bioRxiv Subject Collection: Neuroscience's Journal

A Developmental Atlas of the Drosophila Nerve Cord Uncovers a Global Temporal Code for Neuronal Identity
The assembly of functional neural circuits depends on the generation of diverse neural types with precise molecular identity and connectivity. Unlocking general principles of neuronal specification and wiring across the nervous system requires a systematic and high-resolution characterisation of its diversity, recently enabled by advances in single-cell transcriptomics and connectomics. However, linking the molecular identity of neurons to circuit architecture remains a key challenge. Here, we present a high-resolution developmental transcriptional atlas for the Drosophila melanogaster nerve cord, the central hub for sensory-motor circuits. With an unprecedented 38x coverage, this atlas enabled robust alignment to the adult connectome. We found that birth time sets a discrete versus continuous organisation of neuronal molecular identity, a difference we also identified in the connectome. We discovered a set of 17 transcription factors expressed in a conserved temporal sequence across all lineages, establishing a global temporal code for neuronal identity based on birth order, linking specification to differentiation across the nerve cord. Lastly, by mapping sex-specific transcriptional profiles to the connectome, we uncovered apoptosis and transcriptional divergence as key drivers for sex-specification. By resolving how molecular identity is temporally organized, this atlas opens new avenues to dissect the molecular mechanisms underpinning the development of neural circuits.

Variants in glycine decarboxylase activate mechanisms of mitochondrial energy metabolism in the brain.
Brain energy metabolism is produced from glucose by mitochondrial oxidative phosphorylation. Variants in the mitochondrial enzyme glycine decarboxylase (GLDC) cause a rare neurological disease, non-ketotic hyperglycinemia (NKH), with expected hallmarks of brain glycine elevation and responsiveness to folate deficiency that are equivalent to the severity of Gldc mutations. We remarkably find that brains of young-attenuated mutant mice with a 1.5-fold increase in glycine are reduced [gt] 5-fold in GLDC, show a decline in both the mitochondrial lipoyl-transfer protein GCSH and lipoylation of the pyruvate dehydrogenase (PDH) complex, as well as concomitant rise in signatures of astrocyte mitochondrial b-oxidation of fatty acids and activation of neuronal PDH. Our findings suggest a novel GLDC mechanism of remodeling mitochondrial energy systems throughout the brain, established early in and sustained throughout post-natal NKH disease.

Spatio-molecular gene expression reflects dorsal anterior cingulate cortex structure and function in the human brain
In the human brain, the dorsal anterior cingulate cortex (dACC) plays key roles in various components of cognitive control, and is particularly relevant for reward processing and conflict monitoring. The dACC regulates expression of fear and pain, and its dysfunction is implicated in a number of neuropsychiatric disorders. Compared to more recently specialized neocortical areas, such as the dorsolateral prefrontal cortex (dlPFC), the dACC is evolutionarily older. The region's agranular structure, and other evolutionary specializations, such as the presence of von Economo neurons (VENs), contribute to its specialized roles in cognitive and emotional processing. Here, we generated paired spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the dACC in ten adult neurotypical donors to define molecular profiles for dACC cell types and spatial domains. Using non-negative matrix factorization (NMF), we integrated these data by identifying gene expression patterns within the snRNA-seq data, which were projected onto the SRT data to infer the spatial localization. Combining these data with publicly available resources, we revealed insights about molecular profiles, spatial topography, enrichment of disease risk, and putative connectivity of spatially-localized dACC cell types, including VENs. Utilizing published dlPFC snRNA-seq and SRT data collected in the same neurotypical brain donors used here, we deployed cross-region comparison analyses between dACC and dlPFC to understand spatio-molecular specializations and laminar organization across human brain evolution. To make this comprehensive molecular resource accessible to the scientific community, we made both raw and processed data freely available, including through interactive web applications.

Taste dysfunction in Long COVID
Persistent taste dysfunction may occur both as acute and long-term symptoms of SARS-CoV-2 infection (Long COVID), yet the underlying mechanisms are unknown at the histological, cellular, and molecular levels. This study investigates the underlying pathology in 28 non hospitalized subjects who reported persistent taste disturbances for over 12 months after testing positive for SARS-CoV-2. To assess taste function, subjects completed the Waterless Empirical Taste Test (WETT), which quantifies the subject's ability to taste each of the five human taste qualities: sweet, umami, bitter, sour, and salty. Biopsies of fungiform papillae were collected from 20 participants and analyzed histologically for overall taste bud structure and innervation and by quantitative PCR (qPCR) for expression of markers for different taste receptor cells (TRCs). Although all subjects reported subjective taste dysfunction, only five scored below the 20th percentile on overall taste sensitivity. However, 12 subjects exhibited total loss of one or more taste qualities and another 13 subjects tested below the 95% confidence interval for at least one taste modality. Notably, loss of sweet, umami, or bitter tastes - qualities mediated by a PLC{beta}2-transduction cascade - was significantly more common than loss of sour and salty, and this loss correlated with reduced expression of PLC{beta}2 mRNA. Histological analysis revealed generally preserved taste bud structure and innervation in all cases, with occasional disorganization resulting in isolated PLC{beta}2-immunoreactive cells. Our findings suggest long term taste dysfunction after COVID-19 disproportionately impacts PLC{beta}2-dependent taste 38 qualities and is not due to widespread structural damage of the taste periphery.

A Novel Approach-Avoidance Task to Study Decision Making Under Outcome Uncertainty
To behave adaptively, people need to integrate information about probabilistic outcomes and balance drives to approach positive outcomes and avoid negative outcomes. However, questions remain about how uncertainty in positive and negative outcomes influence approach-avoid decision-making dynamics. To fill this gap, we developed a novel Probabilistic Approach Avoidance Task (PAAT) and characterized behavior in this task using sequential sampling models. In this task, participants (N=34, 24 females) made a series of choices between pairs of options, each consisting of variable probabilities of reaching a positive outcome (monetary reward) and of reaching a negative outcome (aversive image). Participants tended to choose options that maximized the likelihood of reward and minimized the likelihood of aversive outcomes. Moreover, the weights they placed on each of these differed for choices where these likelihoods were in opposition (i.e., the riskier option was also more rewarding; incongruent trials) relative to when these were aligned (congruent trials). Computational modeling revealed that the relative influence of rewarding and aversive outcomes on choice was captured by differences in the rate of decision-relevant information accumulation. These modeling results were validated with a series of model comparisons and posterior predictive checks, demonstrating that our sequential sampling models reliably captured our behavioral data. Together, these findings improve our understanding of the influence of motivational conflict, outcome type, and levels of uncertainty on approach-avoid decision-making.

Duet model of predictive coding unifies diverse neuroscienceexperimental protocols
The brain continuously generates predictions about the external world, allowing us to rapidly detect and prioritize unexpected events, such as a mistuned piano note or an omitted one. Experimental studies have shown that neurons in sensory cortices respond to various types of contextual deviants across different protocols, and sensory response is not reduced to zero when a stimulus is fully expected. To account for diverse forms of observed deviations, here we introduce duet predictive coding, a minimal and biologically plausible framework in which functional subgroups of neurons encode positive and negative prediction errors separately. In contrast to classical predictive coding, which assumes top-down input is purely inhibitory, our theory posits that it is context-dependent rather than absolute. This model reproduces neural responses observed in diverse predictive coding paradigms across visual and auditory cortices. Critically, our framework predicts the existence of neurons tuned to negative prediction errors in the oddball paradigm, a prediction confirmed by our analyses, yet overlooked by classical predictive coding models. Our findings suggest that the brain's deviance detection relies on duet predictive error computation, offering a unifying explanation across seemingly disparate experimental protocols.

Pak, a downstream gene of ecdysone signaling, determines left-right polarity in the Drosophila brain through neuronal cell chirality
Left-right (LR) asymmetry is a conserved characteristic of the brain in various animals and is related to its higher-order functions. The Drosophila brain has an LR asymmetric structure known as an asymmetrical body (AB). LR asymmetric neurite remodeling lateralizes the AB, and ecdysone signaling determines LR specificity. However, the mechanisms underlying LR specificity remain unclear. We found that the Slit/Dreadlocks/Roundabout/p21-activated kinase (Pak) signaling axis determines the LR polarity of the AB downstream of ecdysone signaling in the type II neuroblast lineage before LR asymmetric neurite remodeling. In Drosophila, the intrinsic chirality of cells (cell chirality) defines the LR asymmetry of various non-neuronal organs. We suggested that neurons derived from type II neuroblasts exhibit cell chirality, which is established through Pak and ecdysone signaling and determines the LR polarity of the AB. As cell chirality is broadly observed in eukaryotes, our study reveals a novel mechanism underlying LR asymmetry of the brain.

Mapping the microRNA-mediated crosstalk between insulin resistance and Alzheimers disease : a computational genomic insight
Insulin resistance (IR) and Alzheimers disease (AD) share overlapping molecular mechanisms, but the precise link between these conditions remains unclear. MicroRNAs, as post-transcriptional regulators of gene expression, may mediate this connection by targeting genes involved in both pathways. In this study, we employed a multi-step bioinformatics approach to identify microRNAs that simultaneously regulate genes associated with IR and AD. Twenty key IR-related genes were selected from the literature, and their microRNA regulators were predicted using five computational tools. These predictions were validated using experimentally supported databases (TarBase and miRTarBase), and each miRNA-gene interaction was scored. Sixteen high-confidence microRNAs were shortlisted based on cumulative prediction and validation scores. These microRNAs were then analyzed for their interactions with AD pathway genes via KEGG pathway analysis. The AD-related target genes were further processed through protein-protein interaction network analysis using STRING and hub gene identification via Cytoscape. Functional enrichment of these hub genes using Gene Ontology and KEGG analysis revealed their involvement in shared biological processes, including apoptosis, insulin signaling, glucose metabolism, and neuroinflammation. Prominent candidates such as miR-7-5p, miR-106b, miR-424-5p, and miR-15a were identified. These results suggest that a subset of microRNAs may serve as critical molecular links between IR and AD, offering potential targets for early diagnosis and intervention.

Integration of a neuronal RNAseq dataset with the draft Gryllus bimaculatus transcriptome refines gene predictions and highlights potential systematic response to injury
The cricket Gryllus bimaculatus presents a compelling model for investigating neuroplasticity due to its unusual capability of adult structural reorganization. The molecular pathways underlying these changes are entirely unknown. Here, we reanalyzed RNAseq data, drawn from deafferented neuronal tissue one, three, and seven days post-injury, that was previously used to assemble a de novo transcriptome. In this current analysis, we aligned our original RNAseq data to the publicly available G. bimaculatus draft genome, and used the resulting alignments to refine and update the existing annotations. We identified over 10,000 missing genes and reported a measurable improvement in BUSCO scores. These updated annotations were then used as the basis for a DESeq2 differential expression analysis and subsequent functional enrichment analysis to further explore the potential molecular basis of this compensatory anatomical plasticity. Days one and three showed the largest post-deafferentation expression differences. Overall, more transcripts were upregulated rather than downregulated. Protein-protein interactions enriched for G-protein-related signaling, hormone metabolism, and membrane dynamics were evident. Changes in expression of factors related to small GTPases and nervous system development were particularly intriguing. We also identified a surprising enrichment of GO terms related to muscle contraction in this neuronal-specific transcriptome. Identifying these and other differentially regulated transcripts can be used to design hypotheses around well-conserved molecular mechanisms that may be involved in this unique example of adult structural plasticity in the cricket.

The Motion Sensitivity and Predictive Utility of Different Estimates of Inter-regional Functional Coupling in Resting-state Functional MRI.
Numerous methods exist for quantifying statistical dependencies, termed functional coupling (FC), between regional brain activity recorded with resting-state functional magnetic resonance imaging (rs-fMRI). However, their efficacy in mitigating the effects of known sources of noise, such as those induced by participant head motion, and in augmenting effect sizes for brain-wide association studies (BWAS), remains unclear. Here we compared 10 different measures of FC, including correlations, partial correlations, coherence, mutual information, and partial information decomposition, and one measure of effective connectivity (EC; regression dynamic causal modelling), across two independent datasets comprising a total of 1,797 participants (867 males). Each method was evaluated for its ability to mitigate motion-related confounds in FC/EC estimates and for its utility in predicting 94 behavioural measures, as assessed via cross-validated kernel ridge regression. Our analyses showed that EC was most resistant to motion artifacts but had the weakest behavioral predictions. Conversely, traditional correlation-based methods showed the highest sensitivity to motion, but offered the strongest behavioral prediction across most domains and datasets. Nonetheless, relative differences in predictive accuracies were small, indicating that the use of different FC or EC metrics in rs-fMRI does not significantly impact BWAS effect sizes.

Nanoscale dendritic shaft constrictions shape synaptic integration in fine caliber principal neuron dendrites
Traditionally, theoretical studies typically described dendritic morphology as optimized for efficient synaptic voltage transfer from spines to the soma, implemented as a tubular design respecting Rall's 3/2 rule for impedance matching at branch points. Here, we reveal that this view is an oversimplification. Using three high-resolution imaging techniques, we demonstrate that dendrites in cortical and hippocampal neurons contain nanoscale constrictions, comparable in diameter to spine necks. We provide theoretical and experimental evidence that these constrictions partition the dendrite into distinct electrical compartments, significantly shaping dendritic integration of synaptic potentials.

Visual performance fields during Saccadic Suppression of Image Displacement
Visual perception is not homogeneous throughout the visual field. Performance is generally better along the horizontal meridian compared to the vertical meridian, and in the lower compared to the upper visual field. These asymmetries in visual performance are reflected in structural asymmetries in early visual cortex. When exploring a visual scene, eye movements occur continuously, with visual perception resulting from a tight interplay between the visual as well as the oculomotor systems. Literature on visual performance across visual fields during saccades is limited, but existing studies show that perceptual performance during saccades is indistinguishable between the upper and the lower visual fields, or altogether better in the upper visual field compared to lower. In the current exploratory study, we asked participants to detect the direction of target displacement across visual fields, while performing a saccade as well as at fixation. During fixation and saccade viewing conditions, performance on the task was better along the horizontal compared to the vertical meridian. However, we did not observe a robust difference in performance between the lower and upper visual field, neither at fixation nor when participants were requested to perform saccades. We interpret our results based on known behavioural and neural anisotropies, as well as considering evolutionary approaches to the perception-action cycle.

Biophysically relevant network model of the piriform cortex predicts odor frequency encoding using network mechanisms
Olfactory-guided animals utilize fast concentration fluctuations in turbulent odor plumes to perceive olfactory landscapes. Recent studies demonstrate that the olfactory bulb (OB) encodes such temporal features present in natural odor stimuli. However, whether this temporal information is encoded in the piriform cortex (PCx), the primary cortical target of OB projections, remains unknown. Here, we developed a biophysically relevant PCx network model and simulated it using previously recorded in vivo activities of mitral and tufted cells from OB in response to 2Hz and 20Hz odor frequencies for three odor mixtures. Analysis of the pyramidal cells' (PYRs) activity during the initial 500ms of odor stimulation revealed that 4.4-11.8% of cells exhibited significantly different average firing rates for the two different frequencies. Furthermore, 1D convolutional neural network (CNN) models trained and tested on PYRs' activities achieved discrimination accuracies of 73-95%. However, cells showing significant frequency discrimination contributed similarly to CNN performance as the non-discriminating cells. Using virtual synaptic knockout models, we found that eliminating either feedback or feedforward inhibition onto PYRs improved CNN decoding accuracy across all odor conditions. Conversely, eliminating recurrent excitation among pyramidal neurons or eliminating recurrent inhibition among both interneuron types simultaneously degraded CNN accuracy. Removing recurrent connections within individual interneuron populations had minimal effects on the performance. Our PCx model demonstrates that it can discriminate between 2Hz and 20Hz odor stimuli, with a bidirectional capability of performance modulation by specific circuit motifs. These findings predict that the piriform cortex encodes and processes temporal features of odor stimuli.

Bright Light Exposure Reduces Negative Affect and Modulates EEG Activity in Sleep-Deprived and Well-Rested Adolescents
This study investigated whether a single morning session of bright light exposure modulates alertness, cognition, mood, and EEG activity in well-rested and partially sleep-deprived adolescents. Forty-seven subjects were assigned to a well-rested (8 h sleep) or a sleep-deprived group (4 h sleep). All underwent 30 minutes of morning bright light exposure, with EEG, cognitive testing, and ratings of sleepiness and affect conducted pre- and post-intervention. Behavioral and electrophysiological changes were compared within and between groups. Associations between changes in EEG activity and behavioral outcomes were explored using correlation analyses. Bright light significantly reduced negative affect and improved Digit Span Forward task performance. No changes were observed in positive affect, subjective sleepiness, or Digit Span Backward scores. EEG analysis revealed decreased delta activity in the anterior cingulate and increased beta activity in the right insula and fronto-parietal regions. Behavioral and EEG effects were similar across groups; however, only in the sleep-deprived group changes in beta activity significantly correlated with reduced negative affect. These results suggest that bright light may acutely enhance emotional state, cognitive performance, and cortical arousal in adolescents. The link between beta activity and affective improvement under sleep deprivation suggests a potential mechanism by which light supports emotional regulation.

MyeliMetric: A Python-Based Toolbox for Standardized G-ratio Analysis of Axon-Myelin Integrity
The g-ratio, defined as the ratio of an axon's diameter to the total fiber diameter (axon plus myelin), is a key metric for assessing myelin integrity and axonal conduction velocity in both the central and peripheral nervous systems. Deviations from the physiological range often signal underlying pathology. Despite its diagnostic importance, there is currently no standardized, open-source tool for g-ratio analysis from post-segmented electron microscopy images. To address this gap, we developed MyeliMetric, a Python-based, user-friendly toolbox that streamlines g-ratio data preprocessing and integrates biologically informed validation, requiring minimal statistical expertise to operate without introducing common analytical errors. It is built on the principle that g-ratios exhibit relative consistency across varying axon diameters in healthy conditions. To rigorously assess this relationship, MyeliMetric implements a binning strategy that groups axons into biologically relevant diameter cohorts, enabling the detection of size-dependent deviations in g-ratio distributions. This approach addresses common limitations in conventional analyses, including insufficient sampling, pseudo-replication, and artifacts such as misleading regression slopes. Validation using both synthetic and published datasets from rodent models of demyelination demonstrated the tool's accuracy, reproducibility, and biological relevance. Synthetic data yielded expected outcomes, and in experimental models, MyeliMetric reliably detected reductions in myelin thickness through g-ratio shifts while minimizing artifacts, thereby providing biologically meaningful insights. It is available on GitHub: https://github.com/Intakhar-Ahmad/NeuroMyelin-G-Ratio-Analysis-Toolkit

Speed Vascular Patterns in the Spatial Navigation System
The hippocampal formation is central to spatial navigation, hosting neurons that encode position, direction, and speed. Yet, the brain-wide vascular dynamics supporting these processes remain poorly understood, especially during naturalistic behaviors. Here, we improved functional ultrasound (fUS) imaging to examine how cerebral blood volume (CBV) changes relate to behavioral parameters in rats during free exploration. High-resolution imaging of hippocampal-parahippocampal regions during open-field exploration reveals strong correlations between CBV dynamics and animal speed, with distinct regional activation patterns and temporal delays. Lagged general linear modeling uncovers information flow from the thalamus to parahippocampal regions, including the medial entorhinal cortex, and to hippocampal subfields (dentate gyrus, CA1 - CA3), consistent with a hierarchical processing framework. The analysis also links CBV with angular head speed and the dorsal thalamus. Decoding analyses show that CBV signals not only encode speed precisely but also capture spatial features like proximity to walls and corners, even when univariate analyses do not. This decoding remains robust across animals, underscoring the universality of speed encoding in vascular dynamics. We also identify slow CBV oscillations in the hippocampus aligned with minute-scale speed fluctuations, suggesting a neurovascular signature of exploratory behavior. These findings reveal a hemodynamic signature of speed representation in the navigation system, arising from energy demands in a continuous attractor network model for path integration, where population activity and synaptic currents increase quadratically with animal speed as both peak firing rates and neuronal recruitment scale linearly with animal speed. Moreover, they highlight functional ultrasound imaging as a powerful approach for probing the hemodynamic basis of navigation.

Beyond Threat: Changes in Visuocortical Engagement and Oscillatory Brain Activity during Non-Aversive Associative Learning
Aversive conditioning produces selectively heightened visuocortical responses to conditioned stimuli stimulus (CS) that predict aversive unconditioned events (US). However, it is unclear whether similar neural signatures emerge as a consequence of mere association formation between a CS-US pair, i.e., when a CS predicts a neutral event. To address this, we paired a soft tone (65 dB) with one of two high-contrast circular gratings (15 or 75 degrees; CS+; counterbalanced), while two intermediate orientations (35, 55 degrees) were never paired with the neutral tone, serving as generalization stimuli (GS). A sample of 22 participants viewed each grating for 3000 ms, with the tone presented during the last 1000 ms of each grating presentation. Gratings were flickered (turned on and off) at a temporal rate of 15 Hz, to evoked steady-state Visual Evoked Potentials (ssVEPs), a metric of visuocortical engagement. Time-frequency decomposition via Morlet wavelets quantified changes in the amplitude of alpha-band (8-13 Hz) oscillations - an additional electrophysiological index that has been shown to be sensitive to aversive conditioning. Contrary to findings observed during aversive conditioning, alpha amplitude increased, rather than decreased, during CS+ trials relative to GSs. Likewise, ssVEP amplitude was higher for GSs than for the CS+, which again is the opposite of what is found during aversive conditioning. These findings suggest that a CS paired with non-aversive outcomes engages mechanisms consistent with working memory, anticipation, or imagery processes, reflected in heightened alpha amplitude and attenuated ssVEP, rather than the defensive potentiation observed during aversive conditioning.

Social Anxiety Increases Autonomic and Visuocortical Generalization of Conditioned Aversive Responses to Faces
Aversive generalization learning is an adaptive trait that is necessary for survival in a dynamic environment. However, this process is exaggerated in persons with anxiety disorders, leading to overgeneralization of learned threat associations, hyperreactive fight-or-flight responses, and persistent avoidance. Patients with social anxiety disorder (SAD) exhibit impaired conditioned threat discrimination particularly with respect to social stimuli, such as faces. The present study examined the relationship between social anxiety and generalization of visuocortical and pupil dilation responses to a series of facial morphs, one of which was always paired with a noxious sound. Steady-state visual evoked potentials (ssVEPs; N = 65) increasingly fit a model of generalization, and pupil dilation responses (N = 62) also decreasingly discriminated the CS+ as a function of social anxiety. These results contribute to a growing body of work suggesting that SAD dysregulates the ability of autonomic responses to specifically target social threat. The finding of widened visuocortical tuning in SAD implicates a role of the visual system in driving attentional biases in anxiety disorders, including increased visual processing of safety signals similar to threat cues.

Structural Validation of the Intermediate Leptomeningeal Layer in the Human Central Nervous System
Traditionally, the human central nervous system (CNS) is described as having three meningeal layers, from outer to inner: dura mater, arachnoid mater, and pia mater. The arachnoid and pia mater are called the leptomeninges, and the space between them is filled with cerebrospinal fluid (CSF). Using gross dissection, light microscopy, and ultrastructural methods on fresh postmortem and cadaveric fetal to adult age CNS specimens (N=61), we demonstrate the presence of a fibro-cellular intermediate leptomeningeal layer (ILL) in the human CNS along the entire neural axis, from the cortex to the caudal end of the spinal cord. ILL divides the subarachnoid space (SAS) into two distinct structural compartments, traversed by vessels and nerves. The ILL shows unique structural features, such as dips into the sulci and fissures of the brain as a double-fold membrane carrying the vessels, bears intra-layer trabeculae, and creates the perivascular sheath. In the spinal cord, ILL shows the presence of distinct meningothelial cells with macrophage-like properties. Moreover, throughout the neural axis, it appears to be a non-sieved barrier, characterized by the presence of tight and adherens junctions.

Temporal windows of perceptual organization: Evidence from crowding and uncrowding
Organizing visual input into coherent percepts requires dynamic grouping and segmentation mechanisms that operate across both spatial and temporal domains. While crowding disrupts target perception when nearby elements fall within the same spatial pooling window, specific flanker configurations can alleviate this effect through Gestalt-based grouping, a phenomenon known as uncrowding. Here, we examined the temporal dynamics underlying these spatial organization processes using a Vernier discrimination task. In Experiment 1, we varied stimulus duration and found that uncrowding emerged only after 160 ms, suggesting a time-consuming process. In Experiment 2, we manipulated the stimulus onset asynchrony (SOA) between the target and flankers. We found that presenting good-Gestalt flankers briefly before the target (as little as 32 ms) significantly boosted uncrowding, even in the absence of temporal overlap between the two stimuli. This effect was specific to conditions in which flankers preceded the target, ruling out pure temporal integration and masking accounts. These findings suggest that spatial segmentation can be dynamically facilitated when the temporal order of presentation allows grouping mechanisms to engage prior to target processing. Moreover, the observed time course indicates that segmentation is not purely feedforward, particularly for stimuli that are likely to recruit higher-level visual areas, pointing instead to the involvement of recurrent or feedback processes.

Microsaccades track shifting but not necessarily maintaining covert visual-spatial attention
Covert attention enables the brain to prioritise relevant visual information without directly looking at it. Ample studies have linked covert visual-spatial attention to the direction of small fixational eye movements called microsaccades, offering researchers and clinicians a potential non-invasive tool to track internal states of covert attention. However, other studies have reported only a weak link or no link at all. We now show that the link between covert visual-spatial attention and microsaccades critically depends on the stage of attentional deployment. Across two experiments--each employing a distinct but widely adopted approach to fixational control--we show that spatial microsaccade biases were more pronounced (Experiment 1) or even exclusively present (Experiment 2) during the initial stage of shifting covert spatial attention, even when covert attention was subsequently maintained as testified by enhanced visual discrimination. This shows that the involvement of the brain's oculomotor system in covert visual-spatial attention qualitatively changes over the course of attentional deployment, and how its peripheral fingerprint in the form of microsaccades reliably indexes shifting but not necessarily maintaining covert visual-spatial attention.

Facilitating analysis of open neurophysiology data on the DANDI Archive using large language model tools
The DANDI Archive has become a key resource for open neurophysiology data, now hosting over 400 datasets in the Neurodata Without Borders (NWB) format. While these datasets hold tremendous potential for reanalysis and discovery, many researchers face barriers to reuse, including unfamiliarity with data access methods and difficulty identifying relevant content. To address these challenges, we introduce an AI-powered, agentic chat assistant and a semi-automated notebook generation pipeline. The chat assistant serves as an interactive tool for exploring and understanding neurophysiology datasets in the DANDI Archive. It leverages large language models (LLMs) and integrates with agentic tools to guide users through data access, visualization, and preliminary analysis. The notebook generator autonomously analyzes a the internal structure of a dataset with minimal human supervision, executing inspection scripts and generating visualizations. Based on this exploration, a second LLM agent then produces an introductory instructional Python notebook tailored to the dataset. We applied this system to 12 recently published datasets. Review by neurophysiology and data science specialists found that the generated notebooks were generally accurate and well-structured, with most notebooks rated as "very helpful". This work illustrates how AI can reduce barriers to scientific data reuse and foster broader engagement with complex neurophysiology datasets.

Gradient scheme optimization for PRESS-localized edited MRS using weighted pathway suppression
This study aimed to design and implement an optimized gradient scheme for PRESS-localized edited magnetic resonance spectroscopy (MRS) to enhance suppression of out-of-voxel (OOV) artifacts. These artifacts, which originate from insufficient crushing of unwanted coherence transfer pathways (CTPs), are particularly challenging in editing schemes for metabolites like gamma-aminobutyric acid (GABA) and glutathione (GSH). To address this, a volume-based likelihood model was developed to guide gradient scheme optimization, prioritizing suppression of CTPs based on likelihood. A volume-based likelihood model for CTP weighting was integrated into a Dephasing optimization through coherence order pathway selection (DOTCOPS) gradient optimization. Using a genetic algorithm with a new dual-penalty cost function, gradient schemes were optimized to maximize pathway-specific suppression. Hardware and sequence constraints, maximum gradient amplitudes and delay durations respectively, informed the optimization. Validation of the optimized scheme was performed with simulations and in vivo using an edited sequence in three brain regions (posterior cingulate cortex PCC, thalamus, and medial prefrontal cortex mPFC), with particular focus on OOV artifact reduction and spectral quality improvements. The optimized gradient scheme demonstrated improved k-space crushing efficiency (by an average of 197%). OOV artifacts were reduced in all brain regions, particularly in highly OOV-susceptible regions (thalamus and mPFC). Improvements were most notable around 4.3 ppm with significant OOV amplitude reductions (p < 0.001). By using a volume-based likelihood model for CTP prioritization, the optimized scheme ensures robust and region-agnostic performance in reducing OOV artifacts.

Neural Convergence of Graded Belief and Binary Belief Uncertainty
Belief was defined by William James as "the psychological process or function of cognizing reality", and the recent philosophical literature has emphasized that there are two types of belief: categorical and graded. The relationship between these two belief types is complex, and it is often assumed that the degrees of graded belief reflect confidence. However, this claim has not yet been addressed empirically. In this functional magnetic resonance imaging study we let N=29 young healthy participants rate their graded belief in 16 propositions from the conspiracy theory spectrum and estimated certainty scores from the ratings that we associated with brain activation during the presentation of the propositions. We found associations of uncertainty (i.e. negative associations with certainty scores) with brain activation in the dorsomedial prefrontal cortex (dmPFC), right dorsolateral prefrontal cortex (dlPFC), and posterior parietal cortex. The clusters in the dmPFC and dlPFC replicated associations with explicit ratings of uncertainty in binary belief decisions we identified in a prior study on domain-general belief. These results provide empirical evidence for a link between graded belief and uncertainty in human cognition and emphasize the role of doubt as a relevant process to take into account in concepts of graded belief.

Pupil dilation as a marker of attention/effort in aging and mild cognitive impairment
Pupil dilation (PD) can be easily measured and reflects responses to subjectively salient or cognitively demanding events. It therefore holds promise as a cognitive marker especially for individuals with mild cognitive impairment (MCI) or other neurodegenerative conditions with restricted abilities to respond in cognitive assessments. We assessed PD during two tasks, an oddball task for investigating attentional allocation and a Simon task which additionally allows for investigating cognitive effort in younger adults (YAs), older adults (OAs), and patients with MCI. PD is a useful marker for investigating attention and cognitive effort in MCI, as suggested by elevated PD to salient stimuli in particular of individuals with better attentional control in MCI patients, as well as YAs and OAs. Measurement of PD may serve as an easy-to-administer measure to assess changes in cognitive function in healthy aging and MCI.

A novel interoceptive subfornical organ to infralimbic cortex circuit relays airway inflammation effects on fear extinction
There is growing interest in the impact of internal body states on the brain and behavior. The detrimental effects of chronic lung inflammation on mental health are well recognized, however, underlying mechanisms are not known. Here, using a murine model of allergic asthma we report compromised fear extinction in mice with severe but not mild airway inflammation (AI); an effect abolished by anti-interleukin-17A (IL-17A) antibodies. Investigation of innate immune cells, microglia as-well-as transcriptomic signatures in the subfornical organ (SFO), a brain interoceptive node lacking a traditional blood-brain-barrier, revealed significant alterations in severe AI mice. IL-17 Receptor A (IL-17RA) was expressed in SFO microglia and upregulated in severe AI mice. Notably, ablation of microglial IL-17RA improved fear extinction in severe AI mice. Furthermore, we identified direct SFO projections to the infralimbic (IL) cortex, a key area regulating extinction. Importantly, chemogenetic inhibition of the SFO-IL circuit led to improved fear extinction in severe AI mice. Collectively, we report a unique body-to-brain interoceptive mechanism engaging the SFO and an SFO-to-IL circuit, through which airway inflammatory mediators compromise fear extinction. Beyond asthma, our findings are relevant to other pulmonary pathologies (e.g. bacterial pneumonia, ARDS, COVID-19) highlighting a risk for cortical dysfunction and fear pathologies such as PTSD.

Formic acid impairs α-synuclein seeding activity in human and mouse brains
-Synuclein (-syn) is an abundant monomeric protein that can aggregate into fibrils and form neuropathological inclusions in the brains of patients with synucleinopathies. New evidence suggests that the mouse-human transmission barrier of -syn is lower than previously reported, emphasizing the need for improved biosafety procedures when working with -syn aggregates. Histopathology of -syn-infected brain represents a significant potential source of occupational exposure, and current methods for tissue fixation do not inactivate the ability of pathologic -syn to seed the conversion of endogenous, monomeric -syn into fibrils. In this study, we tested whether 96% formic acid treatment could reduce the seeding activity of -syn aggregates in paraformaldehyde-fixed brain samples from dementia with Lewy bodies (DLB) patients and -syn pre-formed fibrils (PFF)-injected mouse brains. Using real-time quaking-induced conversion (RT-QuIC), we found that formic acid treatment reduced -syn seeding dose (picograms of -syn seeds per ml of brain homogenate) in DLB and mouse brain by 6 and 8 logarithms, respectively. RT-QuIC reactions seeded with formic acid-treated brain homogenates showed significantly longer lag phase, and decreased total thioflavin T fluorescence compared to untreated samples, indicating that formic acid treatment impairs the ability of pathological -syn to seed monomeric -syn. Importantly, the -syn pathologic features and the immunostaining quality were preserved in formic acid-treated tissues. Our results demonstrate that formic acid treatment is a quick and efficient procedure for reducing -syn seeding activity in fixed brain samples, thereby lowering the risk of accidental exposure in laboratories without compromising the quality of histopathological analysis.

Functional network architecture and dynamics of the somato-cognitive action network
The somato-cognitive-action-network (SCAN) is a recently discovered brain network. SCAN interdigitates somatomotor networks and is functionally connected to the cingulo-opercular/action-mode network. SCAN is therefore thought to play a role in motor/action planning. This view of SCAN, however, is based on its "static" functional connectivity--i.e. FC estimated using data pooled over an entire scan session or dataset. However, this approach necessarily overlooks changes in network activity and connectivity that occurs over shorter timescales. In this report, we extend analyses of SCAN's static architecture, demonstrating that, at the whole-brain level, SCAN vertices exhibit overlapping network membership, such that, while they form a cohesive sub-network, they may also couple transiently and dynamically with other networks. We examine these potential co-activations by focusing on SCAN dynamics and through the identification of distinct coupling modes -- co-activation patterns (CAPs). We show that CAPs differentially contribute to SCAN's static architecture and that their frequency varies across following limb immobilization.

NeuroSuite for Long-term Functional and Structural Studies of Air-Liquid Interface Cerebral Organoids
Over the past decade, air-liquid interface cerebral organoids (ALI-COs) have emerged as powerful in vitro models that capture essential structural and functional traits of the human brain, offering an exciting alternative to traditional animal models in neuroscience. Yet, the full potential of these systems has remained untapped due to the lack of non-invasive, long-term electrophysiological tools capable of preserving organoid integrity. Existing techniques, ranging from patch clamping to rigid and 3D microelectrode arrays, often compromise organoid growth and disrupt delicate cytoarchitecture. Here, we present NeuroSuite, an innovative bioelectronic platform designed to overcome these challenges. At its core is Neuroweb, a perforated, ultra-thin, and conformable organic microelectrode array engineered for minimal disruption of nutrient and oxygen exchange. Neuroweb is reusable and supports stable recordings for over six months, making it uniquely suited for longitudinal studies. Coated with poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS), a high-performance mixed ionic-electronic conductor, Neuroweb delivers exceptional signal-to-noise ratio recordings with high spatial precision. By pairing Neuroweb with NeuroMaps, an intuitive software for interactive analysis and visualisation, NeuroSuite enables long-term, non-invasive tracking and spatial mapping of electrical activity from brain organoids and ex vivo brain slices at the air-liquid interface. Following rigorous validation, we demonstrate that NeuroSuite can capture both high- and low-frequency throughout maturation. Our pipeline reveals evolving network connectivity, including the development of GABA-ergic interneurons, and concurrent shifts in high-frequency spiking and low-frequency oscillations indicative of a refinement in the excitatory-inhibitory balance. Finally, automated data acquisition and spatial spike mapping highlight local activity changes in response to media composition, a factor often overlooked in conventional recordings. NeuroSuite thus opens a new frontier in organoid neuroscience, enabling precise, long-term monitoring essential for modelling neurological diseases, understanding human brain development, and accelerating drug discovery.