bioRxiv Subject Collection: Neuroscience's Journal

Map of spiking activity underlying change detection in the mouse visual system
Visual behavior requires coordinated activity across hierarchically organized brain circuits. Understanding this complexity demands datasets that are both large-scale (sampling many areas) and dense (recording many neurons in each area). Here we present a database of spiking activity across the mouse visual system--including thalamus, cortex, and midbrain--while mice perform an image change detection task. Using Neuropixels probes, we record from >75,000 high-quality units in 54 mice, mapping area-, cortical layer-, and cell type-specific coding of sensory and motor information. Modulation by task-engagement increased across the thalamocortical hierarchy but was strongest in the midbrain. Novel images modulated cortical (but not thalamic) responses through delayed recurrent activity. Population decoding and optogenetics identified a critical decision window for change detection and revealed that mice use an adaptation-based rather than image-comparison strategy. This comprehensive resource provides a valuable substrate for understanding sensorimotor computations in neural networks.

A simple, open-source restraint system for magnetic resonance imaging in awake rats
Magnetic resonance imaging (MRI) is a critical tool for translational neuroscience, offering cross-species insights into brain structure and function; however, its application in preclinical research is constrained by routine anesthesia use or sedation, which alters neural activity and limits comparisons to awake human imaging. Awake rodent functional MRI (fMRI) provides a powerful platform for investigating brain function under physiologically relevant conditions, but implementation is limited by technical challenges, particularly head motion and stress during scanning. Most restraint systems employ initial anesthesia, compromising translatability of findings, and highlighting the need for improved designs. We developed a novel restraint system optimized for awake rat fMRI. The system consists of modular 3D-printed components and can be assembled in under five minutes. It is accompanied by a protocol that includes head-post implantation followed by an 11-day habituation period post-surgical recovery. The system eliminates the need for isoflurane anesthesia, ear bars, and bite bars, reducing stress and improving animal comfort. It supports integration with behavioral paradigms such as pupil tracking and licking responses. High-resolution T2-weighted anatomical images and functional scans obtained using the system showed excellent spatial clarity and minimal motion artifacts. Quality control metrics, including head motion parameters and temporal signal-to-noise ratio, confirmed the system's stability and suitability for awake imaging. Functional connectivity analysis revealed robust positive correlations between functionally relevant regions. This system offers a scalable, reproducible, and animal-friendly solution for awake rat fMRI. While the current design limits direct cranial access for multimodal recordings, it enables high-quality, behaviorally enriched imaging without anesthesia.

Coarse-graining reveals collective predictive information in a sensory population
Biological systems perform complex computations using hundreds of individual actors, but they do so efficiently and in a way that can be read out and interpreted by other biological networks. Coarse-graining may allow for key collective features to be effectively and efficiently communicated. In the brain, early sensory systems perform prediction, which can compensate for lags in neural processing. This computation is collective, meaning it relies upon interactions between many neurons, and operates in complex, dynamic natural environments. Taking these two facets of biological complexity together, we search for maximally-predictive collective variables in large groups of retinal ganglion cells responding to dynamic natural visual scenes. To find collective variables that best capture predictive computations in the neurons, we apply a tractable, approximate implementation of the information bottleneck method to neural data. We infer a lower-dimensional representation that is maximally informative about the future neural activity. We observe scaling relationships between this mutual information estimate, neural subset size, and information decay timescale. Further, the structure of collective modes changes for predicting at short versus longer timescales.

Topological decoding of grid cell activity via path lifting to covering spaces
High-dimensional neural activity often reside in a low-dimensional subspace, referred to as neural manifolds. Grid cells in the medial entorhinal cortex provide a periodic spatial code that are organized near a toroidal manifold, independent of the spatial environment. Due to the periodic nature of its code, it is unclear how the brain utilizes the toroidal manifold to understand its state in a spatial environment. We introduce a novel framework that decodes spatial information from grid cell activity using topology. Our approach uses topological data analysis to extract toroidal coordinates from grid cell population activity and employs path-lifting to reconstruct trajectories in physical space. The reconstructed paths differ from the original by an affine transformation. We validated the method on both continuous attractor network simulations and experimental recordings of grid cells, demonstrating that local trajectories can be reliably reconstructed from a single grid cell module without external position information or training data. These results suggest that co-modular grid cells contain sufficient information for path integration and suggest a potential computational mechanism for spatial navigation.

A cytosolic function of DNMT1 controls neuronal morphogenesis via microtubule regulation
Proteins traditionally confined to a single cellular compartment are increasingly recognized to exert non-canonical functions in alternative domains. The DNA methyltransferase 1 (DNMT1), classically defined as the maintenance methyltransferase that preserves DNA methylation patterns during replication, exemplifies this versatility. Beyond its canonical role, DNMT1 is highly expressed in the developing and adult brain, where it contributes to transcriptional regulation in postmitotic neurons. Notably, cytoplasmic DNMT1 localization has been observed in neural cells, and emerging evidence links DNMT1 to mitochondrial function with implications for neurodegenerative disease, whereby the underlying functional mechanisms remain to be fully elucidated. Here, we identify a previously unrecognized cytosolic function of DNMT1 in developing cortical excitatory neurons. Through genetic perturbation, proteomics, and high-resolution imaging, we show that DNMT1 regulates dendritic and axonal branching independently of its catalytic activity and nuclear localization. Instead, DNMT1 operates as a cytosolic scaffold interacting with the polarity regulator DOCK7 to modulate Rac1/STMN1 signaling, microtubule dynamics, and organelle trafficking. These findings expand the conceptual framework of DNMT1 from a genome guardian to a dual-compartment regulator that coordinates cytoskeletal remodeling and mitochondrial positioning. Beyond advancing our understanding of neuronal morphogenesis, this work provides mechanistic insight into how DNMT1 mutations may lead to neurodegenerative diseases.

Inhibition of CGRP receptor ameliorates AD pathology by reprogramming lipid metabolism through HDAC11/LXRβ/ABCA1 signaling
The Calcitonin gene-related peptide (CGRP) receptor has gained attention in Alzheimers Disease (AD) research due to its involvement in regulating neuroinflammation. However, its role and mechanism in AD pathology remain unclear. Here, we demonstrate that CALCRL, a core component of the CGRP receptor, is upregulated in the hippocampus of AD dementia patients and 5FAD mice. Knockout of the CGRP receptor ligand Calca or pharmacological blockade using Rimegepant (Rim), reduces soluble A{beta}1-42 oligomer-induced neuronal death and glial inflammation. Rim treatment also rescues neurobehavioral impairments, neurodegeneration, and lipid metabolism dysfunction in 5FAD mice. Mechanistically, these effects are mediated through HDAC11 inhibition, which enhances LXR{beta} acetylation and ABCA1 expression, promoting the reprogramming of neuronal lipid metabolism. Importantly, this CALCRL/HDAC11/LXR{beta}/ABCA1 axis is conserved across both humans and mice. Our findings uncover a novel mechanism underlying AD pathogenesis and highlight the therapeutic potential of targeting CGRP signaling in AD.

Multiarrangement: A Plug & Play Geometric Data CollectionPackage For Video Stimuli
We present Multiarrangement, an offline, open-source Python toolkit for collecting human similarity judgments for video stimuli through multi-arrangement tasks. Participants arrange subsets of stimuli in a 2D arena such that Euclidean distances reflect perceived dissimilarity. The toolkit supports two experiment paradigms: a set-cover scheduling system that uses combinatorial cover designs to guarantee pair coverage with minimal trials, aiming to avoid overwhelming the participant for stimulus-rich settings, and an adaptive Lift-the-Weakest scheduling that focuses each new trial on the globally least certain pair and informative neighbors. Across trials, partial distance evidence is integrated into a representational dissimilarity matrix using normalized weighted averaging, with an optional inverse MDS refinement that minimizes cross-trial prediction error. We document task design, algorithms, evaluations, and provide practical guidance for easy and reliable usage

Policy-Gradient Reinforcement Learning as a General Theory of Practice-Based Motor Skill Learning
Mastering any new skill requires extensive practice, but the computational principles underlying this learning are not clearly understood. Existing theories of motor learning can explain short-term adaptation to perturbations, but offer little insight into the processes that drive gradual skill improvement through practice. Here, we propose that practice-based motor skill learning can be understood as a form of reinforcement learning (RL), specifically, policy-gradient RL, a simple, model-free method that is widely used in robotics and other continuous control settings. Here, we show that models based on policy-gradient learning rules capture key properties of human skill learning across a diverse range of learning tasks that have previously lacked any computational theory. We suggest that policy-gradient RL can provide a general theoretical framework and foundation for understanding how humans hone skills through practice.

CASPR facilitates clearance of degenerating axons by Schwann cells and macrophages after peripheral nerve injury
In the peripheral nervous system (PNS) debris of injured axons is efficiently removed by Schwann cells (SCs) and macrophages (Mphs) - a process which is vital for nerve regeneration. Molecular so-called eat-me signals, mediating axon-SC/axon-Mph crosstalk and debris clearance after injury are just at the beginning of being identified. Herein, we describe the axonal node protein contactin-associated protein (CASPR) as a potential novel signal for axonal debris removal in peripheral nerve injury. In healthy nerves, CASPR is restricted to Ranvier's nodes interacting with glia-derived partner proteins to assure saltatory action potential propagation. In injured murine and human nerves, we describe upregulation and re-localization of CASPR protein along the axons. Enhanced CASPR presence after injury appears to involve local axonal translation rather than transcriptional regulation. Of note, CASPR overexpression in murine central and peripheral neurons in vitro has a growth inhibitory effect. More importantly, axonal debris deriving from injured nerves - and hence having increased CASPR content - are phagocytosed more efficiently than debris of healthy nerves. Interfering with CASPR by function-blocking antibodies strongly reduces axonal debris uptake. This finding demonstrates a functional relevance of CASPR as a potential eat me signal in this process.

The development of the brain was revealed by brain entropy (BEN) during movie watching from the age of three to twelve years
Mapping the developmental landscape of brain function is a key objective in modern neuroscience, greatly advanced by the public release of neuroimaging datasets. Here, we utilized movie-watching fMRI to study brain entropy (BEN) in 3-12-year-olds from OpenNeuro. The results of the analysis revealed that decreasing BEN within the action-mode network (AMN) serves as a key developmental marker in children. The AMN underpins goal-directed cognition, and its entropy reduction may signify a crucial shift from early, externally driven sensorimotor processing toward the emergence of more internalized, self-referential thought processes associated with the default-mode network. These findings highlight BEN as a powerful and sensitive tool for deciphering the principles of functional brain development.

Butyrate rescues chlorpyrifos-induced social deficits through inhibition of class I histone deacetylases
Chlorpyrifos (CPF) is a widely used organophosphate pesticide effective through inhibiting acetylcholinesterase, which leads to the accumulation of acetylcholine and continuous nerve stimulation. In addition to its well-known acute toxicity, exposure to CPF has also been linked to chronic conditions such as an increasing risk of autism spectrum disorder (ASD) and adverse effects on gut health, including disturbances to the gut microbiome and metabolism. However, the underlying mechanism of CPF's contribution to ASD remains unclear, and the roles of the gut microbiome and gut metabolites in CPF-induced neurodevelopmental toxicity remain elusive. Using a high-throughput social behavior assay, we found that embryonic exposure to CPF induced lasting social deficits in zebrafish. Through a small-scale screen of common health beneficial gut microbiome metabolites, we discovered that butyrate effectively rescued CPF-induced social deficits. RNA sequencing of zebrafish brain tissues revealed that early exposure to CPF induced a lasting suppression of neuronal genes, including many ASD risk genes, and elevated expression of circadian genes. Butyrate partially reversed the suppression of key neuronal genes. Butyrate is a non-selective inhibitor of histone deacetylases (HDACs). Through a series of loss-of-function experiments utilizing CRISPR-Cas9-induced knockouts and selective chemical inhibitors, we found that the class I HDAC, HDAC1, most likely mediates butyrate's rescue effect. Metabolomics analysis detected changes in several nitrogen metabolism-related pathways in the zebrafish gut following CPF exposure. Metagenomics analysis revealed an increase in abundance of the denitrifying bacteria Pseudomonas and a reduction in the nitric oxide-sensitive bacteria Aeromonas in the CPF-exposed zebrafish gut microbiome. Our results connect CPF-exposure with changes in the gut microbiome, metabolome, epigenetics, gene expression, and behavior, inspiring a novel hypothesis for the underlying molecular mechanisms of CPF-induced neurodevelopmental toxicity. In the long run, our findings may help elucidate how CPF exposure contributes to autism risk and inspire therapeutic developments.

Corticosterone-linked microglial activity underpins sexually dimorphic neuroplasticity after ketamine anesthesia.
Anesthesia recovery is critical for resuming normal physiological and neuronal functions; however, the mechanisms involved remain elusive. Here, we identify a female-selective corticosterone-mediated microglia-neuron interaction in vivo during ketamine anesthesia recovery, absent in males. This microglia-neuron interaction induces plastic and functional neuronal changes, as evidenced by increased spine density and mEPSC frequency, which is occluded upon microglia depletion. We show that this process is driven through upregulation of the stress-responsive co-chaperone Fkbp5 mRNA and its protein, FKBP51, in female microglia. Fkbp5/FKBP51 is a key intermediary in a corticosteroid-induced stress response, and its involvement points towards a critical interface between endocrine signaling and microglia. Thus, to counteract the observed KXA-mediated corticosterone increase in the blood, we remove the primary source of corticosterone through adrenalectomy. Close microglia-neuron interaction was absent, but was reinstated after corticosterone injection. Our findings offer a new mechanism of microglia-mediated neuronal plasticity during anesthesia recovery, which is mediated through corticosterone, enhancing our understanding of sex differences in brain function.

Selective coupling and decoupling coordinate distributed brain networks for precise action
The mammalian brain is fundamentally interconnected. Across species, a single neuron typically forms thousands of synapses spanning local and long-range connections. This architecture suggests that brain function is distributed, but it remains poorly understood how relevant networks are selectively engaged to produce appropriate behaviors. To address this, we recorded >40,000 neurons, simultaneously monitoring five cerebellar and cerebral brain areas as mice performed complex motor actions, capturing interactions of >5,000,000 cross-area neuron pairs. This revealed that complex pre-movement cross-area interactions coordinate distributed networks to produce precise and consistent actions. Prior to action production, action-informative neural populations across the brain become coupled, while non-informative populations decouple. This coupling and decoupling was mirrored by two distinct local field potential oscillations linking neuron-level to population-level dynamics. External modulation of these dynamics revealed their necessity for skilled action. Our work highlights that a complex pre-movement orchestration of coupling and decoupling ensures the selective engagement of relevant distributed networks to produce precise action.

Patterns of intersubject correlations parallel organizational gradients during naturalistic viewing
Recent studies have robustly demonstrated that human cortical function can be described through sensory-transmodal gradients of cortical function, while naturalistic movie watching paradigms have been leveraged to index cortical synchronization. We leveraged two independent 7T movie fMRI acquisitions to assess correlations between these measures across movies, datasets, and spatial scales. At the whole-brain level, we observed robust relationships between intersubject correlations and a visual-transmodal connectivity gradient which was independent of movie content. Within functional networks, correlations were particularly pronounced for the visual, the dorsal attention, and default mode networks. Our results support the ability of naturalistic paradigms to offer targeted insight into multiscale processing hierarchies. Robust relationships across movies suggest that we might understand movie-watching as a brain state that is independent of movie-content. Overall, this work suggests an important confluence of within-subject functional organizational axes and inter-subject synchronization when the brain is engaged in the processing of naturalistic stimuli.

Electrically Contrasting Periodic Polymer Interfaces Guide Neuronal Networks
The nervous system constitutes a highly ordered, integrated network of cells. Understanding this neuroanatomical architecture in vitro is fundamental to elucidating the cellular computations underlying functional network formation. Neuronal connectivity orchestrated through axonal pathfinding, is an interplay of biochemical signals and electromechanical properties of the growth substrate. This study focusses on how neuronal morphology and networking are affected by the periodic, micrometer-scale patterned stripes of two electrically contrasting polymers - poly(vinylidenefluoride-trifluoroethylene) (PVDF-TrFE) and poly(3,4-ethylenedioxythiophene) - poly(styrene sulfonate) (PEDOT:PSS). This periodic confinement provides a length-scale driven cue which unfolds as a self-organized, frequency-modulated spatial phenomenon. Primary cortical cultures on these patterned substrates reveal significant differences with more elaborate network formation on PVDF-TrFE stripe. The features observed at the stripe boundaries, along with the dependence on stripe width, suggest that the neurons exhibit a preference to remain confined within the PVDF-TrFE region, with growth cones deflecting away from the PEDOT:PSS regions. These observations show a promising route for development of a functional template capable of directing axonal growth, synapse formation and neural rewiring in early models of connectivity disorders in vivo.

Simulated 5-HT2A receptor activation accounts for the high complexity of brain activity during psychedelic states
Serotonergic psychedelics, such as LSD, psilocybin, and DMT, have strong effects on human brain activity, yet their mechanisms of action at the whole-brain level are only partially understood. Here, we present a biophysically-based meanfield model that integrates cellular and network-level details to simulate the effects of these compounds at different spatial scales. By incorporating the brain-wide distribution of 5-HT2A receptors, our model mechanistically links receptor activation to a reduction in leak membrane potassium conductance, consistent with electrophysiological data. Our simulations reveal that this microscopic perturbation leads to the emergence of a brain state characterized by asynchronous and irregular dynamics with increased firing rates, as well as significant alterations in spectral power. Specifically, we find a robust decrease in power within the delta, theta, and alpha frequency bands, a result consistent with empirical findings. This change in dynamics is accompanied by an increase in spontaneous complexity, as quantified by the Lempel-Ziv complexity index, as observed experimentally. Furthermore, our model accurately replicates experimental findings regarding the Perturbational Complexity Index (PCI), demonstrating that PCI does not increase significantly by psychedelic drug administration. This crucial dissociation, where spontaneous complexity and spectral power are increased while perturbational complexity is preserved, highlights the distinct neurophysiological substrates underlying different metrics in psychedelic states. Our multiscale model provides a robust, mechanistic framework for understanding how serotoninergic psychedelics modulate global brain activity, offering new insights consistent with empirical neuroimaging and electrophysiological data.

Variation of Myelin-associated Gene Expression and Ndrg1 within the Prefrontal Cortex as Determinants for Initial Level of Response to Alcohol
Background: Studies in humans and animal models have documented relationships between initial sensitivity to alcohol and alcohol drinking behavior. Prior expression profiling studies of C57BL/6J and DBA/2J mice and rhesus macaques within the prefrontal cortex (PFC) have shown variation in myelin gene expression may be linked with alcohol sensitivity and consumption. Methods: Combining gene expression studies from human and mouse PFC, we identified a cross-species gene network enriched for myelin-associated genes. Since myelin expression is correlated to alcohol sensitivity and alcohol drinking behavior, we hypothesized basal levels of PFC myelin gene expression may be a genomic determinant for these behavioral responses. Using an animal model of CNS demyelination, and localized knock down of N-myc downstream regulated gene 1 (Ndrg1), we measured effects of cortical myelin reduction on initial alcohol sensitivity and drinking behavior. Results: Reducing myelin-related gene expression significantly altered sensitivity to alcohol and decreased alcohol consumption. Mouse genetic-based studies identified Ndrg1 as a putative quantitative trait gene for sedative-hypnotic responses to alcohol. Site-specific injections of shNdrg1 lentivirus into PFC led to a significant decrease in NDRG1 expression, causing increased alcohol behavioral sensitivity and reduced preference for high concentrations of alcohol. Conclusion: Myelin is an important biological component underlying CNS disorders. Our studies demonstrate the role of a novel candidate gene (Ndrg1), and myelin-associated gene expression, as an important factor modulating initial sensitivity to alcohol and alcohol consumption. Differences in the expression of myelin-related genes, including Ndrg1, may serve as future therapeutic targets for the treatment of alcohol use disorders.

MRI-based classifier to identify close-to-onset cases in C9orf72 genetic frontotemporal dementia
Predicting symptom onset in genetic frontotemporal dementia (FTD) is crucial for advancing targeted interventions and clinical trial design. Brain changes begin years before clinical symptoms emerge, making neuroimaging a strong candidate for onset prediction. However, FTD is highly heterogeneous, encompassing diverse molecular pathologies, affected brain networks, and symptom trajectories. This variability limits the predictive power of any single imaging biomarker and underscores the need for an integrative, multimodal approach to improve prediction accuracy and generalizability. We used machine learning to integrate diverse neuroimaging features, identifying a robust signature for risk stratification. We analyzed T1-weighted and T2-weighted MRI scans from 71 symptomatic C9orf72 carriers, 90 presymptomatic carriers, and 69 healthy controls from the GENFI cohort. We used FreeSurfer to measure cortical thickness and subcortical volumes, and BISON to quantify white matter hyperintensities (WMH). We applied Principal Component Analysis for dimensionality reduction and trained a random forest classifier to distinguish symptomatic carriers from controls. The model was subsequently applied to the presymptomatic cohort to identify individuals whose brain patterns resembled those of symptomatic cases, under the hypothesis that greater similarity indicated a higher risk of conversion. We validated the model with neuropsychological data and a two-year longitudinal follow-up. The classifier distinguished symptomatic C9orf72 carriers from controls with 87.0% accuracy. When applied to presymptomatic carriers, the model identified 21.1% of the cohort as having brain features comparable to those of symptomatic cases. This "high-risk group" showed significant neuropsychological weaknesses in executive function, language and social cognition compared to the non high-risk group. The model accurately predicted clinical conversion within a two-year period with 84.5% accuracy, a 70% sensitivity and a 93.3% negative predictive value. Our findings demonstrate the utility of a machine learning approach using multi-modal MRI to identify presymptomatic C9orf72 carriers at high risk of disease onset within the next two years. By capturing subtle neuroanatomical patterns associated with disease processes, this approach offers a promising method for stratifying genetic FTD carriers prior to symptom onset. Such predictive models could optimize patient selection in future clinical trials.

Flexible Steering and Conflict Resolution: Pro-Goal/Anti-Goal Gating in Drosophila Lateral Accessory Lobes
Navigation comprises multiple processes: sensory integration, position estimation, decision, and finally, motor command generation, which is the control problem. Previous studies discovered that PFL3 neurons compute a heading-goal error and directly project to the descending neurons that generate the steering commands. Yet, this direct pathway is necessary but not sufficient for the flexible control required to pursue goal while avoiding threats and resolving conflicts. Using the Drosophila connectome and circuit modeling, we uncover a layered control architecture in the lateral accessory lobes (LAL) that arbitrates between goal pursuit and stimulus-driving overrides. First, a dorsal pathway that forms a dominant indirect ''pro-goal'' push-pull circuit that amplifies left-right asymmetries. Second, a faster ventral pathway forms an ''anti-goal'' circuit that recruits and inverts the pro-goal circuit to redirect movement, and only engages when a goal is present. The architecture also resolves two symmetry challenges: Rear Stalemate (goal 180 behind) and Front Stalemate (threat dead ahead), by rapidly amplifying tiny perturbations into decisive turns. Together, these motifs instantiate comparator, override, and gating principles in a compact neural controller, yielding testable predictions for insect motor control and design rules for bio-inspired, embodied intelligence.

Disentangling structure-function relationships between the human hippocampus and the whole brain using track-weighted dynamic functional connectivity.
Understanding how structural and functional connectivity shape hippocampal interactions with the rest of the brain is critical for elucidating its role in cognition. Here, we combine high-resolution diffusion MRI, a novel fibre-tracking pipeline designed to specifically probe anatomical connectivity of the in vivo human hippocampus, and track-weighted dynamic functional connectivity (TW-dFC) to investigate how direct anatomical connections between the hippocampus and the rest of the brain relate to time-varying functional interactions. In Study 1, TW-dFC maps were computed for 10 participants from the Human Connectome Project and subjected to ICA and k-means clustering to derive a data-driven parcellation of the hippocampus based on its structure-function relationships. This revealed circumscribed clusters distributed along anterior-posterior and medial-lateral axes, which broadly aligned with hippocampal subfields. In Study 2, we examined the resting-state functional connectivity profiles of each TW-dFC derived cluster in an independent sample of 100 participants. Each hippocampal cluster displayed distinct patterns of functional connectivity with specific substructures within medial temporal, parietal, frontal and occipital cortices as well as subcortical and cerebellar regions. Our findings demonstrate that TW-dFC provides a powerful framework for anatomically informed functional parcellation of the hippocampus and offers new insights into the structural-functional organisation underlying hippocampal-(sub)cortical interactions. Our approach opens new avenues for probing memory systems in health and their disruption in aging and disease.

A comprehensive, open-source battery of movement imagery ability tests: Development and psychometric properties
Imagining actions is a covert and multidimensional skill difficult to quantify. Comprehensive assessments rarely combine measures of imagery generation, maintenance, and manipulation. We developed and validated a combination of tests to assess these processes of movement imagery, online. 180 healthy individuals completed the MIQ-RS questionnaire (generation), the Imagined Finger Sequence Task (iFST; maintenance), and the Hand Laterality Judgement Task (HLJT; manipulation). MIQ-RS showed a bifactorial structure (visual and kinesthetic modalities) according to confirmatory factor analysis, and its reliability (internal consistency) was good. In the iFST, internal validity analyses via generalized mixed models showed a clear effect of sequence complexity, stronger for execution than imagery. Reliability, estimated via signal-to-noise ratios (SNRs) using hierarchical Bayesian models, was also adequate (SNR > 1.6). In the HLJT, expected effects of rotation angle, hand view, and their interaction, consistent with biomechanical constraints, were also found. Reliability was also adequate (SNR > 1.75). Criterion validity across tests, assessed using Bayesian Spearman correlations, showed that correlations were generally absent (BF01 > 3), and when present, of small magnitude (r < 0.27). Test-retest reliability (122 participants reassessed 6-8 days after), computed via Intraclass Correlation Coefficients (ICCs), was generally adequate (ICCs > 0.67). We conclude that the online versions of these tests showed adequate structural/internal validity and (test-retest) reliability. However, weak criterion validity suggests individuals with high ability to generate movement imagery may not necessarily have high ability to maintain and/or manipulate movement imagery, underscoring the need for comprehensive assessment of this capacity.

Disrupted Integration-Segregation Balance in the Intact Hemisphere in Chronic Spatial Neglect
Spatial neglect is a common and disabling consequence of right hemisphere stroke, characterized by a failure to attend to the contralesional left space, and frequently persists into the chronic stage. There is robust evidence on the role of right-hemisphere frontoparietal dysfunction, interhemispheric structural disconnection and maladaptive activity in the left hemisphere in the persistence of neglect. However, the specific impact of right frontoparietal dysfunction on the functional (re)organization of the left hemisphere remains poorly understood. In this study, we introduce a novel application of functional connectivity gradient analysis to investigate macroscale functional reorganization in the non-lesioned left hemisphere of patients with chronic left spatial neglect. Focusing on resting-state fMRI data, we demonstrate that abnormal segregation patterns in the left frontoparietal and default mode networks are robustly associated with neglect severity and spatial attentional bias. Notably, the principal gradienttypically capturing a global unimodal-to-transmodal hierarchy--was altered in these patients, suggesting a reorganization favoring lateralized unimodal networks. We also show that the structural integrity of the left inferior fronto-occipital fasciculus (IFOF) plays a key role in shaping these functional dynamics. These findings reveal a previously overlooked aspect of neglect pathophysiology: the maladaptive dominance of the non-lesioned hemisphere's intrinsic architecture. By combining innovative gradient-based metrics with classical lesion approaches, our study offers a new framework for understanding neglect as an emergent property of large-scale network imbalance, with clinical implications for diagnosis and intervention, and theoretical consequences for models of hemispheric asymmetries and conscious access.

Computational modelling of schizophrenia-associated alterations of ion-channel-encoding gene expression predicts a decrease in delta power
Schizophrenia presents with a wide range of phenotypes that can help to understand the the mechanisms of the disease. Among these, alterations in delta oscillations are especially amenable to experimental investigation, yet the mechanisms underlying these changes remain insufficiently understood. Biophysically detailed computational modeling offers a powerful approach to investigate these phenomena, as it enables multi-scale integration of genetic and electrophysiological data. In this study, we developed a minimal network model composed of biophysically detailed, multicompartmental neurons to replicate experimental data on the effects of pharmacological blockage of gabaergic neurotransmission on delta-band power. We inserted post-mortem RNA expression data from the anterior cingulate and prefrontal cortices of individuals with schizophrenia and matched controls into the model to study the effects of schizophrenia-associated alterations of ion-channel expression on delta-oscillation power. Our simulations revealed a significant reduction in delta-band power in schizophrenia, driven by altered expression of calcium channel genes in pyramidal neurons. These results provide insights into the genetic contributions to oscillatory disruptions observed in schizophrenia, and our modelling framework can help to develop stratification strategies that bridge genetics and in vivo electrophysiology.

SEIZURE OCCURRENCE IN FCD TYPE II IS PREDICTED BY LESION POSITION AND LINKED TO CYTOARCHITECTURAL ALTERATIONS
Focal cortical dysplasia (FCD) is a common malformation of cortical development and a major cause of early-onset, drug-resistant epilepsy. FCD type II is defined by abnormal lamination, altered cellular composition, and pathological cells, notably dysmorphic neurons (DNs) and balloon cells. DNs are thought to drive epileptogenicity through both cell-autonomous and non-cell-autonomous mechanisms, the latter including not only aberrant connectivity but also indirect modulation of excitability in local cell populations. We performed a multiscale structural and morphological analysis to elucidate the basis of FCD epileptogenicity and the impact of somatic mTOR mutations during brain development. Using a mouse model of FCD type II, we show that lesions in frontal and motor cortical regions are the strongest predictors of spontaneous seizure occurrence. This localization-dependent epileptogenicity offers an experimental explanation for the higher clinical epileptogenicity of frontal FCDs and suggests that posterior lesions may remain silent - an open question in human pathology. In our model, FCD tissue displayed considerable expansion, with cortical thickness up to ~20% in seizure-bearing animals. This expansion coincided with an overall ~40% reduction in neuronal density, consistent with tissue hypertrophy. DN density did not differ between seizure and non-seizure animals, challenging the notion that higher DN load directly predicts epileptogenesis. At the microscopic level, we describe DN axonal pathologies, including giant varicosities. In the cortex, these appeared as vesicle-filled boutons, whereas along callosal axons they were frequent but largely empty. Bouton density was markedly reduced in FCD cortex. Together, these findings leave the net synaptic effect of dysmorphic neurons unresolved, challenging the assumption that axonal hypertrophy translates into increased excitatory drive. While morphological abnormalities in FCD type II are well documented, their functional consequences remain incompletely understood. Here, we used macro- and microscopic structural features of FCDII to assess seizure susceptibility, providing new insights into epileptogenesis.

Prolactin Shapes Cortical Plasticity in Fathers
Caregiving alters the mammalian brain to support infant survival. While hypothalamic circuits are known to drive innate parental behaviors, information about the effect of parenthood on sensory processing and perception remain scarce, especially in fathers. We longitudinally imaged the same neurons in male mouse primary auditory cortex (ACx) before, during, and after fatherhood using two-photon calcium imaging. Behaviorally, males shifted from pup-directed aggression and self-oriented behaviors to transient parental care. In ACx, fathers showed enhanced and faster discrimination of pup ultrasonic vocalizations compared with matched narrowband noise. Slice electrophysiology revealed increased intrinsic excitability accompanies fatherhood. Mechanistically, we found elevated prolactin signaling in ACx, and manipulating prolactin levels modified the improvement in neuronal discriminability. Together, these results identify, in males, cortical plasticity and link prolactin to experience-dependent plasticity of sensory circuits that support caregiving. Our findings outline a father-specific mechanism that differs in key aspects from similar mechanisms in mothers.

Spatiotemporal representations of contextual associations for real-world objects
In the real world, objects always appear in context. Many objects are reliably associated with a certain scene context (e.g., pots appear in kitchens) and other objects that appear in the same context (e.g., pans appear together with pots). Previous neuroimaging work suggests that such contextual associations shape the neural representation of isolated objects even in the absence of the scene context. Yet, three key questions remain unanswered: (1) How do representations of contextual associations relate to perceptual and categorical representation in visual cortex, (2) how do they emerge across time, and (3) how are they mechanistically implemented? To answer these questions, we recorded fMRI and EEG while participants (human, both sexes) viewed isolated objects stemming from two scene contexts. Multivariate pattern analysis on the neural data revealed that objects from the same context were coded more similarly than objects from different contexts in object-selective LOC and scene-selective PPA, even when systematically controlling for perceptual and categorical similarities. Such contextual relation representations emerged relatively late during visual processing (i.e., after perceptual and categorical representations), specifically in the anterior PPA, and likely through a mixture of object-to-object and object-to-scene associations. Together, our results demonstrate that contextual relation representations emerged for isolated objects, and without a task that encourages their formation, suggesting that objects automatically activate context frames that support visual cognition in real-world environments.

Direction Selectivity in Naturalistic Action Observation: Distributed Representations Across the Action Observation Network
Perceiving the direction of observed actions is critical for interpreting intentions and guiding social interaction. While direction selectivity has been extensively studied with simple stimuli such as dots, gratings, or point-light displays (PLDs), little is known about how the brain encodes direction in naturalistic, repetitive actions that are seen frequently in daily life. The present fMRI study investigated direction-selective representations during observation of complex actions performed along three bidirectional dimensions (left-right, up-down, front-back) within a 96-video stimulus set. The brain activity was analyzed using multivariate pattern analysis (MVPA) and multiple regression representational similarity analysis (RSA). MVPA revealed above-chance classification of action direction across occipital, parietal, and motor cortices, with the highest decoding in occipital, primary motor, and somatosensory regions. Crucially, RSA demonstrated that when accounting for low-level and motor features, direction information was still represented in early visual cortex, occipito-temporal areas, parietal regions, and motor-related regions. These findings indicate that action direction is represented across multiple levels of the action observation network (AON), extending from early sensory regions to higher-order parietal and frontal cortices. By using naturalistic, repetitive action videos, this study provides new evidence that the coding of action direction in the human brain is broadly distributed, reflecting the complexity of perceiving actions in everyday life. These findings suggest that direction selectivity is a core feature of the action observation network, linking basic motion processing with higher-level action understanding.