bioRxiv Subject Collection: Neuroscience's Journal

Mecp2 deficiency induces dysphagia in a preclinical model of Rett Syndrome
Rett Syndrome is a rare, x-linked genetic neurological disorder caused by MECP2 gene mutations. This progressive neurodevelopmental disorder hinders patients ability to breathe and eat normally. It is unclear how Mecp2-deficiency results in a high percentage of dysphagia and aspiration pneumonia in patients with Rett syndrome. We aim to determine the effects of Mecp2-deficiency on swallow related neuromuscular mechanisms contributing to dysphagia in Rett syndrome. Swallow and breathing were detected using electrophysiology in the submental and laryngeal muscle complexes and the hypoglossal and vagus nerves. Several medullary motoneuron populations involved in swallowing were examined by immunohistochemistry in pre and post symptomatic Mecp2-deficient male and female mice. Swallow-related submental complex duration and amplitude were significantly decreased in both Mecp2-/y and Mecp2+/- compared to wild-type, due to decreased motor unit activation. In both Mecp2-deficient mice, cholinergic staining in hypoglossal, facial, and trigeminal nuclei were decreased. We noted a significant increase in the transition time from inspiration to swallow, swallow to the subsequent inspiration, and impaired respiratory rhythm regeneration in Mecp2-/y, but not Mecp2+/- mice. Mecp2-deficiency resulted in impaired brainstem cholinergic signaling, which contribute to weakened submental muscle complex activity, and impaired swallow related laryngeal vestibular closure. These results suggest Mecp2-deficient mice are a viable pre-clinical model to further study dysphagia in Rett syndrome.

MatClassRSA v2 release: A MATLAB toolbox for M/EEG classification, proximity matrix construction, and visualization
MatClassRSA is a MATLAB toolbox that performs magnetoencephalography and electroencephalography (M/EEG) classification and other analyses related to Representational Similarity Analysis (RSA). The toolbox is designed for cognitive neuroscience researchers who wish to perform classification-based decoding analyses of their data---often repeated trials of evoked responses---or derive Representational Dissimilarity Matrices (RDMs) as input to RSA. Organized as a collection of user-called functions, MatClassRSA v2 comprises five main modules: Preprocessing, Reliability, Classification, RDM Computation, and Visualization. The Classification module supports multiple classifiers (LDA, RF, SVM) and classification schemes (e.g., multiclass, pairwise, cross-validated, train-test, hyperparameter optimization) and offers basic statistical analyses via permutation testing. Functions in other modules include, for example, trial-averaging and noise normalization; reliability estimation; non-classification RDM construction; and hierarchical and non-hierarchical clustering visualizations. The toolbox is freely available on GitHub under an MIT license and includes the main codebase, a User Manual, example function calls, and illustrative analyses. This preprint provides a general background of M/EEG classification for RSA as well as a narrative overview of the v2 MatClassRSA release, its updated functionalities, and illustrative analyses performed using the toolbox.

GABA-glutamate corelease is a mechanism for state-dependent neurotransmission
Ventral tegmental area neurons projecting to lateral habenula (LHb) corelease the main inhibitory and excitatory transmitters, GABA and glutamate (VTAGG). Yet the functional role of this synchronous signal remains unclear. We hypothesized that the sign of VTAGG action depends on postsynaptic state in LHb. Ex vivo, activating VTAGG terminals evoked excitatory and inhibitory responses in LHb that varied with postsynaptic membrane potential. In vivo, VTAGG inputs drove net inhibition and supported positive reinforcement that was dependent on GABA, but not glutamate, release. Using chemogenetics to bidirectionally modulate LHb, we found that LHb hyperpolarization shifted VTAGG effects toward excitation, abolishing positive reinforcement, whereas LHb depolarization enhanced net inhibition and positive reinforcement. Thus, the activity state of LHb neurons dictates whether GABA-glutamate corelease is functionally inhibitory or excitatory and can reverse the motivational valence of VTAGG input, supporting a homeostatic role for GABA-glutamate cotransmission with broad implications for disorders of imbalanced motivation.

Copper-Free Click Chemistry Enables High-Fidelity Engineering of Mitochondria Targeted Brain-Derived Exosomes
Mitochondrial dysfunction is a hallmark of neurodegenerative and neuroinflammatory disorders, including hypertension and cardiovascular disease, yet strategies for safe and precise mitochondrial-targeted delivery remain limited. Here, we establish strain-promoted azide-alkyne cycloaddition (SPAAC) as a biocompatible, high-fidelity chemical platform for engineering mitochondria-targeted brain-derived exosomes (BR-EVs). Copper-free click conjugation of a mitochondrial-targeting ligand (e.g. Cy5-DBCO) under mild aqueous conditions preserved vesicle morphology (30-150 nm core; 120-200 nm hydrodynamic), proteomic composition, and uptake dynamics. Time-course imaging and fluorescence recovery after photobleaching (FRAP) revealed unaltered endocytic kinetics, >75 % mitochondrial colocalization, and intact organelle architecture. In vivo neuroinflammation and biodistribution analyses demonstrated immunological neutrality, strong central nervous system retention, and minimal peripheral dispersion following intracerebroventricular administration. Proteomic profiling of unlabeled Sprague-Dawley (SD) and hypertensive Dahl salt-sensitive (DSS) BR-EVs uncovered hypertension-driven enrichment of oxidative and complement pathways correlating with mitochondrial fragmentation and reactive oxygen species generation in neuronal cultures. These findings establish SPAAC-mediated ligand conjugation as a biocompatible and chemically precise approach for generating mitochondria-targeted exosomes that preserve exosomal identity, biodistribution, and signaling fidelity-advancing a foundational platform for organelle-specific delivery and mechanistic imaging in the central nervous system.

Analysis of cortical dysplasias using b-tensor encoding diffusion MRI in an animal model
Cortical dysplasias are malformations of cortical development characterized by disorganization of the cyto- and myeloarchitecture of the neocortex. They are a common cause of epilepsy and their diagnosis through conventional imaging can often be challenging, hindering surgical treatments. Diffusion-weighted magnetic resonance imaging (dMRI) has the ability to infer tissue properties at the microscopic scale, making it a promising technique for detection of cortical dysplasias. This study aims to assess the microarchitecture of the cerebral cortex in a murine model of cortical dysplasia using diffusion-weighted magnetic resonance imaging (dMRI) acquired with b-tensor encoding. Pregnant Sprague-Dawley rats were administered either carmustine (BCNU) or saline solution on day 15 of gestation. Their offspring were imaged at 120 days of age using a 7 tesla scanner, acquiring diffusion-sensitive images with b-tensor encoding. Images were processed with Q-space trajectory imaging with positivity constraints (QTI+) to derive various metrics along a curvilinear coordinate system across the neocortex. After scanning, the brains were processed for immunofluorescence and histological examinations. Experimental animals exhibited a significant reduction of microscopic fractional anisotropy ( FA) and anisotropic kurtosis (Ka) in the middle and lateral cortical layers compared to the control animals. Immunofluorescence and histological analysis showed decreased and dysorganized myelinated fibers, and an increase of glial processes in BCNU-treated animals. Given the applicability of b-tensor encoding in clinical scanners, this approach holds promise for improving detection of focal cortical dysplasias in patients with epilepsy.

Canopy1/Cnpy1 is required for proper V2R processing and transport; its loss impairs the function and circuit organization of basal/V2R vomeronasal sensory neurons
The vomeronasal organ (VNO) is a specialized chemosensory structure in the nasal cavity that detects pheromones and mediates social and reproductive behaviors. The VNO of rodents is populated by different types of vomeronasal sensory neurons (VSNs). Apical VSNs, located near the lumen, express the transcription factor (TF) Meis2, V1R family receptors, and the G protein subunit Gao; the VSNs distributed closer to the basal lamina express the TF Tfap2e/AP-2{varepsilon}, V2R receptors, and the G protein subunit Gai2. In addition, sparse cells in the VNO express the Formyl Peptide Receptors (FPRs). Single-cell mRNA sequencing (scRNA Seq) identified over 980 differentially expressed genes between these cell types, with many linked to the endoplasmic reticulum (ER). Among these ER proteins, Canopy1 (Cnpy1), was found to be among the most enriched genes in V2R+ VSNs. Previously studied only in zebrafish, Cnpy1 was found to affect Fgfr1 signaling and is thus also known as "FGF signaling regulator-1". In a previous study, we discovered that AP-2e upregulates Cnpy1 expression. Although Cnpy1 knockout mice are viable and have normal VNO development at birth, they experience a progressive degeneration and loss of V2R-expressing VSNs. Prior to symptoms, the basal VSNs of KO mice display reduced V2R protein immunoreactivity in the soma and a complete absence of the protein at the lumen of the VNO, rendering the neurons non-functional. Cnpy1 KOs exhibit altered guidance cues and adhesion molecule expression, along with disrupted connectivity to the accessory olfactory bulb (AOB). Our study shows that distinct neuronal types depend on unique ER protein repertoires to maintain proper proteostasis. The loss of Cnpy1 highlights the importance of cell-type-specific ER factors in the differentiation and function of specific neurons, revealing mechanisms that drive neuronal diversity and vulnerability to ER gene disruption.

Rapid neocortical network modifications via dendritic plateau potential induced plasticity
Learning in brains is associated with changes in neuronal network activity thought to be driven by synaptic plasticity. While recent work in the hippocampus has revealed some of the mechanisms involved there, less is known about how neocortical circuits adapt, especially during behavior. Here to determine if neocortical areas possess rapid plasticity mechanisms that could support online adaptations we used optical imaging and intracellular membrane potential (Vm) recordings to examine the activity of layer V neurons in a higher visual area of mice learning a task. The introduction of a novel rewarded stimulus resulted in a rapid modification of population activity that featured abrupt alterations in single neuron selectivity. Vm recordings revealed that both naturally occurring and experimentally-induced dendritic calcium plateau potentials (plateaus) rapidly alter the action potential (APs) output and Vm dynamics of neurons over many seconds of time around the plateau, in some cases from one trial to the next. Trains of high frequency APs had no effect. Finally, experimental inhibition during learning of the distal dendritic region responsible for initiating plateaus reduced the rate of population level adaptation. Our findings suggest that the deep layers of higher order visual cortex possess a rapid learning mechanism mediated by plateau-induced synaptic plasticity.

N6-methyladenosine RNA methylation is a novel epitranscriptomic regulator of excessive alcohol drinking and vulnerability to relapse
While internal RNA modifications have been known for decades, the contribution of epitranscriptomics to alcohol use disorder (AUD) remains unexplored. Here we investigated, for the first time, the role of the most abundant mRNA modification, N6-methyladenosine (m6A) in the regulation of alcohol drinking and alcohol mediated gene expression. The fat mass and obesity associated gene (FTO) plays a key role in erasing m6A RNA methylation marks. We generated brain m6A hypermethylated mice with selective deletion of FTO in neurons by crossing FTO-floxed mice (FTO-fl/fl) with the synapsin-1-CRE deleter line (Syn1-CRE). Neuronal FTO-deficient mice showed enhanced initial motivation for alcohol, achieved escalated (dependent) drinking more rapidly after repeated cycles of alcohol intoxication and were more susceptible to relapse to heavy drinking following a period of abstinence. Alcohol-naive neuronal FTO-deficient mice exhibited potentiated alcohol-induced anxiolytic and sedative effects and blunted anxiogenic responses, despite unaltered alcohol metabolism. We carried out RNA-Seq of enriched methylated RNA by immunoprecipitation (MeRIP) and RNA-Seq profiling of unenriched RNA to study alcohols effect on the epitranscriptomic and transcriptional landscape. We observed that a history of alcohol intoxication induces robust RNA m6A hypermethylation in the hippocampus and that FTO-deficiency markedly alters m6A methylation and transcriptional dynamics. GSEA pathway analysis showed that neuronal FTO deficiency induces addiction-relevant pathways and alters monoaminergic and GABAergic neurotransmission, providing a molecular basis for the heightened vulnerability to alcohol abuse. Our findings demonstrate that neuronal m6A RNA methylation is a novel regulator of excessive alcohol drinking and alcohol-dependent gene expression and its dysregulation may contribute to the pathogenesis AUD.

A validated panel of commercial antibodies for reliable detection of FET proteins.
The FET protein family comprises the highly conserved RNA-binding proteins FUS, EWS and TAF15 which are implicated in RNA metabolism and neurodegenerative diseases such as ALS and FTLD. Despite their structural similarity, reliable detection of individual FET proteins remains challenging due to antibody cross-reactivity and inconsistent localisation patterns reported in the literature. To address this, we systematically evaluated 23 commercially available antibodies for specificity and performance across western blotting, immunocytochemistry, and immunohistochemistry. Using single and double shRNA knockdowns in HeLa cells, we confirmed target engagement and identified antibodies which were specific as well as those with significant cross-reactivity. Immunofluorescence in rat primary neurons and HeLa cells showed antibody and cell type dependent variations in nuclear and cytoplasmic localisation; from these, we identified a subset that demonstrated high-quality, region-specific staining in postmortem human brain tissue. Our findings highlight substantial variability in antibody performance and underscore the need for rigorous validation to ensure reproducibility in FET protein research. We present a validated panel of antibodies suitable for diverse applications, providing a critical resource for studies of FET protein biology and pathology.

Longitudinal Exploration of Auditory Sensory-Perceptual Processing in CLN3 Disease (Juvenile Neuronal Ceroid Lipofuscinosis (Batten disease)): A High-Density Auditory Evoked Potential (AEP) Study.
Background: There is currently limited information about sensory and perceptual abilities across the progression of CLN3 disease (Juvenile Neuronal Ceroid Lipofuscinosis; Batten disease), a recessively inherited lysosomal storage disorder and a leading cause of childhood neurodegeneration. Clinical symptoms include vision loss, motor impairments, and cognitive challenges, making it difficult to accurately assess neurocognitive and perceptual abilities. Thus, there is a critical need to identify objective biomarkers that can be used to inform disease progression and track treatment response in this population. Methods: This exploratory study investigates longitudinal changes in auditory sensory perceptual processing in a small sample of individuals with genetically confirmed CLN3 disease (N=4; 3 male) compared to a cross-sectional sample of 60 neurotypical (NT) controls using high-density electroencephalography (EEG). We utilized a duration mismatch negativity (MMN) paradigm, identical to what has been used in our previous cross-sectional study. We examined the auditory evoked potentials (AEPs) of the standard tones across three different stimulus onset asynchrony conditions and examined the N1 and P2 components of the AEP. Results: We found age related differences in the amplitudes of the N1 and P2 components in individuals with CLN3 disease relative to NT controls. These amplitude differences were most notable in CLN3 disease when participants were presented with standard tones that had the slowest presentation rate. Specifically, N1 and P2 amplitudes were more negative than NT controls in childhood and adolescence and as CLN3 disease participants aged, the amplitude of the AEPs was greater than controls. Further, a more positive N1 amplitude during the longest stimulus presentation condition was associated with both reduced verbal intelligence and working memory abilities in CLN3 disease participants. Conclusions: Our preliminary findings parallel recently published work in a mouse model of CLN3 disease that showed both sex- and age-dependent disruptions in central auditory processing. Taken together, we demonstrate the utility of auditory EEG measures as a sensitive, objective and translational measure in CLN3 disease that may serve as a potential outcome measure useful in tracking disease progression. Continued work is needed in humans focused on sex-based differences and longitudinal changes of auditory processing in CLN3 disease.

A New Method for Optimal Placement of Tumor Treating Fields Electrodes
Overview: Tumor Treating Fields (TTFields) provide a non-invasive treatment option for newly diagnosed glioblastoma. While optimization of electrode placement is important to increase treatment efficacy, clinical therapy planning is done using an undisclosed and proprietary software (NovoTAL), which is clinically unvalidated. This study investigates a new computational approach for optimizing TTFields electrode placement and is compared to the current clinical standard. Methods: We developed a new computational pipeline integrating patient-specific anatomical data to optimize electrode configurations in five representative glioblastoma cases with diverse tumor locations and sizes. Two optimization strategies were employed: one maximizing electric field intensity at the tumor, and another enhancing coverage of the adjacent brain while maintaining sufficient tumor intensity. Results were compared to electrode placements generated by NovoTAL. Additional simulations with artificial tumors assessed the effects of tumor size and location. Results: Optimized electrode placements improved electric field intensity in tumors by 18%-34% compared to the clinical standard. Coverage-weighted optimizations provided broader field coverage without significantly compromising tumor intensity. Smaller or surface-adjacent tumors benefited most from optimization, achieving precise targeting and enhanced coverage. Extensive randomized placement analyses highlighted the superior performance of the optimized configurations. Analysis of artificial models showed consistent improvements across varying tumor locations and sizes. Conclusion: Personalized optimization of TTFields electrode placement significantly improves electric field targeting of tumors and adjacent brain regions. This approach outperforms standardized planning software and clinical practices and supports future development of adaptive, automated strategies for individualized TTFields therapy in glioblastoma.

A 4-pole Theory-Based Compensation Method using Multiple Loads for Impedance Spectroscopy of Porcine Brain Tissue
Accurate determination of the electrical properties of brain tissue -conductivity and relative permittivity - is essential for modeling and optimizing neurostimulation and neuroimaging and modulation techniques such as EEG, MEG, TMS, and TES. However, large discrepancies in reported conductivity values highlight the methodological challenges associated with impedance measurements. In this study, we present a systematic evaluation of compensation methods in impedance spectroscopy to improve measurement accuracy using a self-developed four-point platinum electrode designed for biological tissue applications. Three compensation algorithms - open-short, open-short-load, and multiple-load - were implemented and compared using an RC parallel test circuit that emulated typical measurement conditions, with load resistances ranging from 250 Ohm to 5000 Ohm. Quantitative error analysis demonstrated that the multiple-load method achieved the lowest normalized root mean square error (3.4%) and superior stability across frequencies from 100 Hz to 1 MHz. The calibrated probe was subsequently applied to post mortem porcine brain tissue, yielding conductivity values of grey matter of 0.109 S/m and white matter of 0.074 S/m. These results are significantly lower than standard simulation parameters of 0.275 S/m, and 0.126 S/m for grey and white matter, respectively. Finite-element simulations revealed that using the measured conductivities increased electric field predictions by 2.1% for TMS and 46% for TES in the maximum electric field magnitude, respectively. Our findings demonstrate that accurate impedance compensation is critical for reliable characterization of brain tissue and for enhancing the precision of neurostimulation modeling in the future.

Silmitasertib, an FDA-designated orphan CK2 Inhibitor, ameliorates neuropathology and motor dysfunction in a Huntington's disease mouse model
Huntington's disease (HD) is a devastating autosomal dominant neurodegenerative disease that manifests with progressive motor, cognitive, and psychological impairments. HD is caused by a polyQ (CAG) repeat expansion in the huntingtin (HTT) gene, leading to the misfolding and aggregation of mutant HTT protein (mHTT) and the preferential degeneration of the striatum. Previously in our lab, we identified Protein Kinase CK2 as an important kinase involved in the pathophysiology of HD. Specifically, the alpha prime catalytic subunit of CK2 (CK2') is upregulated in HD, and genetic depletion of CK2' in HD mice results in improved motor behavior, decreased mutant Htt aggregation, and improved neuronal function. Silmitasertib (CX-4945) is an FDA designated orphan drug that inhibits CK2. This study aims to investigate whether CX-4945 treatment ameliorates HD pathology. We treated prodromal and late symptomatic HD mice, and used a variety of immunohistochemical, biochemical, physiological and behavioral approaches. We found that CX-4945 presented benefits in the amelioration of HD pathophysiology in both treated groups. Importantly, we found CX-4945 decreased mHtt aggregation, increased DARPP-32 expression and excitatory synapse density, restored homeostatic astrocyte phenotypes and ameliorated neuroinflammation and microgliosis, altogether resulting in improved motor behavior. These results support CX-4945 as a strong candidate for a targeted therapy to treat HD.

Comparing Methods for Mass Univariate Analyses of Human EEG: Empirical Data and Simulations
Electroencephalography (EEG) is a widely used method for investigating human brain dynamics. However, EEG analyses are frequently conducted with limited a priori knowledge regarding locations or latencies of meaningful statistical effects. This makes it difficult for researchers to form regions of interest (ROIs), which are then analyzed using traditional statistical models such as analysis of variance. In addition, exploratory studies, or studies interested in determining the exact temporal and spatial extent of a predicted effect may aim to examine many sensor locations and time points, often jointly. To address this, mass univariate analyses have become a valuable complement to ROI-based approaches. These methods attempt to correct for multiple comparisons while mitigating the risk of false positives and false negatives, thus enabling statistical inference in high-dimensional EEG data. Here, we review and evaluate different approaches for delineating spatial and temporal effect boundaries in three different datasets, focusing on within-subjects comparisons. Specifically, we focus on permutation-based approaches and their Bayesian alternatives to address condition differences in i) steady-state evoked responses, ii) event-related potentials, and iii) time-frequency data. Overall, simulation results indicate that cluster-based permutation tests provide a relatively liberal approach to correct for multiple comparisons across domains, with high sensitivity for detecting large effects. In contrast, the permutation-based tmax procedure yields the most conservative method across datasets. Bayesian approaches inherently are continuous in nature and thus strongly depend on the selection of thresholds for when support for a hypothesis is considered meaningful.

COSTS AND BENEFITS OF ACTING TOGETHER: A NON-HUMAN PRIMATE MODEL OF COOPERATIVE DECISION-MAKING
Cooperation is a crucial aspect of social behavior, allowing individuals to achieve goals unattainable alone. However, collective actions require costly inter-individual coordination, making continuous cost-benefit evaluation essential before engaging in cooperation. Non-human primate models can help uncover the evolutionary foundations of human cooperation and its underlying neural mechanisms. To this aim, we developed a novel paradigm to analyze the dyadic behavior of two macaques, who took turns in choosing between individual and cooperative actions to obtain variable rewards. Each monkey used a joystick to guide a cursor toward one of two targets, each indicating both the reward magnitude and the action type (i.e. 'solo action' or 'joint action') required to obtain their payoff. We first observed a linear improvement in dyadic performance with the expected reward magnitude. Although macaques tended to prefer individual actions, they selected to act jointly under favorable payoff conditions, indicating that voluntary cooperation in macaques can emerge as a reward-driven process. Logistic models of their choices revealed the subjective cost monkeys assigned to cooperation, which was consistent across subjects. Nonetheless, the gain rate across different sessions increased over time, suggesting that macaques possess the cognitive ability to optimize their dyadic strategies, by estimating not only the coordination costs but also the benefits of cooperation. We observed a progressive reduction in the subjective cost assigned to joint action, which was not directly dependent on performance improvements. Our findings suggest that non-human primates can weigh the costs and benefits of cooperation, highlighting their ability to dynamically adjust social strategies based on reward contingencies.

Adult Drosophila aversion to caffeine requires a unique TrpA1 isoform and the PLC signaling cascade
Taste in Drosophila melanogaster is crucial to survival, influencing feeding, mating, and egg laying behaviors. Taste organs are located on various parts of the body, including the legs, proboscis, wings, and ovipositor. Taste neurons detect chemicals via receptors like GRs, IRs, and TRPs, with bitter and sweet tastes linked to specific neurons (Gr66a+ and Gr5a+). Bitter substances such as caffeine activate neurons, resulting in rejection behavior. TrpA1 channels, associated with aversive responses, are involved in complex behaviors and could interact with taste receptors. Our results show that caffeine mixed with sucrose reduces proboscis extension in flies compared to sucrose alone, a response that requires only the TrpA1-E isoform out of the five possible ones. Furthermore, our data demonstrate that this avoidance requires TrpA1 and signaling via PLC and IP3-receptors in adult Gr66a+ neurons.

Harmonized Protocol for Segmentation of the Hippocampal Tail on High-Resolution in vivo MRI from the Hippocampal Subfields Group (HSG)
The hippocampus is a heterogeneous structure with cytoarchitectonically distinct subfields that exhibit heterogeneous lifespan trajectories and are differentially susceptible to diseases. Advances in high-resolution imaging have accelerated research on these structures, yet variability in segmentation protocols limits cross-study comparability. The Hippocampal Subfields Group (HSG) is an international consortium addressing this challenge by developing a reliable, accessible, and freely available segmentation protocol for high-resolution T2-weighted 3 tesla MRI scans (http://www.hippocampalsubfields.com). Here, we present the harmonized protocol for the posterior portion of the hippocampus (the 'tail'), complementing the previously established 'body' protocol, and with an anterior 'head' protocol under development. The tail protocol provides standardized definitions of the external boundaries for the posterior-most extent of the hippocampus, facilitating consistent segmentation from surrounding tissues. The research community was extensively involved through an online survey that incorporated comprehensive protocol details, feasibility assessments, tutorial videos, and illustrative segmentations. Through this collaborative process, consensus emerged to exclude subfield labeling in the hippocampal tail due to limited visibility of internal landmarks and substantial anatomical variability in this region. All proposed boundary guidelines were deemed clear and agreed upon via a Delphi procedure. The harmonized tail protocol has high intra- (Averaged ICC(2,1) > 0.98; Averaged Dice Similarity Coefficient = 0.92) and inter-rater reliability (Averaged ICC(2,k) > 0.98; Averaged Dice Similarity Coefficient = 0.86) and offers a practical framework for replicable segmentation. By establishing standardized guidelines, this protocol enhances comparability of findings across developmental, aging, and clinical research and is compatible with ongoing technological advances.

Unveiling the Multifaceted Networks of the Left DLPFC for Precision TMS Targeting
The left dorsolateral prefrontal cortex (lDLPFC) is the standard target for transcranial magnetic stimulation (TMS) to ameliorate treatment-resistant depression (TRD), yet non-response rates remain high. TMS efficacy has been linked to the stimulation site's functional connectivity, particularly its anti-correlation with the subgenual cingulate cortex (SGC). While this pragmatic strategy has demonstrated clinical utility, it offers limited insight into how the lDLPFC's network interactions contribute to site-dependent variability in treatment response. Here, we used connectivity-based parcellation within an lDLPFC region encompassing common TMS targets and adjacent areas to delineate functional subdivisions and characterize their connectivity to large-scale networks and behavioral associations. Our results revealed a hierarchical organization: a coarse two-pole antagonism between anterior-central and superior-posterior subregions and a finer nine-cluster architecture exposing lDLPFC's heterogeneity along anterior-posterior and ventral-dorsal axes. Anterior-central areas were strongly anti-correlated with SGC and default-mode network, positively connected with salience, dorsal attention, and control networks, and associated with cognitive control. In contrast, superior-posterior subregions displayed the inverse pattern, while ventral clusters engaged somatomotor and visual networks, and language-related processes. Central and superior-anterior clusters showed differentiated profiles, including associations with inhibition, social cognition, and perceptual functions. To aid clinical translation, we derived an lDLPFC likelihood map integrating granularities, highlighting anterior-central lDLPFC as the strongest TMS candidate considering the relevance of its connectivity and behavioral profiles to depression, while indicating that neighboring subregions have distinct functions. These findings underscore the lDLPFC's hierarchical and heterogeneous organization and provide a network-informed reference for developing individualized, symptom-specific TMS interventions.

Impact of the pulse artifact on evoked activity in human wakefulness and sleep
The investigation of the neural evoked response to the heartbeat quantified using electroencephalography (i.e., heartbeat evoked potentials or HEPs), has gained recent attention in neuroscience, notably as a measure of interoception, the sensory system responding to internal bodily states. One main challenge in measuring HEPs is their susceptibility to cardiac artifacts contamination, including the cardiac field artifact and the pulse artifact (PA), the latter possibly caused by the mechanical pressure of pulsating vessels. Here, we aimed at assessing the impact of PAs on HEPs and auditory evoked potentials (AEPs, a proxy of the neural responses to exteroceptive sensory stimuli). To this aim, we compared two pre-processing pipelines using independent component analysis in healthy volunteers (N=30). The first, standard, pipeline excluded ocular, muscle, sweating-related activity and cardiac-related activity stemming from the cardiac field artifact. The second, pairwise phase consistency (PPC) pipeline, in addition to the removal of the aforementioned components, used the quantitative metric of PPC between independent components and the ECG to remove the cardiac-related PA. We tested how these two pre-processing approaches influenced HEPs and AEPs recorded under diverse neurophysiological conditions (wakefulness, N2, N3, and REM sleep). Comparing the HEPs from the standard and the PPC approaches (cluster-based permutation statistics, p<0.05, two-tailed) revealed a significant effect of PAs, particularly in wakefulness, followed by REM and N2 sleep, with Cohen's d effect sizes of 1.92, 0.95 and 0.88, respectively. By contrast, PA correction had a negligible effect (p>0.05, two-tailed) on the HEPs in N3 sleep and on the AEPs in all vigilance states. Our results emphasize the need to account for the PA as a significant confounding factor when comparing HEPs across groups with varying vascular or cardiac conditions.

MExConn: A Mechanistically Interpretable Multi-Expert Framework for Multi-Organelle Segmentation in Connectomics
Electron microscopy (EM) provides subcellular resolution which has made it a critical tool in fields such as cellular biology and connectomics. However, manual annotation of subcellular organelles in these EM images is extremely labor-intensive and impractical at scale. While computational segmentation methods have been developed, most existing approaches are limited to segmenting a single organelle at a time, neglecting the inherent shared information present in EM images containing multiple organelles. To address this, we present MExConn, the first known interpretable multi-expert U-Net architecture in the connectomics field that employs a shared encoder and multiple decoder heads to simultaneously segment multiple organelles from the same input EM image. MExConn significantly outperforms five baselines, including single-organelle model and four state of-the-art connectomics segmentation models in all evaluation metrics, reducing the Variation of Information by up to 33.54% on average across organelles. A key novelty of our approach is that MExConn offers mechanistic interpretability by revealing that the shared encoder learns shared representations essential for accurately segmenting multiple organelles. Through systematic analysis of encoder gradients with respect to each decoder output, we identify channel-wise importance profiles and reveal that many encoder channels are jointly essential for all organelles, while others are organelle-specific. Rigorous experiments on three connectomics datasets demonstrate the effectiveness of MExConn in both segmentation performance and interpretability, establishing it as a principled approach for multi-organelle analysis in connectomics. The source code is publicly available at https://github.com/abrarrahmanabir/MExConn.

Gut metabolite IPA alleviates white matter injury post-ICH by enhancing myelin debris phagocytosis via Stap1 inhibition
Background: Intracerebral hemorrhage (ICH) causes neurological dysfunction and white matter injury (WMI) characterized by myelin loss, axonal injury and myelin debris accumulation. Microglia-mediated debris clearance is critical for WMI repair. The microbiota-gut-brain axis plays an essential role in the central nervous system diseases, one of the ways in which gut microbiota affects brain is via producing metabolites. Indole-3-proprionic acid (IPA), a tryptophan-derived metabolite that mainly produced by Clostridium sporogenes, exhibits anti-inflammatory and neuroprotective properties. However, its effect on ICH remains unclear. This study aims to investigate the IPA level after ICH and the therapeutic effects of IPA on neurological deficits and WMI, as well as the potential mechanisms underlying IPA-mediated neuroprotection. Methods: An ICH model was established using C57BL/6 mice, which then received intragastric IPA (20 mg/kg/day). Fecal abundance of IPA-related genes and IPA levels in feces and plasma were measured by qPCR and UPLC-MS/MS. Behavioral tests, qPCR, and immunofluorescence staining were used to assess neurological function, myelin integrity, and axonal injury. In vitro, BV2 microglia, with or without Stap1 knockdown, were co-cultured with myelin debris to assess IPA?s effects on phagocytosis. Additionally, targeted plasma IPA profiling was performed in 30 ICH patients and 30 matched healthy controls. Results: The relative abundance of IPA production-related genes and IPA levels in feces and plasma were significantly decreased after ICH and remained low into the chronical phase. After IPA administration, the neurological deficits, myelin loss and axonal injury of mice with ICH were significantly improved. In vitro, IPA increased BV2 microglia myelin debris phagocytosis by inhibiting Stap1 expression. IPA levels were significantly reduced in ICH patients, consistent with ICH mouse model. Conclusions: Our findings demonstrated that the gut microbiota-derived metabolite IPA could facilitate neurological deficits recovery and alleviate WMI, which could be a promising therapeutic strategy to improve ICH prognosis.

Independent Filter Analysis for Group Discrimination in fMRI
Traditional group-level fMRI analysis approaches, such as Independent Component Analysis (ICA), often rely on unsupervised dimensionality reduction to map subjects into a common feature space. While effective for capturing common variance across all subjects, the preservation of discriminative features between groups of participants is not guaranteed. To address this limitation, we introduce Independent Filter Analysis (IFA), a supervised extension of group ICA that explicitly models group-discriminative information as part of the dimensionality reduction steps. Prior to unmixing, IFA constructs a subspace that simultaneously retains both shared and group-specific information, enhancing sensitivity to group effects while preserving biological interpretability. We validated IFA using simulated data and paired condition comparisons from three Human Connectome Project (HCP) tasks. In the simulation, IFA achieved 95% classification accuracy, outperforming group ICA, which failed to detect subtle group differences. On the HCP data, IFA increased network matrix classification accuracy by up to 15% and produced spatial maps that more precisely reflected task-relevant differences.

Transcutaneous auricular vagus nerve stimulation enhances emotional bias towards happiness in healthy young adults: A comparative study of electrical and ultrasound stimulation
Transcutaneous auricular vagus nerve stimulation (taVNS) is an emerging neuromodulation technique demonstrating promise in emotional regulation. This study investigated the acute effects of both electrical (E-taVNS) and ultrasound (U-taVNS) modalities on emotional bias using a facial emotion categorization task in healthy young adults. Fifty-nine participants underwent a single-blind, sham-controlled, within-subject design, with emotional bias assessed at pre-, during-, and post-stimulation phases. Our findings revealed that both E-taVNS and U-taVNS significantly enhanced emotional bias scores, shifting the perception of neutral and ambiguous faces towards positive interpretations and reducing negative emotional bias. No significant differences in efficacy were observed between the two stimulation modalities. Furthermore, individual differences in interoceptive awareness were found to be associated with the observed taVNS effects. These results suggest that both electrical and ultrasound taVNS can acutely modulate emotional regulation, highlighting the potential of taVNS as a non-invasive, well-tolerated alternative for interventions targeting emotional bias and mood disorders.

Cumulative timing-dependent changes in corticospinal excitability during suprathreshold paired-pulse transcranial magnetic stimulation
Transcranial magnetic stimulation (TMS) is widely used to assess inhibitory and facilitatory circuits within the primary motor cortex. However, accumulating evidence suggests that even brief TMS paradigms may induce unintended changes in corticospinal excitability. Here, we examined whether suprathreshold paired-pulse TMS delivered at inter-stimulus intervals (ISIs) associated with intracortical facilitation or long-interval cortical inhibition (LICI) elicits cumulative changes in motor-evoked potential (MEP) amplitude. In experiment 1, we reanalysed data from 17 participants who received 20 suprathreshold paired-pulses at eight ISIs (10-200 ms) and 40 unconditioned single pulses. Stimulation was pseudo-randomised and distributed evenly across four blocks. A linear mixed-effects model assessed trial-wise changes in MEP amplitude across ISIs. We replicated the design in an independent sample (n=10, experiment 2). A significant trial-by-ISI interaction was observed in both cohorts. Specifically, MEP amplitudes increased across trials for ISIs of 20 and 30 ms (p<0.05), but remained stable at LICI-related ISIs (100-150 ms). A similar increase was also seen with single-pulse TMS. These findings demonstrate that suprathreshold paired-pulse TMS at short ISIs can cumulatively enhance corticospinal excitability during stimulation. Furthermore, the results suggest potential for using these protocols not just for probing cortical circuits, but also as interventions to modulate motor system excitability.

Age-Dependent Effects of Paraquat-Induced Parkinsonism on Serum Alpha-Synuclein Expression, Substantia Nigra Histoarchitecture and Neurobehaviour in Male Wistar Rats
Background Paraquat (PQ), a widely used herbicide, has been implicated in Parkinsons disease (PD)-like neurodegeneration through oxidative stress and alpha-synuclein (a-syn) dysregulation. Age is a critical determinant of vulnerability to neurotoxins. This study investigated age-dependent effects of paraquat-induced Parkinsonism on serum a-syn expression, substantia nigra histoarchitecture, and neurobehavior in male Wistar rats. Methods Sixty-three male Wistar rats were stratified into juvenile, young-adult, and adult cohorts and assigned to control, paraquat, or PQ+Recovery groups (n = 7). Paraquat (10 mg/kg, i.p.) was administered twice weekly for three weeks; recovery animals were monitored for two months. Neurobehavioral tests including hanging wire, open field, and Y-maze were conducted at baseline, post-exposure, and post-recovery. Serum and substantia nigra a-syn were quantified using ELISA, and histology assessed cytoarchitectural changes. Data were analyzed using t-tests and ANOVA (p is less than or equal to 0.05). Results Neurobehavioral outcomes showed no significant differences in spontaneous alternation across cohorts. Latency-to-fall remained stable in young-adult and juvenile rats but declined in adult PQ+Recovery animals (p = 0.05). Line crossings decreased in adult paraquat rats (p = 0.02). Urine pools decreased significantly in young-adult paraquat (p = 0.0010) and PQ+Recovery groups (p = 0.0016), with group effects in young-adult (p = 0.007) and juvenile cohorts (p = 0.047). Substantia nigra a-syn showed no significant differences (p > 0.22); serum a-syn differed in young adults (p = 0.039), with reduced levels in the recovery group (p = 0.047). Histology revealed paraquat-induced neuronal degeneration which was most severe in adults, and partial structural restoration after recovery period. Conclusion Paraquat induces mild, age-dependent neurotoxic effects, with adults showing the greatest vulnerability. Differential serum a-syn responses and histological findings highlight developmental stage as a key modulator of susceptibility and recovery following environmental neurotoxin exposure.

Neural and Behavioral Responses to Social Norm Violations Across Trust and Fairness Contexts
Fairness and trust are core components of social decision making, yet little is known about how individual differences shape neural responses across these contexts. Because the Trust Game (TG) and Ultimatum Game (UG) involve different forms of norm violation, betrayal and interpersonal unfairness, they allow us to test whether neural responses generalize across social contexts Using fMRI during both the TG and UG, we examined how trait-level social cognition interacts with brain systems supporting norm evaluation. Participants demonstrated robust sensitivity to fairness in the Ultimatum Game. A whole-brain psychophysiological interaction analysis revealed that connectivity between the posterior temporoparietal junction (pTPJ) and dorsolateral prefrontal cortex (dlPFC) during unfair offers from a human partner was moderated by the interaction between Autism Quotient (AQ) scores and dorsal anterior cingulate cortex (dACC) response to betrayal in the Trust Game. Individuals with higher AQ showed distinct patterns of pTPJ-dlPFC coupling depending on their neural sensitivity to trust violations. These findings highlight a cross-task mechanism through which trait-level social cognition and trust related conflict signals shape network-level responses to interpersonal unfairness.