bioRxiv Subject Collection: Neuroscience's Journal

Effects of electroconvulsive shock on the function, circuitry, and transcriptome of dentate gyrus granule neurons
Therapeutic use of electroconvulsive shock (ECS) is 75% effective for the remission of treatment-resistant depression. Like other more common forms of antidepressant treatment such as fluoxetine, ECS has been shown to increase neurogenesis in the hippocampal dentate gyrus of rodent models. Yet the question of how ECS-induced neurogenesis supports improvement of depressive symptoms remains unknown. Here, we show that ECS-induced neurogenesis is necessary to improve depressive-like behavior of mice exposed to chronic corticosterone (Cort). We then use slice electrophysiology to show that optogenetic stimulation of adult-born neurons produces a greater hyperpolarization in mature granule neurons after ECS vs Sham treatment. We identify that this hyperpolarization requires the activation of metabotropic glutamate receptor 2 (mGluR2). Consistent with this finding, we observe reduced expression of the immediate early gene cFos in the granule cell layer of ECS vs Sham subjects. We then show that mGluR2 knockdown specifically in ventral granule neurons blunts the antidepressant-like behavioral effects of ECS. Using single nucleus RNA sequencing, we reveal major transcriptomic shifts in granule neurons after treatment with ECS+Cort or fluoxetine+Cort vs Cort alone. We identify a population of immature cells which has greater representation in both ECS+Cort and fluoxetine+Cort treated samples vs Cort alone. We also find global differences in ECS- vs fluoxetine-induced transcriptomic shifts. Together, these findings highlight a critical role for immature granule cells and mGluR2 signaling in the antidepressant action of ECS.

Molecular control of temporal integration matches decision-making to motivational state
Motivations bias our responses to stimuli, producing behavioral outcomes that match our needs and goals. We describe a mechanism behind this phenomenon: adjusting the time over which stimulus-derived information is permitted to accumulate toward a decision. As a Drosophila copulation progresses, the male becomes less likely to continue mating through challenges. We show that a set of Copulation Decision Neurons (CDNs) flexibly integrates information about competing drives to mediate this decision. Early in mating, dopamine signaling restricts CDN integration time by potentiating CaMKII activation in response to stimulatory inputs, imposing a high threshold for changing behaviors. Later into mating, the timescale over which the CDNs integrate termination-promoting information expands, increasing the likelihood of switching behaviors. We suggest scalable windows of temporal integration at dedicated circuit nodes as a key but underappreciated variable in state-based decision-making.

Coupling of saccade plans to endogenous attention during urgent choices
The neural mechanisms that willfully direct attention to specific locations in space are closely related to those for generating targeting eye movements (saccades). However, the degree to which the voluntary deployment of attention to a location is necessarily accompanied by a corresponding saccade plan remains unclear. One problem is that attention and saccades are both automatically driven by salient sensory events; another is that the underlying processes unfold within tens of milliseconds only. Here, we use an urgent task design to resolve the evolution of a visuomotor choice on a moment-by-moment basis while independently controlling the endogenous (goal-driven) and exogenous (salience-driven) contributions to performance. Human participants saw a peripheral cue and, depending on its color, either looked at it (prosaccade) or looked at a diametrically opposite, uninformative non-cue (antisaccade). By varying the luminance of the stimuli, the exogenous contributions could be cleanly dissociated from the endogenous process guiding the choice over time. According to the measured timecourses, generating a correct antisaccade requires about 30 ms more processing time than generating a correct prosaccade based on the same perceptual signal. The results indicate that saccade plans are biased toward the location where attention is endogenously deployed, but the coupling is weak and can be willfully overridden very rapidly.

Activity of spinal RORβ neurons is related to functional improvements following combination treatment after complete SCI
Various strategies targeting spinal locomotor circuitry have been associated with functional improvements after spinal cord injury (SCI). However, the neuronal populations mediating beneficial effects remain largely unknown. In a mouse model of complete SCI, virally-delivered BDNF (AAV-BDNF) activates hindlimb stepping and causes hyperreflexia, whereas sub-motor threshold epidural stimulation (ES) reduced BDNF-induced hyperreflexia. Given their role in gating proprioceptive afferents and potential convergence point of BDNF and ES, we hypothesized that an enhanced excitability of inhibitory ROR{beta} neurons would be associated with locomotor improvements. Ex vivo spinal slice recordings revealed that the excitability of ROR{beta} neurons was decreased in mice with poor locomotor function after SCI, but was similar between the uninjured and 'best stepping' SCI groups. Further, chemogenetic excitation of ROR{beta} neurons reduced BDNF-induced hyperreflexia and improved stepping, similar to ES. Our findings identify inhibitory ROR{beta} neurons as a target population to limit hyperreflexia and enhance locomotor function after SCI.

The Role of Inhibition in fMRI Resting-State Negative Correlations
Resting-state brain activity, as observed via functional magnetic resonance imaging (fMRI), displays non-random fluctuations whose covariance structure (aka functional connectivity; FC) is commonly parsed into spatial patterns of positive and negative correlations (PCs and NCs). Mapping NC patterns for certain key seed regions has shown considerable promise in recent years as a tool for enhancing neuro-navigated targeting and clinical outcomes of repetitive transcranial magnetic stimulation (rTMS) therapies in psychiatry. These successes bring to the fore several major outstanding questions around the neurophysiological origins of fMRI NCs, the answers to which should prove useful for future therapeutic protocol development. In this work, we studied candidate mechanisms for the emergence of fMRI NCs using connectome-based computational modeling. Simulations of fMRI data under manipulation of inhibitory parameters WI and {lambda}, representing local and network-mediated inhibition respectively, were explored, focusing on the impact of inhibition levels on the emergence of NCs. Despite the considerable difference in time scales between GABAergic neuronal inhibition (tens of ms) and fMRI FC (dozens of seconds), a clear relationship was observed, whereby the greater levels of overall inhibition led to significantly greater magnitude and spatial extent of NCs. We show that this effect is due to a leftward shift in the FC correlation distribution, leading to a reduction in the number of PCs and a concomitant increase in the number of NCs. Relatedly, we observed that those connections available for recruitment as NCs were precisely those with the weakest corresponding structural connectivity. Relative to nominally default values for the models used, greater levels of inhibition also improved, quantitatively and qualitatively, single-subject fits of simulated to empirical FC matrices. Our results provide new insights into how individual variability in anatomical connectivity strengths and neuronal inhibition levels may determine individualized expression of NCs in fMRI data. These, in turn, may offer new directions for optimization and personalization of rTMS therapies and other clinical applications of fMRI NC patterns.

An immune signature of postoperative cognitive decline in elderly patients
Postoperative cognitive decline (POCD) is the predominant complication affecting elderly patients following major surgery, yet its prediction and prevention remain challenging. Understanding biological processes underlying the pathogenesis of POCD is essential for identifying mechanistic biomarkers to advance diagnostics and therapeutics. This longitudinal study involving 26 elderly patients undergoing orthopedic surgery aimed to characterize the impact of peripheral immune cell responses to surgical trauma on POCD. Trajectory analyses of single-cell mass cytometry data highlighted early JAK/STAT signaling exacerbation and diminished MyD88 signaling post-surgery in patients who developed POCD. Further analyses integrating single-cell and plasma proteomic data collected before surgery with clinical variables yielded a sparse predictive model that accurately identified patients who would develop POCD (AUC = 0.80). The resulting POCD immune signature included one plasma protein and ten immune cell features, offering a concise list of biomarker candidates for developing point-of-care prognostic tests to personalize perioperative management of at-risk patients. The code and the data are documented and available at https://github.com/gregbellan/POCD .

Emotion induction modulates neural dynamics during ideational originality
Emotions remarkably impact our creative minds; nevertheless, a comprehensive mapping of their underlying neural mechanisms remains elusive. Therefore, we explored the influence of induced emotional states on ideational originality and its associated neural dynamics. Participants were randomly presented with three short videos with sad, neutral, and happy content. After each video, ideational originality was evaluated using the alternate uses task (AUT). Ideational originality was significantly higher after induction of the happy state than the neutral state; in contrast, there was a nonsignificant difference between the sad and neutral states. Associated neural dynamics were assessed through EEG time-frequency (TF) power and phase-amplitude coupling (PAC) analysis. Our findings suggest that emotional states elicit distinct TF and PAC profiles associated with ideational originality. Relative to baseline, gamma activity was enhanced after the neutral induction and more enhanced after the induction of a happy state, but reduced after the induction of a sad state in 2-4 seconds after starting the task. Our PAC findings suggest that the attention system may be silent after the induction of a happy emotional state to load rich materials into working memory (WM) and active in the sad state to maintain these materials in WM.

Circadian Rhythms in Murine Ocular Tissues including Sclera are affected by Neurobasal A Medium Preincubation, Mouse Strain, but not Sex
Purpose: Our understanding of ocular clocks has been profoundly advanced by the development of real-time recording of bioluminescence of PER2::LUC knock-in mouse explants. However, the effect of sex, mouse strain and culturing conditions on ocular clocks remains unknown. Here, we studied the role these variables play on PER2::LUC bioluminescence rhythms of ocular tissues: retinas, corneas and posterior eye cups (PEC). We also tested the hypothesis that the sclera contains a circadian oscillator by using scraped PEC as a proxy. Methods: Retinas, corneas, intact and scraped PECs were obtained from male and female PER2::LUC knock-in mice maintained on either a pigmented C57BL/6J or albino RjOrl:SWISS background. PER2::LUC bioluminescence rhythms in ocular tissues were measured using a Lumicycle. Results: We compared PER2::LUC bioluminescence rhythms between ocular tissues and found that all ocular tissues oscillated, including the scraped PEC, which was previously not known to oscillate. The rhythms in scraped PECs had lower amplitudes, longer periods and distinct acrophases compared to other ocular tissues. Ocular tissues of RjOrl:SWISS mice oscillated with higher amplitudes compared to the ones of C57BL/6J, with corneal rhythms being most affected by mouse strain. A 24h preincubation with Neurobasal A medium enhanced rhythms of ocular tissues, whereas sex differences were not detected for these rhythms. Conclusions: We discovered a novel oscillator in the sclera. PER2::LUC bioluminescence rhythms in murine ocular tissues are enhanced by Neurobasal A medium preincubation, mouse strain but not sex.

Vividness of Visual Imagery Supported by Intrinsic Structural-Functional Brain Network Dynamics
Vividness of visual imagery is subject to individual variability, a phenomenon with largely unexplored neurobiological underpinnings. By analyzing data from 273 participants we explored the link between the structural-functional organization of brain connectomes and the reported intensity of visual imagery (measured with VVIQ-2). Employing graph theory analyses we investigated both the structural (DTI) and functional (rs-fMRI) connectomes within a network of regions often implicated in visual imagery. Our results indicate a relationship between increased local efficiency and clustering coefficients in the structural connectome in individuals who experience more vivid visual imagery. Increased local efficiency and clustering coefficients were mirrored in the functional connectome with increases in left inferior temporal regions, a region frequently identified as a critical hub in the visual imagery literature. Furthermore, individuals with more vivid imagery were found to have lower levels of global efficiency in their functional connectome. We propose that the clarity and intensity of visual imagery are optimized by a network organization characterized by heightened localized information transfer and interconnectedness. Conversely, an excessively globally integrated network might dilute the specific neural activity crucial for generating vivid visual images, leading to less locally concentrated resource allocation in key regions involved in visual imagery vividness.

Manifold Learning Uncovers Nonlinear Interactions between the Adolescent Brain and the Social Environment in Predicting Mental Health Problems
Advanced statistical methods that capture the complex interplay between adolescents and their social environments are essential for improving our understanding of how differences in brain function contribute to mental health problems. To move the study of adolescent mental health beyond what we have achieved so far- a complex account of brain and environmental risk factors without understanding the neurobiological embedding of the social environment- we need to find ways of studying the complex, nonlinear relationships between brain function and adolescents' experiences in the real-world. Manifold learning techniques can discover and highlight latent structure from high-dimensional, complex biomedical data, such as fMRI. Here, we develop a novel manifold learning technique, exogenous PHATE (EPHATE), to capture the interplay between brain function and adolescents' social environments. By applying EPHATE, we demonstrate that harmonizing cutting-edge computational methods with longstanding developmental theory can advance efforts to detect and predict mental health problems during the transition to adolescence.

The Magic Impacts of Sounds on Consumer's Brain: How Do Natural Sounds Nudge Green Product Purchase?
Despite extensive research on nudging techniques aimed at promoting green consumption, the influence of natural sounds on encouraging environmentally friendly behavior remains relatively understudied. It is valuable to examine how sounds matter in green marketing, as more and more firms are using background sounds in video advertisements. Drawing on the Stimulus-Organism-Response model, we propose that natural sound increase early attentional congruency associated with green products, thereby promoting customers' purchase of green products. To test on our theory, we conducted an experiment using an event-related potentials (ERP) method and employed a hierarchical drift-diffusion model (HDDM). The results show that compared with unnatural sounds, natural sounds not only increased the purchase rates for green products but also enhanced decision-making efficiency (drift rate) in favor of purchasing green products. Additionally, consumers also exhibited a reduced frontal early P2 wave (150-230ms) in response to green products under natural sounds, indicating that natural sounds increased the early attentional congruency associated with green products. More importantly, the early attentional congruency provides an explanation for how natural sounds nudge the efficiency of purchasing decisions for green products. This study thus contributes to the discovery of a new psychological path that helps deepen our understanding of how natural sounds can nudge green consumption. It also provides actionable implications for green consumption market managers.

Intermittent stimulation of the basal forebrain improves working memory in aged nonhuman primates.
Aging and some dementias feature parallel declines in the basal forebrain and cognitive capacity. Here, we tested the potential of one-hour daily intermittent basal forebrain stimulation to restore cognitive performance in aged male and female monkeys. Stimulation improved working memory in weeks, with performance remaining above study entry through the 15 month duration of the intervention. Effects persisted for at least 12 weeks after stimulation ceased. Parallel studies with a cholinesterase inhibitor did not produce lasting improvements in behavior. Brain stimulation led to immediate increases in tissue plasminogen activator levels in cerebrospinal fluid, and long-term increases in PET measures of glucose utilization. Intermittent basal forebrain stimulation thus triggers key components of neurotrophic signaling and leads to improved brain metabolism and better performance in working memory in senescent monkeys.

Functional Mapping of Movement and Speech Using Task-Based Electrophysiological Changes in Stereoelectroencephalography
Introduction: Stereoelectroencephalography (sEEG) has become the predominant method for intracranial seizure localization. When imaging, semiology, and scalp EEG are not in full agreement or definitively localizing, implanted sEEG recordings are used to test candidate seizure onset zones (SOZs). Discovered SOZs may then be targeted for resection, laser ablation, or neurostimulation. If a SOZ is eloquent, resection and ablation are both contraindicated, so identifying functional representation is crucial for therapeutic decision making. Objective: We present a novel functional brain mapping technique that utilizes task-based electrophysiological changes in sEEG during behavioral tasks and test this in pediatric and adult patients. Methods: sEEG was recorded in twenty patients with epilepsy, aged 6-39 (12 female, 18 of 20 patients < 21 years old), who underwent implanted monitoring to identify seizure onset. Each performed 1) visually cued simple repetitive movements of the hand, foot, or tongue while electromyography was recorded, and 2) simple picture naming or verb generation speech tasks while audio was recorded. Broadband changes in the power spectrum of the sEEG were compared between behavior and rest. Results: Electrophysiological functional mapping of movement and/or speech areas was completed in all 20 patients. Eloquent representation was identified in both cortex and white matter, and generally corresponded to classically described functional anatomic organization as well as other clinical mapping results. Robust maps of brain activity were identified in healthy brain, regions of developmental or acquired structural abnormality, and SOZs. Conclusion: Task based electrophysiological mapping using broadband changes in the sEEG signal reliably identifies movement and speech representation in pediatric and adult epilepsy patients.

The structure of an Amyloid Precursor Protein/talin complex indicates a mechanical basis of Alzheimer's Disease.
Misprocessing of Amyloid Precursor Protein (APP) is one of the major causes of Alzheimer's disease. APP is a transmembrane protein comprising a large extracellular region, a single transmembrane helix and a short cytoplasmic tail containing an NPxY motif (normally referred to as the YENPTY motif). Talin is a synaptic scaffold protein that connects the cytoskeletal machinery to the plasma membrane via binding to one of two highly conserved NPxY motifs in the cytoplasmic tail of integrin transmembrane receptors. Here we report the crystal structure of an APP/talin complex identifying a new way to couple the cytoskeletal machinery to synaptic sites via APP. Structural modelling reveals that APP forms an extracellular meshwork that mechanically couples the cytoskeletal meshworks of both the pre-, and post-synaptic compartments. In this context, we propose APP processing as a mechanical signalling pathway with similarities to Notch signalling, whereby the cleavage sites in APP represent mechanical sensors, with varying accessibility to cleavage by secretases. During synaptogenesis in healthy neurons, the APP/talin linkage would provide an exquisite mechanical coupling between synapses, with tightly controlled APP processing providing instructions to maintain this synchrony. Furthermore, APP directly coupling to the binary switches in talin indicates a role for APP in mechanical memory storage as postulated by the MeshCODE theory. The implication that APP is a regulator of mechanical signalling leads to a new hypothesis for Alzheimer's disease, where mis-regulation of APP dynamics results in loss of mechanical integrity of the synapse, corruption and loss of mechanical binary data, and excessive generation of the toxic plaque-forming A{beta}42 peptide. In support of this model, we show that talin1 depletion has a dramatic effect on APP processing in cells. Much needs to be done to experimentally validate this idea, but we present here a novel theory of Alzheimer's Disease with a role for APP in the mechanically coded binary information storage in the synapse, which identifies a potential novel therapeutic strategy for treating Alzheimer's Disease.

Focal cortical dysplasia type II-dependent maladaptive myelination in the human frontal lobe
Focal cortical dysplasias (FCDs) are local malformations of the human neocortex and a leading cause of intractable epilepsy. FCDs are classified into different subtypes including FCD IIa and IIb, characterized by a blurred gray-white matter boundary or a transmantle sign indicating abnormal white matter myelination. Recently, we have shown that myelination is also compromised in the gray matter of FCD IIa of the temporal lobe. Since myelination is key for brain function, we investigated whether deficient myelination is a feature affecting also other FCD subtypes and brain areas. Here, we focused on the gray matter of FCD IIa and IIb from the frontal lobe. We applied in situ hybridization, immunohistochemistry and electron microscopy to quantify oligodendrocytes, to visualize the myelination pattern and to determine ultrastructurally the axon diameter and the myelin sheath thickness. In addition, we analyzed the transcriptional regulation of myelin-associated transcripts by real-time RT-qPCR and chromatin immunoprecipitation (ChIP). We show that densities of myelinating oligodendrocytes and the extension of myelinated fibers up to layer II were unaltered in both FCD types but myelinated fibers appeared fractured mainly in FCD IIa. Interestingly, both FCD types presented with larger axon diameters when compared to controls. A significant correlation of axon diameter and myelin sheath thickness was found for FCD IIb and controls, whereas in FCD IIa large caliber axons were less myelinated. This was mirrored by a down-regulation of myelin-associated mRNAs and by reduced binding-capacities of the transcription factor MYRF to promoters of myelin-associated genes. FCD IIb, however, had significantly elevated transcript levels and MYRF-binding capacities reflecting the need for more myelin due to increased axon diameters. These data show that FCD IIa and IIb are characterized by divergent signs of maladaptive myelination which may contribute to the epileptic phenotype and underline the view of separate disease entities.

Automated identification and quantification of stereotypical movements from video recordings of children with ASD
Importance: Stereotypical motor movements (SMMs) are a form of restricted and repetitive behavior (RRB), which is a core symptom of Autism Spectrum Disorder (ASD). Current quantification of SMM severity is extremely limited, with studies relying on coarse and subjective caregiver reports or laborious manual annotation of short video recordings. Objective: To demonstrate the utility of a new open-source AI algorithm that can analyze extensive video recordings of children and automatically identify segments with heterogeneous SMMs, thereby enabling their direct and objective quantification. Design, setting, and participants: This retrospective cohort study analyzed video recordings from 319 behavioral assessments of 241 children with ASD, 1.4 to 8 years old, who participated in research at the Azrieli National Centre for Autism and Neurodevelopment Research in Israel. Behavioral assessments included cognitive, language, and autism diagnostic observation schedule, 2nd edition (ADOS-2) assessments. Exposures: Each assessment was recorded with 2-4 cameras, yielding 580 hours of video footage. We manually annotated 7,352 video segments containing heterogeneous SMMs performed by different children (21.14 hours of video). Main outcomes and measures: We used a pose-estimation algorithm (OpenPose) to extract skeletal representations of all individuals in each video frame and trained an object-detection algorithm (YOLOv5) to identify and track the child in each movie. We then used the skeletal representation of the child to train an SMM recognition algorithm using a PoseConv3D model. We used data from 220 children for training and data from the remaining 21 children for testing. Results: The algorithm accurately detected 92.53% of manually annotated SMMs in our test data with 66.82% precision. Overall number and duration of algorithm identified SMMs per child were highly correlated with manually annotated number and duration of SMMs (r=0.8 and r=0.88, p<0.001 respectively). Conclusion and relevance: These findings demonstrate the ability of the algorithm to capture a highly diverse range of SMMs and quantify them with high accuracy, enabling objective and direct estimation of SMM severity in individual children with ASD. We openly share the "ASDPose" dataset and "ASDMotion" algorithm for further use by the research community.

Olfactory bulb stimulation mitigates Alzheimer-like disease progression
Background: Deep brain stimulation (DBS) has demonstrated potential in mitigating Alzheimer's disease (AD). However, the invasive nature of DBS presents challenges for its application. The olfactory bulb (OB), showing early AD-related changes and extensive connections with memory regions, offers an attractive entry point for intervention, potentially restoring normal activity in deteriorating memory circuits. Aims: Our study examined the impact of electrically stimulating the OB on working memory as well as pathological and electrophysiological alterations in the OB, medial prefrontal cortex, hippocampus, and entorhinal cortex in amyloid beta (A{beta}) AD model rats. Methods: Male Wistar rats underwent surgery for electrode implantation in brain regions, inducing Alzheimer's-like disease. Bilateral olfactory bulb (OB) electrical stimulation was performed for 1 hour daily to the OB of stimulation group animals for 18 consecutive days, followed by evaluations of histological, behavioral, and local field potential signal processing. Results: OB stimulation counteracted A{beta} plaque accumulation and prevented AD-induced working memory impairments. Furthermore, it prompted an increase in power across diverse frequency bands and enhanced functional connectivity, particularly in the gamma band, within the investigated regions during a working memory task. Conclusion: This preclinical investigation highlights the potential of olfactory pathway-based brain stimulation to modulate the activity of deep-seated memory networks for AD treatment. Importantly, the accessibility of this pathway via the nasal cavity lays the groundwork for the development of minimally invasive approaches targeting the olfactory pathway for brain modulation.

Adult Neurogenesis Reconciles Flexibility and Stability of Olfactory Perceptual Memory
The abilities to learn and store memories are inherently at odds with each other: the brain must be flexible enough to quickly store new information, but stable enough to avoid overwriting old memories. We show that adult neurogenesis can overcome this flexibility-stability dilemma. We develop a computational model for adult neurogenesis and structural spine dynamics in the olfactory bulb that captures many experimental observations and show that the transient properties of adult-born neurons confer multiple contributions to addressing this problem. First, the enhanced plasticity of young neurons allows them to flexibly encode new memories; as the neurons age, these memories stabilize, while remaining in the same neural ensemble. Second, the young new neurons' enhanced excitability and susceptibility to apoptosis maintain the flexibility of the memory. Finally, the period of sensory-dependent dendritic elaboration establishes an additional substrate of memory that facilitates rapid relearning. The model makes experimentally testable predictions and identifies a new functional role of adult neurogenesis in olfaction: memory consolidation.

Temporal interference electrical neurostimulation yields fMRI BOLD activation in humans
Temporal interference electrical neurostimulation (TI) is a relatively new method of non-invasive neurostimulation that may be able to stimulate deep brain regions without stimulating the overlying superficial regions. Despite studies in rodents, almost no studies have investigated its effects on human brain activity along with safety and tolerability profiles. We performed simultaneous TI stimulation and fMRI to investigate the effects of TI on human BOLD signals. Here we show that TI can induce increased BOLD activation in humans, with good safety and tolerability profiles. We also show the limits of spatial precision and explore the nature and causes of additional off target effects. TI may be a promising approach for addressing questions about the causal role of deep brain structures in human cognition and may also afford new clinical treatments.

A worldwide ENIGMA study on epilepsy-related gray and white matter compromise across the adult lifespan
Objectives: Temporal lobe epilepsy (TLE) is commonly associated with mesiotemporal pathology and widespread alterations of grey and white matter structures. Evidence supports a progressive condition although the temporal evolution of TLE is poorly defined. This ENIGMA-Epilepsy study utilized multimodal magnetic resonance imaging (MRI) data to investigate structural alterations in TLE patients across the adult lifespan. We charted both grey and white matter changes and explored the covariance of age-related alterations in both compartments. Methods: We studied 769 TLE patients and 885 healthy controls across an age range of 17-73 years, from multiple international sites. To assess potentially non-linear lifespan changes in TLE, we harmonized data and combined median split assessments with cross-sectional sliding window analyses of grey and white matter age-related changes. Covariance analyses examined the coupling of grey and white matter lifespan curves. Results: In TLE, age was associated with a robust grey matter thickness/volume decline across a broad cortico-subcortical territory, extending beyond the mesiotemporal disease epicentre. White matter changes were also widespread across multiple tracts with peak effects in temporo-limbic fibers. While changes spanned the adult time window, changes accelerated in cortical thickness, subcortical volume, and fractional anisotropy (all decreased), and mean diffusivity (increased) after age 55 years. Covariance analyses revealed strong limbic associations between white matter tracts and subcortical structures with cortical regions. Conclusions: This study highlights the profound impact of TLE on lifespan changes in grey and white matter structures, with an acceleration of aging-related processes in later decades of life. Our findings motivate future longitudinal studies across the lifespan and emphasize the importance of prompt diagnosis as well as intervention in patients.

Spatial attention alters visual cortical representation during target anticipation
Attention enables us to efficiently and flexibly interact with the environment by prioritizing some image features, such as location or orientation, even before stimulus onset. We investigated how covert spatial attention affects responses in human visual cortex prior to target onset and how it affects behavioral performance after target onset, using a concurrent psychophysics-fMRI experiment. Performance improved at cued locations and worsened at uncued locations, relative to distributed attention. BOLD responses in cortical visual field maps changed in two ways: First, there was a stimulus- independent baseline shift, positive in map locations near the cued location and negative elsewhere. Second, population receptive field centers shifted toward the attended location. Both effects increased in higher visual areas. Together, the results show that spatial attention has large effects on visual cortex prior to target appearance, altering neural response properties across the entirety of multiple visual field maps.

Unethical amnesia brain: Memory and metacognitive distortion induced by dishonesty
Unethical actions and decisions may distort human memory in two aspects: memory accuracy and metacognition. However, the neural and computational mechanisms underlying the metacognition distortion caused by repeated dishonesty remain largely unknown. Here, we performed two fMRI studies, including one replication study, with an information-sending task in the scanner. The main moral decision task in the scanner involves consistency and reward as two main factors, combined with a pre-scan and post-scan memory test together with mouse tracking. With multiple dimensions of metrics to measure metacognition, we test whether the inter-subject metacognition change correlates with how participants trade off consistency and reward. We find that the compression of representational geometry of reward in the orbitofrontal cortex (OFC) is correlated with both immediate and delayed metacognition changes. Also, the functional connectivity between the dorsolateral prefrontal cortex (DLPFC) and the left temporoparietal junction (lTPJ) under dishonest responses can predict both immediate and delayed metacognition changes in memory. These results suggest that decision-making, emotion, and memory-related brain regions together play a key role in metacognition change after immoral action, shedding light on the neural mechanism of the complex interplay between moral decisions, cognitive processes, and memory distortion.

Causal Brain Network Evaluates Surgical Outcomes in Patients with Drug-Resistant Epilepsy: A Retrospective Comparative Study
Network neuroscience has greatly facilitated epilepsy studies; meanwhile, drug-resistant epilepsy (DRE)is increasingly recognized as a brain network disorder. Unfortunately, surgical success rates in patients with DRE are still very limited, varying 30% ~70%. At present, there is almost no systematic exploration of intracranial electrophysiological brain network closely related to surgical outcomes, and it is not clear which brain network methodologies can effectively promote DRE precision medicine. In this retrospective comparative study, we included multicenter datasets, containing electrocorticogram (ECoG) data from 17 DRE patients with 55 seizures. Ictal ECoG within clinically-annotated epileptogenic zone (EZ) and non epileptogenic zone (NEZ) were separately computed using six different algorithms to construct causal brain networks. All the brain network results were divided into two groups, successful and failed surgery. Statistical results based on the Mann-Whitney-Utest show that: causal connectivity of frequency band (8 ~ 13 Hz) in EZ calculated by convergent cross mapping (CCM) gains the most significant differences between the surgical success and failure groups, with a P value of 7.85e-08 and Cohen's d effect size of 0.77. CCM-defined EZ brain network can also distinguish the successful and failed surgeries considering clinical covariates (clinical centers, DRE types) with p<0.001. Based on the brain network features, machine learning models are established to predict the surgical outcomes. Among them, SVM classifier with Gaussian kernel function and Bayesian Optimization demonstrates the highest average accuracy of 84.48% through 5-fold cross validation, further indicating that the CCM-defined EZ brain network is a reliable biomarker for predicting DRE's surgical outcomes.

Individualized fMRI neuromodulation enhances visuospatial perception: a guided approach targeted towards the neuro-rehabilitation of cortical blindness and deceleration of subjective cognitive impairment.
Neuromodulation is a growing precision-medicine approach to modulating neural activity that can be used to treat neuropsychiatric, and general pathophysiologic conditions. We developed individualized fMRI neuromodulation (iNM) to study the mechanisms of visuospatial perception modulation with the long-term goal of applying it in low-vision patient populations having cortical blindness or visuospatial impairment preceding subjective cognitive impairment. To determine these mechanisms, we developed a direction and coherence discrimination task to engage visual perception (VP), visual imagery (VI), selective extero- intero-ceptive attention (SEIA), and motor planning (MP) networks. Participants discriminated up and down direction, at full and subthreshold coherence under iNM or control (no iNM). We determined the blood-oxygen-level-dependent (BOLD) magnitude as area under the curve (AUC) for VI, SEIA, and MP encoded networks and used a decoder to predict the stimulus from brain maps. The increased AUC BOLD magnitude under iNM across directions and coherences ranged from: 48-76% for SEIA, 26-59% for MP, 20-47% for VI, and 100% for strong VP coherences, but decreased for weak coherences. iNM increased classification performance. Our results imply a causal role of iNM-induced visuospatial mechanisms in strengthening these networks and provide a pathway for more accurate encoding models and effective treatment.

Opioid receptor expressing neurons of the central amygdala gate behavioral effects of ketamine in mice
Ketamine has anesthetic, analgesic, and antidepressant properties which may involve multiple neuromodulatory systems. In humans, the opioid receptor (OR) antagonist naltrexone blocks the antidepressant effect of ketamine. It is unclear whether naltrexone blocks a direct effect of ketamine at ORs, or whether normal functioning of the OR system is required to realize the full antidepressant effects of treatment. In mice, the effect of ketamine on locomotion, but not analgesia or the forced swim test, was sensitive to naltrexone and was therefore used as a behavioral readout to localize the effect of naltrexone in the brain. We performed whole-brain imaging of cFos expression in ketamine-treated mice, pretreated with naltrexone or vehicle, and identified the central amygdala (CeA) as the area with greatest difference in cFos intensity. CeA neurons expressing both OR (MOR) and PKC{delta} were strongly activated by naltrexone but not ketamine, and selectively interrupting MOR function in the CeA either pharmacologically or genetically blocked the locomotor effects of ketamine. These data suggest that MORs expressed in CeA neurons gate behavioral effects of ketamine but are not direct targets of ketamine.

Whole-brain neural substrates of behavioral variability in the larval zebrafish
Animals engaged in naturalistic behavior can exhibit a large degree of behavioral variability even under sensory invariant conditions. Such behavioral variability can include not only variations of the same behavior, but also variability across qualitatively different behaviors driven by divergent cognitive states, such as fight-or-flight decisions. However, the neural circuit mechanisms that generate such divergent behaviors across trials are not well understood. To investigate this question, here we studied the visual-evoked responses of larval zebrafish to moving objects of various sizes, which we found exhibited highly variable and divergent responses across repetitions of the same stimulus. Given that the neuronal circuits underlying such behaviors span sensory, motor, and other brain areas, we built a novel Fourier light field microscope which enables high-resolution, whole-brain imaging of larval zebrafish during behavior. This enabled us to screen for neural loci which exhibited activity patterns correlated with behavioral variability. We found that despite the highly variable activity of single neurons, visual stimuli were robustly encoded at the population level, and the visual-encoding dimensions of neural activity did not explain behavioral variability. This robustness despite apparent single neuron variability was due to the multi-dimensional geometry of the neuronal population dynamics: almost all neural dimensions that were variable across individual trials, i.e. the "noise" modes, were orthogonal to those encoding for sensory information. Investigating this neuronal variability further, we identified two sparsely-distributed, brain-wide neuronal populations whose pre-motor activity predicted whether the larva would respond to a stimulus and, if so, which direction it would turn on a single-trial level. These populations predicted single-trial behavior seconds before stimulus onset, indicating they encoded time-varying internal modulating behavior, perhaps organizing behavior over longer timescales or enabling flexible behavior routines dependent on the animals internal state. Our results provide the first whole-brain confirmation that sensory, motor, and internal variables are encoded in a highly mixed fashion throughout the brain and demonstrate that de-mixing each of these components at the neuronal population level is critical to understanding the mechanisms underlying the brains remarkable flexibility and robustness.

Maternal cannabis use alters excitatory inputs to corticostriatal efferent neurons in rat offspring
With the recent surge in cannabis legalization across North America, there is legitimate concern that rates of cannabis use during pregnancy will dramatically increase in the coming years. However, the long-term impacts of prenatal cannabis exposure (PCE) on the brain and behavior remain poorly understood. Using a model of passive cannabis vapor exposure, we have previously shown that PCE impairs behavioral flexibility in an attentional set-shifting task in adult offspring, which is orchestrated in part by excitatory inputs from the medial prefrontal cortex (mPFC) to the nucleus accumbens (NAc). Given the fundamental role of these corticostriatal inputs in coordinating flexible reward-seeking strategies, we used a combination of retrograde tracing and ex vivo electrophysiology to test the hypothesis that maternal cannabis use alters the synaptic and intrinsic membrane properties of corticostriatal efferent neurons in exposed male and female rat offspring. Specifically, pregnant rat dams were trained to self-administer vaporized cannabis (69.7% THC; 150 mg/ml) twice daily throughout mating and gestation and offspring were subsequently injected with fluorescent retrobeads into the NAc core prior to conducting whole-cell ex vivo recordings of spontaneous excitatory and inhibitory post-synaptic currents (EPSC and IPSC, respectively) in retrolabeled mPFC neurons in adulthood. Our results indicate that PCE increases the frequency of spontaneous glutamatergic events (EPSCs) in NAc-projecting mPFC neurons in a sex-specific manner, which drives changes in excitatory to inhibitory (EPSC/IPSC) ratio, particularly in females. Furthermore, the amplitude of phasic glutamatergic events was reduced in cannabis-exposed offspring of both sexes, suggesting changes in postsynaptic receptor function. Altogether, these data demonstrate that PCE shifts the balance of excitatory/inhibitory inputs onto NAc-projecting mPFC neurons with limited effects on membrane conductance in females, resulting in reduced sex differences following maternal cannabis self-administration. These results provide putative neurophysiological mechanisms mediating previously observed behavioral changes, and future studies will need to test if these cannabis-induced changes are causal to long-term deficits in behavioral flexibility that have been previously documented in exposed offspring.

Deep Learning Models for Atypical Serotoninergic Cells Recognition
Background: The serotonergic system modulates brain processes via functionally distinct subpopulations of neurons with heterogeneous properties, including their electrophysiological activity. In extracellular recordings, serotonergic neurons to be investigated for their functional properties are commonly identified on the basis of "typical" features of their activity, i.e. slow regular firing and relatively long duration of spikes. Thus, due to the lack of equally robust criteria for discriminating serotonergic neurons with "atypical" features from non-serotonergic cells, the physiological relevance of the diversity of serotonergic neuron activities results largely understudied. New Methods: We propose deep learning models capable of discriminating typical and atypical serotonergic neurons from non-serotonergic cells with high accuracy. The research utilized electrophysiological in vitro recordings from serotonergic neurons identified by the expression of fluorescent proteins specific to the serotonergic system and non-serotonergic cells. These recordings formed the basis of the training, validation, and testing data for the deep learning models. The study employed convolutional neural networks (CNNs), known for their efficiency in pattern recognition, to classify neurons based on the specific characteristics of their action potentials. Results: The models were trained on a dataset comprising 43,327 original spike samples, alongside an extensive set of 6.7 million synthetic spike samples, designed to mitigate the risk of overfitting the background noise in the recordings, a potential source of bias. Results show that the models achieved high accuracy and were further validated on "non-homogeneous" data, i.e., data not used for constructing the model, to confirm their robustness and reliability in real-world experimental conditions. Comparison with existing methods: Conventional methods for identifying serotonergic neurons allow recognition of serotonergic neurons defined as typical. Our model based on the analysis of the sole spike reliably recognizes over 92 features of spike and activity. Conclusions: The model is ready for use in experiments conducted with the here described recording parameters. We release the codes and procedures allowing to adapt the model to different acquisition parameters or for identification of other classes of spontaneously active neurons.

PCSK9 deficiency promotes the development of peripheral neuropathy
PCSK9 is a serine protease primarily produced and secreted by the liver. Its best-known and studied function is to induce the hepatic degradation of the low-density lipoprotein (LDL) receptor (LDLR), thereby increasing the concentration of LDL-cholesterol (LDL-C) in the blood. Beyond its effects on LDL-C metabolism, recent studies have reported pleiotropic biological roles for PCSK9 notably in septic shock, vascular inflammation, viral infection, and cancer. While the function and the structural integrity of peripheral nerves are critically influenced by circulating lipids and cholesterol levels, the impact of PCSK9 in the peripheral nervous system is still unexplored. In this study, we investigated the consequences of PCSK9 deficiency on the physiology of peripheral nerves. We found that PCSK9 deletion in mice leads to peripheral neuropathy characterized by a reduction of mechanical pain sensations. PCSK9 deficient mice also presented skin structural changes with a reduction of number of terminal nociceptive Schwann cells, Remak fiber axonal swelling, as well as hypomyelination of small nerve fibers. Interestingly, peripheral nerves of PCSK9 deficient mice presented an upregulation of the fatty acid transporter CD36 expression which correlated with an increase in nerve lipid contents and structural mitochondrial abnormalities. Our findings demonstrate that PCSK9 plays a critical role in the peripheral nerves by regulating lipid homeostasis, and through its impact on CD36, PCSK9 deficiency could lead to the development of symptoms related to peripheral neuropathy.

Closed-loop auditory stimulation targeting alpha and theta oscillations during REM sleep induces phase-dependent power and frequency changes
Background: Alpha and theta oscillations characterize the waking human electroencephalogram (EEG) and can be modulated by closed-loop auditory stimulation (CLAS). These oscillations also occur during rapid eye movement (REM) sleep, but whether they can be modulated by CLAS is not known. Objective: Investigate whether CLAS can modulate alpha and theta oscillations during REM sleep in a targeted phase-dependent manner. Methods: We recorded high-density EEG during an extended overnight sleep period in 18 healthy young adults. Auditory stimulation was delivered during both phasic and tonic REM sleep in alternating 6 s ON and 6 s OFF windows. During the ON windows, stimuli were phase-locked to four orthogonal phases of ongoing alpha or theta oscillations detected in a frontal electrode (Fz). Results: During ON windows, the four orthogonal phases of ongoing alpha and theta oscillations were targeted with high accuracy. Alpha and theta CLAS induced phase-dependent changes in power and frequency at the target location. Frequency-specific effects were observed for alpha trough (speeding up) and rising (slowing down) and theta trough (speeding up) conditions. These phase-dependent changes of CLAS were observed during both REM sleep substages, even though the amplitude evoked by auditory stimuli which were not phase-locked was very much reduced in phasic compared to tonic REM sleep. Conclusions: This study provides evidence that faster REM sleep rhythms can be modulated by CLAS in a phase-dependent manner. This offers a new approach to investigate how modulation of REM sleep oscillations affects the contribution of this vigilance state to brain function.

A transient brain endothelial translatome response to endotoxin is associated with mild cognitive changes post-shock in young mice
Sepsis-associated encephalopathy (SAE) is a common manifestation in septic patients that is associated with increased risk of long-term cognitive impairment. SAE is driven, at least in part, by brain endothelial dysfunction in response to systemic cytokine signaling. However, the mechanisms driving SAE and its consequences remain largely unknown. Here, we performed translating ribosome affinity purification (TRAP) and RNA-sequencing (TRAP-seq) from the brain endothelium to determine the transcriptional changes after an acute endotoxemic (LPS) challenge. We found that LPS induces a strong acute transcriptional response in the brain endothelium that partially correlates with the whole brain transcriptional response and suggested an endothelial-specific hypoxia response. Consistent with a critical role for the IL-6 pathway, loss of the main regulator of this pathway, SOCS3, leads to a broadening of the population of genes responsive to LPS, suggesting that an overactivation of the IL-6/JAK/STAT3 pathway leads to an increased transcriptional response that could explain our prior findings of severe brain injury in these mice. To identify any potential sequelae of this acute response, we performed brain TRAP-seq following a battery of behavioral tests in mice after apparent recovery. We found that the transcriptional response returns to baseline within days post-challenge. Despite the transient nature of the response, we observed that mice that recovered from the endotoxemic shock showed mild, sex-dependent cognitive impairment, suggesting that the acute brain injury led to sustained, non-transcriptional effects. A better understanding of the transcriptional and non-transcriptional changes in response to shock is needed in order to prevent and/or revert the devastating consequences of septic shock.

Combining function and structure in a single macro-scale connectivity model of the human brain
Combining the macro-scale functional and structural connectivity matrices of the human brain could provide useful information on how various diseases and conditions affect the brain. However, it is not a simple task to combine such information as they are derived usually in very different ways with functional information typically gathered using fMRI, EEG, or MEG whereas structural information relies on robust diffusion-weighted MRI tractography methods. This work proposes a solution to this problem using an analogy to an electric circuit with the functional information being the voltage sources and the structural information resistance of the elements in the circuit. The voltage sources and resistances can be used to solve the current in the circuit using Modified Nodal Analysis, for example. In the proposed analogy, the solved electric current represents how the functional information flows in the structural brain network. This work demonstrates a connection-specific example of such analysis as well as whole-brain analysis using data from the Human Connectome Project. How this is achieved is explained in the method sections which has a complimentary Python function that can readily be applied to any project that has both functional and structural connectivity data. The main motivation for the proposed analysis method is that it could provide new information on various conditions and diseases such as Alzheimer's or multiple sclerosis that affect the human brain. In a sense, the proposed approach is a macro-scale version of the classical Hodkin-Huxley model.