensory-motor circuitry in spinal muscular atrophy (SMA) disease progression, however mechanisms underpinning tripartite synapse dysfunction remains to be fully elucidated. The aims of this study were to further define PAP and motor neuron synaptic defects in human SMA disease pathology and implement a therapeutic intervention strategy to improve motor neuron function. Methods: We derived astrocyte monocultures and motor neuron astrocyte co-cultures from healthy and SMA patient induced pluripotent stem cell (iPSC) lines to assess intrinsic astrocyte filopodia defects and phenotypes occurring at the synapse-PAP interface, respectively, using cell surface capture mass spectrometry proteomics, confocal and super resolution microscopy, synaptogliosome isolation, and electrophysiology. Results: SMA astrocytes demonstrated intrinsic filopodia actin defects featuring low abundance of actin-associated cell surface N-glycoproteins, and decreased filopodia density and CDC42-GTP levels after actin remodeling stimulation. This phenotype is likely driven by the significant reduction of CD44 and phosphorylated ezrin, radixin and moesin ERM proteins (pERM) within SMA astrocyte filopodia. The dual combination of SMN1 gene therapy and forskolin treatment, an adenylyl cyclase activator leading to increased cyclic adenosine monophosphate (cAMP) levels and actin signaling pathway stimulation, led to extensive branching and increased filopodia density of SMA astrocytes during actin remodeling. SMA patient-derived motor neuron and astrocyte co-cultures, particularly samples derived from male patient iPSC lines, demonstrated a significant decrease in synapse number, actin-associated pre-synaptic neurotransmitter release protein, synapsin I (SYN1), and PAP-associated expression of pERM and glutamate transporter, EAAT1. Our astrocyte-targeted SMN1 augmentation and forskolin treatment paradigm restored SYN1 protein levels within the SMA synaptogliosome, resulting in significant increases in motor neuron synapse formation and function, but did not fully restore PAP-associated proteins levels at the synapse. Conclusions: SMA astrocytes demonstrate intrinsic actin-associated defects within filopodia, which correlates with decreased pERM levels at tripartite motor neuron synapses. We also define a SMN- and cAMP-targeted treatment paradigm that significantly increases pre-synaptic neurotransmitter release protein levels to improved SMA motor neuron synapse formation and function.

Psilocybin can produce sustained benefits in affective and trauma-related disorders, yet if and how it reshapes sensory representations of learned valence associations remains largely unclear. To address this, we used longitudinal two-photon calcium imaging in awake C57BL/6 mice to examine how psilocybin modulates layer 2/3 auditory cortex activity at single-cell and population levels. Evoked responses were measured for tones with or without prior associations with valenced stimuli, as well as for the valenced stimuli themselves. Most responsive neurons were selective for tones alone, while distinct subsets responded exclusively to reward or aversive stimuli, and a smaller population encoded both. Psilocybin selectively reduced responses to aversive stimuli and earlier-established aversive-associated tones, without affecting aversive association, reward responses, or responses to newly aversive-associated tones. At the population level, psilocybin acutely increased coordination across tone-responsive neurons, while later reducing it selectively among neurons encoding the aversive-associated tone. These results demonstrate that psilocybin preferentially dampens well consolidated aversive sensory representations in auditory cortex, rather than fresh associations, without broadly affecting auditory processing or new aversive learning.

Consciousness remains poorly understood as a causative force: existing theories treat it as an epiphenomenal correlate of neural activity rather than explaining how inner experience controls its substrate. I present Recurrent Integration Fractal Theory (RIFT), proposing that consciousness arises when fractal compression of sensory information generates a holographic endospace: the spatiotemporal dimension in which the Self perceives the outer world (exospace) and, through autopoietic feedback, controls the molecular substrate from which it emerged, making consciousness causally efficacious rather than epiphenomenal. In RIFT networks, core neurons form recurrent loops through fractal dendritic trees, generating dynamic information integration through coincidence-based synaptic selection. Coincident EPSPs program somatic multifractals, Ising lattices of ion channels and membrane lipids, encoding a fractal Self-attractor: a geometric field whose coherent point sources generate the holographic endospace through which the Self arises. The Self modulates multifractal growth through lipid domains, controlling ion channel opening probability and action potential generation. Through Generational Fractal Mapping, compressed seeds of prior conscious moments integrate with new EPSPs, replacing infinite downscaling as in classical fractals with sequential self-referential mapping that sustains incremental updating of inner experience, temporal continuity of the Self and Self-attractor transfer across brain regions for global conscious access, establishing irreducibility and unity: the whole is in each part. This architecture was validated computationally against three core properties of consciousness: irreducibility, information integration, and holographic encoding. RIFT generates testable predictions for lipid substrate disruption in Alzheimer's disease, fractal signatures of conscious states, and criteria for consciousness in artificial systems with autopoietic feedback.

High-fat diet (HFD) consumption engages reward circuitry and promotes neuroadaptations that contribute to overeating and obesity. While mesolimbic dopamine pathways are central to hedonic feeding models, the contribution of sensory cortical systems remains poorly understood. Here, we performed whole-brain activity mapping using Targeted Recombination in Active Populations (TRAP) and network analysis to define the distributed neural consequences of short-term HFD exposure in male and female mice. HFD increased caloric intake in both sexes, with females consuming significantly more than males. Brain-wide analysis revealed striking sex-specific adaptations: HFD selectively increased isocortical activity in males, with the somatosensory cortex (SS) emerging as the most prominently modulated region. SS activity negatively correlated with HFD intake, primarily in males. Network analysis using the SMARTTR pipeline demonstrated that HFD reorganized network activity in a sex-dependent manner, biasing male networks toward associative cortical-thalamic hubs, whereas female networks preferentially recruited subcortical and brainstem structures. To determine causality, we bidirectionally manipulated SS pyramidal neurons using chemogenetics during limited-access HFD exposure. Inhibition of the SS increased HFD intake in males, whereas activation reduced cumulative intake in females, without affecting locomotion. These findings establish the SS as a sex-specific regulator of palatable food consumption and demonstrate that similar behavioral outcomes emerge from distinct circuit architectures across sexes. Collectively, this study expands prevailing reward-centric models of hedonic feeding by identifying sensory cortical control as a critical component of diet-induced neuroadaptations, with important implications for sex-specific therapeutic strategies targeting overeating and obesity.

Although the influence of Brain-Derived Neurotrophic Factor (BDNF) has been characterized across numerous neural settings, how individual cells decode this pleiotropic message into context-dependent signaling responses remains unresolved. Using highly multiplexed single-cell mass cytometry to simultaneously measure levels of 19 signaling markers and 18 cell ID markers, we constructed a temporal atlas of BDNF-induced signaling relative to two control conditions across diverse spinal cord lineages and maturation states. We demonstrate that not all cells contribute to the global BDNF response with ~47-75% of cells having increased ERK phosphorylation at peak activation. Our analysis of 20 uniquely identified cell identities reveals that TrkB/p75NTR receptor stoichiometry sets the potential for response, but ultimately the sustained reduction of surface TrkB predicts BDNF sensitivity. Surprisingly, identical receptor profiles in distinct cell types yield fundamentally different signaling responses, indicating that cell identity acts as the final arbiter of the BDNF message. These findings reframe BDNF sensitivity as a form of prepared competence. This work thus provides a framework for understanding how intracellular context dictates the functional interpretation of neurotrophic cues.

Self-transcendence, the reorientation of experience away from the self toward others, nature, or broader meaning, is a fundamental dimension of human psychology, yet its causal neural architecture remains poorly understood. Here we applied lesion network mapping to 88 neurosurgical patients with pre- and post-operative assessments of trait self-transcendence to identify the distributed brain network whose disruption alters this capacity. The resulting network showed significant spatial correspondence with the default mode network and, at a finer parcellation level, with frontoparietal control subnetworks. Leave-one-out analyses identified posterior midline regions as the most stable correlates of increased self-transcendence following brain lesions. Independent validation against fMRI meta-analyses of self-referential processing, compassion, and ketamine administration, alongside a neuromodulation target previously shown to modulate the sense of self, converged on a consistent model. These findings provide causal evidence for a network architecture in which posterior midline hubs constrain, and brainstem and anterior midline regions facilitate, self-transcendent experience.

Metacognition refers to the capacity to monitor one's own actions, internal states, and cognitive processes. A central question in cognitive neuroscience is whether metacognitive evaluation operates as a direct readout of performance signals or requires computationally independent neural mechanisms. Single-process theories propose that both arise from shared decision variables, while the Higher-Order Representation theory holds that metacognition requires re-representation through distinct computational processes. To test these frameworks, participants produced timed motor intervals and evaluated their own performance without external feedback, termed temporal error monitoring (TEM). Vision Transformer decoding applied to PCA-optimized single-trial EEG captured {theta}, , and {beta} dynamics during both task phases. First-order timing was decodable from any individual frequency band, whereas second-order metacognitive inference required simultaneous integration across all three bands before action termination. Individuals whose metacognitive states were more accurately decoded showed stronger TEM precision, with no equivalent relationship observed for first-order performance decoding. These findings establish metacognitive evaluation as a computationally distinct process requiring higher-order multi-band neural integration rather than a direct readout of first-order timing signals.

Non-invasive brain stimulation (NiBS) studies frequently report exploratory correlations between individual-level changes in neurophysiological and behavioural measures. However, these analyses are typically underpowered and rely on ratio-based change scores with known statistical limitations. We addressed these limitations by pooling individual data from three independent studies (total N = 69), providing adequate power to detect small to medium effects. All studies applied 20 Hz transcranial alternating current stimulation (tACS) targeting the pre-supplementary motor area (preSMA) and right inferior frontal gyrus (rIFG), regions central to inhibitory control. Changes in preSMA-rIFG connectivity measured with EEG imaginary coherence (ImCoh) and response inhibition (stop-signal reaction time, SSRT) were quantified using reliable change indices (RCI), which were z-standardised within studies to enable pooled mixed-effects regression. No meaningful association was found between tACS-induced ImCoh change and SSRT change (r = .013, marginal R2 = .004), with project-wise correlations that were small, non-significant, and inconsistent in direction. Sensitivity analysis using ratio-based change scores converged on the same null result (r = .014), though ratio scores showed severe distributional violations relative to the approximately normal RCI distributions, supporting the methodological case for RCI on statistical grounds. These results provide no support for a systematic individual-level brain-behaviour coupling between preSMA-rIFG connectivity and response inhibition following 20 Hz tACS, and suggest that any true effect is likely to be small. The present work offers a methodological benchmark for quantifying individual-level brain-behaviour coupling in NiBS research, and highlights the need for more sensitive neural markers and adequately powered design.

Voxelwise encoding models trained on functional MRI data can produce detailed maps of cortical organization. However, voxelwise encoding models must be trained on many hours of brain responses from each participant, limiting clinical applications. In this study, we introduce a cross-participant modeling framework for rapid cortical mapping. In this framework, voxelwise encoding models are trained on many hours of brain responses from previously scanned reference participants, and then transferred to a new participant by aligning brain responses using a small set of stimuli. We evaluated cross-participant encoding models on linguistic semantic mapping, non-linguistic semantic mapping, and auditory mapping. In each case we found that cross-participant encoding models had more accurate selectivity estimates and prediction performance than within-participant encoding models trained on the same amount of data from the new participant. We also found that cross-participant encoding models improved with the amount of data from each reference participant and the number of reference participants. These results demonstrate that cross-participant modeling can substantially reduce the amount of data required for accurate cortical mapping, which may facilitate new clinical applications of functional neuroimaging.

Cognitive processes such as decision-making, working memory, and motor planning operate across a hierarchy of timescales, manifesting as rapid neural transients alongside slower physiological mechanisms like short-term plasticity. Conventional Dynamic Causal Modelling (DCM) limits our ability to study these dynamics by assuming stationary parameters, whilst recent time-varying approaches often rely on segmenting data into epochs. This segmentation artificially resets neural states between windows, fundamentally obscuring the continuous hysteresis essential to sequential processing. To address this limitation, we introduce DCM for Sequential Responses (DCM-SR), a generative framework that embeds parameter evolution directly within the first-level model whilst employing a continuous state-space formulation that removes the requirement for epoching. This approach generalises non-stationarity to all neural mass parameters, including synaptic gains and time constants, modelling them as piecewise smooth trajectories that evolve alongside continuous neural states. Consequently, the model explicitly captures two distinct forms of temporal memory: transient history dependence, where responses are shaped by the carryover effect of recent perturbations, and path dependence, where the system's trajectory through parameter space determines its responsiveness. The framework accommodates both exogenous, stimulus-locked transitions and endogenous, autonomous state changes, permitting inference on both external perturbations and internal drivers of network evolution. Simulations establish the model's face validity, demonstrating robust parameter recovery and conservative model selection that accurately discriminates between genuine parameter evolution and spurious complexity. We applied the framework to empirical data from an auditory go/no-go task, modelling a full sequence of cognitive phases from initial cue processing and anticipation through to motor preparation and execution. This analysis established construct validity by resolving the biophysical generators of the contingent negative variation, attributing this slow potential to sustained thalamocortical drive and deep-layer hyperpolarisation rather than superficial-layer activity. Furthermore, the model captured trial-specific modulations of the hyperdirect pathway during motor inhibition, tracking the dynamic interplay between prefrontal executive control and basal ganglia gating. DCM-SR offers the first principled approach to decomposing compound signals such as slow cortical potentials into evolving synaptic mechanisms and continuous state trajectories, and provides a necessary bridge for investigating the biophysical implementation of extended cognitive phenomena including evidence accumulation and physiological hysteresis.

Age-related hearing loss (ARHL), or presbycusis, is one of the most prevalent sensory deficits in older adults and has been increasingly implicated in cognitive decline and dementia. This study characterizes ARHL in a rhesus macaque model by combining histological, physiological, and cognitive assessments. Aged macaques exhibited progressive cochlear degeneration, with marked outer hair cell loss at mid-to-high frequencies, elevated auditory thresholds, reduced distortion product otoacoustic emissions, and impaired auditory brainstem responses including amplitude reduction, latency prolongation, and diminished temporal precision. Despite modest reductions in inner hair cell ribbon synapse counts, hypertrophic changes were observed. These auditory deficits correlated with subtle impairments in visual working memory, as measured by a delayed match-to-sample task, underscoring a potential sensory-cognitive link. By capturing cross-domain aging markers in a translationally relevant primate model, this work lays a foundation for mechanistic studies and therapeutic interventions targeting both hearing and cognition in aging populations.

Neuromuscular reflexes elicited by sensory nerve stimulation provide valuable insights into neural motor control pathways. Analysis at the level of individual motor units (MUs) is feasible via electromyographic decomposition, but the factors shaping MU-specific reflex responses remain poorly understood. We investigated long-latency responses to cutaneous electrical stimulation in a large population of tibialis anterior MUs from nine healthy subjects during isometric ankle dorsiflexion at 10-30% of maximum voluntary contraction. Individual MU reflex responses differed markedly. Using 1000 stimulation pulses per trial, substantially more than the 150-300 typically reported in previous studies, provided more reliable estimates of cutaneous reflex characteristics. Across the motor pool, reflex magnitude increased with force level (p < 0.001) while excitation probability correlated significantly with MU recruitment threshold in 78% of subjects (p = 0.012). Furthermore, excitation probability increased systematically with contraction intensity (p < 0.001) for individually tracked MUs. Post-excitatory depression (PED) magnitude correlated significantly with excitation probability (r = 0.50, p < 0.001) of individual MUs. A targeted reflex-removal analysis, validated by MU simulations incorporating realistic excitation probabilities into ordinary firing patterns, reduced the PED by 84.2% in simulated data but only by 34.7% in recorded units. These findings suggest that the PED is a complex, hybrid phenomenon, resulting from synchronization-induced discharge resetting and additional independent inhibitory components. These findings demonstrate that MU-level reflex excitability to somatosensory input is influenced by state- and identity-dependent motor neuron characteristics, underscoring the importance of using sufficient stimulation pulses for reliable reflex measures and MU population analysis.

Axons are the brain's wiring, organized into bundles that connect nearby and distant regions. Axon caliber determines signal conduction velocity and varies both within and across bundles, reflecting the brain's diverse functional demands. Much of what we know about this organization derives from 2D histology, assuming cylindrical axons whose calibers are described by their radius. Yet, recent 3D histology reveals that the radius varies along an individual axon---with implications for both characterizing axon caliber and potentially conduction velocity predictions. We show in 450,000 3D rat axon reconstructions that---despite this individual variation---axon bundles possess stable radius distributions at the ensemble level, which 2D cross-sections faithfully represent. This representativeness extends to conduction velocity predictions, as along-axon variation has only modest impact. In particular, large axons exhibit especially stable conduction, emphasizing their key role in time-critical signaling. With 2D sampling validated, we leverage 46 million human corpus callosum axons from 2D histology to determine sample size requirements across neuroscience applications. Our findings reinforce decades of 2D histology-based research on axon organization and its functional implications, while guiding future study design.

Myelin oligodendrocyte basic protein (MOBP) is an abundant oligodendrocyte gene implicated in multiple neurodegenerative diseases. Genetic variation at the MOBP locus has been associated with risk for progressive supranuclear palsy (PSP), amyotrophic lateral sclerosis (ALS), frontotemporal lobar degeneration (FTD), corticobasal degeneration (CBD), Alzheimer's disease (AD), Lewy body dementia (LBD), and Creutzfeldt-Jakob disease (CJD). Epigenetically, MOBP promoter hypermethylation and reduced expression have been reported in multiple system atrophy (MSA). Although MOBP is thought to play a role in oligodendrocyte morphology and myelin structure, how genetic and epigenetic variation at this locus influences gene regulation and contributes to disease risk remains poorly understood across neurodegenerative disorders. Here, we investigated whether shared or disease specific genetic mechanisms at MOBP converge on altered DNA methylation and expression across neurodegenerative disorders. We analysed MOBP variants using summary statistics from recent GWAS for ALS, PSP, FTD, LBD, PD, MSA, AD, and CJD. Colocalisation (COLOC and SuSiE coloc) was used to test whether disease-associated variants overlapped between diseases, and with oligodendrocyte expression quantitative trait loci (eQTLs) and bulk brain methylation quantitative trait loci (mQTLs). To further investigate mQTL effects at this locus, rs1768208, a variant previously associated with PSP, was genotyped in an overlapping brain methylation cohort, allowing direct testing of genotype methylation associations in frontal white matter tissue. ALS and PSP GWAS demonstrated strong association at MOBP, with most strongly associated SNPs (e.g. rs631312, rs616147, rs1768208) shared between both disorders. Colocalisation analyses indicated high posterior probability that ALS and PSP share the same causal variant, with weaker overlap with FTD. mQTL colocalisation highlighted cg15069948, located near an exon junction within MOBP, as strongly colocalising with the ALS/PSP risk variants. In complementary tissue analyses, rs1768208 (T) carriers showed hypomethylation at cg15069948 in PSP brains. No genotype-methylation effects were detected in MSA or PD. Together with prior evidence of promoter hypermethylation and reduced expression in MSA, our findings identify cg15069948 as a regulatory methylation site linking ALS/PSP risk variants to altered MOBP methylation, and support MOBP dysregulation as a shared feature of neurodegeneration. However, the underlying mechanisms appear disease specific, highlighting the complexity of involvement of this gene across neurodegenerative disorders.

Declining spatial navigation abilities are a critical hallmark of aging, where the loss of spatial abilities precedes global cognitive impairment. While navigational decline is traditionally attributed to deficits in higher-order cognitive functions, emerging cognitive-motor frameworks suggest that age-related sensorimotor alterations play a significant, yet previously overlooked, role. Here, we investigate the coupling between locomotor integrity and navigation by combining an immersive virtual-reality path-integration paradigm with systematic manipulations of landmark availability and reliability, while recording gait kinematics alongside neural dynamics using high-density mobile-EEG from 30 young and 32 older adults. We demonstrate that older adults accumulate angular homing error more rapidly than younger adults, a deficit linked to altered gait dynamics. These age-dependent differences are reflected in increased mid-frontal theta activity, highlighting a robust coupling between gait-related sensorimotor alterations and decline in navigation. Older adults also exhibited increased reliance on visual landmarks, and particularly those with degraded gait, yet this compensatory reweighting of navigational cues remained less efficient and less precise than in younger adults. These findings highlight sensorimotor gait alterations as a central determinant of age-related navigation deficits, challenging the traditional separation of motor and cognitive domains and identifying locomotor integrity as a critical target for preserving spatial navigation abilities.

Alzheimers disease (AD) is a devastating neurodegenerative disorder characterized by memory loss and a decline in cognitive function. Hallmarks of AD include an age-dependent accumulation of toxic amyloid beta 42 in the brain, energy dyshomeostasis caused by mitochondrial dysfunction, and iron overload. However, the role of iron overload and mitochondrial dysfunction in AD pathology is unknown and their precise relationship with amyloid beta 42 toxicity in AD pathology is unclear. C. elegans provide a powerful model system to untangle and clarify these relationships. In this study, we quantify the temperature-dependence of iron toxicity at 16, 20 and 25 degrees centigrade in neurons and muscle of C. elegans that overexpress amyloid beta 42. We found that amyloid beta 42, regardless of the cell type expression, caused accelerated paralysis compared to age matched WT worms with the greatest degree of paralysis observed at an elevated temperature 25 degrees centigrade. Moreover, the combination of iron toxicity and amyloid beta 42 results in an enhanced paralytic phenotype at 16 degrees centigrade. Thus, iron exposure potentiates amyloid beta 42 toxicity observed at low temperatures. Iron toxicity stimulated both maximum and leak respiration in WT and amyloid beta 42 worms. Amyloid beta 42 worms also exhibited increased leak respiration at baseline that was further exacerbated by iron toxicity. Iron burden and sensitivity increased amyloid beta 42 peptide toxicity. Amyloid beta 42 worms exhibited reduced levels of Ca, Zn, Mn, and K. Overall, our results suggest that iron potentiates amyloid beta 42 toxicity at low temperature and enhances amyloid beta 42 peptide mediated mitochondrial bioenergetic dysfunction in C. elegans.

Selective attention enables prioritization of behaviorally relevant information through coordinated control of neural excitability. Although theta-band (3-7 Hz) rhythms are implicated in top-down attentional sampling in non-human primates, how intrinsic theta phase organizes sensory gain and behavior in humans, and whether this control operates symmetrically across hemispheres, remains unknown. We recorded electroencephalography (EEG) and pupillometry in typically developing human participants (n = 21; 14.7 {+/-} 3.8 YO) performing a covert spatial attention task. Behaviorally, participants responded faster during leftward relative to rightward attention. This behavioral asymmetry was paralleled in the neural data: anticipatory modulation of parieto-occipital alpha and beta power emerged selectively during leftward attention, whereas rightward attention did not recruit comparable posterior oscillatory processes. Mechanistically, ipsilateral fronto-central theta phase emerged as a potential driver of this asymmetry. Intrinsic theta phase predicted trial-by-trial reaction time (RT) in a cue-direction-specific manner. During leftward attention, 3-Hz theta-phase over left fronto-central cortex modulated behavior and was significantly coupled to coordinated posterior alpha-band activity. In contrast, 6-7 Hz theta-phase over right fronto-central cortex modulated behavior during rightward attention but showed no relationship with alpha or beta modulation; instead, it modulated early sensory gain, indexed by P1 amplitude. Consistent with these distinct architectures, RT was jointly predicted by lower pre-stimulus alpha power and higher P1 amplitude over the attended hemisphere during leftward attention, whereas only P1 amplitude predicted performance during rightward attention. Resting-state alpha power did not differ across hemispheres, indicating that these effects were task-evoked rather than baseline spectral differences. Critically, older participants, who demonstrated enhanced behavioral performance, also exhibited a larger hemispheric asymmetry. Together, these findings reveal developmentally emerging, direction-specific neural control dynamics underlying human spatial attention.

Eye movement-related eardrum oscillations (EMREOs) appear to consist of a pulse of oscillation occurring in conjunction with saccades. However, this apparent pulse could occur either because there is an increase in energy at that frequency at the time of saccades (a true pulse), or because there is saccade-related phase resetting of ongoing energy at that frequency band, thus appearing like a pulse when averaged in the time domain across many trials. Here we conducted a spectral analysis at the individual trial level in humans performing a visually guided saccade task to determine whether the power at the EMREO frequency (30-45 Hz) is higher during saccades than during steady fixation. We found both an increase in sound power in the EMREO frequency band associated with saccades, i.e. sound pulses at the individual trial level, as well as, phase resetting at saccade onset/offset. While both factors contribute to the apparently pulse-like EMREO signal, phase resetting appears to be more prevalent across participants. The prevalence of phase resetting has implications for the underlying mechanism(s) producing EMREOs as well as functional consequences for how the ear might respond to incoming sound in an eye-position dependent fashion.

Background: Monoamine transporters (MATs), including the dopamine, norepinephrine, and serotonin transporters (DAT, NET, SERT), are essential regulators of synaptic neurotransmission that rely on complex oligomeric bio-assemblies for proper function. The regulatory influence of naturally occurring, alternatively spliced truncated isoforms on bio-assembly dynamics remains profoundly underexplored. Methods: To decode these interactions at the atomic level, we deployed a multiscale computational framework. We integrated genomics-guided multimer predictions with massive-scale, near-million-atom molecular dynamics (MD) simulations within explicit lipid bilayers. The thermodynamic stability of these heteromeric complexes was quantified using membrane-adapted MM/PBSA calculations, which were subsequently correlated with dynamics-aware evolutionary profiling to map co-evolutionary interaction hotspots. Results: Our analyzes reveal that the NET-derived truncated isoform A0A804HLI4 acts as a pan-family potential inhibitor. It forms stable, exergonic heterodimers with canonical NET and DAT, thermodynamically outcompeting native homodimerization. In full tetrameric simulations, the integration of a single isoform precipitates a macro-structural disruptions of the SERT complex. The variant anchors at non-native interfaces, locking the assembly into an asymmetric, non-native state. Residue-level thermodynamic decomposition and evolutionary mapping isolated conserved structural elements (most notably Gln236) that dictate this high-affinity cross-reactivity across the SLC6 family. Conclusions: Truncated MAT isoforms execute a dynamic mechanism of inhibitory effects and may systematically downregulate synaptic reuptake capacity by sequestering functional monomers. These findings establish a thermodynamically grounded, high-resolution model of isoform-induced bio-assembly disruptions. Crucially, they expose these non-canonical, isoform-driven interfaces as conserved and highly druggable targets, offering a distinct pharmacological paradigm for precision interventions in neuropsychiatric and neurodegenerative pathologies. Key Words: Serotonin and dopamine biochemistry, Truncated isoforms, Complex structure prediction, Monoamine transporters, Molecular co-evolution

Adaptive behavior requires the ability to monitor the accuracy of self-generated actions, including the production of precise time intervals. Here, we investigated the neural mechanisms underlying temporal error monitoring in rats by combining a time production and error-reporting task with selective pharmacological inactivation of the orbitofrontal cortex (OFC) and anterior cingulate cortex (ACC). We found that OFC inhibition impaired the production of time intervals in a dose-dependent manner, indicating its critical role in generating temporally precise actions, whereas ACC inhibition left time production intact but caused a systematic overestimation of temporal errors and increased overconfident responses on incorrect trials. Analyses of choice behavior revealed that ACC inactivation disrupted the use of trial history and shifted decision thresholds, suggesting that ACC implements a hierarchical read-out of ongoing temporal performance. These results support a functional dissociation in which OFC provides the temporal signal for action, while ACC evaluates errors and confidence. Our findings establish a causal link between prefrontal circuits and self-monitoring of time, offering a model for hierarchical temporal control and evaluation in the rodent brain.

Elucidating how normal aging increases vulnerability to neurodegeneration remains a major gap in our understanding of disease risk and progression. The dorsal striatum serves as the primary input nucleus of the basal ganglia and is a key region implicated in multiple neurodegenerative diseases (NDDs) (1). In Colon et al. 2025 (2), we examined the impact of normal aging on neuroinflammatory signaling and perineuronal net (PNN) homeostasis within the dorsal striatum. We observed age associated shifts in the inflammatory landscape and evidence of increased microglial activation, yet PNN homeostasis was largely preserved (2). PNNs are highly organized extracellular matrix (ECM) specializations that preferentially enwrap the soma and proximal dendrites of fast-spiking GABAergic parvalbumin (PV) interneurons, where they contribute to the regulation of synaptic plasticity and provide protection against oxidative stress (3,4). Building on these findings, we developed a working hypothesis to explain the apparent preservation of PNN homeostasis despite an aging-associated pro-inflammatory environment. The shift toward a proinflammatory milieu, together with increased gliosis and phagocytic activity, would be expected to impact the maintenance and integrity of perineuronal nets. The observed increase in phagocytosis-related markers may reflect microglia directed activity as well as contributions from additional central nervous system (CNS) cell populations. Microglia are specialized embryonic derived myeloid cells that serve as the resident immune cells of the brain and contribute to PNN homeostasis under physiological conditions (5). In Colon et al. 2025, we observed evidence of microgliosis (e.g., morphological changes, Iba1, Trem2) along with elevated expression of markers associated with phagocytosis (e.g., Cd68) and extracellular matrix modifying proteases (e.g., Mmp9, Adam17) capable of cleaving key PNN components (2). Importantly, Cd68 expression is not exclusive to microglia and has been detected in brain infiltrating macrophages, reactive astrocytes, and neutrophils during inflammation (6, 7, 8). Thus, increased Cd68 levels may not solely reflect microglial phagocytic activation but may also reflect astrocyte reactivity and phagocytic phenotypes. Furthermore, astrocytes are the most abundant glial cell in the brain, and they play a major role in maintaining CNS homeostasis by regulating extracellular neurotransmitter concentrations, providing metabolic support, contributing to the synthesis and remodeling of PNN components, and modulating neuronal communication through their involvement in the tetrapartite synapse (9, 10, 11, 12). Astrocytes can also phagocytosis microglial debris, myelin, and synapses (7). To better define the cellular source of phagocytic activity and its relationship to PNN remodeling in aging, we performed immunostaining for microglia (Iba1+), astrocytes (GFAP+), phagolysosomal activity (CD68+), and PNNs using Wisteria floribunda agglutinin (WFA+), enabling us to assess the spatial relationship between phagocytosis and PNN components.

Background: Transcranial Magnetic Stimulation (TMS) studies identify the Resting Motor Threshold (RMT) to calibrate stimulation intensity. However, this procedure is time-consuming and subject to variability. We developed an automated procedure to improve the efficiency and standardization of RMT determination. New method: We developed an algorithm that measures MEP amplitudes and automatically adjusts stimulation intensity to determine the RMT. Experiment 1 compared this automated method with the manual procedure in terms of reliability and equivalence. Experiment 2 developed a fast automated process, assessing it against both the manual and initial automated procedures. Results: Across both experiments the automated approach demonstrated excellent test-retest reliability and strong agreement with the manual method (Intraclass Correlation Coefficients >=0.95), giving estimates of RMT statistically equivalent to those of manual measurements within +/-3% MSO, with the majority of comparisons within +/-2% MSO. Experiment 2 optimized the procedure, allowing empirical determination of the RMT in an average of <3 minutes with only 33-34 pulses. Comparison with existing methods: RMT-Finder provides a reliable and time-efficient alternative to manual approaches. To the best of our knowledge RMT-Finder presents the first closed-loop feedback approach to identify the RMT without manual intervention. This procedure can improve standardization and reproducibility in TMS studies. Conclusions: Automating RMT assessment allows rapid and highly reproducible assessment of this standard TMS measurement, making it viable for inclusion in routine clinical applications that require standardized procedures.

The functional organization of the teleost telencephalic pallium remains poorly understood, particularly regarding the presence of modality-specific sensory domains and their topographic arrangement. Here, we used in vivo wide-field voltage-sensitive dye imaging to map sensory-evoked neural activity across the dorsal surface of the telencephalic pallium of adult goldfish. Somatosensory, auditory, gustatory, and visual stimulation revealed distinct, modality-specific domains primarily located within the dorsomedial (Dm) and dorsolateral (Dl) pallium. Within Dm, somatosensory and auditory stimuli activated partially overlapping territories in the caudal subregion (Dm4), exhibiting clear somatotopic and tonotopic organization along the mediolateral axis. Gustatory stimulation selectively engaged Dm3, where different tastants activated spatially distinct but partially overlapping domains. A more rostral subregion (Dm2) responded only to high-intensity somatosensory stimulation, suggesting involvement in processing negatively valenced inputs. Visual stimulation activated a circumscribed area within the dorsolateral pallium (Dld2),that closely matched cytoarchitectural boundaries. Pharmacological blockade of ionotropic glutamate receptors markedly reduced sensory-evoked responses, indicating that these maps depend on glutamatergic synaptic transmission. Together, these findings show that the goldfish pallium contains distinct, spatially organized sensory representations and a refined internal functional architecture. This organization suggests that pallial topographic sensory maps may not be exclusive to mammals and birds. Based on these results, we propose that dorsomedial and dorsolateral pallial regions may be functionally comparable to components of the mammalian mesocortical network, more than to the pallial amygdala or the neocortex. This framework provides a new perspective on pallial organization in teleosts and contributes to understanding the evolutionary origins of the vertebrate pallium.

Although congenital Zika virus (ZIKV) syndrome is well-characterized, the neurodevelopmental consequences of postnatal infection are less understood. Here we used a rhesus macaque model to investigate the developmental consequences of ZIKV infection during infancy on the brain and behavior, building on our prior research. Male and female infant rhesus macaques infected with ZIKV at 1 month of age were compared to sex-, age-, and rearing-matched uninfected controls and infants treated with the TLR3 agonist PolyIC as a control for activation of the innate immune system. Longitudinal behavioral assessments revealed alterations in emotional regulation following ZIKV exposure, including poor state control scores obtained from the Infant Neurobehavioral Assessment Scale early after ZIKV infection and longer-term displays of increased hostility during an acute stressor. While attachment bonds to caregivers were preserved, ZIKV-infected infants showed sex-specific alterations in behavioral regulation during caregiver separation compared to controls. At 3 months of age, MRI scans revealed larger total cerebrospinal fluid (CSF) volume and reduced volumes in visual processing regions in ZIKV-infected infants compared to controls. Postnatal ZIKV exposure also resulted in sex-specific brain structural alterations with males exhibiting amygdala hypertrophy, whereas ZIKV-infected females had volumetric reductions in temporal-limbic and temporal-auditory cortices. These findings demonstrate that postnatal ZIKV infection disrupts the development of sensory, social and emotion-regulatory systems and CSF function, highlighting the critical need for long-term monitoring of exposed children.

Transactive response DNA binding protein 43 kDa (TDP-43) pathology, is a central molecular hallmark of amyotrophic lateral sclerosis (ALS). However, the underlying triggers are incompletely understood. Here, we show that infection with herpes simplex virus (HSV) induces molecular hallmarks of ALS in various in vitro and in vivo models and is associated with an increased risk of ALS in human population data. German healthcare provider data (n = 238,440) and herpesvirus serology of an ALS patient and control cohort (n = 1,100) showed that HSV infection elevated the ALS risk by 210% and odds by ~65%, respectively. On a molecular level, HSV infection promoted TDP-43 pathology in neuronal cell models, human iPSC-derived motoneurons and cerebral organoids, mice, and human tissue sections. This effect was triggered by HSV-1 or 2, but not by several other related herpesviruses. Mechanistically, the infected cell protein 0 (ICP0) of HSV-1/2 drives TDP-43 pathology by disturbance of promyelocytic leukemia nuclear bodies (PML-NBs), thereby abrogating TDP-43 SUMO2/3ylation. Taken together, we reveal a previously unrecognized association between HSV infection and ALS and clarify the underlying molecular mechanism that drives TDP-43 pathology. Our data may guide future studies into therapeutic and prophylactic interventions against ALS.

The replacement of a single codon in the human prion gene, causing the substitution of glycine with valine at position 127 (G127V) of the prion protein (PrP), prevents development of prion disease. We set out to explore if prion disease survival extension manifests in mice if the V127 mutant is delivered through a recombinant adeno-associated virus (rAAV) packaged as a selfcomplementary DNA. The notorious delivery limitations of rAAVs were overcome using a crosscorrection approach that relied on the expression of the mutation in the context of glycosylphosphatidylinositoI-anchorless ({Delta}GPI) PrP. In this proof-of-concept study, we inoculated Rocky Mountain Laboratory (RML) prions into knock-in mice, in which the endogenous murine prion protein gene (Prnp) was replaced with the bank vole prion protein gene (BvPrnp). Prion-inoculated mice that were retro-orbitally transduced with a protective rAAV vector encoding BvPrnpV127{Delta}GPI survived ~50 days longer than control mice that were unprotected. A deep proteomic analysis revealed that BvPrnpV127{Delta}GPI was protective by slowing perturbations to the proteome observed in late-stage RML prion disease. In addition to capturing details of synaptic decay and depletion of proteins in proximity to PrP, the proteomic dataset revealed the identity of proteins of potential diagnostic value that may be central to the brains attempt to fight prion disease by contributing to astrocytosis or microgliosis, by coping with calcium influx, or by enhancing the endoplasmic reticulum processing of essential proteins. Taken together, our results demonstrate that a gene therapy based on a GPI-anchorless PrP containing the G127V mutation can delay the onset of prion disease in mice, providing a framework for development of a corresponding therapy in humans.

Endocannabinoid (eCB) signaling is a key regulator of reward-related dopaminergic signaling, particularly in response to drugs of abuse, such as cocaine. To date, our understanding of this mechanism has primarily been limited to male subjects. Prior work establishes that female cocaine users have more adverse outcomes, and female rats show greater sensitivity to cannabinoid type 1 receptor (CB1R) regulation of cocaine self-administration. Therefore, we hypothesize that female rats exhibit enhanced eCB regulation of cocaine-evoked dopamine (DA). We used in vivo fiber photometry recording of the dopamine biosensor, dLight 1.3b, in the nucleus accumbens medial shell (NAcms) in response to cocaine in male and female rats. Rats were pretreated with cannabinoid-targeting drugs to investigate the effects of CB1R inactivation or augmentation of the eCB 2-AG on cocaine-evoked DA. Our results revealed that CB1R inactivation attenuates cocaine-evoked DA in male and female rats, but females showed enhanced sensitivity for CB1R regulation of cocaine-evoked DA. Cocaine-evoked DA was enhanced by augmenting 2-AG levels, and females again showed increased sensitivity to this manipulation. Finally, females show greater cocaine-evoked DA when in a non-estrous cycle compared to estrous, reinforcing that estrous cycle is a determinant of cocaine-evoked DA. These data indicate that females show enhanced eCB regulation of cocaine-evoked DA signaling, underscoring the importance of sex as a biological variable in our understanding of endocannabinoid regulation of drug reward.

Language impairments in aphasia are characterized by various representational disruptions that may be reflected in discourse production. This research examines the capacity of transformer-based language models, particularly GPT-2, to serve as a computational framework for analyzing variations in aphasic narrative speech. A longitudinal dataset of narrative speech samples collected at six time points from individuals with aphasia (N = 47) was utilized as part of an intervention study. All transcripts were processed via the GPT-2 language model to obtain activation values from each of the 12 transformer layers. Statistically significant differences in activation magnitude across aphasia subtypes were found at every layer (all p < .001), with the most pronounced effects in the deeper layers. Pairwise Tukey HSD tests revealed consistent distinctions between Broca s aphasia and both Anomic and Wernicke s aphasia, suggesting a shared activation profile between the latter two. Longitudinal tests revealed significant changes over time, especially in the final three layers (10-12). These findings suggest that transformer-based activation patterns reflect meaningful variation in aphasic discourse and could complement current diagnostic tools. Overall, GPT-2 provides a scalable tool to model representational dynamics in aphasia and enhance the clinical interpretability of deep language models.

The hippocampus and the prefrontal cortex interact across a range of cognitive functions, yet how these regions represent space and how these representations evolve across learning remains poorly understood. We recorded large-scale neural activity from the hippocampus (CA1) and the medial prefrontal cortex (mPFC) as rats acquired proficiency in radial maze tasks over weeks. We identified a form of trial-by-trial flickering in which one hippocampal place field gradually overtook the other across successive trials, whereas mPFC firing fields switched randomly. While hippocampal flickering decreased as the task was mastered, mPFC flickering remained random and persisted throughout learning. Population-level UMAP embeddings revealed that mPFC states transitioned smoothly across trials, with the within-session representational drift stabilizing only after a two-week period. These findings suggest that while the hippocampus stabilizes its spatial maps during learning, the mPFC maintains a flexible, flickering representation that facilitates the extraction of abstract task structure and the rapid adaptation required for behavioral flexibility.

The dorsal anterior midline thalamus (aMT) consists of several closely packed nuclei that are important for motivated and emotional behavior. Previous work on aMT has focused on cells and synapses in the paraventricular thalamus (PVT), and little is known about the adjacent paratenial thalamus (PT). Here we examine neural circuits involving PT using a combination of molecular profiling, anatomical tracing, electrophysiology, and optogenetics. We first find that Protein Kinase C-delta (PKCd) selectively labels thalamocortical (TC) cells concentrated in PT but largely absent from neighboring PVT. We show that TC cells in PT project to the infralimbic region (IL) of the medial prefrontal cortex (mPFC), where they contact and drive L2/3 pyramidal cells. In return, we find that IL mPFC primarily projects to PT over nearby PVT, making connections onto reciprocally connected TC cells. However, these cortical inputs are even stronger onto thalamostriatal (TS) and thalamoamygdala (TA) cells, allowing the mPFC to broadcast to the subcortex. Together, our findings help to parcellate aMT, highlight PT as a distinct thalamic nucleus, establish reciprocal connectivity between PT and IL mPFC, and show cortico-thalamic throughput to the subcortex.

The benefits of routines for daily functioning are widely acknowledged, yet, despite their apparent importance, methods for quantifying routine maintenance and the causes of their disruption remain lacking. Here, we propose a novel means of defining and quantifying routines (transition entropy). Using the transition entropy, we show that routines can be robustly elicited on tasks that require searching through a grid of squares for a hidden target. Over two experiments (N=100 each), we show that use of routines---as quantified by transition entropy---is robustly perturbed by frequent switches between search grids, as locations specific to the currently irrelevant grid become competitive for selection. Using a normative model that tracks task dynamics, we show that disruption to routines can be attributed to reduced sensitivity to the odds of success for completing a task. This suggests that routine maintenance may be disrupted by over-sensitivity to a lack of reward early in routine performance, or increased expectations regarding the utility of pursuing other tasks.

Remembering events in the correct order, and generating ordered sequences of actions, are fundamental abilities across species. Behavioral studies, and theoretical work, raise the possibility that the brain represents serial order by a domain-general neural code, following the principle of Competitive Queuing. However, direct neurophysiological evidence for Competitive Queuing exists only in the motor domain. When humans and non-human primates prepare for a series of movements, several of the upcoming movements are represented in parallel, with their representational strength reflecting ordinal position in the sequence. We test the generalizability of this so-called primacy gradient across motor sequences and memorized auditory sequences. Using a multivariate decoding approach, Experiment 1 replicated the presence of a Competitive Queuing primacy gradient in magnetoencephalography (MEG) data of young healthy adults (n = 23) when they prepared a sequence of finger movements from memory. Importantly, we observed a similar primacy gradient when participants anticipated a sequence of tones they had learned before, in the absence of any movement. In Experiment 2 (n = 23; naive cohort), we rule out the possibility that this primacy gradient in auditory memory is explained by any learnt association between tones and movements, or by MEG signal fluctuations that are unrelated to discrete sequential events. In sum, we find a similar neural signature of serial order coding when humans prepare a sequence of movements, and when they anticipate a sequence of sounds. This lends support to the generalizability of Competitive Queuing.

Working memory (WM) provides a flexible but capacity-limited workspace for maintaining information over short intervals, whereas long-term memory (LTM) serves as a vast and enduring repository for preserving information over extended periods. Decades of research suggest that they are two distinct yet connected systems that together enable adaptive behavior. The link between WM and LTM may not be straightforward, however, as recent evidence has shown that activation-dependent competition among items in WM can weaken their representations in LTM. In the current study, we examined how dynamic competition among items for limited WM resources affects their retention in LTM. We induced competition between items by manipulating temporal expectations in a WM task with either a short (1 s) or a long (4 s) memory delay. Human participants (N = 20) initially prioritized items expected to be tested early, but shifted their priority to items expected to be tested later when the early test did not occur. Using electroencephalography (EEG) and multivariate pattern analysis (MVPA), we tracked the dynamic fluctuations in WM contents based on expected task relevance across the delay window. We linked these temporal profiles during WM with the long-term recognition performance of each item and found that forgetting was associated with a marked decrease in neural evidence for items deemed no longer relevant during the later delay period. These results demonstrate that WM representations fluctuate with temporal expectations and that the de-prioritization of items during WM maintenance is what drives their long-term forgetting.

The ventrolateral prefrontal cortex (vlPFC) is well known for its involvement in high-level functions such as cognitive control and language. However, vlPFC's role in visual processing is less clear. Here, we investigated how neuronal ensembles in the vlPFC dynamically encode different types of visual information. Using chronic recording of spiking activity, we investigated vlPFC's representational geometry in a macaque monkey passively viewing a large set of naturalistic images, and compared this to representations in deep neural networks (DNNs). We found that the vlPFC processes visual information in two stages. First, an "early" response from 50 to 90 ms after stimulus onset encodes the low spatial frequency component of an image. It contains sufficient information to form a coarse estimate of the position and category of a salient object. Then, from 100 ms on, the representational geometry changes and contains much richer information. This late period contains non-categorical information typically present in conscious experiences such as the orientation of a face and natural scenes in the background. The late window also enables sub-category identification, which is boosted by the low spatial category prior. These results suggest that the vlPFC has a dual role in natural vision: first forming fast low-spatial-frequency-based priors shaping feed-forward visual processing, and subsequently maintaining a detailed and rich representation of a visual scene.

Adolescent brain maturation involves structural changes effecting a shift in excitation/inhibition (E/I) balance, yet the functional implications of these changes remain unclear. One implication is a shift with respect to criticality. Adult brains, at rest, operate near a critical phase transition, at the boundary between an active, excitation-dominant phase, and an absorbing, inhibition-dominant phase. Special properties emerge when neural systems are balanced at criticality, including maximal susceptibility to perturbation, dynamic range, and information transmission. Thus, a clear picture of how adolescent brain maturation affects E/I balance and criticality is needed to understand how maturational processes shape cognition. Here, we leverage the dynamical properties of longitudinally-collected resting-state EEG recordings during N = 310 sessions from 169 healthy human participants ranging in age from 10 to 33 years old to quantify E/I and proximity to criticality. We find that adult brains operate closer to criticality, including spectrally-widespread increases in long-range temporal correlations and amplitude bistability. We also find band-specific changes in excitation versus inhibition whereby the mechanisms driving low-frequency ({theta} to ) oscillations shift towards lower E/I -- possibly because of increasing inhibition -- while the mechanisms driving high-frequency ({gamma}) oscillations shift towards higher E/I, possibly because of decreasing inhibition. Opening eyes shifts brains towards lower E/I, and these state-dependent shifts are larger in adults. We simulate developmental effects with a neural mass model of coupled excitatory and inhibitory neurons providing a parsimonious account of how changes in brain dynamics could arise as a function of changes in local connectivity of excitatory and inhibitory neurons. Results indicate developmental movement towards criticality, and greater adaptability to state-specific demands, through adolescence to adulthood, reflecting changes in E/I balance with implications for cognitive development.

Spontaneous helping behaviors such as allogrooming are vital for survival in social species, yet their underlying neural mechanisms remain largely unknown. Although oxytocin (OXT) is known to modulate allogrooming, the precise neural circuits, molecular pathways, and sensory drivers remain unclear. Here, using a social emergency paradigm in mice, we show that observer mice selectively allogroom distressed, anesthetized conspecifics, a behavior that is guided by main olfactory system cues and mitigates the demonstrator anxiety. We identify an oxytocinergic circuit from the paraventricular hypothalamus to the medial olfactory tubercle (PVNOXT-mOT) that is necessary and sufficient for this helping behavior. In vivo fiber photometry reveals that PVNOXT-mOT activity and OXT release are temporally locked to allogrooming initiation. This behavioral effect requires oxytocin receptor (OXTR) signaling specifically on mOT dopamine D1 receptor-expressing neurons, where OXTRs suppress neuronal excitability via G protein-gated inwardly rectifying K+ (GIRK) channels. Disruption of this inhibitory mechanism induces neuronal hyperexcitability and impairs allogrooming, a deficit rescued by restoring GIRK function. These findings define a PVNOXT-mOT circuit for prosocial helping, revealing an oxytocinergic pathway with potential therapeutic relevance for neuropsychiatric disorders characterized by social deficits.

Working memory requires the stable maintenance of neural representations across temporal gaps, yet the circuit mechanisms that generate and stabilize persistent activity remain unsolved. Prevailing models emphasize recurrent excitation as the principal substrate of persistence, but how inhibitory and modulatory interactions shape the stability of temporal dynamics is unclear. Here, using trace conditioning in Drosophila, a working memory-dependent form of associative learning, we identify reciprocal inhibition as a circuit mechanism for sustaining persistent activity. In trace conditioning, a trace interval separates the conditioned and unconditioned stimuli, requiring maintenance of a neural representation across the trace interval, to support learning. Combining virtual-reality behavior, targeted neurogenetic perturbations, in vivo two-photon calcium imaging, and real-time neurotransmitter measurements, we uncover a reciprocal inhibitory microcircuit within the ellipsoid body that is selectively engaged during trace, but not delay (overlapping CS-US), conditioning. During the trace interval, ER2/4m neurons exhibit sustained activity, while reciprocally connected ER3/4d neurons show progressively strengthened suppression, forming a dynamically stabilized inhibitory loop. Disrupting GABA synthesis or reception within this circuit abolishes persistent activity and impairs trace learning, demonstrating the causal requirement for reciprocal inhibition in working memory maintenance. We further show that glutamatergic and nitric oxide signaling enhance inhibitory efficacy during the trace interval. In vivo neurotransmitter imaging reveals temporally structured dynamics in which glutamatergic signaling precedes and amplifies sustained GABAergic inhibition, consistent with modulatory stabilization of circuit persistence. Together, these findings identify reciprocal inhibition, reinforced by modulatory signaling, as a core circuit mechanism for dynamically stabilizing persistent neural representations. Our results challenge excitation-centric models of working memory and establish inhibitory-modulatory loops as a fundamental substrate for maintaining memory traces across time.

Breathing is controlled by a distributed brainstem network that includes multiple catecholaminergic nuclei. The locus coeruleus (LC), the brain's primary source of noradrenaline (NA), projects to several respiratory centers, including the Kolliker-Fuse (KF) nucleus in the pons. While LC neurons are predominantly noradrenergic (NAergic), many co-release glutamate, which may contribute to the state-dependent modulation of breathing, particularly during opioid exposure. Here, we examined how opioids affect NAergic and glutamatergic signaling in the LC-KF circuit using optogenetics and whole-cell patch clamp recordings in mouse brain slices. Optogenetic activation of LC terminals evoked glutamatergic excitatory postsynaptic currents (EPSCs) in KF neurons that were presynaptically inhibited by the opioid receptor agonist Met-enkephalin. Additionally, ~36% of glutamate-responsive KF neurons exhibited postsynaptic opioid inhibition via GIRK currents, while KF neurons receiving excitatory NAergic input showed minimal opioid sensitivity. To assess the behavioral role of glutamate release from all catecholaminergic neurons, we compared breathing in awake VGluT2fl/fl::TH-Cre mice (lacking VGluT2 in tyrosine hydroxylase-positive neurons) to control littermates and TH-Cre hemizygous mice using whole-body plethysmography. The conditional VGluT2 knockout mice exhibited prolonged inspiratory duration, increased tidal volume, and reduced respiratory rate during baseline breathing, with state-dependent differences emerging during hypercapnia. Systemic morphine administration diminished these genotype differences, and machine learning analysis using dynamic time warping confirmed that genotype-specific breathing patterns were distinguishable at baseline, but not after morphine. These findings demonstrate that glutamate co-release from catecholaminergic neurons modulates respiratory patterning in a state-dependent manner and is selectively vulnerable to opioid inhibition.

Play is a fundamental aspect of childhood and plays a crucial role in the development of creativity, yet its neural mechanisms remain poorly understood. We tested the hypothesis that more frequent play is associated with stronger functional integration among the default mode network (DMN), executive control network (CN), and salience network (SAL), as these cortical networks have been implicated in creativity in adults. In a preregistered study of infants and toddlers (Study 1; N = 143, 10 months to 3 years, 67 boys, Baby Connectome Project), parent-reported play and imitation behaviors increased sharply from 1 to 2 years, and were associated with stronger within-DMN connectivity and DMN-CN coupling, controlling for age, sex, and head motion. In middle childhood (Study 2; N = 108, ages 4 to 11 years, 52 boys), parent-reported play frequency declined with age, as did cross-network coupling involving SAL. However, children who engaged more frequently in play showed higher DMN-SAL and CN-SAL connectivity. Finally, in a quasi-experimental comparison (Study 3; N = 45; ages 4 to 12 years, 20 boys), children enrolled in a curriculum that includes guided play (Montessori) showed higher DMN-SAL and DMN-CN connectivity than peers in traditional schools, suggesting that pedagogies that center child-led exploration might enable protracted brain network integration. Across these three studies, play was consistently associated with greater integration among DMN, SAL, and CN, a pattern previously linked to creativity in adults. Our findings offer a potential mechanism linking childhood play to later creativity through its role in supporting brain integration during development.

Bidirectional interfaces combined with neural decoding algorithms are essential for closed-loop (CL) neuromodulation, enabling simultaneous neural monitoring and responsive optogenetic stimulation. However, implementing these capabilities in compact wireless headstages for freely moving animals remains challenging, as most existing platforms rely on tethered setups and external processors to execute computationally intensive decoders. This work presents the design and optimization of a neural decoder integrated into a bidirectional wireless system for CL optogenetic experiments in rodents. The proposed platform combines 32-channel electrophysiological recording with neuromorphic feature extraction, dimensionality reduction, and a nonlinear support vector machine (NL-SVM) decoder implemented on a resource-constrained Spartan-6 FPGA. Temporal dynamics are captured using spike-count features and leaky integrators, while principal component analysis (PCA) reduces the feature space to six components, enabling sub-millisecond inference with minimal memory and power requirements. Model size is further reduced using k-means clustering during training to limit the number of support vectors. Decoder performance was validated using datasets from non-human primate and rat motor cortex recordings. The proposed decoder achieved accuracy comparable to convolutional neural networks (R2 = 0.85 vs. 0.87) and outperformed Wiener filters (R2 = 0.81) while requiring significantly fewer computational resources. The full system was further demonstrated in vivo through wireless closed-loop optogenetic stimulation in rats, achieving a variance accounted for (VAF) of 0.9148. Overall, this work introduces a versatile, fully self-contained, and resource-efficient platform for real-time untethered closed-loop neuroscience experiments

Prediction is foundational to theories of perceptual processing and learning, in both neuroscience and AI. However, it remains unclear whether prediction occurs routinely during naturalistic perception, and what level of abstraction the brain predicts. Here, we address both questions by analysing 7T fMRI recordings of humans viewing 73,000 natural images. We use deep generative models to quantify spatial predictability at multiple levels of abstraction, and relate these to retinotopically precise responses across V1-V4, while rigorously controlling for local image features. This reveals that, even during natural scene viewing, responses throughout visual cortex are modulated by spatial predictability, with more predictable inputs evoking weaker responses. In central vision, we observe a hierarchy of predictions that parallels the feature-encoding gradient: V1 is most sensitive to low-level unpredictability, with later areas progressively sensitive to higher-level unpredictability -- diverging from recent proposals, in both neuroscience and AI, that prediction operates primarily at higher levels of abstraction. At higher eccentricities, prediction effects are amplified but even V1 is tuned to high-level predictability, consistent with these prior accounts. Together, these results suggest that the visual system implements distinct prediction regimes across the visual field, thereby reconciling conflicting accounts of what visual cortex predicts.

Nociception is an essential response for organisms to avoid potential harm and promote survival. Its molecular determinants are largely conserved across Eumetazoa. TRPV receptors are polymodal ion channels exhibiting selective peripheral expression and functional coupling that underpins nociception and pain modulation in complex organisms. However, the execution of protective behaviours triggered by TRPVs is also found in species with a simpler nervous organisation, thus encouraging their investigation in invertebrate model organisms to increase understanding of animal nociception. Cephalopods represent an interesting invertebrate phylum with respect to the evolution of the nervous system, whose complexity suggests it might support pain-like states that exist in vertebrates. This possibility is reflected by the inclusion of cephalopods in the UK and EU animal welfare legislations. Despite this, there is poor characterisation of cephalopod molecular nociceptors. For this reason, we used in silico analysis to identify two TRPV channels in Octopus vulgaris genome (Ovtrpv1 and Ovtrpv2). We validated the putative transcript sequences and highlighted prevalent expression in sensory tissues. We investigated the functional competence of these TRPVs by heterologously expressing Ovtrpv1 and Ovtrpv2 cDNA into Caenorhabditis elegans null mutants of the orthologous genes, ocr-2 and osm-9 respectively. Ovtrpvs successfully rescued the aversive response to chemical and mechanical noxious stimuli in the C. elegans mutants, suggesting these receptors are polymodal nociceptors. Additionally, complementary investigation using Xenopus laevis oocytes showed Ovtrpv1 and Ovtrpv2 form an active heteromeric channel gated by nicotinamide. This study highlights Ovtrpvs as an important route to better understand nociceptive detection in cephalopods.

Human-dog interaction is widely used to alleviate stress, yet the accompanying cortical and autonomic dynamics during acute stress and recovery remain incompletely characterized. In this study, 70 adult dog owners completed a standardized stress protocol while prefrontal cortex activity was continuously monitored with functional near-infrared spectroscopy (fNIRS), alongside subjective stress and salivary cortisol measures. Participants then underwent a recovery phase involving interaction with a companion dog, manipulating contact type (direct in-person vs. indirect video conferencing), and familiarity (own vs. unfamiliar dog). Stress responses were quantified through heart rate (HR), heart rate variability (HRV), low- and high-frequency spectral power (LF, HF, and LF/HF), and prefrontal functional connectivity (FC) based on maximum cross-correlation coefficients between fNIRS channels. As expected, HR, HRV-derived indices, and FC increased from baseline to the stress phase, confirming robust engagement of autonomic and prefrontal networks. During the recovery phase, all dog interaction conditions demonstrated reductions in HR, LF/HF ratio, and FC toward or below baseline, consistent with physiological and neural stress recovery; direct interaction was associated with particularly pronounced parasympathetic enhancement and a drop in FC that fell significantly below baseline in some cases. Across groups, HRV, LF/HF, and FC were the most consistent predictors of subjective stress ratings, whereas associations with cortisol were limited. These findings suggest that human-dog interaction promotes coordinated autonomic and prefrontal recovery from acute stress, and that fNIRS-derived metrics might provide a marker of stress modulation that can distinguish high-cognitive load and low-cognitive demand states beyond traditional stress indices.

Adaptive embodied behavior involves transforming structured knowledge about the relationship between environment and action into motor signals, but how these transformations are coordinated across brain networks remain unknown. Participants learned associations between visual cues and isometric exertions that varied in force and duration, forming a two-dimensional cognitive map of a force-time space. During behavior, this force-time space was expressed in several cortical regions using grid-like coding schemes, indicating sensorimotor cognitive maps. Importantly, while mnemonic regions such as the entorhinal cortex maintained an unwarped, task-relevant representation, the primary motor cortex encoded a force-time space distorted by perceived effort during motor execution. Dynamic causal modeling showed inhibitory motor-to-mnemonic coupling that predicted the transformation of effort-weighted motor signals into sensorimotor maps. Furthermore, individual differences in learning and navigating the force-time space independently shaped mnemonic map geometry and perceived effort. These findings demonstrate that sensorimotor cognitive maps emerge from dynamic interactions between motor and mnemonic systems and are shaped by individual differences during the learning and execution of movement.

Arousal and valence are fundamental dimensions of affective experience signifying levels of activation and pleasantness, respectively. These dimensions play a crucial role in shaping emotional responses and behaviors, with significant implications for psychopathology. Previous machine learning studies had some success decoding these states from brain activation patterns observed during task-based functional magnetic resonance imaging (fMRI), but the results have varied across studies. Moreover, prior studies have often been limited by small sample sizes, weak decoding performance, and non-whole-brain analyses, leaving the neural representations of arousal and valence largely unresolved. Here we successfully decoded arousal and valence from whole-brain task-fMRI data collected from 132 participants during exposure to 300 unique emotional stimuli, including 150 movie clips and 150 text scenarios that reliably induced a wide range of arousal and valence states. Mass univariate general linear models identified block-level activation (emotion stimuli > washout) from all gray matter voxels. Multivariate regression analysis predicted arousal and valence ratings based on these gray matter activations. Patterns in the fMRI data underlying arousal and valence were robust, as they were successfully decoded across both induction modalities using five different linear multivariate regression models. Although significant, decoding from scenarios was less successful than from movies, likely due to their more imaginative nature. In particular, decoding arousal from scenarios only showed low predictive utility. Representations of arousal and valence were widespread throughout the brain, and we reveal cerebellar and brainstem contributions that have largely been absent in past fMRI decoding studies. These findings clarify the distributed neural basis of arousal and valence and provide a foundation for future clinical research on the role of these constructs in affective dysregulation.

Compared with model-based and phenomenological descriptions of the spatiotemporal dynamics of resting-brain activity, statistical characterizations of resting-state fMRI (rs-fMRI) data remain relatively underexplored. Some sophisticated analysis techniques, such as Mapper-based topological data analysis (TDA) and innovation-driven coactivation pattern analysis (iCAP), can distinguish real data from phase-randomized (PR) surrogates, suggesting that rs-fMRI data are not as simple as stationary Gaussian processes. However, the exact statistical properties that distinguish real rs-fMRI data from PR surrogates have not yet been determined. In this study, we conducted system identification analysis and surrogate data analysis to specify key statistical properties that allow TDA and iCAP to discriminate real rs-fMRI data from PR surrogates. We first analyzed rs-fMRI data concatenated across scans using autoregressive (AR) modeling and found that the scan-concatenated rs-fMRI data were weakly non-Gaussian. However, non-Gaussianity alone was insufficient to reproduce realistic TDA and iCAP results because of non-stationarity across scans. AR modeling of single-scan data revealed that rs-fMRI data were statistically indistinguishable from a Gaussian distribution within a single scan, although TDA and iCAP results still differed between the real data and PR surrogates. A new surrogate dataset designed to preserve non-stationarity successfully reproduced realistic TDA and iCAP results, suggesting that TDA and iCAP likely capture the non-stationarity of rs-fMRI data to distinguish it from PR surrogates. Together, these results indicate approximate Gaussianity and non-stationarity in rs-fMRI data, providing a data-driven and statistical characterization of resting-state brain activity that can serve as a quantitative reference for whole brain simulations and generative models.

High-fat diet (HFD) feeding disrupts systemic glucose metabolism, yet the underlying neural mechanisms remain incompletely understood. Here, we demonstrate that glucose-excited (GE) neurons in the ventromedial hypothalamus (VMHGE) are essential for acute glucose regulation and that their function is compromised by HFD via structural synaptic remodeling. We found that HFD feeding suppresses canonical Wnt signaling and downregulates R-spondin 1 (RSPO1), a Wnt enhancer, in the VMH. This Wnt inhibition leads to a loss of dendritic spines and blunted glucose-sensing in VMHGE neurons. Conversely, central administration of RSPO1 restores Wnt/{beta}-catenin signaling, promotes synaptogenesis, and recovers neuronal glucose responsiveness. Consequently, RSPO1 treatment ameliorates HFD-induced glucose intolerance by enhancing peripheral glucose utilization. These findings identify the RSPO1-Wnt signaling axis as a critical regulator of VMH neuronal plasticity and metabolic homeostasis, providing a mechanistic link between diet-induced synaptic pathology and systemic metabolic dysfunction.

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AbstractA fundamental paradigm in neuroscience is that neurons represent the world through fixed tuning functions, with stable mappings from stimulus features to firing rates1. Here, we report that tuning can instead shift rapidly and coherently across a neural population, enabling a dynamic transition from detecting a broad category to discriminating individual exemplars. We set out to address a longstanding debate in visual neuroscience about whether the inferotemporal cortex uses a specialized code for specific object categories or a general-purpose code that applies to all objects. We found that face-selective cells in macaque inferotemporal cortex initially adopted a general code optimized for face detection. However, after a rapid concerted population event lasting less than 20 ms, the neural code transformed into a face-specific one, with two striking features: response gradients to principal detection-related dimensions reversed direction, and new tuning emerged for multiple higher-dimensional features that support fine face discrimination. These dynamics in face patches were specific to face stimuli and did not occur in response to non-face objects. Thus, for faces, face cells transition from detection to discrimination by switching from an object-general code to a face-specific one. More broadly, our findings indicate that there is a previously unknown mechanism for neural representation: concerted stimulus-dependent switching of the neural code used by a cortical area.

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AbstractEffectively communicating worst-case projections of global future climate—hereinafter referred to as worst-case climate outcomes—is essential for risk assessment and developing robust adaptation strategies to global warming1–7. Yet, current approaches for identifying spatially consistent climate outcomes are limited, with worst-case global climates typically communicated via the average of climate model projections at high global warming levels, such as 3 °C or 4 °C above the preindustrial era8,9. Here we show that extreme global climate outcomes may occur even under moderate 2 °C warming for several sectors. For droughts in global key breadbasket regions, precipitation extremes over highly populated areas and fire weather extremes across forests, global climatic impact-drivers at 2 °C of global warming may turn out to be much more extreme than model-averaged projections at 3 °C or 4 °C warming. We derive these results by identifying sector-specific, spatially consistent potential high- and low-impact global climate outcomes through spatially averaging projected sector-relevant climatic impact-drivers across key global regions. Our approach can easily be adapted to a wide range of sectors to support the improvement of sector-specific climate risk assessment and to inform climate policy. As global warming approaches 1.5 °C (ref.10), these findings underscore the urgency of rapid mitigation to limit warming well below 2 °C, as even a 2 °C world may entail severe impacts.

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AbstractThe conditions under which magma accumulates and is stored are fundamental to unravelling the processes of crust formation, planetary differentiation, geothermal heat recharge and volcanic eruptions. Storage pressure, temperature and volatile saturation are typically inferred from erupted volcanic products. However, changes during kilometres of magma ascent induce disequilibrium crystallization and vesiculation, and inverting back to storage conditions comes with unresolvable uncertainties. Here we explore opportunities arising from magma drilling at Krafla volcano, Iceland, to reconstruct real, in situ magmatic conditions. The findings show that, over the approximately 5 min in which the magma is quenched, vapour bubbles consisting of H2O and CO2exsolve, grow and resorb, but the changes can be accounted for by multiparametric inversion (for chemistry, vesicularity and vitrification), and that the magma was stored under volatile-saturated lithostatic conditions, unlike previous assertions of lower vapour pressures based on classic methods1. These new disequilibrium simulations reconcile the glass chemistry with conceptual models of magma storage and provide us with the unique pairing of precisely measured depth and volatile pressure on a single magma body and thus a robust method to improve our understanding of magma storage conditions and evolution.

AbstractLarge-scale gradients of functional connectivity between brain areas organize the human neocortex, linking brain topography to the texture of cognition1,2. In adults, three dominant axes—sensory–association, visual–somatosensory and modulation–representation—run, respectively, from primary sensory to transmodal association areas, from visual to body-centred systems and from control and attention networks to default mode and sensory areas1–4. These gradients provide a compact description of large-scale cortical hierarchies that underlie distinct modes of information processing. However, how these gradients and their multiscale biological and cognitive correlates evolve across the lifespan is unknown. Here we establish a continuous normative reference of functional organization from birth to 100 years of age, revealing complex, nonlinear developmental trajectories. Gradient architecture is anchored by primary sensory systems in infancy, differentiates along association and control axes during childhood and adolescence and gradually dedifferentiates during ageing. The importance of this functional architecture is corroborated by biology and behaviour: gradient metrics predict cognitive performance across development; structure–function coupling varies by axis and age; and distinct transcriptomic signatures are strongest early in life and weaken with age, consistent with a transient genetic scaffold for gradient architecture. Our lifespan gradients unify diverse research into developmental brain connectivity and provide a shared multimodal reference for future studies.

AbstractParasitic infections modulate both immune and sensory responses, but how these systems collaborate to elicit protective behaviours remains incompletely understood. The gut epithelium contains specialized sensory cells that detect pathogens and irritants. These include cholinergic tuft cells, which sense parasites and initiate type 2 immune responses1–3, as well as serotonergic enterochromaffin (EC) cells, which detect irritants and communicate with afferent nerve fibres to transmit nociceptive signals4–6. Here we show that paracrine signalling between these cells constitutes a mechanism for neuro–immune interaction and gut–brain communication. We find that tuft cells use two distinct mechanisms of acetylcholine (ACh) release despite lacking synaptic vesicles and excitable membranes. These include acute release in response to parasite-derived metabolites, followed by constitutive ‘leak-like’ release, which occurs with type 2 inflammation. Although both mechanisms can activate muscarinic receptors on crypt-residing EC cells, only the sustained mode of ACh release elicits levels of serotonin sufficient to stimulate vagal afferent neurons that suppress food intake. This two-phase paracrine signalling mechanism explains how parasitic infection progresses from an initial asymptomatic phase to symptomatic established disease, in which type 2 immune and sensory signalling pathways within the gut–brain axis collaborate to evoke protective behaviours.

AbstractMany viruses have adapted to persist in infected humans for life1,2. Variable host control of their ongoing abundance (viral load) can lead to clearance or disease3–5. Here we analysed the viral DNA load of 31 common viruses in human blood and saliva using whole-genome sequencing data from UK Biobank (n= 490,401), All of Us (n= 414,817) and Simons Foundation Powering Autism Research for Knowledge (SPARK;n= 12,519). Viral DNA load varied markedly with age, time of day and season; most viruses were also present at greater abundance in men than in women. Human genetic variation at dozens of loci associated with DNA load of seven viruses: Epstein–Barr virus (EBV, 45 loci), human herpesvirus (HHV)-7 (37 loci), HHV-6B, Merkel cell polyomavirus and three anelloviruses. Variation at the major histocompatibility complex (MHC) locus generated the strongest associations (P= 5.8 × 10–9to 2.5 × 10–1459), which were specific to each virus. TheHLA-B*08:01allele also exhibited a host–virus genetic interaction with EBV subtype (P= 7.4 × 10–70). Other human genetic effects implicated genes encoding proteins that process peptides for antigen presentation, such asERAP1(HHV-7,P= 2.7 × 10–78) andERAP2(EBV,P= 4.6 × 10–111). Mendelian randomization analyses supported a strong causal effect of EBV DNA load on increased risk of Hodgkin’s lymphoma (P= 1.8 × 10–3), but not multiple sclerosis (P= 0.52). This suggests that higher chronic EBV load increases lymphoma risk, whereas associations of EBV infection with autoimmune conditions reflect host immune responses to particular viral epitopes.

AbstractThe earliest morphologically identifiable dogs are from Europe and date to at least 14,000 years ago1–5, although early remains are also found in other regions. The origin of early dogs in Europe, and their relationships to other dogs, has remained elusive in the absence of genome-wide data. Similarly, although dogs were the only domestic animal to predate agriculture, little is known about how the arrival of Neolithic farmers from Southwest Asia affected the dogs living with European Mesolithic hunter-gatherers. Here we analysed 216 canid remains, including 181 from Palaeolithic and Mesolithic Europe. We developed a genome-wide capture approach that enriched endogenous DNA by 10–100-fold and could distinguish dog from wolf ancestry for 141 of 216 remains. The oldest dog data that we recovered are from a 14,200-year-old dog from the Kesslerloch site in Switzerland, and we find that it shares ancestry with later worldwide dogs—inconsistent with the hypothesis that European Upper Palaeolithic dogs derived wholly from a separate domestication process. The Kesslerloch dog already displays more affinity to Mesolithic, Neolithic and present-day European dogs than to Asian dogs, demonstrating that dog genetic diversification had started well before 14,200 years ago. We find a Neolithic influx of Southwest Asian ancestry into Europe, but this seems to have been of smaller magnitude than in humans, suggesting that Mesolithic dogs contributed substantially to Neolithic, and, ultimately, probably also modern, European dogs.

AbstractCarbon capture and storage (CCS) has the potential to help nations meet their Paris Agreement CO2reduction commitments1,2. The ability to capture CO2within mafic and ultramafic rocks through mineralization of carbon is an example of such a CCS technology3,4, but large-scale deployment has yet to be achieved5,6. Each geologic environment in the Earth’s crust requires a distinct carbon storage solution. Whereas some regions of the subsurface contain saline aquifers and sedimentary traps suitable for traditional carbon storage through the injection of high-pressure, dense CO2below impermeable caprocks, other regions may lack caprocks5–9. In these regions, carbon storage is possible through the mineralization of injected water-dissolved CO2forming stable carbonate minerals through its reactions with reactive silicate rocks and minerals6,10,11. A notable challenge to applying this process at scale is that it can require 20–50 times or more water than the mass of CO2stored12. Here we report on an industrial-scale pilot project designed to find a carbon disposal solution for western Saudi Arabia. This arid region has large point-source CO2emitters, including petroleum refining and desalination facilities, but lacks saline aquifers and sedimentary traps13–17. We find that a CO2injection approach based on the recirculation of subsurface fluids can eliminate the need for external water. Our results demonstrate the feasibility of carbon mineral storage in regions in which access to water resources may be limited.

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AbstractArchaeological evidence suggests that dogs diverged from wolves during the Palaeolithic, more than 15,000 years ago1–7. The earliest unequivocal genetic evidence, however, is associated with dog remains from Mesolithic archaeological contexts approximately 10,900 years ago8,9. Here we generate both nuclear and mitochondrial genomes from canid remains at Pınarbaşı in Türkiye (15,800 years ago)10and Gough’s Cave in the UK (14,300 years ago)11, as well as from dogs excavated from two Mesolithic sites in Serbia (Padina between 11,500–7,900 years ago and Vlasac 8,900 years ago)12,13. Our analyses indicate that a genetically homogeneous dog population was already widely distributed across Europe and Anatolia during the Late Upper Palaeolithic (by at least 14,300 years ago). This finding suggests that dogs were exchanged among genetically and culturally distinct western Eurasian Late Palaeolithic human populations, namely the Magdalenian, Epigravettian and Anatolian hunter-gatherers10,14–16. Last, we identify a major influx of eastern Eurasian dog ancestry during the Mesolithic, concomitant with the movement of eastern hunter-gatherer populations into Europe14, which led to the establishment of the primary ancestry characteristics that define European dog populations today.

AbstractThermosensitive transient receptor potential (TRP) ion channels enable somatosensory nerve fibres to detect changes in our thermal environment over a wide physiologic range1–3. In mammals, the menthol receptor, TRPM8, is activated by temperatures below approximately 26 °C and is essential for the perception of cold or chemical cooling agents4–6. A fascinating, yet still unachieved goal is to elucidate mechanisms, both structural and thermodynamic, whereby TRPM8 or other thermosensitive channels are gated by changes in ambient temperature. Recent studies using cryogenic electron microscopy have attempted to address this challenging question but are limited by difficulties in visualizing temperature-evoked conformational sub-states or assessing the energetic landscape governing gating transitions7,8. Here we close this gap by combining cryogenic electron microscopy with hydrogen–deuterium exchange mass spectrometry to elucidate a mechanism for cold-evoked activation of TRPM8. First, we visualize TRPM8 channels in cellular membranes, where bona fide menthol- and cold-evoked open states are captured. We also identify a new ‘semi-swapped’ architecture in which interdigitation of channel sub-units is rearranged substantially following repositioning of the S6 transmembrane helix and elements of the pore region. We then use hydrogen–deuterium exchange mass spectrometry to pinpoint the pore and TRP helices as the regions exhibiting the greatest stimulus-evoked energetic changes that drive channel gating. Specifically, cold-evoked stabilization of the outer pore region repositions the pore lining S6 transmembrane helix while enabling binding of a regulatory lipid to stabilize the open channel. Structural mechanisms associated with activation are validated by comparison of human TRPM8 with the menthol-sensitive but relatively cold-insensitive avian orthologue. We propose a free energy landscape and conformational pathway whereby cold or cooling agents activate this thermosensory receptor.

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AbstractCRISPR–Cas9 is a powerful genome-editing tool1, but genome-wide off-target activity can hinder therapeutic applications. Negative supercoiling ((−)SC) has been implicated in off-target activity, but a molecular-level understanding is lacking. Here, using (−)SC DNA minicircles, we observe supercoiling-driven structural defects in the DNA that are resolved by Cas9 binding. Cryo-electron microscopy structures of Cas9 bound in both the on-target and off-target configurations highlight that the Cas9 HNH domain is poised in a more catalytically competent conformation. New DNA–RNA mismatch geometries are accommodated across the protospacer and structural plasticity in the protospacer adjacent motif distal region of the protospacer is topology dependent. Together, our study reveals the molecular basis for (−)SC-induced Cas9 targeting and provides a framework for the design of next-generation high-fidelity CRISPR effectors with topological context.

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AbstractThe automation of science is a long-standing ambition in artificial intelligence (AI) research1,2. Although the community has made substantial progress in automating individual components of the scientific process, a system that autonomously navigates the entire research life cycle—from conception to publication—has remained out of reach. Here we present a pipeline for automating the entire scientific process end to end. We present The AI Scientist, which creates research ideas, writes code, runs experiments, plots and analyses data, writes the entire scientific manuscript, and performs its own peer review. Its ideas, execution and presentation are of sufficient quality that the manuscript generated by this AI system passed the first round of peer review for a workshop of a top-tier machine learning conference. The workshop had an acceptance rate of 70%. Our system leverages modern foundation models3–5within a complex agentic system. We evaluate The AI Scientist in two settings: a focused mode using human-provided code templates as an initial scaffold for conducting research on a specific topic and a template-free, open-ended mode that leverages agentic search for wider scientific exploration6,7. Both settings produce diverse ideas and automatically test, report on and evaluate them. This achievement demonstrates the growing capacity of AI for making scientific contributions and signifies a potential paradigm shift in how research is conducted. As with any impactful new technology, there could be important risks, including taxing overwhelmed review systems and adding noise to the scientific literature. However, if developed responsibly, such autonomous systems could greatly accelerate scientific discovery.

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AbstractRestricting amino acids from tumours is an emerging therapeutic strategy with substantial promise1. Although typically considered an intracellular antioxidant with tumour-promoting capabilities2, glutathione (GSH), as a tripeptide of cysteine, glutamate and glycine, can be catabolized to release amino acids. The extent to which GSH-derived amino acids are essential to cancers is unclear. Here we show that depletion of intracellular GSH does not alter tumour growth and extracellular GSH is highly abundant in the tumour microenvironment, highlighting the potential importance of GSH outside tumours. Supplementation with GSH rescues cancer cell survival and growth in cystine-deficient conditions, and this rescue depends on the catabolic activity of γ-glutamyltransferases. Finally, pharmacological targeting of the activity of γ-glutamyltransferases prevents the breakdown of circulating GSH, reduces tumour cysteine levels and slows tumour growth. Our findings indicate a non-canonical role for GSH in supporting tumours by acting as a reservoir of amino acids. Depriving tumours of extracellular GSH or inhibiting its breakdown is potentially a therapeutically tractable approach for patients with cancer. Furthermore, these findings change our view of GSH and how amino acids, including cysteine, are supplied to cells.

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AbstractThe characteristic tides of coastal rivers influence the distribution of estuarine and wetland habitats1, the extent of fresh drinking water2, carbon and nitrogen cycles3,4, and sediment export to the ocean5. Despite the importance of riverine tides, their range is generally unknown over most of the world’s rivers because the propagation of tidal waves in channels is complex, gauging stations are scarce and conventional nadir altimetry6has historically been too sparse for use in rivers. Here we use data from the recently launched Surface Water and Ocean Topography (SWOT) satellite to quantify tidal dynamics across 3,172 coastal rivers. Capitalizing on the wide swath coverage of SWOT, we show that over 165,000 river kilometres are influenced by tides. More than 700 million people live near and depend on these coastal transition zones. River size, slope and tidal range at the river mouth influence the extent to which tides propagate within river systems. Natural and artificial obstacles, such as dams, limit tidal propagation in an estimated 16% of all tidal rivers. The tidal dataset opens new possibilities for monitoring and modelling changes in estuarine habitats, fresh drinking water for coastal cities and riverine carbon budgets7across annual to decadal timescales in response to sea-level rise8, megadrought9, intensifying water extraction and river regulation10.

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AbstractMicroRNAs (miRNAs) associate with Argonaute (AGO) proteins to form complexes that down-regulate target RNAs, including messenger RNAs from most human genes1–3. Within each complex, the miRNA pairs to target RNAs, and AGO provides effector function while also protecting the miRNA from cellular nucleases2–5. Although much is known about miRNA-directed gene regulation, less is known about how miRNAs themselves are regulated. One pathway that regulates miRNAs involves unusual targets called ‘trigger’ RNAs, which reverse the canonical regulatory logic and instead down-regulate miRNAs6–9. This target-directed miRNA degradation (TDMD) is thought to require a cullin–RING E3 ligase because it depends on the cullin protein CUL3 and other ubiquitylation components, including the BC-box protein ZSWIM8 (refs.10,11). ZSWIM8 is required for murine perinatal viability and for destabilization of most short-lived miRNAs, which suggests biological importance of TDMD11–13. Here, biochemical and cellular assays establish AGO binding and polyubiquitylation by the ZSWIM8–CUL3 E3 ligase as the key regulatory steps of TDMD, and thereby define a unique cullin–RING E3 ligase class. Cryogenic electron microscopy analyses show ZSWIM8 recognizing distinct AGO and RNA conformations shaped by pairing of the miRNA to the trigger. Specificity of AGO ubiquitylation is established through generalizable RNA–RNA, RNA–protein and protein–protein interactions. The substrate features recognized by the E3 ligase do not conform to a conventional degron14,15but instead establish a two-RNA-factor authentication mechanism for specifying a protein ubiquitylation substrate.

AbstractCinchona alkaloids, which have been studied for more than 250 years, are plant-derived natural products that have collectively had a substantial impact in medicine and basic science1–5. Examples of cinchona alkaloids include quinine, a historically important antimalarial drug, and cinchonidine, a chiral catalyst widely used in process chemistry. However, it is still largely unknown how plants synthesize these well-known compounds. Here we report the discovery of genes responsible for the biosynthesis of the distinctive quinoline–quinuclidine scaffold of cinchona alkaloids. A combination of isotopic labelling, gene silencing, single-nucleus RNA sequencing and comparative transcriptomics revealed the involvement of several unexpected biosynthetic transformations. We also describe a previously unreported quaternary amine intermediate that is generated through an unusual enzymatic cyclization. We show that dihydroquini(di)none, dihydrocinchoni(di)none and cinchoni(di)none can be produced when these genes are heterologously expressed inNicotiana benthamiana. Furthermore, we demonstrate that thisN. benthamianaexpression platform can convert non-native fluorinated and chlorinated tryptamine substrates into dihydrocinchoni(di)none analogues, which suggests that these biosynthetic enzymes can be leveraged to produce halogenated cinchona alkaloid derivatives. These discoveries uncover the long-standing mystery of how the cinchona alkaloid scaffold is biosynthesized and highlight prospects for access to these compounds through metabolic engineering approaches.

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AbstractInsulating oxides are among the most abundant solid materials in the universe1–3. Of the many ways in which they influence natural phenomena, perhaps the most consequential is their capacity to transfer electrical charge during contact4–10—which occurs even between samples of the same oxide—yet the symmetry-breaking parameter that causes this remains unidentified11,12. Here we show that adventitious carbonaceous molecules adsorbed from the environment are the symmetry-breaking factor in same-material oxide contact electrification (CE). We use acoustic levitation to measure charge exchange between a sphere and a plate composed of identical amorphous silicon dioxide (SiO2). Although charging polarity is random for co-prepared samples, we control it with baking or plasma treatment. Observing the charge-exchange relaxation afterwards, we see dynamics over a timescale of hours and connect this directly to the presence of adventitious carbon with time-of-flight mass spectrometry, low-energy ion scattering and infrared spectroscopy. Going further, we confirm that adventitious carbon can even determine charge exchange among different oxides. Our results identify the symmetry-breaking parameter that causes insulating oxides to exchange charge in settings ranging from desert sands4to volcanic plumes5,6, while simultaneously highlighting an overlooked factor in CE more broadly.

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AbstractEngineered T cells, reprogrammed to express chimeric antigen receptors (CAR) or T cell receptors (TCR), have transformed cancer treatment and are being explored as therapeutics for autoimmune and infectious diseases. Enhancing T cell function through genome editing, either by disrupting endogenous genes or precisely inserting DNA payloads, has shown considerable promise1. However, the ex vivo manufacturing process is lengthy and costly, limiting accessibility of these therapies. In vivo generation of CAR T cells could overcome these barriers, but current methods rely either on transient expression with limited durability, or on random integration of DNA payloads that lack specificity. Here we demonstrate that stable and cell-specific transgene expression can be achieved through in vivo site-specific integration of large DNA payloads. We developed a two-vector system to deliver CRISPR–Cas9 ribonucleoproteins and a DNA donor template, using enveloped delivery vehicles and adeno-associated viruses, respectively. We optimized both vectors for T cell-specific delivery and gene-targeting efficiency. By integrating a CAR transgene into a T cell-specific locus, we generate therapeutic levels of CAR T cells in vivo in humanized mouse models of B cell aplasia, and haematological and solid malignancies. These findings offer a pathway to more efficient, precise and widely accessible T cell therapies.

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AbstractRadiative forcing from well-mixed greenhouse gases (WMGHGs) is a main driver of Earth’s energy imbalance and global surface climate change1,2. It remains difficult to constrain, largely because its longwave (LW) instantaneous radiative forcing (IRF) component depends on atmospheric state and is subject to radiative parameterization error3–7. The IRF measures the immediate change in radiative fluxes at the tropopause8–10caused by perturbations in WMGHG concentrations. Here we show that increasing WMGHG concentrations have enhanced LW IRF by 3.69 ± 0.07 W m−2(95% confidence interval) since 1850. We first use global line-by-line radiative transfer simulations to provide a global benchmark of LW IRF for the main WMGHGs under realistic, all-sky conditions. We then identify a robust linear relationship between LW IRF and outgoing longwave radiation (OLR), enabling state-dependent LW IRF to be directly inferred from regressions against satellite-observed OLR. Furthermore, LW IRF explains 91% of the inter-model spread in effective radiative forcing (ERF, which includes rapid atmospheric adjustments beyond the IRF) for CO2(ref.11) across Earth system models. Benchmarking model-simulated IRF using the regression technique reveals that most discrepancies originate from radiation parameterizations and correcting LW IRF biases would reduce uncertainty in CO2ERF by 50%. Our results establish a simple and robust framework for quantifying state-dependent radiative forcing of WMGHGs, providing an observation-informed pathway for future climate assessments.

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February 2026 saw the end of the New Strategic Arms Reduction Treaty, known as New START, the last nuclear arms control agreement between the United States and Russia. Without limitations on nuclear weapons, what comes next? Can scientists step in, as they did in years past, to help stop the risk of nuclear war?

Multifaceted effects of extreme climate-related events are essential for risk models and management

An astronaut and an alien engineer team up against an existential threat in a new film

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AMPA receptors (AMPARs) are multimodal transducers of glutamatergic signals throughout the brain. Their diversity is exemplified in the cerebellum: At afferent synapses, AMPARs mediate high-frequency excitation, whereas in Bergmann glia (BG) they support calcium transients that modulate synaptic transmission. This spectrum arises from different combinations of core subunits (GluA1-4), auxiliary proteins, and posttranscriptional modifications. Using mass spectrometry, cryo–electron microscopy, and electrophysiology, we characterize major cerebellar AMPARs in pigs: calcium-impermeable GluA2/A4 heteromers with four transmembrane AMPAR regulatory protein (TARP) subunits, mainly neuronal in origin, and BG-specific, calcium-permeable GluA1/A4 heteromers containing two type II TARPs. We also showed that GluA4 receptors frequently exhibit compact N-terminal domains that promote their synaptic delivery. Our study defines the organizational principles of mammalian cerebellar AMPAR complexes and reveals how different receptor subtypes support cell type–specific functions.

GDF15, thought to contribute to nausea during pregnancy, also acts as a brake on drinking, researchers argue

The generation and manipulation of high-dimensional quantum states lies at the heart of modern quantum computation. The use of topology to resiliently encode and transport quantum information has been widely investigated in condensed matter and has recently penetrated quantum photonics. However, a route to scale up to a large number of entangled topological photonic modes has been missing. In this work, we demonstrate a method to generate high-dimensional topological photonic entanglement. Our platform relies on designed silicon photonic waveguide topological superlattices, which support nonlinear generation of energy-time–entangled photon pairs on a superposition of multiple topological modes. We show strong signatures of entanglement of up to five topological modes with resilience to nanofabrication imperfections, providing a route toward scalable, fault-tolerant quantum photonic states.

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A pair of studies illuminates these humans’ long, hardscrabble existence

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An Egyptian fossil places the origin of modern apes in northeastern Afro-Arabia

Tissues harbor memories of inflammation, which heighten sensitivity to diverse future assaults. Whether and how these adaptations are sustained through time and cell division remain poorly understood. We show that in mice, epidermal stem cells store lifelong, functional epigenetic records of psoriasis-like skin flares. Applying deep learning to investigate these chromatin dynamics, we unearth CpG dinucleotide density as a major driver of memory persistence. Although unnecessary for inflammation-induced transcription factors to open and establish memories, CpG-enriched sequences thereafter become essential, reinforcing accessibility across cellular generations by integrating DNA demethylation, methylation-sensitive transcription factors, sequence-intrinsic nucleosome disaffinity, and the nucleosome-destabilizing histone variant H2A.Z. Thus, once activated by inflammation-induced transcription factors, DNA sequences orchestrate persistent poise, imparting long-lasting memory to stress-sensitive genes and profoundly affecting tissue fitness upon recall.

Quirk of freezing water found on atomic scales, hinting at technological applications

ArXiv splits from Cornell, aiming to raise funds to cope with rapid growth

Methane measurements, particularly of natural sources, need to be expanded considerably

Although massive cell atlases are already available, it is still a challenge to obtain an atlas of all tissues within a single body, especially in fetuses and pregnant mothers. We present a transcriptomic atlas of 2.56 million single cells covering 115 and 119 tissues from one fetal pig and its pregnant mother, respectively. We found that a cluster of heart capillary endothelial cells with enhanced fatty acid transit capability was enriched for pregnancy but restored after gestation. We also deciphered thatl-leucine transport insufficiency in the trophoblast causes fetal growth restriction by reducing a muscle type II myofiber subcluster. Our “all-from-one” strategy enabled the identification of tissue cell type–specific transcription factors and provided insights into pregnancy heart adaptation and fetal growth restriction.

Malaria in South America remains a serious public health problem.Anopheles(Nyssorhynchus)darlingiis the most important malaria vector across tropical Latin America. Vector-targeted disease control efforts require a thorough understanding of mosquito demographic and evolutionary patterns. We present and analyze whole genomes of 1094An. darlingi(median depth 18x) from six South American countries. We observe deep geographic population structure, high genetic diversity including 13 putative segregating inversions, and no evidence for sympatric cryptic taxa despite high interpopulation divergence. Strong signals of selection are plausibly driven by insecticides, especially on cytochrome P450 genes. Our results will facilitate effective mosquito surveillance and control while highlighting ongoing challenges that a diverse vector poses for malaria elimination in the Western hemisphere.

Resurrection plants can wither to nothing in a drought, then spring back to life. Jill Farrant thinks the feat holds lessons for crops

Algorithms that autonomously control other software and files can become “agents of chaos,” violating privacy, security

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We quantitatively document a sperm whale birth event, revealing collective support behaviors across kinship lines. Using high-resolution drone footage, computer vision, and multiscale network analysis, we studied the interactions within a Caribbean sperm whale unit comprising two matrilines. Our results suggest that a female family member led birth assistance and that after delivery, all individuals oriented toward and helped lift the newborn, taking turns in a coordinated, cross-kin effort. Despite historically observed foraging segregation, kinship barriers dissolved as all unit members contributed. These analyses provide evidence of birth attendance, or assistance, in a nonprimate species, a behavior long considered characteristic only of humans and their close relatives.

Blue Ghost data suggest NASA’s growing commercial Moon program can deliver results

Tsunamis from large subduction earthquakes pose severe coastal hazards, yet their genesis near the trench remains poorly constrained by land-based seismic geodetic data and distant deep-water sensors. Following the 29 July 2025 magnitude 8.8 Kamchatka earthquake, the NASA/CNES Surface Water and Ocean Topography (SWOT) satellite captured a distinct train of short-wavelength tsunami waves, which we link to near-trench tsunamigenesis. Sensitivity analyses of earthquake slip indicated tsunamigenesis within 10 kilometers of the trench, an inference not attainable from land seismology and geodesy or sparse deep-water seafloor pressure records alone. These results provide the first high-resolution, two-dimensional spaceborne observation directly linking the measured dispersive tsunami wavefield to near-trench tsunamigenesis, extending earlier model- and gauge-based inferences. They establish SWOT as a constraint on source processes, with implications for tsunami hazard science and subduction-zone geodynamics.

Telomerase is a reverse transcriptase that synthesizes telomeric repeats at chromosome ends, safeguarding genome integrity. We present the cryo–electron microscopy structure of the budding yeast telomerase, which exhibits substantial divergence from its ciliate and vertebrate counterparts. The structure reveals a stable core formed by telomerase RNA TLC1; the three ever shorter telomere (Est) proteins, Est1, Est2 and Est3; and the Pop1/Pop6/Pop7 complex (Pop1/6/7). TLC1, Est3, and Pop1/6/7 serve critical roles in complex assembly. We identified a zinc finger (ZnF) motif in the telomerase reverse transcriptase (TERT) subunit Est2 that is crucial for telomerase function. Structure prediction suggests the presence of ZnFs in TERT from diverse species. These findings offer insights into the functional organization of yeast telomerase and underscore the evolutionary diversity of telomerase holoenzymes.

Deciphering thalamocortical (TC) activation at the level of individual synapses is essential to understanding how the cortex processes sensory information. In this work, we studied TC computation underlying the emergence of orientation selectivity in the mammalian primary visual cortex (V1). Using two-photon glutamate imaging and optogenetic cortical silencing in vivo, we identified and characterized TC synapses onto mouse V1 layer 4 neurons. We found that TC- but not corticocortical-recipient spines lacked postsynaptic Ca2+signals. Our results directly validate the core predictions of Hubel and Wiesel’s feedforward model and reveal distinctive synaptic properties that are critical for cortical computation and plasticity.

Rapid measurements capture structural transition in a short-lived liquid state of supercooled water

Editors’ selections from the current scientific literature

Internet blackouts and academic isolation cloud efforts to track cultural toll of U.S.-Israeli strikes

The search for the liquid-liquid critical point in supercooled water is challenging owing to rapid crystallization. We studied supercooled water at timescales before ice formation by heating high- and low-density amorphous ices using infrared ultrafast laser pulses, followed by x-ray scattering. By varying the pump laser fluence, we accessed liquid states straddling the predicted critical point. We observed a crossover from a discontinuous to a continuous transition at which broad and slow structural variations occurred, consistent with critical fluctuations and slowing down. We also observed a rapid increase in the heat capacity indicating a critical divergence at 210 ± 8 K coincident with enhanced density fluctuations. These results suggest that our experiments have directly probed the vicinity of a critical point in supercooled water.

Structural constraints stymie patients and physicians when symptoms cannot be easily explained

Despite rising concerns about sycophancy—excessive agreement or flattery from artificial intelligence (AI) systems—little is known about its prevalence or consequences. We show that sycophancy is widespread and harmful. Across 11 state-of-the-art models, AI affirmed users’ actions 49% more often than humans, even when queries involved deception, illegality, or other harms. In three preregistered experiments (N= 2405), even a single interaction with sycophantic AI reduced participants’ willingness to take responsibility and repair interpersonal conflicts, while increasing their conviction that they were right. Despite distorting judgment, sycophantic models were trusted and preferred. This creates perverse incentives for sycophancy to persist: The very feature that causes harm also drives engagement. Our findings underscore the need for design, evaluation, and accountability mechanisms to protect user well-being.

15,800-year-old puppy pushes confirmed origin of our canine companions back nearly 5000 years

Specific DNA sequence features encode the persistence of epigenetic memory of inflammation

The Early Miocene fossil record documenting hominoid evolution has long been restricted primarily to sites in East Africa, whereas contemporaneous North African sites have only yielded remains of cercopithecoid monkeys. Here, we describe a fossil ape from North Africa, a new genus (Masripithecus) from the Early Miocene (~17 million to 18 million years) of northern Egypt, on the basis of mandibular remains. A combined molecular-morphological Bayesian tip-dating analysis positionsMasripithecuscloser to crown hominoids than coeval fossil apes from East Africa, thereby filling a phylogenetic and biogeographic gap in the evolution of stem hominoids. This evidence suggests that crown Hominoidea might have originated during the Early Miocene in the underexplored northeastern part of Afro-Arabia, rather than in eastern Africa or Eurasia.

One defining feature of complex organisms is the ability to maintain protein homeostasis beyond cellular boundaries. We review how extracellular proteostasis is organized as a hierarchical network spanning pericellular, tissue, and systemic tiers. At each tier, secreted chaperones, proteases, vesicles, receptors, immune sentinels, and clearance organs cooperate to recognize, buffer, and eliminate misfolded proteins. Feedback through immune signaling, stress-induced protein secretion, and glymphatic and lymphatic transport adjusts capacity to proteotoxic load. We illustrate how failures in this stratified defense underlie neurodegenerative disorders and systemic amyloidoses, and we highlight strategies that stabilize extracellular proteins, augment clearance pathways, or enhance fluid transport. Viewing extracellular proteostasis as an integrated systems-level network reveals opportunities for combinatorial and preventive therapies.

Understanding how cells make decisions over time requires the ability to link past molecular states to future phenotypic outcomes. We present TimeVault, a genetically encoded system that records and stores transcriptomes within living mammalian cells for future readout. TimeVault leverages engineered vault particles that capture messenger RNA through polyadenosine [poly (A)]–binding protein. We demonstrate that the transcriptome stored by TimeVaults is stable in living cells for more than 7 days. TimeVault enables high-fidelity transcriptome-wide recording with minimal cellular perturbation, capturing transient stress responses and revealing gene expression changes underlying drug-naïve persister states in lung cancer cells that evade epidermal growth factor receptor (EGFR) inhibition. By linking past and present cellular states, TimeVault provides a powerful tool for decoding how cells respond to stress, make fate decisions, and resist therapy.

During eukaryotic transcription, RNA polymerase II (Pol II) must overcome nucleosome obstacles and, because of DNA’s helical structure, must also rotate relative to DNA, which generates torsional stress. However, there is limited understanding of how Pol II transcribes through nucleosomes while supercoiling DNA. In this work, we determined that Pol II generates a torque of 9 piconewton-nanometers (pN·nm) alone and 13 pN·nm with transcription factor IIS (TFIIS), making it a powerful rotary motor. When Pol II encounters a nucleosome, passage becomes more efficient on a chromatin substrate compared with on a single-nucleosome substrate, which demonstrates that chromatin substantially buffers torsional stress during transcription. Furthermore, topoisomerase supercoiling relaxation allows Pol II to transcribe through multiple nucleosomes. Our results reveal a role of chromatin beyond the more conventional view of it being just a roadblock to transcription.

Non-volatile memories (NVM) that operate reliably at high temperature are essential for electronics in extreme environments. Here, we reported graphene (Gra)/HfOx/tungsten (W) memristors that operated reliably up to 700 °C with an ON/OFF current ratio >103, data retention >50 hours and endurance >109switching cycles. Transmission electron microscopy (TEM) revealed significant W diffusion into the inert platinum (Pt) electrode of conventional Pt/HfOx/W memristors after high-temperature annealing, which was an effect responsible for the thermal failure of conventional devices but not observed in Gra/HfOX/W devices. First-principles calculations attributed the enhanced thermal stability to weaker W adsorption and higher surface diffusion barriers on graphene than metals like Pt. These results underscore the critical role of interfacial engineering and potential of 2D materials in enabling reliable high-temperature NVM technologies.

Climate change forces species to adapt rapidly to avoid extinction. To directly observe rapid adaptation and extinction, we conducted synchronized evolution experiments withArabidopsis thalianain 30 locations across Western Europe, the Mediterranean, the Levant, and North America. Whole-genome pooled sequencing of ~70,000 surviving plants revealed repeatable allele frequency shifts in similar climates but divergent shifts across contrasting ones, indicating evolutionary adaptation. We identified genetic variants linked to climate adaptation, including genes involved in processes ranging from thermal-stress sensing to spring-flowering timing. Evolutionary trends were often predictable, but variable, across environments. In warmer climates, evolutionary predictability correlated with population survival over 5 years, whereas erratic changes preceded extinction. These results show that rapid climate adaptation is possible, but understanding its limits will be crucial for biodiversity forecasting.

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Sycophantic AI distorts social judgments and behaviors

Highlights from theSciencefamily of journals

Research security policies are emerging across nations seeking to protect their national interests in response to geopolitical shifts. Yet governments impose disclosure requirements and threaten penalties while offering little guidance on the vast gray zone of cross-border collaborations that could invite retribution. A chill sets in among researchers. If the community does not act, the result will be scientific fragmentation at a moment when global challenges demand cooperation. That serves neither security nor innovation.

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Sympathetic neurons activate eosinophils during stress to worsen atopic dermatitis flare-ups

Neuronal function depends on mitochondria, but little is known about their organization across neurons. Using an electron microscopyDrosophilaconnectome, we uncovered quantitative rules governing the morphology and positioning of hundreds of thousands of mitochondria across thousands of neurons. We discovered that mitochondrial morphological features are specific to cell and neurotransmitter type, which provides fingerprints to identify neurons. Mitochondria are positioned with 2- to 3-micrometer precision relative to synaptic and structural features, with systematic differences across neuron types and compartments. Mitochondrial localization correlates with regional activity and postsynaptic targets. Analysis of a mouse visual cortex connectome confirms cell type–specific morphology and identifies partially divergent positioning rules. These results establish mitochondria as circuit-embedded organelles whose distribution links subcellular architecture to brain connectivity.

Twisted stacking of two-dimensional van der Waals (vdW) semiconductors creates moiré superlattices, which provides unprecedented control over quantum states and their light-matter interactions. We demonstrate that a simple twist interface between two single-crystalline bulks of hexagonal boron nitride (hBN) creates moiré quantum wells (QWs) embedded in a three-dimensional vdW structure. hBN moiré QWs strongly confine charge carriers under both optical excitation and electrical injection. Despite their indirect bandgap, they emit intense deep-ultraviolet luminescence in the extreme wavelength bands from 215 to 240 nanometers, exceeding that of state-of-the-art conventional aluminum gallium nitride (AlGaN) multiple QWs by more than an order of magnitude. Furthermore, the twist angle control allows wide tunability of luminescence energy and efficiency in moiré QWs.

A geneticist confronts how we think about free will, character, and wrongdoing

Stratigraphic analysis resets the time of human arrival in Monte Verde, Chile

Trace surface contamination determines how identical materials exchange charge

In vivo delivery systems (IDSs) are designed to protect and transport therapeutics, but their clinical applications are hindered by low delivery efficiency. We identified gut microbiota as key regulators of efficacy of IDS-based therapies and that disrupting commensal-host interactions markedly improves drug and gene delivery. Intestinal epithelial cells sense microbial stimulation and remotely activate Kupffer cells through serotonin production, thereby driving hepatic IDS clearance. Transient suppression of serotonin signaling, through receptor blockade or dietary intervention, mitigates hepatic IDS clearance and improves delivery efficiency. This strategy yielded more than threefold therapeutic enhancement in chemotherapy and oncolytic virotherapy and 5- to 15-fold improvements in somatic genome editing and messenger RNA–based therapies. These findings reveal a gut-liver immune axis that can be therapeutically exploited to improve IDS-based cancer and gene therapies.

Editors’ selections from the current scientific literature

Spinal cord injury patients are scrambling for access to the injection, but researchers say evidence is weak

Eukaryotic gene expression is orchestrated by RNA polymerases (RNAPI, II, and III) and associated factors, yet their real-time dynamics remain obscure. Using single-molecule tracking in living yeast, we quantified the kinetics of 58 proteins encompassing three RNAP machineries. RNAPI and RNAPIII preinitiation complexes (PICs) engage in long-lived chromatin interactions, contrasting with transient RNAPII PICs. We further report kinetics of RNAPII-associated factors for elongation, histone modification, C-terminal domain (CTD) modification, RNA processing, and termination. Many elongation factors show brief rather than persistent association, suggesting dynamic interactions with factor exchange and allowing a potential repertoire of regulatory events. CTD truncation reduces U1 small nuclear ribonucleoprotein residence time and intron retention in ribosomal protein genes, providing insights into cotranscriptional splicing. Our findings establish a framework of dynamic interactions of RNAP machineries.

How intrinsically disordered regions (IDRs) influence chromatin binding and nuclear organization of transcription factors (TFs) remains unclear. We employed proximity-assisted photoactivation (PAPA), a single-molecule protein-protein interaction sensor, to investigate how IDRs might influence TF interactions with each other and with chromatin in live cells. We found that the Sp1 DNA binding domain (DBD) interacted poorly with chromatin and did not colocalize with Sp1. Weak interaction of the isolated IDR with full-length Sp1 was enhanced by fusion to various unrelated DBDs. Live imaging ofDrosophilapolytene chromosomes confirmed that an IDR could confer sharp locus specificity on an otherwise nonspecific DBD. These findings suggest that TF specificity emerges on chromatin when ensembles of diverse, unstructured interactions are scaffolded by transient DNA contacts.

Influential agency may lose research projects, collaborations, and part of its annual budget

Controlled placement of branch points along carbon chains is a core capability in the synthesis of materials, agrochemicals, and pharmaceuticals. Metal hydride hydrogen atom transfer (MHAT) to alkenes represents a valuable elementary step because it accesses branched products directly from abundant α-olefins. MHAT catalysis can also be coupled to secondary transition metal catalytic cycles that would otherwise deliver nonbranched (linear) products. However, the hydridic reagents used in MHAT do not always discriminate between the MHAT catalyst and the secondary metal, leading to mixtures of metal hydrides and, therefore, mixtures of products. In this work, we show that a combination of a lutidinium acid and manganese, a weak reductant, selectively generates cobalt hydrides in the presence of a nickel catalyst. We applied these conditions to a cross-selective alkene-alkene coupling that produces valuable branched materials with exquisite selectivity.

Many animals produce courtship sounds, and receivers prefer some sounds over others. Shared ancestry and convergent evolution may generate similarities in preference across species and underlie Darwin’s conjecture that some animals “have nearly the same taste for the beautiful as we have.” In this study, we show that humans share acoustic preferences with a range of animals, that the strength of human preferences correlates with that in other animals, and that humans respond faster when in agreement with animals. Furthermore, we found greatest agreement in preference for adorned, ancestral, and lower-frequency sounds. Humans’ music listening experience was associated with preferences. These results are consistent with theories arguing that biases in processing sculpt acoustic preferences, and they confirm Darwin’s century-old hunch about the conservation of aesthetics in nature.

Chronic pain exhibits circadian rhythms in humans, but the mechanisms underlying such rhythmicity remain unclear. Here, we found daily oscillations in the nociceptive thresholds in a mouse model of neuropathic pain, driven by a rhythmic circuit from the master clock in the hypothalamus to the descending analgesia system. In the daytime (resting phase), higher vasoactive intestinal peptide (VIP) neuronal activity in suprachiasmatic nucleus (SCNVIP) activates a signaling pathway involving the paraventricular nucleus (PVN) and the ventrolateral periaqueductal gray (vlPAG), ultimately increasing nociceptive sensitivity. At night (active phase), reduced SCNVIPneuronal activity decreases pain sensitivity through this polysynaptic circuit. This study identified a circuit for regulating pain rhythmicity that might be targeted to improve chronic pain management.

Annual cultivated rice was domesticated from perennial wild rice, yet the genetic mechanism of perennial growth habit remains unclear. Using introgression lines of wild and cultivated rice, we identified theEndless Branches and Tillers(EBT1) locus, comprising tandem microRNA156 genes (MIR156BC). This locus is responsible for floral reversion and vegetative propagation contributing to perennial growth in wild rice. The wild rice alleleEBT1W1943exhibits higher chromatin accessibility and lower levels of the repressive histone mark H3K27me3 to resetMIR156BCexpression in tiller buds compared with the cultivated allele. Additionally, we introgressedEBT1and prostrate growth genesPROG1andTIG1to generate recombinant lines exhibiting a robust perennial habit. Our findings pave the way for developing sustainable perennial rice cultivars in the future.

Highlights from theSciencefamily of journals

Chronic kidney disease (CKD) is linked to an elevated fecal abundance ofEnterobacteriaceae, but the ecological drivers of this shift and its impact on disease progression remain unclear. The uremic toxin indoxyl sulfate is produced from microbiota-derived indole in the liver. Here, we found that in mice with adenine-induced CKD, impaired clearance of indoxyl sulfate elevated mucosal expression of the gene encoding inducible nitric oxide synthase (iNOS). The resulting rise in luminal nitrate levels promotedEscherichia coligrowth by means of nitrate respiration. Fecal microbiota from CKD patients generated more indole than feces of healthy controls during anaerobic culture, but only in the presence of nitrate. Nitrate enhanced indole production byE. coli, thereby worsening renal pathology in CKD mice, which was mitigated by iNOS inhibition.

Stacks of boron nitride sheets can be arranged to emit deep ultraviolet light

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Two brain circuits facilitate the interaction between chronic pain and time

Chronic pain often evolves into depression and anxiety, yet mechanisms linking sensory distress to affective dysfunction remain unclear. Integrating human neuroimaging from the UK Biobank with a rodent model, we uncovered biphasic hippocampal remodeling. Hippocampal volume increased during early pain stages, with paradoxical cognitive improvements, but declined with comorbid depression. In rodents, the dentate gyrus (DG) acted as a hub governing this transition: Lesions of DG prevented affective symptoms. Elevated DG activity was linked to hyperactive newborn neurons and microglial recruitment and remodeling, leading to circuit imbalance. Whereas suppressing newborn neuron activity alleviated emotional pathology at the expense of cognition, microglial modulation selectively restored affective behavior without cognitive cost. These findings reveal microglia-mediated hippocampal remodeling as a key mechanism linking chronic pain to mood disorders.

Whether early Earth had a mobile lithosphere and plate tectonics is debated. We present paleomagnetic data quantifying differential motion between lithospheric blocks at ~3.48 billion years ago (Ga). This manifested as47−35+69centimeters per year latitudinal motion of the East Pilbara Craton (Western Australia) across high latitudes, whereas the Barberton Greenstone Belt (South Africa) was stationary at low latitudes. Comparison of this plate motion with candidate analogs suggests either rapid collisional plate tectonics (i.e., an “active-lid”) or an episodically mobile lithosphere. We also document the oldest known geomagnetic reversal at ~3.46 Ga, consistent with an axial dipolar dynamo that reversed less frequently than today’s. The existence and rates of these surface and core geophysical phenomena provide geodynamic context to Earth’s early geophysical and biological evolution.

Synonymous codon usage controls global gene expression in both prokaryotic and eukaryotic species. Nonoptimal codons are known to induce mRNA decay; however, the underlying molecular mechanism remains poorly understood in human cells. Through genome-wide CRISPR screening, we identified the RNA-binding protein DHX29 as a critical regulator of codon-dependent gene expression. Cryogenic electron microscopy and selective ribosome profiling demonstrated that DHX29 directly interacts with the A-site entrance of the translating 80S ribosome, the binding site for the eEF1A•GTP•aminoacyl-tRNA ternary complex, suggesting a role in monitoring aminoacyl-tRNA sampling. Proteomic analysis further revealed that DHX29 recruits the GIGYF2•4EHP complex to mediate global suppression of nonoptimal mRNAs. These findings establish a mechanistic link between synonymous codon usage and the regulation of gene expression.

Under US law and international treaties, drug scheduling is a multiple-choice problem for which the answer that would often be best is not an option

Impacts of farming practices on soil hydrodynamics are central to understanding agricultural landscapes covering almost half of the world’s habitable land. Combining observations from distributed acoustic sensing with physics-based hydromechanical modeling, we tracked minute-resolution, meter-scale seismic and hydrological changes across agricultural fields with controlled histories of tillage and compaction. We show that dynamic capillary effects in soil govern transient stiffness and moisture redistribution in disturbed soils, producing sharp post-rain velocity drops from near-surface saturation and large hysteretic velocity rebounds driven by evapotranspiration. Our seismically inverted estimates of saturation reveal how disturbance alters flux partitioning and storage, establishing agroseismology and distributed acoustic sensing as scalable, noninvasive probes of soil hydromechanics with the potential to improve Earth system models, land management, and hazard resilience.

An Arab neuroscientist is steering a top Israeli university through tumultuous times. She’s learned some hard lessons

A new study challenges pre-Clovis age for Monte Verde site in southern Chile

Their huge facilities, data flows, and computing resources are a natural fit for AI

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Psychological stress is believed to exacerbate dermatitis, yet the neurobiological mechanisms linking stress to immune processes remain elusive. We identified a subset of prodynorphin-positive (Pdyn+) noradrenergic sympathetic neurons in mice that specifically innervate hairy skin, mediating stress-induced exacerbation of skin inflammation in an eosinophil-dependent manner. Genetic ablation of Pdyn+sympathetic neurons or eosinophils mitigated stress-evoked worsening of inflammation in atopic dermatitis–like mice, whereas optogenetic activation of these neurons precipitated inflammation through eosinophils. Pdyn+sympathetic neurons recruited eosinophils through the CCL11-CCR3 axis and activated them through the adrenergic receptor beta2 (Adrb2) in inflamed skin. Our findings reveal a neuroimmunological mechanism underlying psychological stress–induced exacerbation of dermatitis, emphasizing the Pdyn+sympathetic-eosinophil axis as a crucial interface between the brain and skin inflammation, with potential therapeutic implications.

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Our understanding of the timing of the human colonization of South America has been anchored by the Monte Verde II site in Chile, reported to date to ~14,500 years before the present (B.P.) and regarded as one of the most secure pre-Clovis archeological sites. We report the first independent investigation of Monte Verde in the nearly 50 years since initial excavations. We argue that radiocarbon and luminescence dates from alluvial exposures, in combination with the identification of a tephra dated to 11,000 years B.P. stratigraphically underlying the archaeological component, suggest that Monte Verde cannot be older than the Middle Holocene (8200 to 4200 years B.P.). With colonization no longer anchored by Monte Verde, our revised chronology supports a more recent date of human arrival to South America.

Boreal forests provide considerable global land carbon storage and uptake, but they are being rapidly transformed to managed secondary forests, with poorly quantified implications for ecosystem carbon storage. Here we present data from extensive mapping and field inventories of carbon storage in primary forests in Sweden and use multiple methods to show that primary forests store ~72% (70 to 74% across methods) more carbon than managed secondary forests in vegetation, deadwood, soils, and harvested wood products combined. Soils constitute both the largest carbon store and the largest difference between these forest types. The total carbon storage difference between primary and managed secondary forests is 2.7 to 8.0 times larger than previous estimates. Our results challenge estimated past and future contributions of boreal forest management to atmospheric carbon dioxide concentrations.

Seemingly innocuous research decisions can harm scientific credibility, argue a pair of social scientists

T cells are often weakly responsive to tumor self-antigens because of central tolerance, constraining their ability to eliminate tumors. We exploited mechanical force to engineer a weakly reactive T cell receptor (TCR) specific for a nonmutated tumor-associated antigen (TAA), prostatic acid phosphatase (PAP). We identified a catch-bonding “hotspot” whose mutation enhanced T cell activity by increasing TCR–pMHC (peptide–major histocompatibility complex) bond lifetime while preserving physiological affinities and antigen fine specificities. T cells expressing these engineered TCRs showed vastly superior expansion in the tumor, effector phenotypes, and tumor elimination. Crystal structures and molecular dynamics simulations revealed a single amino acid mutation at the catch-bond hotspot primes the TCR for peptide interaction through water reorganization at the TCR-pMHC interface. Catch-bond engineering is a viable biophysically based strategy for transforming tolerized antitumor T cells into potent TCR–T cell therapy killers.

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Human studies test noninvasive “temporal interference” stimulation in epilepsy and other diseases

New regulations ask manufacturers to provide efficacy and safety data—or withdraw their products

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Groundwater depletion poses a challenge to irrigated agriculture and water access. Depleted aquifers can be refilled, but the interventions that have successfully refilled depleted aquifers are rarely reviewed. This work reviews 67 cases of groundwater recovery, where groundwater levels rose after a prolonged period of decline. The interventions that spurred groundwater recovery included policy changes, artificial groundwater recharge, and increased reliance on another water source instead of groundwater. Groundwater recovery can improve water access, restore ecosystems, slow seawater intrusion, and halt land subsidence. However, excessive groundwater recovery can waterlog soils, destabilize buildings, increase liquefaction risks, and intensify flood hazards. This Analytical Review describes how groundwater depletion trends have been reversed through interventions. Stakeholders and managers may consider adapting aspects of these interventions to address groundwater depletion elsewhere.

Earth had variable tectonic plate motions and a strong, stable magnetic field 3.5 billion years ago

Seals and sea lions have highly developed volitional breathing control, to which the phocid seals add vocal production learning, including mimicry. In this work, using histology and ex vivo diffusion magnetic resonance imaging tractography, we provide evidence for a phylogenetic spectrum of accumulative neural adaptations supporting aspects of volitional vocal control across pinnipeds. Otariids and phocid seals, but not coyotes, have a direct connection between the vocal motor cortex and phonatory brainstem nuclei. Harbor seals showed hypertrophic connectivity between the anterior ventrolateral thalamus and the vocal premotor cortex—part of a forebrain circuit related to vocal learning in birds and mimicry in humans and parrots. We demonstrate that phocid seals have auditory-premotor pathways potentially related to developmental call learning.

A new documentary confronts the dire future of North America’s largest terminal lake

Bridge recombinases are naturally occurring RNA-guided DNA recombinases that we previously demonstrated can programmably insert, excise, and invert DNA in vitro and inEscherichia coli. In this study, we report the discovery and engineering of the bridge recombinase ortholog ISCro4 for universal rearrangements of the human genome. We defined strategies for the optimal application of bridge systems, leveraging mechanistic insights to improve their targeting specificity. Through rational engineering of the ISCro4 bridge RNA and deep mutational scanning of its recombinase, we achieved up to 20% insertion efficiency into the human genome and genome-wide specificity as high as 82%. We further demonstrated intrachromosomal inversion and excision, mobilizing up to 0.93 megabases of DNA. Lastly, we provided proof of concept for plasmid-based excision of disease-relevant gene regulatory regions or repeat expansions.

Editors’ selections from the current scientific literature

How animals detect Earth’s magnetic field remains a mystery in sensory biology. Despite extensive behavioral evidence, the neural circuitry and molecular mechanisms responsible for magnetic sensing remain elusive. Adopting an unbiased approach, we used whole-brain activity mapping, tissue clearing, and light sheet microscopy to identify neuronal populations activated by magnetic stimuli in the pigeon (Columba livia). We demonstrate robust, light-independent bilateral neuronal activation in the medial vestibular nuclei and the caudal mesopallium. Single-cell RNA sequencing of the semicircular canal cristae revealed specialized type II hair cells that express the molecular machinery necessary for the detection of magnetic stimuli by electromagnetic induction. Our data support a model whereby electromagnetic input from the semicircular canals activates a vestibular-mesopallial circuit in the pigeon brain.

Populations that are declining as a result of climate change may need to evolve to persist. Although evolutionary rescue has been demonstrated in theory and in the laboratory, its relevance to natural populations facing climate change remains unknown. Here we link rapid evolution and population dynamics in scarlet monkeyflower,Mimulus cardinalis, during exceptional drought. We leverage whole-genome sequencing across 55 populations to identify climate-associated loci. Simultaneously we track demography and allele frequency change throughout the drought. We establish range-wide population decline during the drought, geographically variable rapid evolution, and variable population recovery that is predictable by standing genetic variation in, and rapid evolution at, climate-associated loci. These findings demonstrate the possibility of evolutionary rescue in the wild, showing that genetic variation at adaptive, but not neutral, loci predicts population recovery.

Rejecting ignorance as the cause of antibiotic overuse, a pair of sociologists find more likely explanations

Gene expression patterns underlie development, but their systematic detection in whole embryos has remained elusive. We introduce a whole-embryo imaging platform using multiplexed error-robust fluorescent in situ hybridization (weMERFISH). We quantified the expression of 495 genes in zebrafish embryos at subcellular resolution and generated an online atlas detailing the expression of 25,872 genes and accessibility of 294,954 chromatin regions during embryogenesis. Expression patterns often corresponded to composites of tissue-specific accessible elements, and expression changes aligned with cellular maturation and morphogenesis. Integration with live imaging revealed how similar expression patterns can emerge through different dynamics and showed that sharp boundaries develop through changes in gene expression rather than through cell sorting. These results establish multiplexed whole-embryo spatial transcriptomics and reveal the regulation and dynamics of embryonic gene expression patterns.

Overexpression of the proto-oncogene Src is common to a wide variety of cancers. In this work, we found that Src is noncanonically translocated and inverted onto the cell surface in cancer, both in vitro and in vivo. We identified autophagolysosomal exocytosis (ALE) as a secretory mechanism prominent in cancer cell lines. Src represents the prototypical example of a family of membrane-anchored proteins that are transported by this process. Furthermore, this extracellular membrane–associated Src (eSrc) was found in primary tumors, and anti-Src antibody-based therapies mediated tumor cell killing in cell culture systems and in mouse xenograft models. Thus, intracellularN-myristoylated proteins, prototypically Src, can be topologically inverted onto the cell surface in cancer and targeted with antibody therapeutics.

The growth and penetration of lithium dendrites through electrolytes and separators remain key challenges to realizing high–energy density lithium-metal batteries. Using mechanically strong electrolytes and separators has been considered a promising strategy based on the commonly believed softness of lithium. However, dendrite formation persists in stiff solid electrolytes, suggesting distinct mechanical behaviors. We measured the mechanical properties of individual lithium dendrites using an air-free protocol. We found that lithium dendrites are unexpectedly strong and brittle, with fracture stress greater than ~150 megapascals, unlike the ductile bulk metal. Cryo–transmission electron microscopy and mechanical modeling showed that this behavior arises from solid electrolyte interface constraints and nanoscale strengthening. These findings provide alternative mechanisms for dendrite penetration and dead lithium formation as well as guidance for design strategies for lithium-metal batteries.

Ancient glacial ice melting out of Alaska’s eroding coastline may offer the Northern Hemisphere’s only glimpse into a pivotal climate chapter

Highlights from theSciencefamily of journals

In an interview, Jared Isaacman says agency may accelerate robotic Moon landings and could tackle a new Mars mission in 2028

Biological systems are inherently complex and heterogeneous. Deciphering this complexity increasingly relies on high-throughput single-cell omics methods and tools that efficiently probe the cellular phenotype and genotype. Here, we present a versatile technology based on semipermeable capsules (SPCs) tailored for a variety of high-throughput nucleic acid assays, including single-cell genome and mRNA sequencing, and fluorescence-activated cell sorting–based isolation of individual transcriptomes based on a nucleic acid marker of interest. Being biocompatible, the SPCs support single-cell cultivation and clonal expansion over long periods of time, thereby overcoming a fundamental limitation of droplet microfluidics platforms. Overall, the SPCs represent a customizable and broadly applicable tool for easy-to-use, scalable single-cell omics applications that are built on multistep biochemical reactions.

Strategy produces promising results in cell studies and infected people

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Transformation of pancreatic epithelial cells to malignant pancreatic ductal adenocarcinoma (PDAC) typically involves the progression of precancerous pancreatic intraepithelial neoplasia (PanINs) bearing oncogenicKRASmutations. Here, we tested the impact of PDAC interception using either RAS(ON) multiselective or RAS(ON) G12D-selective pharmacological inhibitors [RAS(ON) inhibitors] in mouse models of PDAC. Treatment of PanIN-bearing mice with RAS(ON) inhibitors prompted regression of premalignant lesions that translated into a delay in tumor onset and an increase in overall survival (OS). Long-term interception in tumor-prone mice resulted in a median OS of more than 1 year compared with less than 5 months in nonintercepted control mice (P< 0.0001). Comparing the survival benefits of RAS(ON) inhibition for cancer interception versus RAS(ON) inhibition for cancer treatment, we found that interception provided a greater survival benefit to mice. These findings suggest that a pharmacological approach may reduce premalignant burden and increase survival in PDAC.

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Exocytosis exposes Src at the outer surface of cancer cells, poised for therapeutic targeting

Conformational biasing (CB) is a rapid and streamlined computational method that uses contrastive scoring by inverse folding models to predict protein variants biased toward desired conformational states. We successfully validated CB across seven diverse datasets, identifying variants of K-Ras, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein, the β2 adrenergic receptor, and Src kinase with improved conformation-specific functions such as enhanced binding or enzymatic activity. Applying CB to the enzyme lipoic acid ligase (LplA), we uncovered a previously unknown mechanism controlling its promiscuous activity. Variants biased toward an “open” conformation state became more promiscuous, whereas “closed”-biased variants were more selective, enhancing LplA’s utility for site-specific protein labeling with fluorophores in living cells. The speed and simplicity of CB make it a versatile tool for engineering protein dynamics with broad applications in basic research, biotechnology, and medicine.

Awards intended to “build the train tracks” for approval of therapies to extend healthy life

New tests gauge whether large language models can use their troves of knowledge to actually make discoveries

The hypothalamic-pituitary-gonadal axis (HPG) controls pubertal development, sexual maturation, and fertility. We identified a role of hypothalamic microglia in controlling the HPG axis through receptor activator of nuclear factor κβ (Rank) signaling. Whole-body and microglia Rank depletion led to hypogonadotropic hypogonadism (HH) resulting from an alteration in gonadotropin-releasing hormone (GnRH) neuron function. In addition, we identified rare gene variants ofRANKin patients with HH. Transcriptional profiling upon Rank loss revealed defective microglia activation and morphological alterations in the median eminence, decreasing the contacts and engulfment of GnRH terminal projections and impairing GnRH neuronal responses to kisspeptin. Overall, our data uncover the microglia as regulator of GnRH neuronal function through Rank signaling, with potential implications for reproductive maturation and fertility.

Profit-seeking investors could align their muncipal bond investments with conservation actions

Site-specific insertion of gene-sized DNA fragments remains an unmet need in the field of genome editing. IS110-family serine recombinases have recently been shown to mediate programmable DNA recombination in bacteria by using a bispecific RNA guide (bridge RNA) that simultaneously recognizes target and donor sites. In this work, we have shown that the bridge recombinase ISCro4 is highly active in human cells and provided structural insights into its enhanced activity. Using plasmid- or all-RNA–based delivery, ISCro4 supports programmable multikilobase excisions and inversions and facilitates donor DNA insertion at genomic sites with efficiencies that exceed 6%. Last, we assessed ISCro4 specificity and off-target activity. These results establish a framework for the development of bridge recombinases as next-generation tools for editing modalities that are beyond the capabilities of current technologies.

Bidders have lined up to take over pieces of the National Center for Atmospheric Research

The state of food security is achieved if no one has to worry whether or how they can acquire—typically purchase—healthy and nutritious meals. In theory, food security could be addressed from two sides: increasing households’ purchasing power or lowering food prices. However, in practice, food insecurity is a by-product of prevailing political and economic systems. Agriculture produces more calories and nutrients than needed to feed humanity, so it is fundamentally an issue of distributive justice, where geography, education, ethnicity, gender, and other mechanisms of marginalization determine one’s food security—through access to wealth. Yet humanity has failed to eliminate poverty and instead of addressing socioeconomic causes of food insecurity, agricultural research and practice are called upon to compensate. This is not only unfair but bound to fail. It also diverts muchneeded scientific capacity from the long list of sustainability challenges that agricultural production systems must address.

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Global warming is altering the fisheries that underpin food security, but projections of these impacts generally exclude evolutionary processes. We describe a model that forecasts how fish will adapt to future climates and the consequences of that evolution for fisheries yields. We predict that fish in warmer waters will grow faster but evolve earlier maturation, decreasing their maximum size. We predict that evolution ameliorates the impacts of climate change on fish fitness but exacerbates its impacts on fisheries yields—worsening losses by ~50%. Excluding evolution overestimates future yields under all emissions scenarios, but evolution’s impacts are greatest under the most extreme scenarios. All life histories may evolve in response to global change—this evolution should be considered in projections of ecosystems and their services.

Recovery of wildflower populations from extreme drought reveals hidden evolutionary resilience

Developmental gene function is often conserved over deep time, but cis-regulatory sequence conservation is difficult to identify. Rapid sequence turnover, paleopolyploidy, structural variation, and limited phylogenomic sampling have impeded conserved non-coding sequence (CNS) discovery. Using Conservatory, an algorithm that leverages microsynteny and iterative alignments to map CNS-gene associations over evolution, we uncovered ~2.3 million CNSs, including over 3,000 predating angiosperms, from 284 plant species spanning 300 million years of diversification. Ancient CNSs were enriched near developmental regulators, and mutating CNSs nearHOMEOBOXgenes produced strong phenotypes. Tracing CNS evolution uncovered key principles: CNS spacing varies, but order is conserved; genomic rearrangements form new CNS-gene associations; and ancient CNSs are preferentially retained among paralogs, but are often lost as cohorts or evolve into lineage-specific CNSs.

Drugs that inhibit KRAS signaling delay the development of pancreatic cancer in mice

Scavengers generally rely on patchily distributed, unpredictable carrion. A long-standing hypothesis suggests scavenging ravens reliably locate such food by directly following large carnivores to their kills. However, by satellite tracking 69 ravens, 20 wolves, and 11 cougars in Yellowstone National Park, we found that following of predators over large distances rarely occurred. Instead, ravens routinely revisited sites where wolf kills were common—returning from distances of up to 155 kilometers to find carrion. Much like navigating to permanent anthropogenic subsidies, ravens appear to remember potential sources of carrion shaped by previous encounters with wolves or their kills. These findings suggest that spatial memory and navigation play a considerably greater role than previously assumed among scavengers, and possibly other wide-ranging species, in search of ephemeral resources.

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Warming oceans and evolution make fish less likely to be on the menu

Single-cell sequencing methods uncover natural and induced variation between cells. Many functional genomic methods, however, require multiple steps that cannot yet be scaled to high throughput, including assays on living cells. In this study, we developed capsules with amphiphilic gel envelopes (CAGEs), which selectively retain cells and large analytes while being freely accessible to media, enzymes, and reagents. Capsules enable high-throughput multistep assays combining live-cell culture with genome-wide readouts. We established methods for barcoding CAGE DNA libraries and applied them to measure persistence of gene expression programs in cells by capturing the transcriptomes of tens of thousands of expanding clones in CAGEs. The compatibility of CAGEs with diverse enzymatic reactions will facilitate the expansion of the current repertoire of single-cell high-throughput measurements and their extension to live-cell assays.

Mapping behavior of individual vertebrate animals across lifespan could provide an unprecedented view into the lifelong process of aging. We created a platform for high-resolution continuous behavioral tracking of the African killifish across natural lifespan from adolescence to death. We found that animals follow distinct individual aging trajectories. The behaviors of long-lived animals differed markedly from those of short-lived animals, even relatively early in life, and were linked to organ-specific transcriptomic shifts. Machine-learning models accurately inferred age and even forecasted an individual’s future lifespan, given only behavior at a young age. Finally, we found that animals progressed through adulthood in a sequence of stable and stereotyped behavioral stages with abrupt transitions, revealing precise structure for an architecture of aging.

Highly pathogenic avian influenza viruses (HPAIVs) derive from H5 and H7 low pathogenic avian influenza viruses (LPAIVs). Although insertion of a furin-cleavable multibasic cleavage site (MBCS) in the hemagglutinin gene was identified decades ago as the genetic basis for the LPAIV-to-HPAIV transition, the mechanisms underlying the occurrence of insertion are unknown. Here, we show that transient H5 RNA structures, predicted to trap the influenza virus polymerase on purine-rich sequences, drive nucleotide insertions, providing empirical evidence of RNA structure involvement in MBCS acquisition. Introduction of H5-like sequences and structures into an H6 hemagglutinin resulted in MBCS-yielding insertions. Our results show that nucleotide insertions that underlie H5 HPAIV emergence result from an RNA structure–driven diversity-generating mechanism, which could also occur in other RNA viruses.

In many algae, photosynthesis is boosted by biophysical CO2-concentrating mechanisms, which pack the CO2-fixing enzyme Rubisco into liquid-like organelles called pyrenoids. Engineering C3crops with algal pyrenoids could increase yields, but progress is hampered by the deep evolutionary divide between crops and algae. Here, we show that hornworts, the only land plants with pyrenoids, have an unusual Rubisco small subunit, RbcS-STAR, the C-terminal coiled-coil domain of which oligomerizes to mediate Rubisco condensation. RbcS-STAR is incorporated into the Rubisco holoenzyme and thus acts as an “innate” Rubisco linker. Expression of RbcS-STAR in pyrenoid-lacking species, includingArabidopsis, is sufficient to induce pyrenoid-like condensates. Our findings reveal a mechanism for Rubisco condensation and a potential route to introduce pyrenoids into crop plants.

The emergence of a chemical system capable of self-replication and evolution is a critical event in the origin of life. RNA polymerase ribozymes can replicate RNA, but their large size and structural complexity impede self-replication and preclude their spontaneous emergence. Here, we describe QT45, a 45-nucleotide polymerase ribozyme, discovered from random sequence pools, that catalyzes general RNA-templated RNA synthesis using trinucleotide triphosphate (triplet) substrates in mildly alkaline eutectic ice. QT45 can synthesize both its complementary strand using a random triplet pool at 94.1% per-nucleotide fidelity and a copy of itself using defined substrates, both with yields of ~0.2% in 72 days. The discovery of polymerase activity in a small RNA motif suggests that polymerase ribozymes are more abundant in RNA sequence space than previously thought.

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Ferroelectricity at atomic-scale thickness would have important applications in next-generation electronics. Here, we report that a ferroelectric phase can be stabilized in titanium dioxide (TiO2) films, a commonly known dielectric widely used in semiconductor technologies, by reducing thickness below 3-nm. Importantly, this ferroelectricity persists down to one nanometer thickness, approximately twice the unit-cell dimension. This thickness-dependent dielectric-to-ferroelectric phase transition demonstrates that an otherwise centrosymmetric, non-ferroic fluorite-structure oxide can undergo structural inversion-symmetry breaking and exhibit voltage-switchable polarization. Atomic-layer deposition (ALD) based low-temperature (below 400 Celsius) synthesis and the stability of this ferroelectricity on both Si and amorphous surfaces (such as amorphous SiO2, amorphous carbon films) demonstrate the feasibility of integration with a large variety of materials.

An updated visual assessment tool can bridge the gap between climate research and political action

Stereoisomers of C13Cl2exhibiting helical orbitals around a ring of carbon atoms were synthesized by atom manipulation on NaCl surfaces. We resolved the enantiomeric geometries of the singlet states by atomic force microscopy and mapped their helical orbital densities by scanning tunnelling microscopy. A π-orbital basis of the helical, non-planar singlets that twists by 90° in one circulation is consistent with a half-Möbius topology. In such a topology, the π-orbital basis changes sign with respect to two circumnavigations and is periodic with respect to four circumnavigations. A quasiparticle on a ring with this boundary condition could be interpreted as carrying a Berry phase of π/2. We demonstrate reversible switching of the topology, between the two singlets of oppositely threaded half-Möbius topology, and the planar, topologically trivial, triplet state. Multireference calculations, including large-scale sample-based ab initio calculations executed on quantum hardware, reveal that the switching is associated with a helical pseudo Jahn-Teller effect.

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Over the last year, the Trump administration has sent one discouraging message after another to young people aspiring to a scientific career in the United States. The corrosive rhetoric that mocks scientific expertise and the proposed—and realized—cuts to funding are driving students away from scientific careers that may no longer exist by the time they graduate. Making matters even worse, cutbacks in visas awarded to foreign students are eroding the opportunities for young American scientists to work with the most talented people in the world. There is perhaps no stronger evidence of the administration’s objectives to reduce the quality of the US scientific workforce than its treatment of the National Science Foundation’s flagship Graduate Research Fellowship Program (GRFP).

The warning signs included a web search, a mother’s doubts, and inklings of a “sexist attitude”

Wildfires, insect outbreaks, and storms cause large pulses of tree mortality. Climate change amplifies these forest disturbances, yet their future magnitude and extent remain uncertain. Here, we simulated future forest disturbance regimes at 100-meter resolution across Europe using a deep learning–based simulation framework. Our results show that forest disturbances will continue to increase throughout the 21st century, with disturbed areas more than doubling relative to the recent past under an unabated continuation of climate change. Wildfires are the main agent driving future disturbance change. Changing disturbances result in an increase in young forests, substantially altering Europe’s forest demography. Because of their profound implications for forest carbon storage and the habitat value of forest ecosystems, disturbances should be a priority of forest policy and management.

Polymer thermoelectrics offer an inherently soft, cost-effective, and lightweight solution to convert ubiquitous heat sources into sustainable electricity. However, their realistic applications are hindered by insufficient performance and the scaling complexity. We introduce irregular hierarchical-porous thermoelectric polymers, featuring irregularly shaped and distributed pores with diameters that range from less than 10 nanometers to micrometers. This porous structure not only enhances multiple phonon-like scattering, achieving a 72% reduction in lattice thermal conductivity, but also unexpectedly improves charge transport through nanoconfinement-enhanced crystallization. The optimized film yields a benchmark figure-of-meritzTof 1.64 at 343 kelvin. Moreover, this method is compatible with easy-to-process spray-coating techniques.

Large study shows simplifying delivery of prevention medication and improving connections to clinics is key

European regulators greenlight new one-dose compound that could help Africa get rid of an ancient burden

The utility model offers a framework for ethical stewardship, patient empowerment, and distributed innovation

Editors’ selections from the current scientific literature

A linker moiety built into the enzyme Rubisco in an early land plant boosts carbon assimilation

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A structure-based approach identifies bacteriophage proteins that block bacterial immunity

Nucleoside analogs (NAs) are essential as antiviral and anticancer therapies. Despite decades of focused medicinal chemistry efforts, their related chemical space remains underexplored, mainly due to their lengthy, single-molecule-oriented syntheses that lack the flexibility required to generate NA libraries. Here we report a flexible, robust, and efficient platform for the high-throughput synthesis of NAs using a photoredox coupling strategy. This approach produces both C- and N-linked NAs, and unifies the synthesis of several disparate NA classes, including 4′-thio, 4′-imino, and ProTides, all from a simple, scalable intermediate. Using this platform, we demonstrate the production of a diverse NA library and identify several hit compounds with anti-HIV-1 activity. We expect this new approach to NAs will inspire and support drug discovery efforts in this area.

Leaders acknowledge White House role in recent controversial moves

Alzheimer’s disease (AD) is the leading cause of dementia and is characterized by progressive amyloid accumulation followed by tau-mediated neurodegeneration. Despite advances in anti-amyloid immunotherapies, important limitations remain, highlighting the need for new therapeutic strategies. Here, we introduce anti-amyloid chimeric antigen receptors expressed in astrocytes (CAR-A) and validate their function in vitro. We show that two CAR-A designs reduce amyloid and associated pathology after plaque formation and prevent early plaque deposition in vivo. Single-nucleus RNA sequencing shows that CAR-A treatment induces a distinct glial response to amyloid pathology involving coordinated activity of astrocytes and microglia. Each construct additionally elicits distinctive, receptor-specific effects in astrocytes or microglia. Together, these findings support the therapeutic potential of CAR-A as a disease-modifying strategy for AD.

Proposed rule at National Institute of Standards and Technology would limit lab access to a few years

The mechanistic target of rapamycin (mTOR) protein kinase forms two multiprotein complexes, mTORC1 and mTORC2, that function in distinct signaling pathways. mTORC1 is regulated by nutrients, and mTORC2 is a central node in phosphoinositide-3 kinase (PI3K) and small guanosine triphosphate Ras signaling networks commonly deregulated in cancer and diabetes. Although mTOR phosphorylates many substrates in vitro, in cells, mTORC1 and mTORC2 have high specificity: mTORC2 phosphorylates the protein kinases Akt and PKC, but not closely related kinases that are mTORC1 substrates. To understand how mTORC2 recognizes substrates, we created semisynthetic probes to trap the mTORC2 :: Akt complex and determine its structure. Whereas most protein kinases recognize amino acids adjacent to the phosphorylation site, local sequence contributes little to substrate recognition by mTORC2. Instead, the specificity determinants were secondary and tertiary structural elements of Akt that bound the mTORC2 component mSin1 distal to the mTOR active site and were conserved among at least 18 related substrates. These results reveal how mTORC2 recognizes its canonical substrates and may enable the design of mTORC2-specific inhibitors.

Self-amplifying RNA (saRNA) enables sustained protein expression from a single administration. In this study, we developed an intramuscular saRNA-lipid nanoparticle (saNppa-LNP) therapy encoding natriuretic peptide type A (Nppa) for cardioprotection. A single injection induced sustained pro–atrial natriuretic peptide (pro-ANP) secretion for 4 weeks; pro-ANP was subsequently cleaved by the cardiac protease corin into active ANP, producing robust cardioprotection in mouse and swine myocardial infarction models. At equivalent doses, saNppa achieved greater efficacy than conventional mRNA. Single-nucleus transcriptomics identified natriuretic peptide receptor 1–positive (Npr1+) endothelial and epicardial cells as primary effectors, with saNppa-LNPs reshaping their paracrine profile to promote cardiomyocyte regeneration and suppress fibrosis. Longitudinal biosafety assessments revealed no systemic toxicity. Together, these results demonstrate that one-shot saNppa-LNP therapy offers durable cardioprotection, supporting the broader potential of saRNA-LNP–based approaches for cardiac therapy.

Self-amplifying RNA improves heart function after myocardial infarction in mice and pigs

Mitigating climate change requires broad societal buy-in. Integrated assessment models (IAMs) produce cost-optimal pathways, but these are complex and not easily customized to reflect individuals’ preferences. Twenty years ago, the stabilization wedge framework introduced a simpler way to discuss decarbonization. Here, we modernized this framework, identifying 36 strategies, each with the potential to mitigate 4% of global emissions by 2050, and quantified their required scale of deployment. People can build personalized decarbonization pathways by choosing a portfolio of these strategies, with more than 6 trillion combinations that are able to limit global warming to 1.5°C. We assessed which strategies IAMs favor and found that they prioritize technological over behavioral and nature-based solutions, with limited agreement. This framework empowers a general audience to construct and debate pathways, by making informed choices that reflect objectives beyond cost-optimization.

Population bottlenecks can lead to evolutionary dead ends by eroding genetic diversity and intensifying inbreeding. Although theory predicts possible escape routes, direct observations of this process are rare. Using whole-genome data from 418 koalas, we found that populations with higher genetic diversity harbored the greatest mutational loads and had declining effective population sizes (Ne), whereas historically bottlenecked but recovering populations displayed reduced mutational load, exhibited increasingNe, and regenerated new, rare variants. We concluded that this pattern was due to rapid demographic expansion, which reshuffled genetic variation through recombination and affectedNemore quickly than it did conventional diversity metrics. Our findings suggest that recovery of bottlenecked populations can occur through rapid demographic growth and that this can reestablish evolutionary potential in threatened populations.

Inflorescences of flowering plants adopt diverse genetically programmed and environmentally tuned architectures. By contrast, continued maintenance of the stem cell pool within the apical meristem is unresponsive to environmental cues. Through a combination of modeling and experimentation inArabidopsis, we reveal a negative feedback loop that buffers environmental signals. This loop comprises the determinacy-promoting pioneer transcription factor LEAFY (LFY) and the indeterminacy-promoting transcriptional corepressor TERMINAL FLOWER1 (TFL1). At the transition to the flower-producing reproductive phase, LFY directly and quantitatively up-regulates expression ofTFL1. TFL1 in turn negatively feeds back onLFYto prevent LFY overaccumulation. This blocks inflorescence termination even under strong florally inductive signals. Our work uncovers a mechanism for robust environmental buffering involving differential responses of two cell populations to the same environmental stimulus.

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Genetically altered astrocytes reduce a cardinal pathological feature of Alzheimer’s disease

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Induced pluripotent stem cells could help treat diseased hearts and brains

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Aging or injury to the joints can lead to cartilage degeneration and osteoarthritis (OA), for which there are limited effective treatments. We found that expression of 15-hydroxy prostaglandin dehydrogenase (15-PGDH) is increased in the articular cartilage of aged or injured mice. Both systemic and local inhibition of 15-PGDH with a small-molecule inhibitor (PGDHi) led to regeneration of articular cartilage and reduction in OA-associated pain. Using single-cell RNA-sequencing and multiplexed immunofluorescence imaging of cartilage, we identified the major chondrocyte subpopulations. Inhibition of 15-PGDH decreased hypertrophic-like chondrocytes expressing 15-PGDH and increased extracellular matrix–synthesizing articular chondrocytes. Cartilage regeneration appears to occur through gene expression changes in preexisting chondrocytes, rather than stem or progenitor cell proliferation. 15-PGDH inhibition could be a potential disease-modifying and regenerative approach for osteoarthritis.

Immune systems in animals, plants, and bacteria often rely on intracellular nucleotide signaling, which viruses can block by sequestering or degrading these signals. We identified structural and biophysical traits shared by diverse viral antidefense proteins and used these traits to develop a computational pipeline that predicts phage proteins whose role is to manipulate bacterial immune signaling. Experimental validation revealed three previously uncharacterized protein families—Sequestin, Lockin, and Acb5—that inhibit the Thoeris system and the cyclic oligonucleotide–based antiphage signaling system (CBASS). Sequestin and Lockin act as nucleotide “sponges,” binding 1″–3′ glycocyclic adenosine diphosphate–ribose (3′cADPR) and histidine conjugated to ADPR (His- ADPR), whereas Acb5 cleaves cyclic guanosine monophosphate–adenosine monosphosphate (3′3′-cGAMP) and related molecules. Structural and mutational analyses explain their binding and catalytic mechanisms. Thousands of homologs occur in phage genomes, highlighting the abundance and diversity of viral strategies to subvert nucleotide-based immunity.

Natural selection can drive the evolution of similar traits through convergent evolution. Short peptides identical to the vertebrate hormone bradykinin (BK) have been reported from the venoms and skin secretions of certain species of wasps (order Hymenoptera) and frogs (order Anura), respectively. In this study, we demonstrate that the genes encoding the BK-like peptides of hymenopteran venoms and anuran skin secretions do not share common ancestry with that of the vertebrate hormone but instead independently evolved multiple times from peptide toxin genes. These peptides serve a defensive function against vertebrate predators and their resemblance to BK was driven by selection for efficacy at the predators’ receptors. Our findings highlight how natural selection can drive repeated convergent evolution of similar molecules across distantly related lineages.

How does the brain optimize sensory information for decision-making in new tasks? One hypothesis suggests that learning reduces redundancy in neural representations to improve efficiency, whereas another, based on Bayesian inference, predicts that learning increases redundancy by distributing information across neurons. We tested these hypotheses by tracking population responses in macaque cortical area V4 as monkeys learned visual discrimination tasks. We found strong support for the Bayesian predictions: Task learning increased redundancy in neural responses over weeks of training and within single trials. This redundancy did not reduce information but instead increased the information carried by individual neurons. These insights suggest that sensory processing in the brain reflects a generative rather than discriminative inference process.

Move comes amid effort to grow the country’s own journals

Highlights from theSciencefamily of journals

Colonization of plant roots by symbionts requires substantial morphodynamic reorganization. Examples are actin-scaffolded microcompartments called infection pockets formed during root nodule symbiosis (RNS) by legumes. We demonstrate that the actin-binding formin SYFO2 is indispensable for rhizobial infection inMedicago truncatula, where it drives actin polymerization in phase-separated and symbiosis-specific nanodomains. SYFO2 also regulates symbiotically active arbuscules formed during mycorrhizal symbiosis in plants outside the nodulating clade, indicating that it was additionally recruited to promote rhizobial infections in legumes. As part of our aim to enable nitrogen fixation in nonlegumes, we activated endogenousSYFO2by stably introducing the RNS master regulator NODULE INCEPTION (NIN) into the natural nonhost tomato. This demonstrates the possibility of recruiting arbuscular mycorrhizae–related genes into an engineered nodulation-specific pathway.

A wealthy family fighting its own disease boosted research on a little-studied brain protein, progranulin. Can it spur new dementia treatments?

Chromosomal inversions are often implicated in divergence between distinct ecotypes, but their role in maintaining continuous adaptive divergence in complex traits remains poorly understood. Using quantitative and population genetics, transcriptomics, and artificial selection experiments, we demonstrate how inversions enable clinal adaptive divergence along a steep environmental gradient despite extensive gene flow in a widely distributed marine fish. We show that three inversions are associated with multiple adaptive traits and harbor the strongest signatures of divergent selection in the genome, implying a crucial adaptive role. These inversions exhibit contrasting selection signatures across latitudes, suggesting that they control distinct aspects of the same complex traits and facilitate adaptation in a modular way to different environmental pressures despite gene flow.

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AbstractRelating billions of proteins across the tree of life remains a challenging task for comparative biosphere genomics and artificial intelligence-driven structure prediction. Here we present DIAMOND DeepClust, a cascaded, ultra-fast clustering method enabling planetary-scale organization of protein space, scaling to trillions of sequences while retaining sensitivity at low identity. Aggregating 19 billion biosphere proteins into 544 million nonsingleton clusters, we show that using our DeepClust database, available for download, can enhance structure prediction with AlphaFold2.

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AbstractBottom-up proteomics relies predominantly on collision-induced dissociation (CID) for peptide sequencing, which has achieved remarkable sensitivity and efficiency now enabling single-cell analysis. However, CID shows limitations in characterizing post-translational modifications and complex proteoforms. Here we have developed an integrated mass spectrometry platform enabling automated collision-, electron- and photon-based fragmentation techniques. Using multi-enzyme deep proteomics workflows, we generated comprehensive datasets to train a unified Prosit deep learning model predicting spectra across all dissociation methods. This publicly available model, now integrated into FragPipe’s MSBooster module, increased protein identifications by >10% on average for both data-dependent and data-independent acquisition across all fragmentation techniques. We demonstrate that alternative approaches, particularly electron-induced and ultraviolet photodissociation, which generate richer, more informative spectra, achieve identification efficiency competitive with CID while providing superior sequence coverage. This work establishes a framework enabling routine application of advanced fragmentation techniques in standard proteomics pipelines.

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AbstractTissue clearing has been widely used for fluorescence imaging of fixed tissues, but its application to live tissues has been limited by toxicity. Here we develop minimally invasive optical clearing media for fluorescence imaging of live mammalian tissues. Light scattering is minimized by adding spherical polymers with low osmolarity to the extracellular medium. A clearing medium containing bovine serum albumin (SeeDB-Live) is compatible with live cells, enabling structural and functional imaging of live tissues, such as spheroids, organoids, acute brain slices and the mouse brains in vivo. SeeDB-Live minimally affects neuronal electrophysiological properties and sensory responses in vivo, and facilitates fluorescence imaging of deep cortical layers in live animals without detectable toxicity to neurons or behavior. We further demonstrate its utility to epifluorescence voltage imaging in acute brain slices and in vivo preparations. Thus, SeeDB-Live expands both the depth and modality range of fluorescence imaging in live mammalian tissues.

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AbstractStructured RNAs play many roles in cells and emerging biotechnology. While large RNAs and ribonucleoprotein complexes often benefit from high-resolution structural analysis through cryogenic-sample electron microscopy (cryoEM), single-domain RNAs, particularly those smaller than ~100 nt (33 kDa), have proven challenging. Here we address this methodological gap by engineering two- and fourfold symmetric scaffolds that enable de novo structure solution of covalently attached RNA guests to beyond 3 Å overall resolution for the best resolved guests. We apply C2 and D2-symmetric scaffolds to post-transcriptionally unmodified tRNAAsp, the fluorogenic aptamer Mango-III, and previously uncharacterized quinine- and 8-oxoguanine-binding aptamers. Experimental Coulomb potential maps with quality sufficient for small-molecule ligand, cation and water molecule placement reveal the molecular basis for specificity and suggest routes for structure-guided RNA engineering. Optimized scaffolds with intrinsic quaternary structure are a new general tool to interrogate the atomistic architecture of natural and designed compact RNA folds by single-particle cryoEM.

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AbstractThe big data era in biology is underway, but the study of organismal form has been slow to capitalize on advances in imaging and computation. Imaging approaches can digitize whole organisms, but low throughput has limited the effort to document morphological diversity. Here, within the open science initiative ‘Antscan’, we applied high-throughput synchrotron X-ray microtomography to capture phenotypes across a diverse and ecologically dominant insect group: ants. Athttps://www.antscan.info, we provide 2,193 whole-body three-dimensional ant datasets from 212 genera and 792 species to broadly cover the ant phylogeny with a global scope, also pairing phenomic data with genome sequencing projects. Scans acquired with standardized parameters facilitate automated analysis, and free access to data can broaden the audience and incentivize methods development. Antscan presents a scalable approach to create libraries of diverse anatomies, heralding an era of studies on the evolution, structure and function of organismal phenotypes.

AbstractThe entorhinal cortex–hippocampal network plays a key role in the processing, storage and retrieval of contextual information. However, how convergent multimodal information provided by the lateral and medial entorhinal cortex (LEC and MEC) is represented by granule cells (GCs), the principal cells of the dentate gyrus (DG), remains poorly understood. In this study, we employed two-photon calcium imaging of LEC and MEC projections in the DG together with GC population activity in mice navigating familiar and novel virtual environments over five consecutive days. We found that LEC inputs primarily convey olfactory information, whereas MEC inputs provide rich context-specific information to the DG. Although environmental representations rapidly emerged in LEC and MEC projections upon exposure to novel environments and remained stable over time, representations in the DG improved gradually and required repeated exposure to stabilize. Our findings suggest that the convergence of rapidly emerging, high-dimensional LEC and MEC inputs into a sparse and slowly evolving GC population code provides an energy-efficient mechanism for generating multimodal, modality-specific and context-specific representations in the DG.

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AbstractNeural cells in the adult human central nervous system (CNS) display extensive transcriptional heterogeneity. How different layers of epigenetic regulation underpin this heterogeneity is poorly understood. Here we profile, at the single-nuclei epigenomic level, distinct regions of the adult human CNS, for chromatin accessibility and simultaneously for the histone modifications H3K27me3 and H3K27ac. We unveil a putativeSOX10enhancer and primed chromatin signatures at HOX loci in spinal-cord-derived human oligodendroglia (OLG) and astrocytes, but not microglia. These signatures in adult OLG were reminiscent of developmental profiles but were decoupled from robust gene expression. Moreover, using high-resolution Micro-C, we show that induced pluripotent stem-cell-derived human OLGs exhibit a HOX chromatin architecture compatible with the primed chromatin in adult OLGs, bearing a strong resemblance not only to OLG developmental architecture but also to high-grade pontine gliomas. Thus, epigenetic memory from developmental states in adult OLG not only enables them to promptly transcribe Hox family genes during regeneration but also makes them susceptible to gliomagenesis.

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AbstractNeuropeptides are functionally diverse signaling molecules in the brain, regulating a wide range of basal bodily and cognitive processes. Despite their importance, the distribution and function of neuropeptides in the human brain remains underexplored. Here we comprehensively map the organization of human whole-brain neuropeptide receptors across multiple levels of description, including molecular and cellular embedding, mesoscale connectivity and macroscale cognitive specialization. Using gene transcription as a proxy, we reconstruct a topographical cortical and subcortical atlas of 38 neuropeptide receptors across 14 different neuropeptide families. We find that most neuropeptide receptors are highly expressed either in the cortex or subcortex, delineating an anatomical cortical–subcortical gradient. Mapping neuropeptide receptors onto hypothalamic nuclei, we demonstrate that neuropeptide receptor gene expression recapitulates fundamental anatomical divisions in the hypothalamus. Neuropeptides preferentially colocalize with metabotropic neurotransmitters, suggesting a system-wide correspondence between slow-acting molecular signaling mechanisms. To investigate the behavioral consequences of distributed neuropeptide systems, we apply meta-analytical decoding to neuropeptide maps and show a spectrum of functions, from sensory-cognitive to reward and bodily functions. Finally, using evolutionary analysis we find extended positive selection for neuropeptides in early mammals, suggesting that refinement of neuropeptides coincides with the emergence of neocortex and higher cognitive function. Collectively, these results show that neuropeptide receptors are highly organized across the human brain and closely intertwined with multiple features of brain structure and function.

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AbstractHow does brain network architecture balance cooperation and competition between distributed circuits? Here we use computational whole-brain modeling to examine the dynamical and computational relevance of cooperative and competitive interactions in the mammalian connectome. Across human, macaque and mouse, we show that to faithfully reproduce brain activity, model architecture consistently combines modular cooperative interactions with diffuse, long-range competitive interactions. Across species, competitive interactions preferentially link regions characterized by opposite profiles of cytoarchitecture, gene expression and receptor expression. The model with competitive interactions provides superior subject specificity, consistently outperforming the cooperative-only model and exhibiting excellent fit to the spatiotemporal properties of the living brain. These properties were not explicitly optimized, instead emerging spontaneously. Competitive interactions in the generative connectivity produce more synergistic and hierarchical dynamics, leading to enhanced performance for neuromorphic computing. Altogether, this work provides a generative link among network architecture, dynamical properties and computational performance in the mammalian brain.

AbstractVisual neurons respond to a vast range of images, from textures to objects, but the rules linking these responses remain unclear. Although tuning to simple features is well established in the primary visual cortex, this framework breaks down in higher areas, where neurons encode diverse and unpredictable features. To ask what features neurons prioritize, we used generative models (deep networks that synthesize new images from a learned latent space), allowing neurons in V1, V4 and the posterior inferotemporal cortex (PIT) to guide image synthesis through closed-loop optimization. We compared models that emphasize texture versus those that emphasize object structure. Although V1 and V4 aligned more strongly with texture-based spaces, many PIT neurons responded equally well to both types of optimized images, revealing a focus on shared local motifs rather than whole-object templates, and this alignment to objects emerged later in their response. These findings reveal coding principles across the ventral stream and clarify the limits of current vision models.

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AbstractAlthough inflammatory processes in rheumatoid arthritis have been described, mechanisms driving pain are poorly defined. Here, we used a multitude of approaches to uncover the neural basis and causes of inflammatory pain. We show in mice with cartilage autoantibody-induced arthritis that early immune activation and a cytokine storm were mainly driven by vascular cells and monocytes/macrophages in the dorsal root ganglion. However, persistently elevated interferons and receptor activation of the MNK1/MNK2–eIF4E signaling pathway at all disease phases caused sensory–motor dysfunction and pain by inducing hyperexcitability and sensitization of a GFRA3+C-fiber subtype of joint-innervating sensory neurons. Signaling pathway inhibition in vivo reversed pain and restored limb function. Like mice, human sensory neurons expressed interferon receptors, and type 1 interferons and signaling were increased only in individuals with painful rheumatoid arthritis. The finding that joint pain before and during arthritis is caused by a defined cytokine and signaling pathway holds promise for targeted therapies for pain relief in arthritis.

AbstractMentalization, inferring others’ emotions and intentions, is crucial for human social interactions and is impaired in various brain disorders. While previous neuroscience research has focused on static mentalization strategies, we know little about how the brain adaptively selects which strategies to use at any given moment. Here we investigate this core aspect of mentalization with computational modeling and functional magnetic resonance imaging (fMRI) during interactive strategic games. We find that most participants can adapt their strategies to the changing sophistication of their opponents, though there are considerable individual differences. Model-based fMRI analyses identify a distributed brain network in which activity and connectivity track this mentalization-belief adaptation. The extent to which people update their beliefs about others’ sophistication can be predicted out of sample from neural activity, providing a neural signature of adaptive mentalization. Our model elucidates the neural basis of mentalization ability and provides a method for assessing these capabilities in healthy and clinical populations.

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AbstractFrom spider dances to human language, multimodality is ubiquitous in natural communication systems. Much scholarship has been devoted to investigating why multimodality evolved and the role it plays in communication. Here, we highlight the role of multimodality in safeguarding the most fundamental prerequisite of all functioning, extant communication systems: honesty. We begin by introducing the arms race between honesty and deception in natural communication systems, and the critical role socially-mediated controls can play in maintaining signal honesty when classic, intrinsic costs are not sufficient. We next introduce three ways by which multimodality buffers signal honesty by 1) providing insurance against signal unreliability in dynamic environments, 2) forming an honest, multimodal gestalt with which to cross-validate signal honesty, and 3) increasing signal complexity, making the entire signal harder to fake. We then discuss the case of highly cooperative societies, with human language emphasized, and argue that signal honesty is important especially in complex and cooperative societies wherein the need to cooperate and be accepted as part of the group may supersede honesty. Finally, we propose future directions wherein human and non-human communication research could expand beyond the well trodden realms of competition and mate attraction to investigate the role of multimodality and honesty in cooperative, “cheap” signals, and emphasize the importance of drawing from both the human and non-human literatures in investigating the forces that have shaped the evolution of communication.

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AbstractTelomeres are protective DNA caps at chromosome ends that prevent cells from mistakenly recognizing them as broken DNA. These structures are safeguarded by a protein complex called Shelterin, particularly through the TRF2 protein encoded by Trf2. Surprisingly, in mouse embryonic stem cells, TRF2 is not essential for telomere protection, suggesting that other mechanisms compensate for its loss. Here we show that a cellular quality control system called nonsense-mediated mRNA decay (NMD), which normally eliminates defective RNA molecules, plays an unexpected role in maintaining telomere integrity in pluripotent cells. Through a genome-wide genetic screen, we discovered that NMD is essential for cell survival when TRF2 is absent. NMD accomplishes this by degrading an aberrant form of the messenger RNA encoded by Trf1, which produces the TRF1 protein, another Shelterin component. Without NMD, this aberrant RNA produces a truncated, harmful version of TRF1 that interferes with normal telomere protection. Our findings reveal that embryonic stem cells use a unique strategy for chromosome end protection, linking RNA quality control to genome stability in a previously unrecognized way.

AbstractLipids and proteins compartmentalize biological membranes into nanoscale domains, which are crucial for signalling, intracellular trafficking and many other cellular processes. Studying nanodomain function requires the ability to measure protein and lipid localization at the nanoscale. Current methods for visualizing lipid localization do not meet this requirement. Here we introduce a correlative light and electron microscopy workflow to image lipids (Lipid-CLEM), combining near-native lipid probes and on-section labelling by click chemistry. This approach enables the quantification of relative lipid densities in membrane nanodomains. We find differential partitioning of sphingomyelin into intraluminal vesicles, recycling tubules and the boundary membrane of the early endosome, representing a degree of nanoscale organization previously observed only for proteins. We anticipate that our Lipid-CLEM workflow will greatly facilitate the mechanistic analysis of lipid functions in cell biology, allowing for the simultaneous investigation of proteins and lipids during membrane nanodomain assembly and function.

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AbstractThe paraspeckle is a disease-relevant biomolecular condensate assembled from long non-coding RNA (lncRNA) NEAT1_2 ribonucleoprotein particles. Paraspeckle biogenesis is suppressed in normal tissues, yet it can be rapidly upregulated under stress. Here we demonstrate that a neurodegeneration-linked RNA-binding protein TDP-43 inhibits NEAT1_2 ribonucleoprotein particle condensation into the paraspeckle, in a concentration-dependent manner, which requires its intact polymerization and RNA binding. This effect is counterbalanced by core paraspeckle proteins such as FUS. Below disruptive concentrations, TDP-43 can be recruited into paraspeckles, forming non-liquid clusters. Under stress, TDP-43 sequestration into de novo nuclear condensates alleviates paraspeckle suppression and increases their dynamism. NEAT1_2 middle-part and 3′-end UG repeats mediate paraspeckle regulation by TDP-43 cotranscriptionally and post assembly, respectively. The deletion of the 3′-end UG repeat increases paraspeckle stability and cytoprotection in stressed human neurons. Consistently, longer 3′-end UG repeats are linked to shorter survival in the neurodegenerative disease amyotrophic lateral sclerosis. Thus, TDP-43 is a critical regulator of paraspeckle condensates linked to cytoprotection.

AbstractBiomolecular condensates spatially organize cellular functions, but the regulation of their size, number, dissolution and re-condensation is poorly understood. The pyrenoid, an algal biomolecular condensate that mediates one-third of global CO2fixation, typically exists as one large condensate per chloroplast, but during cell division it transiently dissolves and reconfigures into multiple smaller condensates. Here, we identify a kinase, KEY1, in the model algaChlamydomonas reinhardtiithat regulates pyrenoid condensate size and number dynamics throughout the cell cycle and is necessary for normal pyrenoid function and growth. Unlike the wild type,key1mutant cells have multiple smaller condensates throughout the cell cycle that fail to dissolve during cell division. We show that KEY1 localizes to the condensates and promotes their dissolution by disrupting interactions between their core constituents, the CO2-fixing enzyme Rubisco and its linker protein EPYC1, through EPYC1 phosphorylation. We develop a biophysical model that recapitulates KEY1-mediated condensate size and number regulation and suggests a mechanism for controlling condensate position. These data provide a foundation for the mechanistic understanding of the regulation of size, number, position and dissolution in pyrenoids and other biomolecular condensates.

AbstractCellular adhesion to the extracellular matrix is essential for morphogenesis, tissue integrity and survival signalling. The best understood adhesion structures are focal adhesions (FAs). In spite of their importance, our knowledge of upstream factors that integrate FA dynamics with other cellular processes, such as metabolism, remains fragmentary. Using a genome-wide screen, we identify aldolase A, a key glycolytic enzyme that converts fructose-1,6-bisphosphate (FBP), as a regulatory switch that links metabolic flux to FA assembly and cell morphogenesis. We show that cellular FBP serves as a signalling metabolite, which transmits information about the metabolic cell state to the actin-based machinery for cell adhesion and protrusion. This mechanism involves FBP binding to the Rac1 inhibitor RCC2 and a concomitant elevation of Rac1 activity resulting in actin reorganization, increased FA assembly and elevated protrusive activity. Here we predict this mechanism to be crucial for processes ranging from development to cancer.

AbstractMembrane protection against oxidative insults is achieved by the concerted action of glutathione peroxidase 4 (GPX4) and endogenous lipophilic antioxidants such as ubiquinone and vitamin E. More recently, ferroptosis suppressor protein 1 (FSP1) was identified as a critical ferroptosis inhibitor, acting via the regeneration of membrane-embedded antioxidants. Yet, regulators of FSP1 are largely uncharacterized, and their identification is essential for understanding the mechanisms buffering phospholipid peroxidation and ferroptosis. Here we report a focused CRISPR–Cas9 screen to uncover factors influencing FSP1 function, identifying riboflavin (vitamin B2) as a modulator of ferroptosis sensitivity. We demonstrate that riboflavin supports FSP1 stability and the recycling of lipid-soluble antioxidants, thereby mitigating phospholipid peroxidation. Furthermore, we show that the riboflavin antimetabolite roseoflavin markedly impairs FSP1 function and sensitizes cancer cells to ferroptosis. Our findings provide a rational strategy to modulate the FSP1–antioxidant recycling pathway and underscore the therapeutic potential of targeting riboflavin metabolism, with implications for understanding the interaction of nutrients, as well as their contributions to a cell’s antioxidant capacity.

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AbstractPattern recognition receptor (PRR)-induced interferon (IFN) is critical for effective immunity. The PRRs Toll-like receptor (TLR) 3, TLR4 and cyclic GMP–AMP synthase (cGAS), together with the stimulator of IFN genes (STING), signal through TANK-binding kinase 1 (TBK1), which activates the type-I/III IFN-inducing transcription factor interferon-response factor 3 (IRF3). The mechanism by which these PRRs activate TBK1 remains unresolved. Here we show that lysine-11 (K11)-linked ubiquitination drives TBK1 activation by these PRRs. The E3 ligase ANKIB1 attaches K11-linked ubiquitin chains to components of the TLR3- and cGAS–STING-induced signalosomes. This facilitates Optineurin recruitment to these complexes, in turn enabling recruitment and activation of TBK1 and IRF3, defining an uncharacterized signalling axis. In mice, ANKIB1 deficiency dampens IFN induction via TLR3 and cGAS–STING, reducing interferonopathy and compromising protection against HSV-1, respectively. Together, our results demonstrate an unanticipated and critical role for ANKIB1-generated K11-linked ubiquitination in the immune response activated by cGAS–STING, TLR3 and TLR4.

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