bioRxiv Subject Collection: Neuroscience's Journal

Non-neuronal signal fluctuations in Alzheimer's disease and in mild cognitive impairment
Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) permits the investigation neural activity thanks to the neurovascular coupling mechanism. However, neural activity accounts for only a portion of the observed BOLD signal fluctuations, as the vasculature integrates multiple physiological inputs that contribute to the response. Research focusing on isolating the vascular components of the BOLD signal revealed that markers of cerebrovascular health, such as cerebrovascular reactivity (CVR), serve as valuable biomarkers for neurodegenerative diseases. This study examines the relationship between vascular metrics and noise in a cohort comprising individuals with Alzheimer's disease (AD), mild cognitive impairment (MCI), and healthy controls (HC). Vascular responses were assessed using three functional contrasts during a hypercapnic challenge: arterial spin labeling (ASL) to measure cerebral blood flow (CBF) reactivity, vascular space occupancy (VASO) to quantify cerebral blood volume (CBV) reactivity, and BOLD imaging. Noise metrics were derived from multi-echo BOLD resting-state data by isolating the TE-independent components of the signal. Mean correlation coefficients for noise vs ASL-CVR are: (-0.12 {+/-} 0.06) for HC, (-0.14 {+/-} 0.08) for MCI, (-0.11 {+/-} 0.05) for AD. Mean correlation coefficients for noise vs BOLD-CVR are: (0.25 {+/-} 0.11) for HC, (0.24 {+/-} 0.07) for MCI, (0.23 {+/-} 0.11) for AD. Mean correlation coefficients for noise vs VASO-CVR are: (0.13 {+/-} 0.10) for HC, (0.13 {+/-} 0.07) for MCI, (0.12 {+/-} 0.12) for AD. These results suggest that TE-independent noise relates to the three vascular contrasts to varying extents and directions, with no significant differences across groups. Further analysis within specific functional networks revealed group differences in certain networks. The observed cortical correlations between noise and vascular features provide important insights into brain function and the progression of neurodegenerative diseases, offering a potential avenue to disentangle vascular and neural contributions in brain network and connectivity studies.

Oxytocin increases trust in humans with a low disposition to trust
In recent years, increasing skepticism regarding oxytocins (OTs) influence on social behavior arose. Low power, HARKing (hypothesizing after the results are known), and replication failures have clouded the field. Here, we directly address these concerns with a high-powered, preregistered study that offers robust evidence for a causal effect of OT on trust among individuals with a low disposition to trust. We recruited 359 low-trusting individuals who participated in a trust game under strict anonymity conditions. Results show that OT administration significantly increased trusting behavior by roughly 15%, with consistent effects across regression models with and without controls for personality traits. A pooled data analysis incorporating a previous sample (n=219) of low-trusting individuals further strengthens this conclusion, yielding a statistically significant 16.9% increase in trust. Crucially, no interaction effect was found between OT and the degree of dispositional trust, suggesting OTs effect is uniform across the low-trusting spectrum. These findings present a strong case for OTs selective trust-enhancing role. By isolating OTs impact within a well-defined subpopulation and experimental context, this study provides a critical pivot in the debate over neurobiological mechanisms of trust.

MECP2 Mutations Rewire Human ESC Fate and Bias Cortical Lineage Commitment
Rett syndrome arises from loss-of-function mutations in the X-linked chromatin regulator MECP2, yet the earliest molecular derailments in human development remain poorly defined. Using isogenic hESC models carrying three patient-derived MECP2 mutations, we followed the transcriptome from pluripotency through neuro-ectoderm, neural stem, and neural progenitor stages and into three-month cerebral organoids. Stage dominated transcriptional variance, but mutants shared a secondary program enriched for synaptic-membrane and extracellular-matrix genes. Single-cell profiling revealed a naive-like, hyper-proliferative state marked by up-regulation of ZFP42 at ESC stage. Strikingly, EMX1, a cortical radial-glia determinant, was consistently suppressed from the earliest stage onward, and cerebral organoids subsequently generated fewer excitatory neurons in favour of inhibitory and glial lineages. These data chart a continuous developmental trajectory for MECP2-mutant human cells and nominate ZFP42 and EMX1 dysregulation as tractable entry points for dissecting Rett pathogenesis.

Age-related degradation of behavioral and network features of Aplysia escape locomotion
Aplysia californica has been a useful model system for studies of the neural basis of behavior, learning, and aging. While the latter topic has been explored with respect to several of its simple reflex behaviors, this study represents the first examination of how one of Aplysia's more complex behaviors, escape locomotion, is affected in animals nearing the end of their natural lifespan. Old animals (12-13mo) showed a greatly reduced gallop response compared with middle-aged adults (5-7mo), together with a loss of locomotion onset latency sensitization. Large-scale VSD imaging was used to record motor programs in isolated brain preparations from middle-aged vs. elderly animals. Old brains displayed the same loss of onset latency sensitization seen in the intact old animal behavior, and also a reduced number of cycles per locomotion episode. Brains from middle-aged animals showed an unchanged number of motor program cycles from that observed in intact animals, but a much more transient motor program onset latency sensitization. A further age-related finding was that while in middle-aged brains repeatedly eliciting the motor program led to progressively increasing cumulative activity across trials, in old brains this same procedure led to progressively decreasing activity. Some of our results are consistent with peripheral processes working in concert with the CNS as animals age to support healthy locomotion behavior and its modification by learning, or with early changes in the brain that are not yet expressed in behavior.

Transfer of graded information through gated receptivity to widely broadcast signals
Making accurate decisions requires the brain to maintain evolving representations of accumulated evidence. The population that maintains this evolving representation may change over the course of evidence accumulation. For example, intervening actions like eye movements and navigation can shift the set of neurons that encode subsequent inputs and outputs. A recent study showed that signals representing accumulated evidence are transferred between parietal neurons with different response fields, enabling continuous evidence integration across both smooth pursuit and saccadic eye movements. More generally, changes in the neural population representing accumulated evidence may result from a switch in the set of neurons representing the relevant behavioral output or a switch in the set of neurons receiving task-relevant information. Here, we present a model that achieves this flexible transfer of graded information without changing synaptic connectivity. Graded signals are widely broadcast throughout the population, with a dynamic gating mechanism controlling which neurons are receptive to this information. This mechanism supports a continuous decision process across changing frames of reference, offering a potentially general framework for cognitive continuity in dynamic environments.

The relationship between sleep, mental health, and performance on tests of pattern separation in young adults
Study objectives: Young adults experience the highest rates of mental health disorders of any age group. Depression and anxiety symptoms are often associated with both sleep disturbances and cognitive impairments. Here, we investigated whether the effects of sleep moderate the effects of depression and anxiety on cognitive performance. We were particularly interested in cognitive tasks designed to tax pattern separation, which we hypothesize are most sensitive to the cognitive impairments caused by mental health symptoms and sleep disturbances. Methods: We recruited young adults (N=89; aged 18-30 years) and remotely monitored their sleep for 7 consecutive days using wrist actigraphy and daily sleep diaries. On day 7, participants completed in-person cognitive testing and mental health questionnaires. Cognitive tests included the Psychomotor Vigilance Task (PVT), Cambridge Neuropsychological Test Automated Battery (CANTAB), and the Mnemonic Similarity Task (MST). The CANTAB Delayed Matching to Sample (DMS) and the MST, are designed to tax pattern separation. Mental health questionnaires included Becks Depression Inventory (BDI) and Becks Anxiety Inventory (BAI). Results: Eighty participants (mean age: 20.13, SD: 2.00) were included in the final analyses. Depressive symptoms were significantly correlated with performance on the PVT and CANTAB DMS. Bedtime and wake-up times were significantly correlated with performance on DMS and MST. Conclusion: Young adults experiencing depressive symptoms tend to have later wake-up times. Sleep timing and mental health independently affect performance on tests of pattern separation. Understanding the relationship between mental health, sleep, and cognitive performance is important for designing interventions to promote well-being in young adults.

Exploring the correspondence between gene expressionand thalamic nuclei using the THALMANAC resource
The thalamus connects the sensory organs and major subcortical brain regions with the neocortex. The thalamus has long been divided into multiple discrete nuclei, based on cytoarchitecture, histochemical stains, and mesoscale connectivity. However, thalamic nuclei do not completely describe thalamic organization. For example, some boundaries between thalamic nuclei are disputed, whereas other nuclei are known to contain subdomains with distinct connectivity and function. Moreover, the correspondence between cellular gene expression and other properties of thalamic projection neurons remains to be established. Spatial analysis of single cell gene expression provides a basis for reevaluating thalamic organization. We present the THALMANAC, (THALamus MERFISH ANalysis and ACcess) a Findable, Accessible, Interoperable, Reusable and Reproducible (FAIRR) resource for exploring and analyzing single-cell transcriptomic variation in the thalamus. The THALMANAC provides streamlined access to thalamic gene expression data registered to the common coordinate framework and tools for quantitative analysis and visualization of these data, all encapsulated in a reproducible, cloud computing platform. Using this resource, we find that gene expression generally supports the parcellation of thalamus into distinct nuclei. Some nuclei, such as the anteromedial nucleus, are additionally composed of discrete subdomains, while other nuclei share patterns of gene expression or are arrayed on a spatial gradient of gene expression. The THALMANAC establishes spatial transcriptomic data as a foundation for delineating thalamic organization.

Neuroanatomical features reveal accelerated brain age in alcohol use disorder
Background: Brain age is a novel measure to characterize the integrity of neurocognitive functioning and brain health in various psychiatric and neurological disorders. Although there is a literature suggesting premature aging of the brain in individuals with alcohol use disorder (AUD), studies directly examining brain age are rare. Therefore, the current study was designed to estimate brain age in AUD individuals using brain morphological features, such as cortical thickness and brain volume. Methods: The sample included a group of 30 adult males with a history of AUD but maintaining abstinence and a group of 30 male controls without any history of AUD. Brain age was computed using an XGBoost regression model with 187 brain morphological features of cortical thickness and brain volume as predictors. An exploratory correlational analysis between brain age measures and features of neuropsychological performance, impulsivity, and alcohol consumption was also performed. Results: Findings revealed that AUD individuals showed an increase of 1.70 years in their brain age relative to their chronological age. Further, in the AUD group, higher brain age was significantly associated with poor executive functioning, while a larger gap between brain age and actual age was associated with lower non-planning impulsivity and later age of onset for regular drinking in those with AUD. Conclusions: AUD individuals manifested accelerated brain aging, possibly representing compromised brain health. Brain age measures were found to be associated with some of the measures of neurocognition, impulsivity, and alcohol consumption. These findings may have important implications for the early identification, prevention, and treatment of AUD. However, future studies with larger sample sizes are needed to confirm these preliminary findings.

Polar angle asymmetries persist despite covert spatial attention and differential adaptation
Visual adaptation and attention are two processes that help manage brain limited bioenergetic resources for perception. Visual perception is heterogeneous around the visual field, it is better along the horizontal than the vertical meridian (horizontal-vertical anisotropy, HVA), and better along the lower than the upper vertical meridian (vertical meridian asymmetry, VMA). A recent study showed that visual adaptation is more pronounced at the horizontal than the vertical meridian, but whether and how the differential adaptation modulates the effects of covert spatial attention remains unknown. In this study, we examined how the effects of endogenous (voluntary) and exogenous (involuntary) covert attention on an orientation discrimination task vary at the cardinal meridians, with and without adaptation. We manipulated endogenous (Experiment 1) or exogenous (Experiment 2) attention via a central or peripheral cue, respectively. Results showed that (1) in the non-adapted condition, the typical HVA and VMA emerged in contrast threshold; (2) the adaptation effect was stronger at the horizontal than the vertical meridian; and (3) regardless of adaptation, both endogenous and exogenous attention enhanced and impaired performance at the attended and unattended locations, respectively, to a similar degree at both cardinal meridians. These findings reveal that, despite a differential adaptation effect, performance asymmetries are resistant to both endogenous and exogenous attention around polar angle.

Neural basis of social-categorization function of language
Languages provide social-category markers that tag people as one or another social group. We investigate how the brain sorts words into one or another language category as a neural basis of this social-categorization function of language. We show that a neural network, including the anterior temporal, insular, orbital frontal, and ventral occipito-temporal cortices in both hemispheres, computes correlation distances between two words to represent intra-language similarity and inter-language difference during categorization of visual words of alphabetic and non-alphabetic languages. These processes occur as early as 150 ms post-stimulus, recruit within-hemisphere functional connections, operate independently of words' semantic meanings and pronunciations, and exhibit consistently across individuals with diverse language backgrounds. These findings advance our understanding of the neural mechanisms of the social-categorization function of language.

The Ingestive Response Reflects Neural Dynamics in Gustatory Cortex
Upon delivery of a taste onto the tongue, the neural gustatory circuit must decide whether to ingest or reject the stimulus. While there has been much work in rodents investigating the neural activity leading to the rejection decision and its associated orofacial movements, characterization of behaviors related to ingestion have received much sparser attention. To address this, here we simultaneously measured electromyographic (EMG) activity of the jaw opener muscle and single-neuron activity from gustatory cortex (GC) so that we could characterize ingestion-related behaviors and their association with neural dynamics. We developed a machine-learning classifier to accurately identify distinct orofacial movements from EMG signals, thereby revealing multiple novel subtypes of ingestion-related behaviors. The frequency of occurrence of each shifts significantly around the time of the consumption decision, a change in behavior that is tightly coupled with the transition in GC's neural firing patterns into the state reflecting the tastant's palatability. These findings demonstrate a direct link between neural dynamics in GC and the orchestration of the physical movements that define ingestive behavior, highlighting GC's general role not just in taste perception and decision making, but also in the control of motor actions.

Traumatic brain injury exacerbates mitochondrial dysfunction in APP/PS1 knock-in mice through time-dependent pathways
Cerebral hypometabolism occurs in both traumatic brain injury (TBI) and Alzheimer's disease (AD), but whether these conditions act through distinct or overlapping mechanisms is unclear. TBI disrupts cerebral metabolism via blood-brain barrier damage, altered glucose transporter expression, calcium buffering abnormalities, and oxidative damage to metabolic enzymes. AD-related hypometabolism is linked to amyloid-beta effects on mitochondria, including impaired respiration, oxidative stress, and altered mitophagy, fusion, and fission. We tested whether TBI-induced mitochondrial dysfunction exacerbates abeta-mediated impairment using a closed-head injury (CHI) model in APP/PS1 knock-in (KI) mice. Injuries were delivered at 4-5 months of age, before plaque formation and mitochondrial deficits in KI mice. Bioenergetics were measured at 1, 4, and 8 months post-injury in hippocampus and cortex using Seahorse assays on isolated mitochondria. At 1 month, genotype-by-injury interactions revealed greater dysfunction in KI mice than either condition alone, with males more vulnerable than females. At 4-8 months, amyloid-mediated effects predominated, while TBI-specific changes were no longer apparent, suggesting recovery or convergence onto shared mechanisms. These results indicate that TBI can temporarily worsen mitochondrial dysfunction in the context of early amyloidosis, with sex influencing vulnerability. Findings provide insight into the temporal relationship between TBI and amyloid-induced mitochondrial deficits and support the importance of sex as a biological variable in neurodegenerative disease progression.

Electrospectrometry of the Mouse Brain
To understand how electric field fluctuations organize within the brain, we developed deep electrospectroscopy, a method to assess possibly nonlinear spectral similarity between the local field potential of different areas. Applying this technique on recordings from nearly 500 areas of the mouse brain, we reveal an organization made of isolated landmarks and groups of spectrally similar areas. Such communities were mostly found in the forebrain and showed an organization that did not strictly follow the cytoarchitecture. For instance, visual parts of the cortex, colliculus and hippocampal regions were found in the same community. Electrospectral communities were also found to reshape with context, growing in size around brain areas required for a task. These analyses paint a detailed picture of the modularity underlying the structure and dynamics of electroencephalograms.

Changes in cerebral glucose metabolism at rest following hemicontusive spinal cord injury in mice: A whole-brain autoradiographic study
Spinal cord injury (SCI) disrupts brain-spinal cord communications and results in profound brain reorganization. Here, we apply high-resolution, voxel-based, whole-brain metabolic mapping using the [14C]-2-deoxyglucose autoradiographic method in mice to assess functional brain reorganization in a subacute stage (1 week after SCI). Right moderate contusive injury at the cervical 5 level (C5) was confirmed by glial fibrillary acidic protein (GFAP) immunohistochemical staining. SCI compared to sham-lesioned animals showed significant motor deficits (grip strength, rotarod) alongside decreases in glucose uptake in sensorimotor regions of the cortex, basal ganglia, and thalamus, which receive monosynaptic afferents (the ventral posterolateral thalamic nucleus, VPL) or multi-synaptic afferents from the spinal cord (the primary somatosensory and motor cortices, caudate putamen). In contrast, regions in the limbic system (the amygdala, accumbens nucleus, lateral septum, and hippocampus) and in the cerebellum demonstrated increases in glucose uptake in SCI animals. Most of these effects were noted bilaterally, suggesting functional reorganization involving higher order neural circuits bilaterally. The current findings underscore the broadness of brain reorganization in the subacute stage following incomplete SCI. Functional whole-brain metabolic mapping provides a roadmap for future targeted studies examining neuroplastic mechanisms in search of new therapeutic strategies.

Ca2+ Plateau Potentials Reflect Cross-Theta Cortico-Hippocampal Input Dynamics and Acetylcholine for Rapid Formation of Efficient Place-Cell Code
A central tenet of Systems Neuroscience lies in an understanding of memory and behavior through learning rules, but synaptic plasticity has rarely been shown to create functional single-neuron code in a causal and biophysically rooted manner. Behavioral Time-Scale Synaptic Plasticity (BTSP), identified in vivo, holds a great potential for explaining instantaneous hippocampal selectivity emergence by long-term potentiation (LTP), yet the cellular and endogenous mechanisms are unknown, impeding broader conceptualization of this novel rule for its algorithmic, systems-level and theoretical implications. Here, we addressed this gap by in-vivo, ex-vivo, in-silico and computational approaches to seek neurophysiologically inspired protocols for synaptically evoking Ca2+ plateau potentials and inducing potentiation in the CA1. We found induction of BTSP-LTP is best explained by a theta-oscillation-paced, gradually developed cellular state being supported with precisely timed weak ramping inputs. Remarkably, the previously presumed one-shot LTP for in-vivo place-field formation is possible under the influence of muscarinic activation. Through modeling, the notion of acetylcholine-gated BTSP gave rise to a computational advantage for low-interference continual learning. We further demonstrated that biophysics of Transient Receptor Potential (TRPM) and NMDA receptor (NMDAR) channels powerfully shapes the cross-theta dynamics underlying BTSP. These results which cover pre-, post-synaptic and neuromodulatory factors and their timing suggest fundamental principles for graded plateau potentials and hippocampal LTP induction. Overall, our work dissects cellular mechanisms potentially important for a prominent in-vivo hippocampal plasticity phenomenon, and offers a biological basis for framing BTSP as an input-dynamics-aware, neuromodulation-tuned synaptic algorithm.

TDP-43 expression in the cytoplasm leads to early synaptic and mitochondrial abnormalities in an inducible mouse model of ALS/FTD
TDP-43 proteinopathy is the primary pathology associated with amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), indicating that these neurodegenerative diseases have common underlying mechanisms. We have previously shown that transgenic (Tg) mice conditionally overexpressing a cytoplasmic form of human TDP-43 protein (TDP-43-{Delta}NLS) in forebrain neurons replicate key features of FTD/ALS, including altered cognitive, motor and social behaviors. These behavioral phenotypes and changes in plasticity-related gene expression can be detected as early as 1 month after Tg induction, before overt neurodegeneration occurs. To assess early ultrastructural features in this model, we performed Transmission Electron Microscopy (TEM) analysis in the cortex (Ctx) and hippocampus (Hp) of Tg animals and their non-Tg controls. TEM evaluation of Ctx and Hp revealed that synaptic density was significantly decreased and synapse length was increased in both regions of Tg animals. Synaptic cleft thickness was increased and post-synaptic density thickness was decreased only in the Ctx of Tg mice, revealing differential regional effects in synaptic morphology. We analysed mitochondrial density and we found an increase in the Ctx and a decrease in the Hp of Tg animals, with preserved individual mitochondrial area. Lastly, transcriptomic and proteomic analysis from both transgenic TDP-43-{Delta}NLS mice and human proteinopathy showed widespread decreased expression of synaptic structure and function genes. The alterations in synaptic density and architecture reported here, combined with the mRNA/protein expression data, suggest that TDP-43-{Delta}NLS mice may exhibit abnormal synaptic transmission and that ultrastructural changes play a role in the early behavioral deficits observed in this model.

Meningeal macrophages exhibit diverse calcium signaling at steady-state and in response to aberrant cortical hyperexcitability in awake mice
The meninges, which envelop and protect the brain, host a large number of resident macrophages that play a crucial role in regulating homeostasis and neuroinflammation. Intracellular Ca2+ signaling mediates a variety of macrophage functions. While diverse, ontogeny, transcriptional profiles, and phenotypes of meningeal macrophages have been described, little is known about their spatiotemporal Ca2+ signal dynamics in healthy and diseased states. Using two-photon functional Ca2+ imaging in a novel transgenic reporter mouse line, combined with an event-based Ca2+ signaling analysis pipeline, we comprehensively characterized the Ca2+ activity of meningeal macrophages both at steady-state and in response to cortical spreading depolarization (CSD), a pathophysiological brain hyperexcitability event, implicated in migraine, traumatic brain injury, and stroke. In homeostatic meninges of behaving mice, perivascular macrophages exhibit several Ca2+ activity features, including event duration and signal frequency spectrum, distinct from those of interstitial non-perivascular macrophages. The Ca2+ activity of dural perivascular macrophages is uniquely coupled to behaviorally driven diameter fluctuation of their associated vessels. Most perivascular and non-perivascular meningeal macrophages displayed propagating intracellular Ca2+ activity. Both macrophage subtypes also exhibit synchronized intercellular Ca2+ elevations, likely driven by an external factor. In response to CSD, the majority of perivascular and non-perivascular meningeal macrophages show a persistent decrease in their Ca2+ activity. Smaller subsets of both macrophage subtypes display either acute or persistent increases in Ca2+ activity, with the latter response mediated by CGRP/RAMP1 signaling. Collectively, our results highlight a previously unknown diversity of meningeal macrophage Ca2+ signaling at steady-state and in response to an aberrant brain hyperexcitability event.

Molecular Logic of Cell Diversity and Circuit Connectivity in the REM Sleep Hub
The complexity of the brain arises from the diversity of its circuits and the molecular heterogeneity of the cells that compose them. A mechanistic understanding therefore requires mapping cellular identity and connectivity at single-cell resolution. Here we define the cellular taxonomy of the murine sublaterodorsal tegmental nucleus (SLD), a critical hub for REM sleep, using single-nucleus RNA sequencing. We identified all major brain cell classes, with oligodendrocytes as the most abundant, and resolved seventeen transcriptionally distinct neuronal groups defined by neurotransmitters, neuromodulators, and neuropeptides, each with unique molecular signatures. Projection-specific analysis further revealed that glutamatergic subpopulations targeting the ventrolateral periaqueductal gray (vlPAG) and ventral medulla are molecularly distinct, marked by characteristic receptor motifs. Strikingly, we provide the first direct evidence that SLDGLUT neurons innervate the vlPAG. This newly uncovered SLDGLUT-vlPAG pathway represents a previously unrecognized circuit node for REM sleep regulation, with the potential to act as a REM-OFF population suppressing it. Together, these findings establish a transcriptionally resolved atlas of the SLD, reveal the molecular logic of its circuit connectivity, and nominate candidate molecular actuators of REM sleep control, opening new avenues for dissecting how brainstem circuits orchestrate REM state and its transitions.

Circadian phosphotimer generates time cues through PER dimerization-mediated trans-phosphorylation
The circadian clock generates autonomous molecular rhythms that regulate sleep cycles, chronotypes, daily physiology, and expression patterns of almost the entire genome. Temporal phosphorylation of PERIOD (PER) proteins creates a phosphotimer that is critical for clock function. Although previous studies show that PER stably binds the casein kinase CK1, cis-acting phosphorylation of PER by CK1 is not compatible with slow PER phosphorylation extended over 24 hrs. So how can PER phosphorylation be programmed in a slow and controlled manner? Here, we show that the timing cues are encoded by PER-PER dimerization-mediated trans-phosphorylation, which enables the necessary time delay in phosphorylation and slow phosphorylation. When PER dimerization is disrupted, PER phosphorylation and circadian rhythms are severely compromised. In mouse models with point mutations in the PER dimerization domain, circadian period is shortened to ~20 hrs, and the phase of wake/sleep cycles is dramatically advanced, switching a nocturnal animal to a half diurnal animal.

Spared nerve injury induces long-term and brain region-specific changes in oligodendrocyte density in mice
Background: Emerging evidence suggests a role for non-neuronal cells in the pathophysiology of chronic pain. Chronic pain causes profound alterations of the transcriptomic program of oligodendroglia, but the effect of pain on the oligodendroglial cells themselves remains unknown. Methods: Male and female C57BL6/J mice underwent spared nerve injury (SNI). Mechanical hypersensitivity was assessed five weeks later using the von Frey test. Six weeks post-surgery, mice were perfused, brains dissected, and immunostained for oligodendrocyte precursors cells (OPC) and mature oligodendrocytes (OL) in four brain regions involved in pain chronification: anterior cingulate cortex (ACC), central amygdala (CeA), basolateral amygdala (BLA), and periaqueductal gray (PAG). Results: We found OL were reduced in the ACC and CeA of both sexes six weeks after SNI. Conversely, BLA OL were increased in both sexes following SNI. There was a sex-dependent effect of SNI on PAG-OL, where OL were only reduced in females. SNI did not affect OPC in any of the studied brain regions, but female PAG and BLA appeared to have fewer OPC than males independent of SNI. Conclusion: Long-term nerve injury differentially affects OL in a brain region- and sex-dependent manner. This effect is observable six weeks after injury, suggesting a long-lasting impact of chronic pain on oligodendroglial cells. OPC, on the other hand, are remarkably stable. This finding aligns with previous literature showing OPC maintain homeostasis, even in pathological conditions.

Common Phenomenal and Neural Substrate Geometry in Visual Motion Perception.
What is a possible physical substrate of the qualitative aspects of consciousness (qualia)? Answering this question is a central goal of consciousness research. Due to their subjective and ineffable nature, finding a quantitative way to characterise qualia from verbal description has thus far proven elusive. To overcome the challenge of expressing subjective experience, recent structural and relational approaches have been proposed from mathematics. Yet, as far as we know, no attempts have been made to evaluate the relationship between a certain structure of qualia and a structure of its possible underlying physical substrate. Towards this ambitious goal of linking qualia and the physical, we set out to make an empirical first step by focusing on qualia of visual motion in human participants and their possible neural substrate recorded in mouse primary visual cortex. From human participants (N=171), we obtained dissimilarity ratings of visual motion experiences induced by 48 stimuli, spanning across 8 directions and 6 spatial frequencies. Analysis revealed similarity structures of visual motion qualia that were disassociated from similarity structures purely expected from physical parameters or their combinations. From nine individual mice, we recorded single-neuron activity (n=751) with optical imaging in both awake and lightly anaesthetised conditions (isoflurane 0.6-0.8%, which retains neural responses and renders mice unresponsive to sensory stimulation). From neuron population responses to a similar set of motion stimuli, we computed a distance matrix that is comparable to our human dissimilarity matrix. Quantitative analyses show structural commonalities between human qualia structure and mouse neural structure, where a categorical organisation of stimulus direction best explains human qualia structure and mice neural activity. Interestingly, these commonalities held true for both awake and lightly anaesthetised conditions, leaving a possibility that mice may have been unresponsive but conscious of visual motion under light anaesthesia. Finally, we list several empirical factors that can be improved to promote our qualia structure approach in the future.

Parameter scalability of multivariate Granger causality
Estimating causal interactions between signals provides unique insights into their dynamics. In neuroscience, causal inference has been widely used in electrophysiological data to shed light on brain communication. Multivariate autoregressive models (MVAR) often form the basis of causal estimation methods. However, given the high-dimensionality of whole-brain data, MVARs can become too large for proper estimation, and reducing the dimensions to a reasonable range affects causal inference. In this study, we provide a clear, practical range for each parameter, motivate the choice of the causal estimation algorithm, and guide the optimization of model parameters for practical analyses. To that end, we simulate electrophysiological data with underlying causalities and estimate the causality with current algorithms based on MVAR models. We then model how the samples, signals, and MVAR order affect the performance and computation time of each algorithm. Our results indicate that, although all algorithms scale at least quadratically with the three parameters together, some are more sensitive to the number of signals and others to the number of samples. We further reveal that the number of samples required for accurate causal inference depends on the number of signals involved. Generally, more recent algorithms designed for robustness scale worse in computation time than older, simpler algorithms. Overall, this work highlights the need to consider scalability in Granger causality inference.

Association of cytochrome c oxidase dysfunction with amyloidosis in Alzheimer's disease and patient-derived cerebral organoids
Patients with Alzheimer's disease (AD) demonstrate brain mitochondrial dysfunction and energy deficiency that are closely associated with cognitive impairment. Cytochrome c oxidase (CCO), also known as mitochondrial complex IV, is the terminal enzyme in mitochondrial electron transport chain (ETC). Consistent with the pivotal role of CCO in mitochondrial bioenergetics and high demand for energy to sustain neuronal function, CCO dysfunction has been linked to neurological disorders including AD. However, it remains unclear whether mitochondrial CCO dysfunction represents an adaptive response to AD-associated toxic molecules versus a bona fide pathology to promote AD development. In this study, by meta-analysis of publicly available proteomics analysis of post-mortem frontal lobe tissues from four large cohorts of patients with AD we identified loss of key CCO subunits including mitochondrial DNA (mtDNA)-encoded COX1 and COX3 as well as nuclear DNA (nDNA)-encoded COX5A, COX6B1, COX7C, COX8A, and NDUFA4 in patients with AD. Further biochemical analysis using post-mortem frontal lobe tissues showed lowered CCO activity of neuronal mitochondria from patients with AD, suggesting CCO vulnerability and its potential association with amyloidosis in AD. Lastly, in addition to the inverse relationship between neuronal CCO activity and brain amyloidosis in the tested AD cohort, pharmacological inhibition of CCO promoted amyloid production and elevated beta-secretase 1 (BACE1) activity in cerebral organoids derived from human induced pluripotent stem cells (hiPSCs) from one nonAD and one AD subject. The simplest interpretation of the results is that CCO dysfunction in the frontal lobe is a phenotypic mitochondrial change accompanying AD, which may contribute to the development of brain amyloidosis.

Differential Burst dynamics of Slow and Fast gamma rhythms in Macaque primary visual cortex
Gamma oscillations have been ubiquitously observed across a wide spectrum of brain areas in multiple species. They tend to occur intermittently in the form of bursts, rather than being produced as sustained and continuous rhythmic activity. Recent studies have shown that large visual sinusoidal gratings elicit two distinct gamma rhythms, namely, slow ({approx} 20-35 Hz) and fast gamma ({approx} 40-65 Hz), in the primary visual cortex (V1) of non-human primates. However, their mechanisms of generation and potential functional role in cortical processing remain unclear. Details of their burst signatures could potentially provide crucial insights about how the two rhythms influence network dynamics. Therefore, we computed burst statistics (durations and latencies) of simultaneously induced slow and fast gamma rhythms in the local field potential (LFP) recorded from area V1 of two adult female bonnet monkeys using several burst estimation methods. We found that slow gamma rhythm exhibited significantly longer burst durations and longer latencies as compared to fast gamma. Slow gamma exhibited higher long-range synchrony compared to fast gamma, as estimated by coherence and weighted phase lag index (WPLI), which could aid in enhanced global coordination in neocortex. Interestingly, longer burst length of slow-gamma could be replicated in a recently-developed noisy Wilson-Cowan network model by simply changing the firing-rate time-constant of the corresponding inhibitory interneuronal population, which leads to both slower and longer bursts. These results are consistent with the hypothesis that the two oscillations are generated by different inter-neuronal classes that operate over different temporal and spatial scales of integration.

The Rod Bipolar Cell Pathway Contributes To Surround Responses In OFFRetinal Ganglion Cells
Sensory neurons can be influenced by stimuli beyond their receptive field center, yet the mechanisms underlying this surround modulation remain poorly understood. In the retina, many OFF ganglion cells exhibit responses to ON stimulation outside their receptive field center. However, disentangling the pathways and cell types contributing to these responses has been challenging with traditional experimental approaches. Here, we combined optogenetics, two-photon holographic stimulation, and multi-electrode array recordings to identify the intermediate retinal cell types involved in this circuit. We found that the pathway formed by rod bipolar cells and AII amacrine cells (one of the primary relays of rod-driven signals under low-light conditions) plays a key role in mediating this surround modulation. Specifically, crossover inhibition exploits the same amacrine cells responsible for surround suppression to disinhibit distant ganglion cells. This suggests that the retina repurposes existing circuits for surround modulation, optimizing resources through multifunctional inhibitory pathways.

Sex and gender differences in perivascular space in early adolescence
Perivascular spaces (PVS) surrounding cerebral blood vessels play an important role in the blood-brain barrier and glymphatic system. Although it was once thought that PVS were either absent or too small to be seen or quantified during healthy development with MRI, recent studies have found visible, quantifiable PVS exist throughout the white matter of the cerebrum in childhood and adolescence. As a result, researchers have begun to explore individual differences, including potential sex-based variations in developing PVS. Meta-analyses in adults have shown that PVS are larger on average in males than in females, and several studies have shown a similar relationship in children. In contrast, no studies to date have examined the association between gender and PVS at any age. This cross-sectional study examined 6,538 youths from a large, nationwide sample of 9- to 11-year-olds in the U.S. to examine the relationship between sex, felt-gender, and PVS count and volume. Using a model-building approach, we conducted a series of linear mixed-effects models to determine the maximum variance explained in PVS count and volume, including age, pubertal development status, race, parent education, BMI z-score, and regional white matter volume, while also adjusting for MRI scanner and site. BMI z-score, age, and parent education were significant predictors of both PVS volume and count. Adding sex to the model improved model fit in all regions, and the further addition of felt-gender significantly improved model fit for PVS count in 5/6 regions of interest. Moreover, we found increases in PVS volume and count were associated with reduced executive function, learning, and memory. As the first study to report an association between felt-gender and PVS, our findings demonstrate the importance of considering gender in addition to sex as a potential source of structural variance in PVS in adolescents.

NOVA: a novel R-package enabling multi-parameter analysis and visualization of neural activity in MEA recordings
Multielectrode array (MEA) technology enables simultaneous recording of electrical signals from neuronal networks, producing complex datasets. Current analytical approaches typically examine a limited number of metrics such as mean firing rate and synchronicity, leaving much of the data underutilized. To address this gap, we created NOVA (Neural Output Visualization and Analysis), an accessible R-based computational tool for comprehensive MEA data interpretation and visualization. NOVA integrates dimensionality reduction through principal component analysis, hierarchical clustering with heatmap generation, and temporal trajectory mapping of network activity patterns. Our code offers both a user-friendly pipeline requiring minimal coding background as well as customizable advanced plotting modules for experienced users. Validation experiments using primary cortical neurons during development and pharmacological manipulation demonstrated NOVA's capacity to detect subtle activity shifts overlooked by conventional methods. Notably, our unbiased approach identified network burst duration as a stronger contributor to activity variance than commonly reported firing rate metrics, exemplifying NOVA's utility for discovering meaningful patterns and generating data-driven hypotheses.

Cerebrovascular response dynamics to hypercapnia in healthy aging
Cerebrovascular dysfunction is an early and underrecognized contributor to cognitive decline. Standard measures such as cerebrovascular reactivity (CVR) during hypercapnia capture only the amplitude of flow responses, providing limited insight into the timing of vascular adaptation. Temporal features, such as delay (onset latency) and time constant (rate of adjustment), together with gain (response amplitude) may serve as more sensitive indicators of vascular health, but cannot be directly obtained from conventional imaging. Here, we investigated cerebral blood flow (CBF), cerebral blood volume (CBV), and blood oxygenation level dependent (BOLD) signal dynamics during hypercapnic challenge in healthy aging. Using a physiologically validated computational model, we estimated delay, time constant, and gain by optimizing the mapping of end-tidal gases to their arterial counterparts in a region-of-interest framework. Once parametrized using CBF, the model successfully predicted CBV and BOLD responses in independent experimental sessions. Across subjects, aging was associated with widespread heterogeneous region-specific changes in delay and substantial reductions in gain and time constant, indicating that cerebrovascular responses become weaker and less adaptable with age. These results demonstrate that calibrated simulations have the ability to track vascular aging, allowing the extraction of parameters that may represent novel biomarkers of cerebrovascular dysfunction. Unlike conventional CVR, temporal hemodynamic parameters capture the dynamics of vascular adaptation, providing a complementary dimension for early detection and therapeutic monitoring in aging and disease.

Motor dysfunction at 4 weeks in streptozotocin-induced diabetic animals
Aims: Diabetic neuropathy is still a severe and common consequence for diabetic patients. The impact of neuropathy emphasizes the need to study its biology in order to treat patients early. The limitations of preclinical neuropathy models to date demand in vivo models that combine early nerve dysfunction detection with low mortality. Streptozotocin is commonly used to cause diabetes in rodents, but conventional high dose design often results in high mortality rates. In this study, I present a secondary analysis of a neuropathy primary model [8], focusing on the 4-week timepoint and validating proximal motor dysfunction in a short timeframe with high survival using F-wave metrics as early biomarkers. Methods: Male Wistar rats received low-dose STZ (30 mg/kg) on alternate days for one week (three injections) or vehicle. At baseline and 4-week, I analyzed blood glucose and body weight, and electrophysiological recordings (M-/F-waves) were performed at endpoint. Results: Rats treated with STZ had significant body weight loss (p < 0.001) and hyperglycemia greater than (20 mmol/L), which was aligned with a negative correlation (Pearson r = -0.77, p = 0.003). Furthermore, in diabetic animals, electrophysiology displayed that M-waves were unchanged, whereas F-waves were absent (p < 0.0001). Moreover, 91.7% of the animals were still alive at the end of the study, indicating a high level of survival. Conclusions: The new approach of this secondary study resulted in development of neuropathy at 4 weeks, accompanied by high survival, which in turn validates F-waves as an early biomarker of nerve dysfunction within a short timeframe. Thus, this new work provides an early and reliable platform for testing neuroprotective drugs and mechanistic work in the short term.

Social learning of emotion and its implication for memory: An ERP Study
Social learning of emotional salience from surrounding social cues is especially advantageous under conditions of uncertainty. Yet, the neural mechanisms underlying this process and its consolidation into long-term memory remain poorly understood. In this two-day EEG study, we examined whether emotional salience from social cues (facial expressions) transfers to perceptually uncertain target images, and whether such learned salience is preserved in memory even after the social cues are removed. On Day 1 (learning session), we found no evidence for automatic emotional salience transfer across trials. Instead, ERP results indicated that social cue use was modulated by participants' metacognitive state of subjective uncertainty, as reflected in the P1 amplitudes. On Day 2 (test session), recognition memory revealed evidence of additive emotional salience: EPN amplitudes were enhanced for accurately classified positive target images previously paired with social cues. In contrast, LPC amplitudes were reduced for negative target images in the social condition, regardless of classification accuracy. Together, these findings suggest that the influence of social cues is contingent on subjective uncertainty. Social cues enhanced emotional salience when internal valence judgments were strong (as for positive images), but led to increased reliance on the cue - and therefore dampened memory encoding - when internal valence judgments were weaker (as for negative images).

Disruption of emotional processing by GBR 12909 in male and female mice highlights novel behavioral paradigms relevant to bipolar disorders.
Bipolar disorders (BD) are defined by a chronic recurrence of manic and depressive phases. Along with mood, acute phases are associated with altered emotions. The biological underpinnings of these changes are unresolved, mostly because modeling the cycling nature of BD is still a major challenge in preclinical studies. One model is based on GBR 12909 administration, a dopamine transporter inhibitor aiming at mimicking some dimensions of mania. It has recently been shown that this model generates a mixed phenotype with negative hedonic biases and anxiety along with the hyperlocomotion. These studies have been only assessed in male animals, and other behavioral dimensions relevant for BD remain to be explored, in particular recognition of conspecifics emotions and reactivity to danger. The objective of this study is to further characterize the GBR model in both sexes by introducing two novel behavioral assays, the sweeping/looming disk and the negative emotion recognition tasks to evaluate response to threat and emotion discrimination. First, we replicated the previous results in the GBR model: higher anxiety, hyperlocomotion, anhedonia in males. These phenotypes were less pronounced in females. GBR also induced a hypersensibility to threat in both sexes in the sweeping/looming disk. GBR abolished preference for the emotional target only in males, suggesting altered emotion recognition. This work introduces new phenotypic dimensions relevant to study BD and highlights the necessity to study both sexes which are not strictly equivalent in their behavioral responses.

Neural Receptive Fields, Stimulus Space Embedding and Effective Geometry of Scale-Free Networks
Understanding how neuronal dynamics couple with stimuli space and how receptive fields emerge and organize within brain networks remains a fundamental challenge in neuroscience. Several models attempted to explain these phenomena, often by adjusting the network to empirical manifestations, but struggled to achieve biological plausibility. Here, we propose a physiologically grounded model in which receptive fields and population-level attractor dynamics emerge naturally from the effective hyperbolic geometry of scale-free networks. In particular, we associate stimulus space with the boundary of a hyperbolic embedding, and study the resulting neural dynamics in both rate-based and spiking implementations. The resulting localized attractors faithfully reflect the structure of the stimulus space and capture key properties of the receptive fields without fine-tuning of local connectivity, exhibiting a direct relation between a neuron's connectivity degree and the corresponding receptive field size. The model generalizes to stimulus spaces of arbitrary dimensionality and scale, encompassing various modalities, such as orientation and place selectivity. We also provide direct experimental evidence in support of these results, based on analyses of hippocampal place fields recorded on a linear track. Overall, our framework offers a novel organizing principle for receptive field formation and establishes a direct link between network structure, stimulus space encoding, and neural dynamics.

Dynamic updating of cognitive maps via traces of experience in the subiculum
In the classical view of hippocampal function, the subiculum is assigned the role as the output layer. In spatial paradigms, some subiculum neurons manifest as so-called boundary vector cells (BVCs), firing in response to boundaries at specific allocentric directions and distances. More recently it has been shown that some subiculum BVCs can be classified as vector trace cells (VTCs), which exhibit traces of activity after a boundary/object has been removed. Here we propose a model of processing within subiculum that accounts for VTCs, taking into account proximodistal differences in subiculum (pSub vs dSub) and CA1. dSub neurons receive feedforward input, either in the form of perceptual information (from BVCs in pSub) or mnemonic information (from place cells in CA1). Mismatch between these two inputs updates associative memory encoded in the synapses between CA1 and dSub. With a range of learning rates, the model captures the majority of experimental findings, including the distribution of VTCs along the proximodistal axis, the percentage of VTCs across different cue types, and the hours-long persistence of the vector trace. Incorporating experimentally reported effects of inserted objects/rewards on place cells (place field shift), we also explain why VTCs have longer tuning distances after cue removal. This adds predictive character to subiculum traces and suggests the online use of mnemonic content during navigation. Our model suggests that mismatch detection for updating spatial memory content provides a mechanistic explanation for findings in the CA1-subiculum pathway. This work constitutes the first dedicated circuit-level model of computation within the subiculum, consistent with known effects in CA1, and provides a potential framework to extend the canonical model of hippocampal function with a subiculum component.

Cerebellar outputs for rapid directional refinement of forelimb movement
Much of our interaction with the world relies on the ability to move our limbs with speed and precision. The cerebellum is critical for movement coordination, yet how outputs from the cerebellum continually guide the limb and whether discrete pathways differentially contribute to adjusting motor output remain unclear. Using intersectional viral approaches in mice, we identify two spatially intermingled yet anatomically distinct cerebellar populations that drive the forelimb either toward or away from the body. Neural recordings reveal cerebellar activity that correlates with and precedes these opposing directional changes in limb movement. Both cerebellar output pathways influence motor neuron and muscle activity within milliseconds, producing reliable effects on limb trajectory despite substantial underlying variability in muscle recruitment patterns. Our findings disentangle a subtype organization to cerebellar limb control, revealing a subcortical circuit basis for online directional refinement during movement execution.

Multimodal MR Imaging for quantification of brain lipid in mice at 9.4T
Background: Advanced MR imaging techniques like steady state Nuclear Overhauser enhancement (ssNOE), transient NOE (tNOE), and myelin water fraction (MWF) provide a non-invasive way to assess the biochemical and structural integrity of brain tissue. Their sensitivity to endogenous lipids and macromolecules allows for the early detection of neuropathological changes, making them valuable tools in studying brain health and disease progression. In this study, we systematically evaluate the repeatability and sensitivity of NOEMTR, tNOE, and MWF for quantifying lipid and myelin content in the brains of wild-type (WT) mice, correlating the results with immunohistochemistry (IHC). Methods: Five 6-month-old C57BL6/J mice were imaged using 3D-NOE, and four mice underwent imaging with 2D tNOE and MWF across four repeated sessions using a 9.4T Scanner. For ssNOE imaging, CEST-weighted images at 56 frequency offsets were acquired using B1rms of 1.0 T and 3s saturation duration. For tNOE, 52 offsets were acquired with a hyperbolic secant inversion pulse (bandwidth = 400Hz, duration = 44ms) and a mixing time of 200ms. For MWF, a multi-echo spin-echo (MESE) sequence was acquired with 40 evenly spaced echoes from 5.5ms to 200ms. For both ssNOE and tNOE, B0 correction was performed using WASSR. Repeatability was quantified using intra- and inter-subject coefficients of variation (COV%). Pearson correlation was performed to see the association between imaging matrices and IHC measures, Luxol fast blue (LFB) stained sections, and myelin basic protein (MBP). Results: All techniques demonstrated high repeatability across the whole brain (WB) and selected regions of interest (ROIs). Whole-brain intra-subject COV% for NOEMTR ranged from 1.92% to 3.40%, with corresponding inter-subject COVs of 1.50%. tNOE exhibited improved intra-subject repeatability with COVs ranging from 0.75% to 5.57%, but a reduced inter-subject COV of 2.97%. MWF imaging showed the highest stability overall, with an intra-subject COV ranging from 0.47% to 2.03% and an inter-subject COV of 0.75%. Visually, tNOE offers superior contrast in myelin-rich areas compared to NOEMTR and MWF imaging, showing greater sensitivity to myelinated regions. tNOE strongly correlates with histological markers: r = 0.83 with MBP staining and r = 0.72 with LFB staining (both p < 0.001). MWF and NOEMTR showed correlations with MBP (r = 0.63 and r = 0.57, respectively). Conclusion: NOEMTR, tNOE, and MWF imaging are reliable and repeatable methods for quantifying macromolecules in the brain. Among these, tNOE emerges as the most sensitive for detecting myelin lipids as confirmed by histological validation. These findings highlight the translational potential of tNOE for studying demyelinating disorders and neurodegenerative diseases. Keywords: Brain, Lipid Imaging, Myelination, Repeatability, NOEMTR, tNOE, MWF

Transdiagnostic connectome-based predictive modeling of many behavioral phenotypes reveals brain network mediators of clinical-cognitive relationships
Connectome-based predictive modeling (CPM) applied to functional MRI connectivity data can identify brain networks that vary with behavioral measures across subjects. The prediction strength also provides an index of how closely an external instrument relates to specific brain networks, potentially impacting their clinical interpretation. Here we use a deeply phenotyped transdiagnostic population (n = 317) to evaluate CPM performance across a variety of clinical and cognitive measures. The findings revealed a wide range of predictive performance for external instruments, with cognitive tests generally predicting better than self-reported clinical measures (unpaired t-test, p < 0.001). Testing the hypothesis that networks supporting cognition should be apparent in networks related to symptomatology, we examined the networks' overlap. The overlap was sparse, but primarily identified the thalamus, cerebellum, somatomotor networks, and the dorsolateral prefrontal cortex as key hubs in mediating relationships between clinical and cognitive measures. The findings reveal the extent to which external measures reflect underlying brain networks and highlight that examining network overlap can identify networks specific to clinically relevant cognitive dysfunction.

Insular input to the prelimbic cortex underlies social affective behavior in rats.
To navigate social interactions, animals must adjust their behavior in response to information derived from conspecifics. The integration of social information and coordination of behavior occurs within a distributed social decision making network. The prelimbic (PL) prefrontal cortex and the insula (IC) are key nodes in the salience network which is anatomically situated to interact with the social brain. We investigated the IC-PL circuit in a social affective preference (SAP) test in which subject rats are exposed to 2 age-matched conspecifics where one is stressed via footshock and the other is naive to stress. Typically, rats approach stressed juvenile conspecifics but avoid stressed adults. Using a combination of local and tract specific loss of function methods, we demonstrate that the PL, anterior IC, and the tracts between the posterior or anterior IC and the PL are necessary when rats face the choice to approach or avoid stressed conspecifics. Going further, chemogenetic inhibition of PL neurons innervated by the IC also interfered with social affective behaviors. These studies enrich our understanding of the neurobiology of social decision making by establishing a mechanistic link between insular and prefrontal circuits.

Locus Coeruleus-Amygdala Circuit Disrupts Prefrontal Control to Impair Fear Extinction
Stress undermines extinction learning and hinders exposure-based clinical therapies for a variety of neuropsychiatric disorders. In both animals and humans, dysfunction in the ventromedial prefrontal cortex (vmPFC) contributes to stress-impaired extinction, but the neural circuit by which stress modulates vmPFC function is not known. We hypothesize that locus coeruleus (LC) norepinephrine undermines extinction learning by recruiting projections from the basolateral amygdala (BLA) to vmPFC. Using a combination of circuit-specific chemogenetics and calcium imaging, we find that activation of LC noradrenergic neurons mimics a behavioral stressor (footshock), induces freezing behavior, reduces spontaneous neuronal activity in the vmPFC, impairs extinction learning, and alters the population dynamics of vmPFC ensembles. Activation of LC also increases shock-induced responses in BLA neurons that project to vmPFC. Selective chemogenetic activation of LCBLA projections impairs extinction; propranolol infusions into the BLA mitigate the effects of LC activation. Together, these results indicate that the BLA serves as a critical interface between the LC and mPFC to mediate stress-induced extinction impairments.

Transition Metal Dichalcogenide Nanoflowers Rescue Immune Cells from the Cytotoxic Effects of Amyloid Aggregates
Parkinson's disease (PD) is a severe pathology caused by a progressive degeneration of neurons in the substantia nigra pars compacta, hypothalamus, and thalamus. Although etiology of PD remains unclear, accumulating evidence indicates that neurodegenerative effects are triggered by the abrupt aggregation of a-synuclein (a-Syn), a small membrane protein that is responsible for cell vesicle trafficking. a-Syn aggregates are highly toxic to neurons and immune cells present in the brain, including macrophages, microglia, and dendritic cells. Transition metal dichalcogenide nanoflowers (TMD NFs) are novel nanomaterials with unique optical and biological properties. However, their effects on the immune system remain poorly understood. In this study, we investigate cytoprotective properties of molybdenum disulfide (MoS2) and molybdenum diselenide (MoSe2) NFs on macrophages, microglia, and dendritic cells exposed to a-Syn fibrils. We found that MoSe2 NFs exerted strong cytoprotective properties fully mitigating toxic effects of a-Syn fibrils, while MoS2 NFs were found to be significantly less potent in rescuing immune cells from a-Syn aggregates. At the same time, MoS2 NFs triggered polarization of macrophages into M1 and dendritic cells into M2 phenotypes, while an increase in both M1 and M2 was observed in microglia exposed to MoS2 NFs. MoSe2 NFs did not trigger polarization of DC cells and microglia in M1/M2 phenotypes, while MoSe2 NFs-facilitated polarization of macrophages into M1 was observed. These results indicate that TMD NFs could be used to improve viability of immune cells and attenuate their phenotypes, which, ultimately, can be used to treat PD and other neurodegenerative pathologies.

Sequelae and reversal of age-dependent alterations in mitochondrial dynamics via autophagy enhancement in reprogrammed human neurons
How aging of human neurons affects dynamics of essential organelle such as mitochondria and autophagosomes remains largely unknown. MicroRNA-induced directly reprogrammed neurons (miNs) derived from adult fibroblasts retain age-associated signatures of the donor, enabling the study of age-dependent features in human neurons, including longitudinal isogenic samples. Transcriptomic analysis revealed that neurons derived from elderly individuals are characterized by gene expression changes associated with the regulation of autophagosomes, lysosomes, and mitochondria, compared to young counterparts. To clarify these changes at the cellular level, we performed live-cell imaging of cellular organelles in miNs from donors of different ages. Older donor miNs exhibit decreased mitochondrial membrane potential, which surprisingly co-occurs with a significant increase in mitochondrial fission and fusion events. We posit that the increased fission and fusion of mitochondria may reflect age-dependent compensation for impaired mitochondrial turnover, perhaps due to changes in autophagy. We subsequently identified a significant decrease in autophagosome acidification in neurons derived from individuals >65 years compared to younger donors, and a corresponding age-dependent reduction in neuritic lysosomes resulting in fewer lysosomes available to acidify autophagosomes. This age-dependent deficit in autolysosome flux was rescued by chemically promoting autophagosome generation, which also reversed the age-dependent increase in mitochondrial fission and fusion and improved mitochondrial health. Together, this work reveals a mechanism by which aging reduces autophagic flux secondary to a loss of neuritic lysosomes, resulting in in mitochondria-intrinsic mechanisms to avoid loss of energy production.

Structured Sampling of Molecularly Classified Mossy Fiber Inputs by Cerebellar Granule Cells
The cerebellar granule cell layer receives mossy fiber inputs from diverse brain regions, yet the principles governing how individual granule cells sample distinct types of inputs remain poorly understood. Using a volumetric correlated light and electron microscopy (vCLEM) dataset from an adult female mouse cerebellum, in which VGluT1 positive and VGluT1 negative mossy fiber terminals are molecularly distinguished, we reconstructed granule cell and mossy fiber connectivity to examine input selection rules. We constructed spatially constrained null models to simulate sampling during adulthood and development. Granule cell-centered analysis showed that granule cells shared less innervation from the same mossy fiber than expected by chance. Moreover, subpopulations of granule cells preferentially sample either VGluT1 positive or VGluT1 negative mossy fibers. In contrast, mossy fiber centered analysis showed that individual terminals distributed their outputs across granule cells in a pattern consistent with random sampling. However, sampling in the adult state was more selective than in developmental simulations. Together, our findings demonstrated structured, non random sampling of cerebellar VGluT1 positive and VGluT1 negative mossy fiber inputs and provide a framework for understanding how granule cells integrate molecularly distinct inputs to support cerebellar computation.

Strong mnemonic prediction errors increase cognitive control, attention, and arousal
Ongoing experience is continuously processed in the context of past events. Divergence between current experience and memory-based predictions (i.e., a mnemonic prediction error; MPE) is theorized to be a signal for the hippocampus that encoding, as opposed to retrieval, should be prioritized. We asked how MPEs place demands on cognitive and neural resources beyond the hippocampus, and whether these demands differ as a function of prediction strength. We investigated these questions across two experiments, wherein we recorded scalp electroencephalography and/or pupillometry as 101 young human adults performed an associative memory task. Strong MPEs, more so than weak MPEs, increased physiological indices of cognitive control (frontal theta), attention (posterior alpha and pupil size), and arousal (pupil size). Trial-level pupil-linked MPE responses scaled with the amount of attention (posterior alpha) allocated during prediction generation. Finally, greater cognitive control (frontal theta) during strong MPEs promoted better learning of prediction violating (i.e., unexpected) stimuli. Collectively, these findings reveal how the mind and brain respond adaptively to violations of strong mnemonic predictions.

Minor Cannabinoids CBD, CBG, CBN and CBC differentially modulate sensory neuron activation
The use of minor cannabinoids has been advanced, in part, by the idea of providing relief from pain and inflammation without the burden of unwanted psychogenic effects associated with {Delta}9THC. In this regard, investigators have focused on the effects of minor cannabinoid activation / desensitization of peripheral sensory neurons on nociceptive signaling and/or peripheral inflammation. With a focus on peripheral nociception, four common minor cannabinoids: cannabidiol (CBD), cannabigerol (CBG), cannabinol (CBN) and cannabichromene (CBC) were studied in primary cultures of mouse Dorsal Root Ganglion (DRG) neurons. We queried if calcium responses induced by the four cannabinoids differed in potency of activation, neuronal size preference, and dose-response relationships. Additionally, we determined the dependence of CBD and CBN on key channel-receptors that are known to mediate pain and/or antinociception. Individually, CBD, CBG and CBC directed greater response magnitudes when compared to CBN. All four minor cannabinoids activated overlapping but distinct size populations of sensory neurons. CBD and CBG activated the widest range of DRG neuron sizes (smaller-larger) overlapping with smaller capsaicin-sensitive neurons. In contrast, CBN and CBC activated predominantly larger sensory neurons. CBD diverged from other minor cannabinoids in directing a linear dose-response profile whereas CBG and CBC directed sigmoidal dose-response profiles and CBN activated DRG neurons with an inverted U-shaped dose-response relationship. CBD-induced activation of DRG neurons was dependent on co-expression of the nociceptive channel TRPV1 plus cannabinoid receptor 1 (CB1R), whereas CBN-induced activation was independent of TRPV1. Overall, we observed that minor cannabinoids CBD, CBG, CBN and CBC differed in their activation of DRG neurons and directed unique activation properties across a diverse population of sensory neurons. Such differences underly the hypothesis that a combination (entourage) of complimentary minor cannabinoids can direct synergistic antinociceptive activity

Distinct laminar origins of high-gamma and low-frequency ECoG signals revealed by optogenetics
Electrocorticography (ECoG) provides a high-spatiotemporal-resolution measure of cortical activity (cortical surface electrical potentials, CSEPs) in humans and animals. The CSEP high-gamma band (H{gamma}, 65-170 Hz) correlates with neuronal firing rates at the columnar spatial scale and is widely used as a biomarker of local activity. Whether H{gamma} reports all stages of columnar processing, intermediate processing in L2/3 (close to the ECoG electrode), or the main columnar output in L5, is unknown. We disentangled the laminar origins of H{gamma} and other ECoG bands by optogenetically suppressing L2/3 or L5 pyramidal cells during micro-ECoG recording in mouse somatosensory cortex. Whisker deflections evoked transient, topographically localized CSEPs. L5 optogenetic suppression most strongly reduced 65-450 Hz (H{gamma}-uH{gamma}) bands in sensory-evoked ECoG signals, whereas L2/3 suppression most strongly reduced 4-30 Hz ({theta}-{beta}) bands. Thus, different CSEP frequency bands reflect layer-specific activity and are biomarkers of distinct stages of columnar processing.

Abnormal expression of splicing regulators RBFOX and NOVA is associated with aberrant splicing patterns at the Neurexin-3 gene in a monogenic autism spectrum disorder
Autism spectrum disorders are diseases characterized by a combination of cognitive, behavioral and neurological symptoms. A complex interplay between environmental factors and a multitude of genetic determinants, most of them composed of low-risk variants, impose difficulties in understanding the molecular and cellular underpinnings of these conditions. In some cases, autistic patients have been shown to display alterations in splicing patterns of several genes, but the extent to which this phenomenon is common in the context of these multifactorial disorders is unknown, nor is it known if monogenic cases of autism also display dysregulation of splicing. Moreover, very few studies have investigated the causal links between splicing alterations in specific genes and the phenotypic characteristics of the neural tissue in autism patients. In this study, we have focused on a monogenic type of autism caused by haploinsufficiency of the Transcription Factor 4 gene, known as Pitt-Hopkins Syndrome. We show that neurons and organoids derived from patients with this disease have altered expression of splicing regulators in the NOVA and RBFOX families, accompanied by aberrant splicing patterns in a substantial number of genes involved in neural tissue development and synapse organization. We focused on a gene encoding a member of the Neurexin Family, the splicing of which normally leads to the production of transcript variants coding for both transmembrane and secreted protein isoforms. In Pitt-Hopkins Syndrome neurons, we detected an aberrant splicing pattern that results in lower expression of the transcript that encodes the secreted isoform, a phenomenon that may explain why the neural tissue in these patients have decreased electrical activity through impaired synapse organization. Our data shed light on the role splicing regulation plays in a monogenic type of autism.

Dithering suppresses half-harmonic neural synchronisation to photic stimulation in humans
While entraining neural rhythms using brain stimulation has been suggested as a therapeutic mechanism to normalise brain activity in conditions such as depression, chronic pain, or Alzheimer's disease, periodic stimulation can also inadvertently entrain brain rhythms at sub- and superharmonics of the stimulation frequency, which could lead to deleterious effects. Slightly jittering stimulation pulses (called "dithering") was previously proposed on the basis of mathematical modelling to selectively entrain a target neural rhythm while avoiding harmonic entrainment. In this study, we investigated the potential of dithering in humans. Using photic stimulation (light flicker) and EEG recordings in healthy participants, we showed that dithering suppresses half-harmonic synchronisation relative to perfectly periodic flicker, and more so than synchronisation at the stimulation frequency. This was also the case for a periodic condition with reduced stimulation amplitude, as predicted by theory. Furthermore, we demonstrated using synthetic data and modelling that the half-harmonic responses observed in participants cannot be explained by the superposition of evoked responses (even when modulated at the half-harmonic frequency), and are better matched by a minimal oscillator model. Our findings are consistent with half-harmonic EEG synchronisation in response to photic stimulation predominantly reflecting half-harmonic entrainment rather than the summation of evoked responses, and with dithering being an effective strategy to suppress subharmonic entrainment.

Slow change blindness from serial dependence
Slow change blindness, when attentive observers fail to notice large changes that happen gradually, raises questions about how visual information is combined across time. One plausible integration strategy is serial dependence: blending information from the recent past into current perception. Here, we investigate serial dependencies in perception of a cartoon object that slowly changes hue. In a one-shot experiment, observers each viewed a single trial with a random degree of hue change and provided one hue judgement response. Across participants, the entire morph was probed. Observers' hue reports revealed an overall bias towards the past that increased in magnitude as more of the morph was experienced. In three follow-up experiments, we verified that observers experienced slow change blindness, confirmed that the bias was serial dependence, and replicated the results with a repeated-trials design. Overall, we provide evidence that serial dependence actively biases perception during gradual changes, producing slow change blindness.

Circulating Lipids are Associated with PTSD Severity and Predict Symptomatic PTSD in a Cohort of Veterans and Service Members
Post-traumatic stress disorder (PTSD) is characterized by chronic stress, alterations in mood, and avoidance after a traumatic event has occurred. While recovery can occur, many PTSD patients suffer life-long impairments. In combat veterans, high rates of PTSD contribute to increased rates of depression and anxiety and a higher likelihood of suicidal ideation. The lack of biological markers for psychiatric conditions such as PTSD highlights the need for omics-based approaches to diagnosis. Discovery of novel blood-based biomarkers could aid in the development of treatments or therapies, quantify groups for those at the highest risk of adverse events, and provide insight into the molecular underpinnings of PTSD. This study used untargeted lipidomics to analyze 602 circulating lipid species in blood from a cohort of 133 veterans and combat members with varying severities of PTSD. We discovered five circulating lipids, including serum total cholesterol, cholesterol ether (ChE(18:2)), and lipids associated with metabolic dysfunction (CL(87:7), MLCL(50:4), PE(18:1e_20:3)) that correlated significantly with increasing PTSD severity after adjustment for multiple comparisons. Additionally, we showed that symptomatic PTSD patients could be separated from asymptomatic controls using these lipid species. This study contributes to the limited research surrounding the role of circulating lipids in PTSD.