bioRxiv Subject Collection: Neuroscience's Journal

Intrinsic and extrinsic mechanisms alter neural cell fate specification in EPM1 Epilepsy
The extracellular milieu, including extracellular vesicles (EVs), plays a pivotal role in brain development by regulating neural processes such as proliferation, differentiation, and migration. In this study, we sought to elucidate the pathogenesis of progressive myoclonus epilepsy type 1 (EPM1), a disease caused by mutations in the CSTB gene, using cerebral organoids (COs) derived from EPM1 patient cells. The results demonstrate that EPM1 COs display increased electrophysiological activity and a disrupted excitatory/inhibitory balance. Single-cell RNA sequencing (scRNA-seq) analysis of ventral EPM1-COs revealed an abnormal specification of progenitor fate, with a shift toward dorsal neuron identities at the expense of inhibitory interneurons. In addition, pathological alterations in EV biogenesis and cargo were identified, including aberrant Sonic Hedgehog (SHH) signaling, which may disrupt cortical patterning. These findings suggest that both intrinsic progenitor identity shifts and extrinsic EV-mediated signaling contribute to EPM1 pathology. Our study highlights potential therapeutic strategies mediated by EVs as a novel approach to mitigate disease progression.

Axonal transcriptome reveals upregulation of PLK1 as a protective mechanism in response to increased DNA damage in FUSP525L spinal motor neurons
Mutations in the gene FUSED IN SARCOMA (FUS) are among the most frequently occurring genetic forms of amyotrophic lateral sclerosis (ALS). Early pathogenesis of FUS-ALS involves impaired DNA damage response and axonal degeneration. However, it is still poorly understood how these gene mutations lead to selective spinal motor neuron (MN) degeneration and how nuclear and axonal phenotypes are linked. To specifically address this, we applied a compartment specific RNA-sequencing approach using microfluidic chambers to generate axonal as well as somatodendritic compartment-specific profiles from isogenic induced pluripotent stem cells (iPSCs)-derived MNs. We demonstrate high purity of axonal and soma fractions and show that the axonal transcriptome is unique and distinct from that of somas including significantly fewer number of transcripts. Functional enrichment analysis revealed that differentially expressed genes (DEGs) in axons were mainly enriched in key pathways like RNA metabolism and DNA damage, complementing our knowledge of early phenotypes in ALS pathogenesis and known functions of FUS. In addition, we demonstrate a strong enrichment for cell cycle associated genes including significant upregulation of polo-like kinase 1 (PLK1) in FUSP525L mutant MNs. PLK1 was increased upon DNA damage induction and PLK1 inhibition further increased the number of DNA damage foci in etoposide-treated cells, an effect that was diminished in case of FUS mutant MNs. In contrast, inhibition of PLK1 increased late apoptotic or necrosis-induced neuronal cell death in mutant neurons. Taken together, our findings provide insights into compartment-specific transcriptomics in human FUS-ALS MNs and we propose that specific upregulation of PLK1 might represent an early event in the pathogenesis of ALS, possibly modulating DNA damage response and other associated pathways.

Slow and fast gamma oscillations show phase-amplitude coupling with distinct high-frequency bands in macaque primary visual cortex
Gamma oscillations (25-70 Hz) can be induced in the visual cortex by presenting stimuli like gratings. Large stimuli produce two distinct gamma oscillations in primate primary visual cortex (V1) - slow (25-40 Hz) and fast (40-70 Hz), possibly due to different interneuronal networks. While fast-gamma has been shown to strongly lock spikes, slow-gamma does not, and hence its role in cortical processing is unclear. Here, we studied potential influence of gamma rhythms on neural activity using phase-amplitude coupling (PAC). We recorded spikes, local field potential and electrocorticogram (ECoG) from V1 of two adult female monkeys while presenting stimuli that simultaneously induced both gamma rhythms, and developed a novel method that reduces the influence of spike-related-transient on PAC. Interestingly, while fast-gamma showed coupling with frequencies above 150 Hz, reflecting spike-locking, slow-gamma showed PAC in a distinct frequency range between 80-150 Hz, which was especially prominent in ECoG. PAC varied with orientation and spatial frequency in the same way as power in the respective frequency bands, confirming dissociation in the coupling of the two gamma rhythms. Thus, fast-gamma could be more involved in spike-locking, while slow-gamma could represent a modulatory signal acting by amplitude modulation between 80-150 Hz at a more global scale.

SIGNAL: Dataset for Semantic and Inferred Grammar Neurological Analysis of Language
Recently, the idea of comparison of models' representations and human brain signals has been a topic of several works. Consequently, several datasets with text data and EEG representations have been published. However, most of the datasets are based on normal reading task with grammatical sentences. At the same time, in the interpretability studies of LLMs, more and more attention is paid to thoroughly designed linguistic tasks based on acceptability measures. In this paper, we present SIGNAL, a dataset for Semantic and Inferred Grammar Neurological Analysis of Language. Our dataset contains a group of sentences with a combination of a fully acceptable sentence and a grammatically or/and semantically incongruent sentences. The dataset has been approved by native speakers and later used for an EEG experiment. In total, our dataset contains recordings of 21 participants, each of whom read 600 sentences. In addition, we present a pilot study where we compare EEG analysis with simple probing experiments.

Differential Engagement of Associative-Limbic and Sensorimotor Regions of the Cerebellum and Basal Ganglia in Explicit vs. Implicit Emotional Processing
Emotional prosody processing involves multiple brain regions, but the specific roles of the cerebellum and basal ganglia in explicit (conscious) and implicit (incidental) tasks are not well known or understood. This study investigated how the cerebellum and basal ganglia contribute to explicit (emotion categorization) and implicit (gender categorization) processing of emotional prosody. Twenty-eight healthy French-speaking participants underwent high-resolution functional MRI while performing a vocal emotion processing task under such implicit and explicit conditions. Behavioral data analyses indicated greater accuracy in the gender discrimination task (implicit processing). Neuroimaging partially supported our hypothesis according to which explicit emotion processing yielded increased activations in associative-limbic regions (e.g., inferior frontal gyrus, Crus I and caudate) linked to higher-order functions, while implicit emotion processing engaged sensorimotor regions (primary motor cortex, primary somatosensory cortex) and areas associated with automatic processing (putamen, posterior insula, cerebellar lobules VIIIa-b and IX). Unexpected activity during task conditions suggest motor preparation effects and more complex brain network dynamics. These results challenge modular views of brain function and highlight the need to consider emotional processing as complex, dynamic, network-based interactions.

Gaze when walking to grasp an object in the presence of obstacles
People generally look at positions that are important for their current actions, such as objects they intend to grasp. What if there are obstacles on their path to such objects? We asked participants to walk into a room and pour the contents of a cup placed on a table into another cup elsewhere on the table. There were two small obstacles on the floor between the door and the table. There was a third obstacle on the table near the target cup. Participants mainly looked at the items on the table, but as they approached and entered the room they often looked at the floor near the obstacles, although there was nothing particularly informative to see there. They relied on peripheral vision and memory of where they had seen obstacles to avoid kicking the obstacles. From well before participants crossed the obstacles, they primarily looked at the object that they intended to grasp. We conclude that people look at positions at which they plan to interact with the environment in a specific manner, rather than at items that constrain such interactions.

Opposite-sex pairing alters social interaction-induced GCaMP and dopamine activity in the insular cortex of male prairie voles
The prairie vole (Microtus ochrogaster) is a monogamous rodent species which displays selective social behaviors to conspecifics after establishing a pair bonded relationship, specifically partner-directed affiliation and stranger-directed aggression. This social selectivity relies on the ability of an individual to respond appropriately to a social context and requires salience detection and valence assignment. The anterior insular cortex (aIC) has been implicated in stimulus processing and categorization across a variety of contexts and is well-situated to integrate environmental stimuli and internal affective states to modulate complex goal-directed behaviors and social decision-making. Surprisingly, the contribution of the aIC to the expression of pair bond-induced social selectivity in prairie voles has been drastically understudied. Here we examined whether neural activity and gene expression in the aIC change in response to opposite-sex pairing and/or as a function of pairing length in male prairie voles. Opposite-sex pairing was characterized by changes to calcium and dopamine (DA) transients in the aIC that corresponded with the display of social selectivity across pair bond maturation. Furthermore, D1 and D2 receptor mRNA expression was significantly higher in males after 48 hrs of cohabitation with a female partner compared to same-sex housed males, and D2 mRNA remained significantly higher in males with a female partner compared to same-sex housed males after a week of cohabitation. Together, these results implicate a role for DA and its receptors in the aIC across the transition from early- to late-phase pair bonding.

Neural networks simulating short-term memory of two inputs with varying commonality
The activity and connectivity of neurons in the primate brain underlying behavior cannot yet be completely specified, but neural networks provide complete models of the connectivity and activity that performs specific tasks and provide insight into the neural computations performed by the primate brain (Fetz and Shupe 2003). Studies of neurons in the monkey cortex have shown that short-term memory of sensory events may be mediated by sustained neural activity. Short-term memory tasks have been modeled with dynamic neural networks using a single continuous variable and a gate input to create a sample-and-hold (SAH) function (Zipser 1991; Maier 2003). Networks trained to perform these short-term memory tasks develop hidden unit activity which resembles that of cortical neurons in monkeys performing memory tasks. We here extend the investigation of single-input SAH networks to networks computing SAH for two continuous-variable inputs that have varying degrees of common mode signal. Results provide insights into computational mechanisms of associative short-term memory of sensory signals with common mode components, such as visual inputs to the two eyes, auditory inputs to the ears and proprioceptive input from multiple muscle spindle afferents. We also examined the attractor states that these SAH networks eventually reach after sufficiently long delay periods and found that these were determined by the shapes of the input-output functions of the hidden units rather than network architecture.

Humidity-dependent structural adaptations of Drosophila melanogaster hygrosensilla
Understanding how organisms detect environmental humidity remains a fundamental problem in sensory biology. While specialized sensory neurons in insect antennae can detect changes in humidity, the mechanism underlying this ability is not fully understood. Here, we present an integrated approach combining precise humidity control, rapid cryo-preservation, and serial block-face scanning electron microscopy (SBF-SEM) to investigate the ultrastructure of hygrosensilla in the vinegar fly Drosophila melanogaster. We developed a deep learning-based segmentation pipeline to analyze three-dimensional structural features of sensilla exposed to different humidity conditions at stable temperature. Our analysis reveals consistent differences in sensilla width between high (80% RH) and low (26% RH) humidity conditions across all chambers of the sacculus. Additionally, we identified chamber-specific patterns in sensilla tapering, indicating specialized structural adaptations across different sensilla populations. The observed structural changes suggest a potential role for mechanical transduction in humidity sensing. This study establishes a technical framework for high-resolution analysis of sensory organs while providing new insights into the structural basis of humidity detection. Our findings advance our understanding of how specialized sensory organs might transduce environmental signals into neural responses.

Development of Non-Spatial Grid-Like Neural Codes Predicts Inference and Intelligence
Piaget's theory emphasizes children develop structured knowledge schemas for assimilating new concepts, yet the neural mechanisms and their link to intelligence remain unclear. In 203 participants aged 8-25 years, we investigated how maturation of neural representations of a two-dimensional knowledge map supports inferential reasoning and assimilation. We found that grid-cell-like neural codes in the entorhinal cortex (EC) strengthen with age, forming structured representations in non-spatial conceptual spaces. This maturation is directly linked to improved inferential reasoning. These grid-like codes support the medial prefrontal cortex (mPFC) in encoding distance relationships between concepts. As participants assimilated new information, they integrated it into existing grid patterns in the EC. Furthermore, maturation of these neural codes predicts real-world intelligence measures, particularly in abstract reasoning. Our findings show that the development of non-spatial grid-like neural codes underpins inference and knowledge assimilation, providing a neural basis for cognitive development and linking cellular neuroscience with intelligence.

Astrocyte-specific secretome profiling reveals its correlation with neurological disorders
Secreted proteins mediate intercellular communication throughout the lives of multicellular organisms. However, due to the lack of new technology for secreted protein capturing, the progress of "secretomics" lags behind. Here, we report a two-step secretome enrichment method (tsSEM) combining unnatural amino acid labeling and click chemistry-based biorthogonal reaction, which enables in vitro secretome profiling in the presence of serum. Using this novel method, we systematically investigated the secretome of human iPSCs-derived astrocytes (iAst) in different disease models and identified a panel of astrocyte-secreted proteins that are responsible for its non-cell autonomous toxicity under disease conditions. Furthermore, we validated two astrocytes-derived novel neurotrophic proteins, FAM3C and KITLG, which we identified from disease models, and found that they could boost neurite outgrowth, protect neurons, and promote neural progenitor proliferation. Our study highlights the utility of secretome profiling of iAst and demonstrates its applications in disease study and target identification and validation in drug development.

Pupillometry and Whole-Brain c-Fos Mapping Uncover Multimodal Mirror Mechanisms in Emotional Contagion Networks of Mice
Emotional contagion (ECo) represents a fundamental form of empathy. In this study, we used pupillometry to quantify ECo by assessing pupil responses of a mouse watching another mouse receive a tail shock. Pupil dilation effectively measured both direct and vicarious emotional response thresholds at the individual level through psychometric curve analysis. The pupillary ECo response diminished when the observer could not see the demonstrator, suggesting a multisensory process involving vision. Viewing videos of tail-shocked mice was sufficient to elicit a pupil response in the observer. Whole-brain c-Fos mapping revealed a broad network of 88 brain regions activated during ECo, with all areas activated in the demonstrator also engaged in the observer. Additionally, in certain brain regions, correlated activation was detected between each observer-demonstrator pair, indicating that ECo promotes a shared neural state. These findings advance our understanding of the neural basis of empathy, with implications for analyzing neuropsychiatric disorder models.

Exploring the Neural Basis and Validity of Ordinal Emotion Representation through EEG
Accurately measuring emotion is a major challenge in advancing the understanding of human emotion and developing emotional artificial intelligence. In many existing studies, participants' emotional ratings in interval scales are considered the true reflection of their emotional experiences. However, recent research suggests that ordinal annotations of emotions can more accurately capture the emotional expression process, providing a potential method for more precise emotion measurement. However, our understanding of the characteristics and validity of this new form of emotion representation is still relatively lacking. In particular, there is a lack of research using neural signals to explore the validity and neural basis of ordinal emotion representation. In this study, we used a video-elicited EEG dataset (n = 123) to identify the neural basis of ordinal emotion representation and demonstrate its validity from a neural perspective. Furthermore, we explored various characteristics of ordinal emotion representation, showing how it is superior to the interval form. First, we conducted inter-situation representational similarity analysis (RSA) and inter-subject RSA to test the degree to which ordinal representation captures both group commonalities and individual differences of emotion. Next, we investigated the characteristics of ordinal representation under different combinations of emotion items, including uni-variate and multivariate emotions, positive and negative emotions. Our results show that both group commonalities and inter-subject variations in EEG features are better explained by ordinal emotion representations than by interval ones. Multivariate ordinal representations showed better inter-subject reliability and higher representational similarity with EEG features compared to univariate counterparts, highlighting the co-occurrence nature of human emotions. Compared to negative emotions, ordinal representation showed greater improvements for positive emotions, suggesting that the complexity of positive emotions is well captured by ordinal representations. Taken together, these findings demonstrate that multivariate ordinal emotion ratings provide a more accurate measure of real emotional experience, which is crucial for enabling machines to precisely understand and express human emotions.

Neural signatures of temporal anticipation in human cortex represent event probability density
Temporal prediction is a fundamental function of neural systems. Recent advances suggest that humans anticipate future events by calculating probability density functions, rather than hazard rates. However, direct neural evidence for this mechanism is lacking. We recorded neural activity using magnetoencephalography as participants anticipated auditory and visual events distributed in time. We show that temporal anticipation, measured as reaction times, approximates the event probability density function, but not hazard rate. Temporal anticipation manifests as spatiotemporally patterned activity in three anatomically and functionally distinct parieto-temporal and sensorimotor cortical areas. In both audition and vision, each of these areas revealed a marked neural signature of anticipation: Prior to sensory cues, activity in a specific frequency band of neural oscillations, spanning alpha and beta ranges, encodes the event probability density function. Strikingly, these neural signals predicted reaction times to imminent sensory cues. These results show that supra-modal representations of probability density across cortex underlie the anticipation of future events.

Elevated EGR1 Binding at Enhancers in Excitatory Neurons Correlates with Neuronal Subtype-Specific Epigenetic Regulation
Brain development and neuronal cell specification are accompanied with epigenetic changes to achieve diverse gene expression regulation. Interacting with cell-type specific epigenetic marks, transcription factors bind to different sets of cis-regulatory elements in different types of cells. Currently, it remains largely unclear how cell-type specific gene regulation is achieved for neurons. In this study, we generated epigenetic maps to perform comparative histone modification analysis between excitatory and inhibitory neurons. We found that neuronal cell-type specific histone modifications are enriched in super enhancer regions containing abundant EGR1 motifs. Further CUT&RUN data validated that more EGR1 binding sites can be detected in excitatory neurons and primarily located in enhancers. Integrative analysis revealed that EGR1 binding is strongly correlated with various epigenetic markers for open chromatin regions and associated with distinct gene pathways with neuronal subtype-specific functions. In inhibitory neurons, the majority of genomic regions hosting EGR1 binding sites become accessible at early embryonic stages. In contrast, the super enhancers in excitatory neurons hosting EGR1 binding sites gained their accessibility during postnatal stages. This study highlights the significance of transcription factor binding to enhancer regions, which may play a crucial role in establishing cell-type specific gene regulation in neurons.

Measuring flicker induced vasodilation at a high spatial and temporal resolution in the human retina.
Neurovascular coupling (NVC) is a crucial process in which blood flow is dynamically adjusted to meet the metabolic demands of active neurons. In this study, we introduce an innovative method for in-vivo imaging of retinal blood vessel dilation in response to visible light stimulation, offering insights into the functional regulation of retinal blood flow. Using high-resolution, high-speed phase contrast imaging, we continuously monitored retinal vessel dynamics in eight healthy subjects, capturing precise temporal and spatial changes in vessel size under both stimulated and baseline conditions. We have measured a significant vessel dilation of 5.2% +/- 1.6% (4.4 um +/- 1.3 um) during flicker-stimulation compared to a dilation of 2.5% +/- 1% (2.1 um +/- 0.9 um) without stimulation. The flexibility of our method also allowed for the exploration of various acquisition and stimulation settings, broadening possibilities for investigating neurovascular coupling in the retina. This work not only enhances our understanding of neurovascular coupling but also has the potential to identify new biomarkers for vision-impairing conditions and neurodegenerative diseases.

The human claustrum activates across multiple cognitive tasks
Cognitive control, the ability to manage information during purposeful actions, is crucial for everyday functioning and can become impaired in a variety of neuropsychiatric disorders. The claustrum, a subcortical brain structure, has recently been implicated in functional mechanisms underlying cognitive control. A current theory on the claustrum's function, the Network Instantiation in Cognitive Control (NICC) model, proposes that the claustrum acts as a cortical network hub synchronizing distant parts of the brain to optimize task performance across cognitive domains. Testing this in this study, we examined the claustrum signal within a dataset (n = 55) that includes functional MRI (fMRI) of healthy participants engaged in four well-established cognitive tasks: the Stroop task, AX-continuous performance task (AX-CPT), cued task-switching, and Sternberg working memory task. Bilateral claustrum activation was observed during certain conditions and trial phases of all four tasks, particularly during active use of cognitive control, and coinciding with task-positive cortical network activations. These findings provide further support for the NICC model of claustrum function, demonstrating claustrum activation across multiple cognitive tasks, and potentially paving the way for new insights into how cognitive processes can become compromised in neuropsychiatric disorders.

Semantic integration demands modulate large-scale network interactions in the brain
The ability to integrate semantic information into the context of a sentence is essential for human communication. Several studies have shown that the predictability of a final keyword based on the sentence context influences semantic integration on the behavioral, neurophysiological, and neural level. However, the architecture of the underlying network interactions for semantic integration across the lifespan remains unclear. In this study, 32 healthy participants (30-75 years) performed an auditory cloze probability task during functional magnetic resonance imaging (fMRI), requiring lexical decisions on the sentence's final words. Semantic integration demands were implicitly modulated by presenting sentences with expected, unexpected, anomalous, or pseudoword endings. To elucidate network interactions supporting semantic integration, we combined univariate task-based fMRI analyses with seed-based connectivity and between-network connectivity analyses. Behavioral data revealed typical semantic integration effects, with increased integration demands being associated with longer response latencies and reduced accuracy. Univariate results demonstrated increased left frontal and temporal brain activity for sentences with higher integration demands. Between-network interactions highlighted the role of task-positive and default mode networks for sentence processing with increased semantic integration demands. Furthermore, increasing integration demands led to a higher number of behaviorally relevant network interactions, suggesting that the increased between-network coupling becomes more relevant for successful task performance as integration demands increase. Our findings elucidate the complex network interactions underlying semantic integration across the aging continuum. Stronger interactions between various task-positive and default mode networks correlated with more efficient processing of sentences with increased semantic integration demands. These results may inform future studies with healthy old and clinical populations.

Nanoparticles loaded with a CSF1R antagonist selectively depletes microglial cells and modulates inflammation in spinal cord injury
Neuroinflammation is a principal event occurring after spinal cord injury (SCI). M1-like microglia are key players in the inflammatory response after injury. We hypothesize that the depletion of this microglia subtype would result in a more pro-resolutive environment, favorable to SCI repair. The colony-stimulating factor 1 receptor (CSF1R) antagonist PLX5622 has been used to deplete microglia in the central nervous system. Although PLX5622 can freely cross the blood-brain barrier after systemic administration, the low drug concentration within the SCI site hampers its effectiveness. Additionally, systemic administration of PLX5622 in the scope of SCI treatment can induce side effects due to off-target accumulation. In this study, we specifically depleted M1-like microglia by designing polymeric nanoparticles loaded with PLX5622 (PLX NPs) to locally treat spinal cord contusion. PLX NP was prepared using a microfluidic-assisted approach showing high encapsulation efficiency (approx. 84%), nanosized dimensions (100 nm), and batch-to-batch reproducibility. PLX NP displayed selective activity in depleting M1-like microglial cells in both resting and lipopolysaccharide (LPS)-activated mixed microglial cell models compared with the free drug counterparts while preserving non-targeted glial cells. Furthermore, locally administered PLX NP downregulated proinflammatory cytokines (e.g., TNF-, IL-6, and IL-1{beta}), increasing the M2/M1-like microglia ratio, thus reducing inflammation in a SCI contusion model. Our data support the hypothesis that local treatment with PLX NPs, a formulation with a high translational value, reduces neuroinflammation, with potential applications in SCI and central nervous system inflammatory diseases.

Beta burst characteristics and coupling within the sensorimotor cortical-subthalamic nucleus circuit in Parkinson's disease
Background: Bursts of exaggerated subthalamic nucleus (STN) beta activity contribute to clinical impairments in Parkinson's disease (PD). Few studies have explored the characteristics and coupling of bursts across the sensorimotor cortical-STN circuit. Objective: We sought to (1) establish the characteristics of sensorimotor cortical and STN bursts during naturalistic behaviours, and (2) determine the predictability of STN bursts from motor cortical recordings. Methods: We analysed 1,478 hours of wirelessly streamed bilateral sensorimotor cortical and STN recordings from 5 PD patients. Results: STN bursts were longer than cortical bursts and had shorter inter-burst intervals. Long bursts (>200ms) in both structures displayed temporal overlap (>30%), with an estimated cortico-STN conduction delay of 8ms. Furthermore, approximately 27% of all STN bursts were preceded by a cortical burst. Conclusion: Cortical beta bursts tend to precede STN beta bursts, with short delays. However, subcortical mechanisms are also likely to contribute to STN burst initiation and propagation.

Soma-centered control of synaptic autophagy by Rab39-regulated anterograde trafficking of Atg9
Presynaptic terminals can be located far from the neuronal cell body and are thought to independently regulate protein and organelle turnover. In this work, we report a soma-centered mechanism that regulates autophagy-driven protein turnover at distant presynaptic terminals in Drosophila. We show that this system is regulated by Rab39, whose human homolog is mutated in Parkinson's disease. Although Rab39 is localized in the soma, its loss of function causes increased autophagy at presynaptic terminals, resulting in faster synaptic protein turnover and neurodegeneration. Using a large-scale unbiased genetic modifier screen, we identified genes encoding cytoskeletal and axonal organizing proteins, including Shortstop (Shot), as suppressors of synaptic autophagy. We demonstrate that Rab39 controls Shot- and Unc104/KIF1a-mediated transport of autophagy-related Atg9 vesicles to synapses. Under starvation conditions, Rab39 in the soma shifts its localization from endosomes to lysosomes, thereby controlling the availability of Atg9 vesicles for trafficking to synapses. Our findings indicate that Rab39-mediated trafficking in the soma orchestrates a cross-compartmental mechanism that regulates the abundance of autophagy at synapses.

Global and local nature of cortical slow waves
Explaining the macroscopic activity of a recorded neuronal population from its known microscopic properties still poses a great challenge, not just because of the many local agents that shape the output of a circuit, but due to the impact of long-range connections from other brain regions. Here we use a computational model to explore how local and global components of a network shape the Slow Wave Activity (SWA). We performed a sensitivity analysis of multiple cellular and synaptic features in models of isolated and connected networks. This allowed us to explore how the interaction of local properties and long-range connections shape the SWA of a population and its neighbors, as well as how the sequential propagation of active Up states lead to the emergence of preferred modes of propagation. We described relevant features of cortical Up states that are modulated by stiff combinations of parameters of the local circuit as opposed to other that are sensitive to the level of excitability of the whole network and the input coming from neighbor populations. We found that while manipulations in the synaptic excitatory/inhibitory balance can create local changes, cellular components that modulate the excitability or adaptation of a population have a long-range effect that leads to changes in neighbor populations too. Additionally, our simulations guided in vivo experiments that showed how heterogeneities in excitability between cortical areas can determine the directionality of travelling waves during SWA. We expect these results to motivate future research exploring and comparing cortical circuits through the analysis of their Up states.

Oxytocin neurons in the paraventricular and supraoptic hypothalamic nuclei bidirectionally modulate food intake
Oxytocin (OT) is a neuropeptide produced in the paraventricular (PVH) and supraoptic (SON) nuclei of the hypothalamus. Either peripheral or central administration of OT suppresses food intake through reductions in meal size. However, pharmacological approaches do not differentiate whether observed effects are mediated by OT neurons located in the PVH or in the SON. To address this, we targeted OT neuron-specific designer receptors exclusively activated by designer drugs (DREADDs) in either the PVH or SON in rats, thus allowing for evaluation of food intake following selective activation of OT neurons separately in each nucleus. Results revealed that DREADDs-mediated excitation of PVH OT neurons reduced consumption of both standard chow and a high fat high sugar diet (HFHS) via reductions in meal size. On the contrary, SON OT neuron activation had the opposite effect by increasing both standard chow and liquid sucrose consumption, with the former effect mediated by an increase in meal size. To further examine the physiological role of OT neurons in eating behavior, a viral-mediated approach was used to silence synaptic transmission of OT neurons separately in either the PVH or SON. Results from these studies revealed that PVH OT neuron silencing significantly increased consumption of HFHS by increasing meal size whereas SON OT neuron silencing reduced chow consumption by decreasing meal size. Collectively these data reveal that PVH and SON OT neurons differentially modulate food intake by either increasing or decreasing satiation signaling, respectively.

Regional heterogeneities of oligodendrocytes determine biased distribution pattern of Ranvier nodes along single axons in sound localization circuit
Distribution of Ranvier nodes along myelinated axons is a critical determinant of conduction velocity, significantly influencing spike arrival timing and hence neural circuit function. The patterns of nodal distribution are not necessarily uniform but vary across brain regions and even along individual axons. Although various factors could contribute to these patterns, the complexity arising from multicellular interactions between oligodendrocytes and axons has left the underlying regulatory mechanisms unclear. In this study, we identified the factors contributing to the emergence of a biased nodal distribution pattern along single axons using the chick brainstem auditory circuit as a model, in which the distance between adjacent nodes (internodal length) varies along the axons of avian cochlear nucleus neurons in a region-dependent manner, thereby enabling precise binaural integration for sound localization. 3D morphometry revealed that these axons were almost fully myelinated by oligodendrocytes exhibiting distinct morphologies and cell densities across regions after hearing onset. The structure of axons did not affect internodal length. Inhibiting vesicular release from the axons did not affect internodal length and oligodendrocyte morphology, either, but caused unmyelinated segments on the axons by suppressing oligodendrogenesis near the presynaptic terminals. These results suggest that the regional heterogeneity in the intrinsic properties of oligodendrocytes determines the biased nodal distribution pattern in the sound localization circuit, while activity-dependent signaling supports the pattern by ensuring adequate oligodendrocyte density. Our findings highlight the importance of oligodendrocyte heterogeneity in fine-tuning neural circuit function.

Machine Learning Identifies Genes Linked to Neurological Disorders Induced by Equine Encephalitis viruses (EEV), Traumatic Brain Injuries (TBI), and Organophosphorus nerve agents (OPNA)
Venezuelan, eastern, and western equine encephalitis viruses (collectively referred to as equine encephalitis viruses---EEV) cause serious neurological diseases and are a significant threat to the civilian population and the warfighter. Likewise, organophosphorus nerve agents (OPNA) are highly toxic chemicals that pose serious health threats of neurological deficits to both military and civilian personnel around the world. Consequently, only a select few approved research groups are permitted to study these dangerous chemical and biological warfare agents. This has created a significant gap in our scientific understanding of the mechanisms underlying neurological diseases. Valuable insights may be gleaned by drawing parallels to other extensively researched neuropathologies, such as traumatic brain injuries (TBI). By examining combined gene expression profiles, common and unique molecular characteristics may be discovered, providing new insights into medical countermeasures (MCMs) for TBI, EEV infection and OPNA neuropathologies and sequelae. In this study, we collected transcriptomic datasets for neurological disorders caused by TBI, EEV, and OPNA injury, and implemented a framework to normalize and integrate gene expression datasets derived from various platforms. Effective machine learning approaches were developed to identify critical genes that are associated, either shared among the three neuropathologies or to either TBI, EEV, and OPNA. With the aid of deep neural networks, we were able to extract important association signals for accurate prediction of different neurological disorders by using integrated gene expression datasets of VEEV, OPNA, and TBI samples. Gene ontology and pathway analyses further identified neuropathologic features with specific gene product attributes and functions, shedding light on the fundamental biology of these neurological disorders. Collectively, we highlight a workflow to analyze published transcriptomic data using machine learning, which can be used for both identification of gene biomarkers that are unique to specific neurological conditions, as well as genes shared across multiple neuropathologies. These shared genes could serve as potential neuroprotective drug targets for conditions like EEV, TBI, and OPNA.

Speech motor cortex enables BCI cursor control and click
Decoding neural activity from ventral (speech) motor cortex is known to enable high-performance speech brain-computer interface (BCI) control. It was previously unknown whether this brain area could also enable computer control via neural cursor and click, as is typically associated with dorsal (arm and hand) motor cortex. We recruited a clinical trial participant with ALS and implanted intracortical microelectrode arrays in ventral precentral gyrus (vPCG), which the participant used to operate a speech BCI in a prior study. We developed a cursor BCI driven by the participant's vPCG neural activity, and evaluated performance on a series of target selection tasks. The reported vPCG cursor BCI enabled rapidly-calibrating (40 seconds), accurate (2.90 bits per second) cursor control and click. The participant also used the BCI to control his own personal computer independently. These results suggest that placing electrodes in vPCG to optimize for speech decoding may also be a viable strategy for building a multi-modal BCI which enables both speech-based communication and computer control via cursor and click.

Stimulation of the Frontal Aslant Tract's origin in the caudal superior frontal gyrus alters ongoing spontaneous rhythmic activity independently from the effector. Evidence from tractography-guided Transcranial Magnetic Stimulation.
The crown of the human Superior Frontal Gyrus (SFG-crown) is a functionally independent region, nestled between the dorsal premotor and supplementary motor cortices, that supports internally-timed action control. The unique SFG-crown's connectivity fingerprint by the Frontal Aslant Tract (FAT), suggests a caudal-rostral pattern of increasing abstractness of action representations. Coherently, since the mid-portion of the caudal SFG contains a representation of action strategies that involve internal timing, we hypothesized that the caudal portion of the SFG may be involved in action execution of internally-timed actions. To test this, we asked 21 healthy participants to perform a self-paced tapping movement with the right index finger or a self-paced articulation of the syllable /da/ while applying online single-pulse TMS to the posterior, middle and anterior origins of the FAT in the left SFG-crown. Results showed that effective TMS (compared to sham) impacted rhythm production in both tasks, only when applied to the posterior SFG region, by reducing the probability of motor events in the 200 ms following TMS. The present data support the hypothesis, that the posterior SFG-crown, associated with the most posterior origin of the FAT fibers, is involved in the production of internally-timed actions, in an effector-independent modality, suggesting a domain-general role in the execution of internally-timed movements.

Brain-Cognitive Gaps in relation to Dopamine and Health-related Factors: Insights from AI-Driven Functional Connectome Predictions
A key question in human neuroscience is to understand how individual differences in brain function are related to cognitive differences. However, the optimal condition of brain function to study between-person differences in cognition remains unclear. Additionally, there is a lack of objective biomarkers to accurately predict cognitive function, with brain age emerging as a potential candidate. Recent research suggests that brain age offers minimal additional information on cognitive decline beyond what chronological age provides, prompting a shift toward approaches focused directly on cognitive prediction. Using a novel deep learning approach, we evaluated the predictive power of the functional connectome during various states (resting state, movie-watching, and n-back) on episodic memory and working memory performance. Our findings show that while task-based connectomes, especially during movie watching, better predict working memory, resting state connectomes are equally effective in predicting episodic memory. Furthermore, individuals with a negative brain-cognition gap (where brain predictions underestimate actual performance) exhibited lower physical activity, lower education, and higher cardiovascular risk compared to those with a positive gap. This shows that knowledge of the brain-cognition gap provides insights into factors contributing to cognitive resilience. Further lower PET-derived measures of dopamine binding were linked to a greater brain-cognition gap, mediated by regional functional variability. Together, our study introduces the brain-cognitive gap, as a new marker, modulated by the dopamine system, to identify individuals at risk of compromised brain function.