bioRxiv Subject Collection: Neuroscience's Journal

Hyperthermic Seizure Susceptibility and Focal Decreases in Parvalbumin-Expressing Cortical Interneurons in a Mouse Model of PCDH19-Clustering Epilepsy
Objective: Protocadherin-19 (PCDH19)-clustering epilepsy (PCE) is a severe genetic epilepsy that manifests with early-onset cluster seizures often triggered by fever, intellectual disability, autistic features, and later neuropsychiatric risk. PCDH19 is an X-linked gene critical for brain development. PCE predominantly affects females and rare mosaic males, but not hemizygous males, likely due to cellular mosaicism arising from random X-inactivation and resultant segregation of wild-type and mutant neurons (so-called cellular interference) during development. We generated a novel PCE mouse model and explored neuronal segregation, seizure susceptibility and cortical interneuron distributions. Methods: Female Pcdh19+/- mice were crossed with X-GFP males to visualize random X-inactivation patterns. Seizure susceptibility was assessed in juvenile mice using hyperthermia and flurothyl exposure. Behavioral testing evaluated cognitive domains. Interneuron distribution in hippocampus and cortex was examined histologically by immunolabeling and crosses with parvalbumin reporter mice. Results: Juvenile Pcdh19+/- females lacked spontaneous seizures but displayed lower seizure thresholds and more severe seizures during hyperthermia. Seizure susceptibility did not differ from controls after flurothyl exposure. Pcdh19+/- females also exhibited segregation of GFP+ cells in the cortex, hippocampal CA1 region and medial ganglionic eminence, with a marked reduction of parvalbumin-positive interneurons in the CA1 hippocampal region. Although parvalbumin interneuron density was unchanged in the Pcdh19+/- female cortex overall, localized decreases arose in GFP- (Pcdh19 knockout) cortical stripes. Interpretation: Juvenile PCE mice exhibit seizure susceptibility to hyperthermia and disrupted the distribution of parvalbumin-expressing interneurons in the hippocampus and cortex. These findings suggest focal parvalbumin interneuron alterations may contribute to PCE pathophysiology.

DTI-ALPS PRIMARILY REFLECTS WHITE MATTER DIFFUSION DISPERSION AND MICROSTRUCTURAL HETEROGENEITY IN NEURODEGENERATION: INSIGHTS FROM MULTI-MODAL MRI
1.1 Background The glymphatic system facilitates clearance of metabolic waste and pathological proteins from the brain, and its dysfunction has been implicated in neurodegenerative disease. The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) has been proposed as a non-invasive MRI marker of glymphatic flow, although its biological specificity remains uncertain. This study aimed to identify the determinants of DTI-ALPS and evaluate whether it primarily reflects white matter (WM) microstructure rather than glymphatic flow in the context of neurodegeneration. 1.2 Methods We examined 100 individuals referred to the Memory Clinic of the Policlinico Hospital in Milan for suspected dementia. All participants underwent a 3T-MRI protocol including 3D-T1-weighted and 3D-FLAIR imaging, double-shell diffusion-weighted imaging (b=1000/2000 s/mm2), and multi-echo gradient-echo sequences for quantitative susceptibility mapping. Within standard DTI-ALPS ROIs, we extracted DTI-ALPS values together with fractional anisotropy (FA), mean diffusivity (MD), and mode of anisotropy (MA) at both b-values, as well as neurite orientation and density imaging (NODDI) metrics, particularly the orientation dispersion index (ODI). WM microstructure was further characterized using the T1/FLAIR ratio and diamagnetic component of susceptibility (DCS). 1.3 Results and conclusions DTI-ALPS correlated inversely with MA (r = -0.84 at b = 1000; r = -0.86 at b = 2000) and positively with ODI (r = 0.73). Moderate correlations with the T1/FLAIR ratio and DCS supported sensitivity to WM alterations. Factor analysis indicated that DTI-ALPS clustered with MA and ODI rather than forming a distinct factor, suggesting that DTI-ALPS primarily reflects WM diffusion dispersion and heterogeneity rather than glymphatic flow in the context of neurodegeneration.

Electrophysiological Brain Connectivity and Subjective States Evoked by Electrical Stimulation of the Human Mediodorsal Thalamus
Recent advances in human intracranial EEG (iEEG) have enabled new investigations into the role of the thalamus in human brain functions. In this study, we applied direct intracranial electrical stimulation (iES) to the mediodorsal (MD) subregion of the thalamus using both high-frequency (50 Hz, iESHF) and low-frequency (0.5 Hz, iESLF) procedures to examine its impact on conscious experience and causal brain connectivity in 30 patients with focal refractory epilepsy (128 electrode contacts). iESHF of the MD elicited reportable changes in conscious experience in 11 of 12 patients (39 sites; 83 stimulations across 27 unique pairs) - predominantly in the visceral, emotional, or somatosensory domains and often described as unpleasant without any lateralization effect. Our connectivity analyses based on iESLF revealed that the cingulate and insular cortices produced stronger electrophysiological responses in the MD (inflow connectivity) than did the sites in the prefrontal cortex (PFC) within the same individuals. Moreover, MD stimulation showed its strongest outflow connectivity to the cingulate, insular, and PFC regions, all significantly stronger than to medial temporal lobe (MTL) structures. Notably, inflow from both MTL and insula sites to the MD were significantly stronger than their reverse directions, indicating clear asymmetry in connectivity. These findings provide direct evidence that stimulation of the human thalamus can modulate conscious experience. They also highlight the extensive bidirectional connectivity between the MD and cingulate and insular cortices along with asymmetric connectivity between the MD and MTL and insula sites in the human brain.

Central role for fast nociceptors in mechanical nocifensive behavior and sensitization
Nociceptors, primary afferent nerve fibers that signal noxious stimuli, are broadly divided into slowly conducting unmyelinated C fibers and fast-conducting myelinated A fibers. Whereas C-nociceptors have been extensively studied, considerably less is known about the function of A-nociceptors. To address this gap, we developed an intersectional genetic approach for robust and selective interrogation and manipulation of mechanically responsive A-nociceptors (A-MNs) in mice. Optogenetic A-MN stimulation induced rapid and precise withdrawal reflexes as well as place aversion and facial expression changes consistent with pain affect, while inhibition strongly impaired mechanical nociceptive withdrawal reflexes, demonstrating that A-MNs are necessary and sufficien t for rapid avoidance of noxious mechanical stimuli. Prolonged A-MN activation induced mechanical allodynia and central sensitization. In a rare individual lacking thickly myelinated A{beta} fibers, mechanical withdrawal reflexes were completely absent, and pain perception reduced. Together, these findings identify fast-conducting mechano-nociceptors as essential drivers of nocifensive behaviors in mice and humans.

MitoEM 2.0 - A Benchmark for Challenging 3D MitochondriaInstance Segmentation from EM Images
We present MitoEM 2.0, a curated data resource for training and evaluating three-dimensional (3D) mitochondria instance segmentation in volume electron microscopy. The collection assembles multiscale vEM datasets (FIB-SEM, SBF-SEM, ssSEM) spanning diverse tissues and species, with expert-verified instance labels emphasizing biologically difficult scenarios, including dense mitochondrial packing, hyperfused networks, and thin filamentous connections with ambiguous boundaries. All releases include native-resolution volumes and standardized processed versions, per-volume metadata (voxel size, modality, tissue, splits), and official train/validation/test partitions to enable reproducible benchmarking. Annotations follow a consistent protocol with quality checks and instance reindexing. Data are provided in NIfTI with nnU-Net-compatible layout, alongside machine-readable split files and checksums. Baseline scripts support common training pipelines and size-stratified evaluation. By consolidating challenging volumes and harmonized labels, MitoEM 2.0 facilitates robust model development and fair comparison across methods while supporting reuse in bioimage analysis, algorithm benchmarking, and teaching.

Head stabilization behavior and underlying circuit mechanisms in larval zebrafish
Head stabilization is essential for animal survival, enabling stable sensory input and effective motor coordination. Animals stabilize their heads in response to vestibular stimuli through the vestibulo-collic reflex (VCR). While the VCR has been characterized in tetrapod vertebrates, it remains unknown whether fish, which lack an anatomical neck, employ a comparable behavior. Here, we demonstrate that larval zebrafish exhibit VCR-like behaviors: they adjust their head orientation relative to the body by rostral body flexion during pitch tilts. The rostral body flexed ventrally during head-up posture, whereas it flexed dorsally during head-down posture. These flexions partially compensated for the head pitch changes, thereby contributing to head stabilization. We also identified the muscles and neural circuits responsible for these two types of body flexions. Both the dorsal and ventral flexions were mediated by the same vestibular nucleus, but neural signals were transmitted through distinct pathways, either involving or bypassing a class of reticulospinal neurons. The dorsal and ventral flexions were ultimately produced by specialized dorsal and ventral muscles in the rostral body, respectively. The neural circuits underlying these body flexions in fish share similarities with those underlying the mammalian VCR. Together, our results demonstrate that fish exhibit a VCR-like behavior through comparable circuit mechanisms, suggesting that the VCR is evolutionarily conserved across vertebrates.

The antiviral Interferon pathway drives astrocyte aging and motor decline
Aging encompasses low-level inflammation and motor decline. Astrocytes are neuroregulatory glial cells that change in aging, particularly in the cerebellum, which is essential for movement coordination. Regulation and functionality of cerebellar astrocytes in aging is unknown. We show that antiviral type I Interferons (IFN-I) drive motor deficits and regional astrocyte aging. Transcriptomics reveal that cerebellar astrocytes, but not cortical, exhibit an antiviral state that intensifies with age, with increased expression of Stat1. Aged mice display motor deficits similar to humans that improve after peripheral IFN-I receptor neutralization, whereas astrocyte Stat1 induces motor deficits during chronic inflammation in adults. While strong systemic inflammation induces astrocyte antiviral state, in aging, chromatin de-repression of Stat1 and nucleotide sensors in cerebellar astrocytes amplifies local IFN-I signaling. We identify functional interaction between a classical immune pathway and astrocytes, representing an actionable strategy to preserve motor function in aging.

When Brain Models Are not Universal: Benchmarking of Ethnic Bias in MRI-Based Cognitive Prediction Across Modalities
Predictive neuroimaging models promise precision medicine but risk exacerbating health inequities if they perform unevenly across ethnic/racial groups. Using the Adolescent Brain Cognitive Development data, we benchmarked ethnic/racial bias in models predicting cognitive functioning from 81 MRI phenotypes across four training strategies. Models trained on one ethnicity performed best within that group. Models trained on participants sampled without regard to ethnicity, a common practice, performed better on White participants, likely because the ABCD sample was predominantly White. Training on equal-sized White and African American subsamples reduced disparities without accuracy loss. Structural MRI exhibited the greatest bias, whereas task-based fMRI phenotypes were more equitable. Stronger brain-cognition associations generalized more equitably, but multimodal stacking despite enhancing prediction, did not improve fairness. Increasing representation of African American participants improved performance up to balanced sampling, with diminishing returns beyond. This first modality-wide benchmark reveals pervasive, modality dependent ethnic bias in cognitive prediction and identifies key factors shaping equity in neuroimaging models.

Cross-task, explainable, and real-time decoding of human emotion states by integrating grey and white matter intracranial neural activity
Decoding human emotion states from neural activity has significant applications in human-computer interfaces, psychiatric diagnostics, and neuromodulation therapies. Intracranial electroencephalogram (iEEG) provides a promising modality for decoding by balancing temporal, spatial, and noise resolutions. However, real-world application of decoding requires high performance that integrates neural activity from both grey and white matter, stable generalization across different contexts, sufficient neural encoding explainability, and robust real-time implementation, all of which remain elusive. Here, we simultaneously recorded iEEG and abundant self-rated valence and arousal scores--measuring the two primitive dimension of emotion--across two emotion-eliciting tasks in eighteen epilepsy subjects. We developed self-supervised deep learning models that achieved high-performance decoding by integrating grey and white matter signals, generalizing across tasks. The models provided strong explainability by revealing shared and preferred mesolimbic-thalamo-cortical subnetworks encoding valence and arousal, as well as the structural connectivity basis underlying grey and white matter integration. Finally, the models were implemented online and realized robust real-time decoding in four new subjects. Our results have implications for advancing emotion decoding neurotechnology and understanding emotion encoding mechanisms.

Interpretable and Brain-Inspired Recurrent Model of Hierarchical Decision-Making Capturing Trial-by-Trial Variability
Humans often make decisions in hierarchical environments, where low-level perceptual judgments inform high-level strategies. Understanding how the brain computationally navigates such multi-level decisions remains an open challenge. While existing models offer statistical insights, they often fall short in capturing the neural mechanisms and trial-by-trial variability underlying individual choices. To address this gap, we developed a neurocomputational model that integrates a biologically inspired attractor network for low-level perceptual decisions with a recurrent neural network (RNN) for high-level strategic adjustments. With minimal architectural constraints, the RNN receives only raw firing rates, feedback, and prior environment, learning to infer environment-switching strategies without explicit access to confidence or stimulus strength. In a hierarchical task combining motion discrimination and bandit decisions (N = 9; ~10,800 trials), the model successfully reproduced three hallmark behavioral patterns observed in humans. Unlike previous models, the model also captured trial-to-trial variability in switching decisions and implicitly learned to estimate decision confidence. For interpretability, we used representational and sensitivity analyses. Representational analyses revealed internal dynamics consistent with evidence accumulation in the anterior cingulate cortex (ACC), while sensitivity analysis identified feedback as the dominant influence on strategy, modulated by recent trial history. This framework combines interpretability and predictive power, moving beyond simple data fitting to provide mechanistic insights into how the brain integrates confidence and feedback to guide adaptive behavior in hierarchical decision-making.

Paw posture is a robust indicator for injury, pain, and age.
Inferring biological states from animal behavior is a crucial but challenging step in biomedical discovery that is constrained by variability and labour-intensive assays, even with AI-powered tools. Here, we show that simple images of static paws, analyzed by our custom keypoint segmentation AI-tool provide accurate read-outs for a wide array of physiological states. Without invasive testing, our method detects postural changes associated with nerve injury, acute pain, aging, and the genetic loss of kpna4, a regulator of paw innervation. Leveraging the toe-spread-reflex, a spinal-circuit driven response, the approach requires no habituation and shows low behavioral variability. Individual digits emerge as biomarkers for internal states with digit V indicating neuropathic pain during nerve damage and digit I reflecting loss of kpna4. Our model is freely available and can readily be adapted to other tasks or species. These findings establish unstimulated paw posture as a scaleable, low-cost, readout for biological states.

Non-canonical, ligand-independent basal mGluR1 signaling tunes Kv1.2 surface expression through PKA
Voltage gated potassium channels are major determinants of excitability of Purkinje cell (PC) neurons in the cerebellum. We have previously shown that in the cerebellum, activation of mGluR1 with agonist DHPG leads to reduced surface expression of Kv1.2 and that Kv1.2 co-immunoprecipitates with PKC-{gamma} and CaMKII which are known interactors of mGluR1. However, mGluR1 can also signal independently of agonist through a constitutively active, protein kinase A-dependent pathway. Here we show that in HEK293 cells, co-expression of mGluR1 increases the surface expression levels of Kv1.2. This effect occurs in absence of mGluR1 agonists and in the presence of an mGluR1 inhibitor. Co-expression of known downstream effectors of the agonist driven mGluR1 pathway, including PKC-{gamma} and CaMKII, had no effect on Kv1.2 surface expression or on the ability of mGluR1 agonist to modulate that expression. In contrast, the inverse agonist BAY 36-7620 significantly reduced the mGluR1 effect on Kv1.2 surface expression, as did pharmacological inhibition of PKA with KT5720.

Increased striatal coupling one week after ischemic stroke revealed by ultrafast functional MRI
Background: Network reorganization following ischemic stroke is thought to play a role in recovery. Although cortico-cortical reorganization is widely established, changes in interhemispheric striatal connections following ischemia remain poorly understood, even when stroke occurs in motor areas. Given the importance of the striatum to motor function, we investigated network-level striatal coupling in stroke using ultrafast resting-state fMRI, which has recently been shown to facilitate the dissection of synchronous oscillatory activity better than its conventional ~1 sec time-resolution counterparts. Methods: A cohort of (N=18) sedated rats were randomized and N=9 rats underwent unilateral photothrombotic ischemic lesioning in motor cortex. One week after the lesion, when plasticity and recovery are well established, all animals were scanned on a 9.4T MRI scanner using a cryogenic coil using an ultrafast resting-state functional MRI sequence with temporal resolution of 90 ms. Data were collected for 24 minutes, and spectral power, phase locking, and functional connectivity were quantified. Histology was performed to confirm lesion extent. Results: While cortico-cortical power, connectivity and synchrony were diminished one week post-stroke as expected, we surprisingly found increased striato-striatal power, synchrony and functional connectivity in the stroked group compared with the control group. In stroked animals, the spectral power in the ultraslow oscillation frequency band (0.02-0.4 Hz) significantly increased in the striatum while decreasing in the cortex. When data were undersampled to "conventional" fMRI temporal resolution (900 ms), the striatal effects were lost, revealing the power of ultrafast fMRI approaches in unveiling such phenomena. Conclusions: Increased striato-striatal coupling, in the form of increased synchrony, spectral power, and functional connectivity, was revealed by ultrafast resting-state fMRI, but not conventional temporal resolution resting-state fMRI. Our findings suggest more involvement of subcortical areas in network reorganization than previously thought.

Sub-strain-Dependent Differences in Gut Barrier Permeability, Bacterial Translocation and Post-Stroke Inflammation in Wistar Rats
Background: Stroke induces profound neuroinflammation and systemic immune dysregulation, including disturbances in gut homeostasis. Experimental evidence suggests that intestinal barrier permeability (IBP) and bacterial translocation (BT) critically influence stroke outcomes. However, biological variability among commonly used rodent sub-strains has received limited attention. Methods: In this pilot study, we compared post-stroke immune responses in two Wistar rat sub-strains obtained from different suppliers: RccHan (Envigo) and RjHan (Janvier). Following transient middle cerebral artery occlusion, animals were assessed 72 hours later and stratified according to the presence or absence of BT. Immune cell populations in blood and bone marrow were analyzed by flow cytometry, and leukocyte infiltration into ischemic brain tissue was quantified by immunohistochemistry. Results: Both sub-strains developed significant infarcts and neurological deficits. RccHan rats displayed larger infarct volumes and more extensive BT across multiple organs. In contrast, RjHan rats exhibited BT mainly confined to mesenteric lymph nodes but showed greater IBP. Although dissemination was broader in RccHan rats, overall bacterial burden was slightly lower compared with RjHan, and extra-intestinal bacterial composition differed between groups. Notably, RjHan rats presented stronger systemic and central immune activation, with marked alterations in lymphocyte and monocyte populations and enhanced granulocyte and T cell infiltration within ischemic lesions. Conclusions: These findings demonstrate that sub-strain origin profoundly influences post-stroke intestinal barrier integrity, bacterial dissemination, and immune responses. Considering sub-strain-related variability is essential to improve reproducibility and translational relevance in preclinical stroke research.

Observing being touched enhances the neural processing and perception of digital gentle stroking
Observing touch activates similar brain regions as experiencing an actual touch, suggesting that visual information can cross-modally influence tactile perception. This electroencephalography (EEG) study investigated how observing being touched affects the processing and perception of digitally delivered tactile stimuli resembling affective stroking or non-affective tapping. Thirty-three participants received touch patterns on their left forearm via a wearable sleeve while viewing spatiotemporally aligned videos of touch or a photo of an arm. Continuity and pleasantness ratings were higher for stroking than tapping. Correlations between continuity and pleasantness ratings for stroking or tapping conditions were stronger when presented with touch videos than with photos. Analysis of evoked brain activity revealed cross-modal effects after 0.6 seconds at centro-parietal and frontal electrodes for stroking, which differed from the effects observed for tapping. Visual modulation of pleasantness ratings correlated positively with processing differences between stroking and tapping in two right frontal clusters in later time windows around 1.36 and 1.8 s. These results suggest that visual inputs influence tactile pleasantness through somatosensory and multisensory processing, as well as frontal valuation of pleasantness. Our study extends previous research on affective touch by demonstrating informative visual cross-modal influences on digitally actuated touch at behavioural and neural levels.

A dynamic causal inference framework for perception-action loops
Causal inference, the process of inferring the causes of our sensory input, is central to multisensory perception. While most computational models of causal inference focus on static perceptual tasks with no temporal or motor components, real-world behavior unfolds dynamically and often involves closed-loop control. Here, we introduce and validate a general modeling framework that unifies multisensory causal inference with optimal feedback control by casting the problem as inference and action in a switching linear dynamical system (SLDS). Our framework combines approximate inference over latent causal structures with a mixture-of-controllers approach, in which each controller is optimized for a specific causal model and weighted by the current belief in that model. We show that classical static models of multisensory perception are special cases of our framework, and extend them to dynamic, action-oriented settings where inference and control evolve over time. Using simulations of previously published behavioral tasks, including visuo-vestibular heading discrimination and path integration with interception, we show that the model reproduces key empirical findings, such as S-shaped biases in heading estimation and motor strategies based on inferred object motion. We also demonstrate the versatility of our approach in novel task extensions, including motion in depth, latent switching dynamics, and multi-objective motor control. Together, our results provide a principled, general-purpose computational account of how causal inference and motor behavior interact in dynamic, uncertain environments, offering a bridge between theories of perception and action.

Multivariate environmental exposures are reflected in whole-brain functional connectivity and cognition in youth
Each individual's complex, multidimensional environment, known as their 'exposome', plays an essential role in shaping cognitive neurodevelopment. Understanding the mechanisms whereby children's exposome influences their development is crucial to facilitate the design of interventions to foster positive developmental trajectories for all youth. Recent work has identified a general exposome factor associated with socio-economic inequality that is strongly related to cognition and individual differences in the spatial organization of functional brain networks in youth. Building on these findings, the current study explores whether alterations in functional connectivity may represent a potential mechanism linking variation in the exposome to cognitive performance. We apply a data-driven, cross-validated, whole-brain machine learning approach, connectome-based statistical inference, to identify patterns of functional connectivity associated with exposome scores among early adolescents enrolled in the Adolescent Brain Cognitive Development (ABCD) Study using data collected during three cognitive tasks and during rest. Additionally, we investigate whether the identified patterns of functional connectivity relate to individual differences in cognitive performance across three domains: General Cognition, Executive Functioning, and Learning/Memory. Models incorporating 10-fold cross-validation over 100 iterations identified consistent functional connections associated with the exposome across task and rest conditions (model performance: ns = 6,137-8,391, rs = 0.34 - 0.44, ps <.001). Results were robust across data collection sites and functional connections common across all significant models were associated with cognitive performance across domains (ps < 0.0009). Collectively, these findings reveal that multidimensional environmental exposures are reflected in patterns of functional connectivity and relate to cognitive functioning among youth.

Expansion of Working Memory Capacity Supports Early Skill Learning
Real-world motor skills depend on the precise spatiotemporal coordination of action sequences refined through practice. Working memory, which transiently maintains and manipulates task-relevant information, supports skill acquisition expanding with extensive training, as shown in expert domains such as in master chess players. Yet, the temporal dynamics of working memory emergence and expansion during the rapid performance gains that define early skill learning remain unclear. We addressed this question across three experiments in which participants learned various naturalistic sequential keypress skills. Within each practice trial, we observed segments of high-initial-skill (HIS)--transient periods of elevated performance followed by skill drops--that persisted throughout training. The keypress content of HIS segments scaled with execution speed and systematically increased with practice, reflecting an expansion of keypress chunk content consistent with the progressive enlargement of working memory capacity. Importantly, HIS segment keypress content continued to rise even after overall performance plateaued. Theta-gamma phase-amplitude coupling ({theta}/{gamma} PAC) and beta ({beta})-band bursts, mechanisms implicated in maintaining and binding individual actions into sequences in working memory, were elevated during HIS segments with hippocampal {theta}/{gamma} PAC predicting HIS segment content. Our results suggest that working memory capacity expands during early learning of a naturalistic skill and continues strengthening with practice after skill plateau is reached, possibly supported by hippocampal theta/gamma phase-amplitude coupling.

Inhibition of oxytocin neurons during key periods of development has long-term behavioural and body composition effects
Oxytocin (OT) is a neuromodulator of social behaviour in mammals and accumulative data support the concept of a critical period for OT action during infancy. However, it is possible that the specific functions of OT depend on different time periods of action. In this study, we aimed to determine whether there are developmental stages during which OT-expressing neurons play a decisive role with long-term consequences. To this end, we chemogenetically inhibited OT-expressing neurons during three critical periods of development (in infants, juveniles, and young adults) in male and female mice, followed by a longitudinal study to assess behaviour and metabolic perturbations. The most pronounced behavioural effects are observed after inhibition during infancy in both sexes. Notably, social memory is consistently impaired in males, regardless of the inactivation period. From a metabolic perspective, in adulthood, an increase in body weight is observed in all cohorts of males but fat mass and adipocyte size increase after inhibition of OT-expressing neurons during juvenile period. In addition, we observed a significant delay in the day of birth and an alteration in feeding behaviour in neonates after inhibiting OT-expressing neurons around the time of birth. Thus, inhibition of OT neurons during three postnatal periods has direct, distinct, and long-lasting consequences on social behaviour and metabolism, depending on the sex and on the timing of inactivation. Our results also demonstrate a role of foetal/neonate oxytocin neurons in the timing of birth and in early feeding behaviour.

Processing of Emotional Faces Has Unique Functional and Cytoarchitectural Associations in those with an Autism Spectrum Diagnosis.
Those with an autism spectrum diagnosis (ASD) have been found to process emotional faces differently than other populations. Processing of emotional faces requires engagement of temporal, frontal, occipital, and limbic brain regions. Functional activity has been shown to differ in those with an ASD, particularly in the amygdala, inferior frontal cortex (IFC), and temporal brain regions. However, the consistency and direction of these associations have been inconsistent across studies. Recent findings have demonstrated that measures of neuron density differ in those with an ASD. Some of these regional differences in cytoarchitecture coincide with regions important to emotional facial processing. Therefore, the interaction between cytoarchitecture and functional activity may be important in elucidating unique neurophysiology in ASD. The present study uses diffusion weighted imaging (DWI) and functional magnetic resonance imaging (fMRI) data from the Adolescent Brain Cognitive Development (ABCD) study to investigate the relationship between cytoarchitecture and functional activity during emotional face processing in those with an ASD. 75 individuals with a reported ASD and 6,396 individuals with no reported diagnosis of an ASD (nASD) were identified. The emotional n-back (EN-Back) task was administered during fMRI acquisition, activating regions of the brain associated with processing emotional faces. Neuron cell body density was positively correlated with functional activation in the left amygdala in the ASD group but not the nASD group. These findings suggest that a unique relationship may exist between neuron cell body density in the left amygdala and functional activity while processing emotional faces in those with an ASD.

A Common Neural Signal of Evidence Accumulation for Perceptual and Mnemonic Decisions
Humans frequently make decisions based on sensory input from the external environment or information retrieved from memory. The centro-parietal positivity (CPP), an event-related EEG potential, has recently been identified as a neural correlate of sensory evidence accumulation during perceptual decision-making tasks. However, it remains unclear whether this component also reflects evidence accumulation during decisions based on long-term memory. The present study investigated whether the CPP serves as a domain-general signal of evidence accumulation across both perception and semantic memory-based decisions. We designed a visual discrimination task in which participants discriminated between the luminance of two alphanumeric strings across three levels of difficulty defined by the luminance difference. In a semantic memory task, participants discriminated between the populations of two different U.S. states, binned into three difficulty levels using US census data. After each decision, participants rated their confidence on a scale from 1 (very low) to 4 (very high). We observed a CPP component in both tasks, the slope of which scaled with the sensory or mnemonic evidence in both stimulus- and response-locked analyses. Furthermore, these CPP slopes were sensitive to reaction times (RT) and confidence in both tasks. Finally, the peak height of the CPP just prior to the response, indicative of one's decision boundary, was strongly correlated across tasks, suggesting that a common threshold was applied to the abstract evidence quantity being accumulated. Our results indicate that the CPP can be used to track the unfolding dynamics underlying decisions made both on the basis of external sensory evidence and internal mnemonic evidence.

Disrupted Top-Down Modulation as a Mechanism of Impaired Multisensory Processing in Children with an Autism Spectrum Diagnosis.
Atypical sensory processing is a core feature of autism, particularly when integration across sensory modalities is required. The neural mechanisms underlying these multisensory differences remain unclear. We recorded high-density EEG while autistic children aged 8-13 (AU; n=40), unaffected siblings of autistic children (SIB; n=26), and non-autistic controls (NA; n=36) performed a simple reaction-time task to auditory (A), visual (V), and audiovisual (AV) stimuli. Analyses targeted event-related potentials (ERPs; P1/N1/P2), alpha-band event-related desynchronization (alpha-ERD), and long-range theta-band functional connectivity (weighted phase-lag index, wPLI). Across all unisensory measures (ERPs, alpha-ERD, and connectivity), groups did not differ, indicating broadly comparable unisensory processing. By contrast, multisensory integration (MSI; operationalized for ERPs and alpha-ERD as AV - (A+V)) differed across groups: NA children showed significant ERP MSI over parieto-central sites that was absent in AU and SIB; and alpha-ERD MSI was present in all groups but significantly reduced in AU, with SIB showing an intermediate profile. Connectivity analyses revealed that AV theta-band fronto-parieto-occipital coupling was reduced in autistic relative to non-autistic children, consistent with weaker large-scale coordination during multisensory processing. Together, these results point to a multisensory-specific deficit in autism spanning early sensory encoding, posterior alpha-ERD, and fronto-posterior coupling. The convergence of results supports a mechanistic account of disrupted multisensory influences on sensory processing due to reduced multisensory attentional orientation. Intermediate SIB profiles suggest inherited liability for these neural phenotypes. These results help explain well-documented behavioral MSI differences in autism by linking impaired early enhancement with attenuated top-down control of sensory cortex.

cuBNM: GPU-Accelerated Brain Network Modeling
Brain network modeling uses computer simulations to infer about latent neural properties at micro- and mesoscales by fitting brain dynamic models to empirical data of individual subjects or groups. However, computational costs of (individualized) model fitting is a major bottleneck, limiting the practical feasibility of this approach to larger cohorts and more complex models, and highlighting the need for scalable simulation implementations. Here, we introduce cuBNM, a Python package which leverages parallel processing of graphics processing units to massively accelerate simulations of brain network models. We show running simulations on graphics processing units is several hundred times faster compared to central processing units. We demonstrate the usage of cuBNM by running optimization of group-level and individualized low- and high-dimensional models. As examples of the utility of individualized models, we investigated test-retest reliability and heritability of simulated and empirical measures in the Human Connectome Project dataset, and found simulated features to be fairly reliable and heritable. Overall, cuBNM provides an efficient framework for large-scale simulations of brain network models, facilitating investigations of latent neural processes across larger cohorts, denser networks, and higher-dimensional models, which were previously less feasible in practice.

Selective targeting of hippocampal fast-spiking basket cell interneurons via noninvasive enhancer-AAV delivery
Accurate targeting of specific brain regions through non-invasive methods has long been a major goal of basic and translational neuroscience. Systemic delivery of AAVs expressing highly region- and cell-type-specific regulatory elements (enhancer-AAVs) continues to emerge as a tractable solution. Here we performed an independent characterization of a novel enhancer element with apparent robust transgene expression in fast-spiking basket cell interneurons in mouse hippocampus. Surprisingly, this vector did not induce expression in other brain regions harboring the same neuron class. Following intravenous administration in mice, robust labeling of FS-BCs across all hippocampal subfields was observed. We validated the FS-BC specificity in hippocampus using immunofluorescence and electrophysiological recordings. Viral labeling was confined to parvalbumin-positive cells exhibiting basket cell morphology and fast-spiking responses. This approach represents a promising avenue for both mechanistic investigation of hippocampal circuit function and potential therapeutic interventions targeting hippocampal pathophysiologies such as epilepsy, schizophrenia, and other neurological disorders in mice and potentially other species.

A Surgical Protocol for a Large, Resealable Cranial Window Enabling Longitudinal, Multi-Modal Electrophysiological Recordings of the Mouse Default Mode Network
The Default Mode Network (DMN) is a central large-scale brain network implicated in a range of cognitive functions and neuropsychiatric disorders, such as major depressive disorder (MDD). Studying the DMN's complex dynamics in animal models provides invaluable insights into its function in both healthy and pathological states. However, performing a stable, long-term, and large-scale electrophysiological recordings from the multiple, deep, and distributed nodes of the DMN in awake, behaving mice has been a significant challenge. Here, we present a novel, two-phase surgical protocol developed to create a large (4x7.6 mm), durable, and resealable cranial window in mice. The procedure is designed to preserve the integrity of the dura mater, which is paramount for long-term brain health and recording stability. This window facilitates repeated, longitudinal recordings from over 1,000 electrodes simultaneously by combining surface-level micro-electrocorticography (micro-ECoG) with two high-density intracranial electrode probes, allowing unprecedented access to the DMN. This technique provides a robust platform for multi-modal, multi-scale interrogation of network-wide electrophysiological dynamics over several weeks, opening new avenues for investigating the neuroplastic changes underlying the pathophysiology of brain disorders and for evaluating the chronic effects of novel therapeutics.

Does Infarct Size Influence Gut Barrier Integrity and Bacterial Translocation after Experimental Stroke?
Background: Ischemic stroke (IS) triggers brain injury and systemic changes, including gut dysbiosis, intestinal barrier dysfunction (IBD), and bacterial translocation (BT). Although larger infarcts are associated with higher infection risk, it is unclear whether lesion size directly influences gut barrier integrity or bacterial dissemination. Methods: Male C57BL/6 mice underwent permanent middle cerebral artery occlusion (MCAO) proximally or distally to generate large or small infarcts. Seventy two hours post ischemia, infarct volume was measured by MRI, and BT was assessed in mesenteric lymph nodes, liver, spleen, and lungs. ZO1 and MMP9 expression were used to evaluate intestinal barrier integrity. Peripheral and central inflammation were assessed by flow cytometry and immunofluorescence. Results: Proximal MCAO produced larger infarcts than distal MCAO. The proportion of animals exhibiting BT was lower in distal MCAO, but this difference was not statistically significant. ZO1 expression did not differ between groups, while MMP9 was increased only in animals with BT, independent of infarct size. BT was associated with more pronounced lymphopenia and enhanced microglial activation and T cell infiltration in the brain. The composition of translocated bacteria was similar across groups. Conclusions: Infarct size alone does not determine IBD or BT, although BT is linked to intestinal and cerebral inflammation. This study evaluates for the first time the effect of lesion magnitude on IBD and BT, highlighting the complex interplay between cerebral injury and gut systemic interactions.

ADHD Medications and Preadolescent Brain Structure: Patterns of Cortical Attenuation from the ABCD Study
Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder in the U.S., and the stimulant and nonstimulant medications used to treat ADHD are among the most widely prescribed treatments in youth. Stimulants--including amphetamine-based (AMP) and methylphenidate-based (MPH) medications--act primarily on dopaminergic and noradrenergic systems, while nonstimulants (NS) more selectively target noradrenergic pathways. Although pharmacotherapy is the most clinically effective treatment, its neurostructural effects remain poorly understood. Leveraging the Adolescent Brain Cognitive Development Study (ABCD Study(R)), we used a machine learning approach to identify neuroanatomical targets of medications, followed by linear mixed-effects modeling to estimate the effects of ADHD status and medication class (AMP, MPH, NS) on cortical thickness, surface area, and cortical and subcortical volumes. ADHD was not associated with statistically significant differences; however, a consistent pattern emerged in which AMP and MPH effects attenuated ADHD effects, suggesting that stimulant medications may attenuate ADHD-related cortical patterns. NS medications showed a similar, albeit weaker, effect pattern. Notably, AMP and/or MPH use was associated with significant effects in the right entorhinal cortex and the right banks of the superior temporal sulcus, potentially reflecting overcompensatory effects, as well as in the left posterior cingulate, possibly indicating de novo medication-related differences.

Single nuclear RNA sequencing shows altered microglial and astrocytic functions in post-mortem Parkinson's disease tissue
Background: Parkinson's disease (PD) is a neurodegenerative disease marked by a progressive loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) and formation of misfolded protein aggregates. A growing body of research has implicated glial cell dysfunction in PD etiology, including the concentration of activated glial cells around protein aggregates in post-mortem tissue. Disruptions in the balance of pro- and anti-inflammatory immune response functions of the microglia and astrocytes is believed to contribute towards neurons being lost as the disease progresses. However, the molecular mechanisms remain unclear. To shed light on the role of inflammation in PD, this study analyses two public single nuclear RNA sequencing datasets of the SNpc from patient and control postmortem brain to identify altered molecular pathways in PD-associated microglia and astrocytes. Results: The results show that both cell types have a significant upregulation in heat shock binding and misfolded protein response pathways, likely in response to the accumulation of protein aggregates. Microglia annotated with the MKI67 marker gene show a decreased expression in PD patient derived tissue. Markers associated with activated/reactivated states in astrocytes and microglia are upregulated in PD samples. Notably, expression of genes associated with resting state microglia and non-inflammatory reactive state microglia are downregulated in PD microglia, including P2RY12, CSF1R, CSF2RA, CSF3R, and TGFBR1. Concurrently, genes associated with activated microglial states such as HSP90AB1 and GPNMB are upregulated. Among the top downregulated functions, genes associated with ion channel functions are downregulated in both astrocytes and microglia. Conclusions: Taken together, the findings imply that astrocytes and microglia respond to protein misfolding pathology in PD by upregulating chaperone protein folding functions. Additionally, the profile of upregulated genes implies that pathways responding to oxidative stress are also activated. The downregulation of inflammation-associated genes in PD microglia paired with the upregulation of misfolding protein response pathways, suggests a switch from immune receptor functions to protein aggregate clearance by the end of disease stages. Finally, GPNMB emerged as a potential target for therapeutic intervention, as the one primary non-HSP gene that is significantly increased in PD-associated microglia.

Development of Recombinant Anti-TLR2 Antibodies and PLGA Nanoparticle-based Gene Therapy for the Treatment of Neuropathic Pain
Neuroinflammation is a key contributor to neuropathic pain, with microglial Toll-like receptor 2 (TLR2) playing a central role in initiating and sustaining proinflammatory responses. However, existing TLR2-targeting antibody therapies are limited by poor delivery to the central nervous system and short-lived efficacy. We developed a non-viral gene therapy strategy using biodegradable poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) to deliver recombinant anti-TLR2 antibody genes. High-affinity nanobody and single-chain variable fragment candidates were selected through phage display screening and shown to suppress TLR2-dependent signaling both in vitro and in vivo. In mouse models of neuropathic pain, a single intrathecal administration of PLGA NP-encapsulated antibody genes produced robust and sustained analgesia, accompanied by reduced glial activation and proinflammatory cytokine expression. These findings demonstrate a modular NP-based platform for sustained antibody expression in the central nervous system and establish its potential for the treatment of chronic pain driven by innate immune activation.

Exclusive ipsilateral representation of sequential tactile differences challenges contralateral dominance
Tactile perception is traditionally attributed to contralateral somatosensory (S1) processing, yet the functional role of ipsilateral S1 in human tactile discrimination remains unclear. Using fMRI during a sequential vibrotactile discrimination task, we examined how frequency information is represented when participants judged which of two successive stimuli delivered to the same fingertip was higher in frequency. Contralateral S1 showed robust activation, and ipsilateral S1 showed suppression during unilateral stimulation; however, linear mixed-effects analyses revealed reliable frequency-dependent modulation in ipsilateral S1, which was absent when no comparison was required. Multivariate representational analyses further demonstrated that fMRI activity patterns representing the differences between successive stimuli were strengthened under memory demands, particularly within ipsilateral S1 and parietal cortices. Furthermore, the representational separability predicted individual discrimination accuracy. The exclusive representation in the ipsilateral S1 was not hand-specific; that is, the results were consistent for both hands, indicating a bilateral and symmetric encoding scheme. These surprising findings demonstrate that the ipsilateral, not contralateral, S1 contributes to tactile discrimination, challenging classic contralateral models of somatosensory processing. These unprecedented findings highlight interhemispheric coordination as a key mechanism underlying perceptual decisions.

Contrasting behavioral and physiological effects of Gtf2i duplication and deletion in mouse models of the 7q11.23 Duplication and Williams-Beuren Syndromes
7q11.23 Microduplication Syndrome (7Dup) and Williams-Beuren Syndrome (WBS) are two ASD-related syndromes characterized by both common and contrasting symptoms, caused by either duplication or deletion of a 1.5-1.8 Mb segment in section q11.23 of Human chromosome 7, respectively. Notably, WBS patients show reduced social fear and are considered hyper-social, while 7Dup patients suffer from social anxiety and withdrawal. Previous work suggests that the GTF2I gene, one of the genes included in this segment, has a major role in the social symptoms of both syndromes. Here, we combine video and thermal imaging in multiple social behavior tests to screen for behavioral and physiological variables showing variations in mice models with either a duplication (Gtf2i+/dup) or a deletion (Gtf2i+/del) of the gene. Our analyses of social behavior, micturition, and defecation patterns identify several differences between wild-type and mutant littermates, some of which show contrasting variations associated with Gtf2i dosage. Interestingly, thermal imaging revealed that Gtf2i dosage dictates the mice's surface temperature profile during the tests, with Gtf2i(+/dup) males exhibiting higher surface temperature than their wild-type littermates, while Gtf2i(+/del) males and females show the opposite tendency. These results suggest that the two mouse models exhibit opposite changes in either their emotional state or thermoregulation capabilities, in correlation with Gtf2i dosage.

Toward Understanding the Role of Visual Hierarchy in Flicker-induced Time Dilation: A Preregistered Study
When a temporal interval is marked by flickering stimuli, its subjective duration is overestimated. The cortical origin of this temporal illusion, termed flicker-induced time dilation (FITD), is not yet well understood. In this pre-registered study, we aimed to explore whether the higher-level regions of ventral visual stream contribute to FITD. By using the semantic wavelet-induced frequency tagging (SWIFT) technique, four experimental conditions were created. Luminance and semantic flickers were created to selectively target the lower- and higher-level regions of the visual hierarchy, respectively. A combined luminance and semantic flicker condition was additionally created to probe the effect of simultaneous entrainment of lower- and higher-level visual regions on FITD. Lastly, to account for the single-pixel modulations and ripple-like motions induced by SWIFT, a control scramble condition was included. The phase-clustering analysis (N = 20) confirmed that the control scramble condition did not result in neural entrainment, whereas the flicker conditions showed entrainment whose magnitude and topography were consistent with their respective experimental manipulations. Nonetheless, the behavioral results indicated that the time dilation effect was not modulated by the flickering conditions neither was its magnitude correlated with the size of entrained oscillations. Moreover, the SWIFT scrambles led to a time dilation effect which was comparable to the flickering conditions. We discussed that while our results are not in agreement with neural entrainment account of FITD, they are not in agreement with the processing principles definition of salience either. Based on the putative shared cortical sources of SWIFT scrambles and luminance-modulated flickers, we conjectured that FITD, and motion-induced time dilation may rely on the same mechanism based on activation of motion sensitive regions. Finally, our results indicated that, at least at the presence of steadily activated lower-level visual and/or motion sensitive areas, periodic activation of ventral stream does not contribute to FITD.

The DNA methylation enzymatic machinery in substance use disorders: a systematic review
Substance use disorders (SUD) are chronic affections defined by similar symptoms across a variety of psychoactive drugs, including alcohol, cocaine, opioids, or methamphetamine. Epigenetic mechanisms such as DNA methylation represent key candidates to help explain the long-lasting effect of these drugs, as well as inter-individual variation in vulnerability. Here, we systematically reviewed current knowledge on the role of DNA methylation and the related enzymatic machinery in rodent models of SUD. Using a prospectively registered methodology, 99 articles were prioritized. A first set of studies manipulated the expression or activity of methylation or demethylation pathways. Depending on the brain region or drug considered, SUD-related behavioral and molecular manifestations were bidirectionally modulated, suggesting both pathogenic and protective roles for drug-induced methylomic plasticity. A second set of articles focused on candidate genes. Although significant heterogeneity across experimental models, brain regions or gene targets resulted in an absence of replicated findings, available data nevertheless support the notion that drugs of abuse trigger DNA methylation changes at discrete loci. Third, recent genome-wide studies have started to demonstrate that these drugs recruit widespread reprogramming. Strikingly, most adaptations occur outside promoter regions, highlighting an important challenge toward their functional interpretation. Finally, studies of drug exposure during gestation or adolescence suggest long-lasting consequences, with the potential for early intervention.

Comparative Evaluation of Assumption Lean Community Detection Methods for Human Connectome Networks
Community detection provides a principled lens on mesoscale organization in functional brain networks, yet many widely used methods presume assortative structure and depend on arbitrary thresholding, which complicates the selection of the community count K. We conducted a systematic benchmark of three assumption lean approaches that operate directly on weighted functional connectivity matrices: the Weighted Stochastic Block Model, Spectral Clustering, and K-means. Performance was assessed on synthetic networks with known ground truth and on three neuroimaging cohorts spanning development, namely the Human Connectome Project, Washington University 120, and the Baby Connectome Project. We compared strategies for choosing K, including post hoc indices such as silhouette, Calinski-Harabasz, C index, modularity, variation of information, Normalized Mutual Information, and zRand, together with a likelihood-based criterion for the Weighted Stochastic Block Model that uses bootstrap confidence intervals for differences in log likelihood between successive values of K. In simulations all methods recovered stable partitions, but the post hoc indices favored incorrect values of K under weak signal and nonassortative mixing. In adult datasets the indices do not yield a unique optimum, whereas the likelihood-based criterion selects a parsimonious range centered near K=11, which is consistent with established sensory and association systems. In infants and toddlers, the same procedure supports a larger K around 15 and reveals developmentally distinct mesoscale architecture, including anterior and posterior subdivisions within default mode and fronto parietal systems. A consensus relabeling scheme based on Hungarian matching with Hamming distance further stabilizes solutions across runs and across values of K. Overall, threshold free weighted methods mitigate assortative bias and the likelihood-based comparison provides a reproducible path to selecting K.