bioRxiv Subject Collection: Neuroscience's Journal

CHD2 Dosage Ties Autolysosomal Pathway to Cortical Maturation in Disease and Evolution
The relatively slow pace of cortical development in humans has long been a topic of investigation. Studies seeking to understand the underlying mechanisms have mostly focused on neurogenetic comparisons with extant species. Here we ask if developmental tempo differences may have also existed between us and our extinct relatives for whom genomes are available. To do so, we nominate a sapiens-specific derived allele, virtually fixed in contemporary populations, which resides in an enhancer region active during early cortical development. The single nucleotide variant is predicted to significantly affect CHD2 expression, a chromatin remodeler known to play an important role in neural development and for which haploinsufficiency is associated with epilepsy and autism. We leverage patient induced pluripotent stem lines (iPSC) and engineered iPSCs in which we reintroduced the ancestral allele and generated heterozygous loss-of-function mutations. We reveal that CHD2 deficiency impairs lysosomal acidification and autophagosome flux. In contrast, ancestralized lines, which we find express higher levels of CHD2, exhibit enhanced lysosomal function and consequently accelerated autophagosome flux, consistent with our observations in chimpanzee and bonobo lines. This set of findings demonstrates that CHD2 dosage critically regulates the autolysosomal pathway. Through deep phenotyping of cortical organoid and neuron cultures, we show that the CHD2-modulated autolysosomal pathway impacts the timing of developmental programs, acquisition of neuronal functional properties and circuit maturation. Finally, we validate an estrogen-dependent rewiring of CHD2 regulation in the evolution of our lineage, providing a mechanistic understanding of how a single nucleotide variant in a regulatory region contributed to the modern pace of neuronal development and maturation. Together, our findings establish CHD2 as a regulator in setting neurodevelopmental tempo via the autolysosomal pathway.

Chronic social instability stress differentially affects the behavior and the transcriptome of the anterodorsal bed nucleus of the stria terminalis between male and female mice
Abstract Stress can be broken down into systemic and processive stressors with processive stressors requiring higher limbic processing. These are also often called social stressors as they require an understanding of social dynamics as opposed to physical based stressors. This differing of processing necessitates we study both phenomena. Additionally, sex is an important aspect of stress research as men and women show differing responses to stress and mood disorder development. To study this, we used a chronic social instability stress (CSIS) paradigm to stress male and female mice. This paradigm is approximately 7-weeks long and involves changing the cage mates of a mouse every 3 days so stable social dynamics cannot form. Afterwards, one cohort was used for avoidance behavior testing using the open field test, the elevated plus maze, the light/dark box emergence test, and the novelty suppressed feeding test. A second cohort was used for bulk RNA-Sequencing of the anterodorsal bed nucleus of the stria terminalis which is a limbic structure known to be related to chronic stress signaling. In the behavior assays, CSIS caused the females to be less avoidant, while the males became more avoidant. Additionally, we found that a low estrogen state in the females caused them to be less avoidant than in a high estrogen state. In the transcriptome, we found major differences between the males and females with the males expressing more genes related to transcription whereas the females expressed more genes related to synaptic transmission. We also found that the transcriptome in the males is more sensitive to the stress than the females. In summary, we have found how social stress is differentially regulated between males and females and how this may be related to the development of stress-related behavioral changes.

Population-level encoding of somatosensation in mouse sensorimotor cortex
Dexterous limb movements rely on somatosensation (touch and proprioception), which provides the sense of the body's posture, movement, and interaction with objects. The heterogeneous responses of single neurons in sensorimotor cortex to somatosensation have led to disparate views of the computational role of this brain area in somatosensory processing. Here, we use population-level analyses of neural activity recorded during active and passive limb movements to assess the structure and summarize the properties of neural encoding in sensorimotor cortex. We used 2-photon imaging to record the activity of thousands of neurons in these brain areas from eight anesthetized mice during passive deflections of each limb. We additionally analyzed neural responses to passive limb movements in eight awake mice, sourced from an open dataset (Alonso et al., 2023), and neural responses to spontaneous limb movements in eight mice, collected during a previous study. To conduct the population-level analyses, we found the principal components of the time-varying neural population activity matrix in each set of experiments. Across all three datasets and behavioral conditions, a small fraction of principal components explained a large fraction of variance in the neural responses. These low-dimensional representations of single and multi-limb movements were well conserved across animals, including orthogonal representations of ipsilateral and contralateral limbs. This organization of somatosensory information mirrors the well-known structure of neural encoding of motor commands. Furthermore, while the activity of individual neurons and small populations best encoded intrinsic variables, larger populations of neurons additionally encode extrinsic variables --- a representational structure that is commonly associated with higher-level brain areas. Together, these analyses demonstrate that population-level encoding of somatosensory information in mouse sensorimotor cortex is structured to facilitate sensorimotor integration across the brain.

Spatial Frequency Maps in Human Visual Cortex: A Replication and Extension
In a step toward developing a model of human primary visual cortex, a recent study developed a model of spatial frequency tuning in V1 (Broderick, Simoncelli, & Winawer, 2022). The model is compact, using just 9 parameters to predict BOLD response amplitude for locations across all of V1 as function of stimulus orientation and spatial frequency. Here we replicated this analysis in a new dataset, the 'nsdsynthetic' supplement to the Natural Scenes Dataset (Allen et al., 2022), in order to assess generalization of model parameters. Furthermore, we extended the analyses to extrastriate maps V2 and V3. For each retinotopic map in each of the 8 NSD subjects, we fit the 9 parameter model. Despite many experimental differences between NSD and the original study, including stimulus size, experimental design, and MR field strength, there was good agreement in most model parameters. The dependence of preferred spatial frequency on eccentricity in V1 was similar between NSD and Broderick et al. Moreover, the effect of absolute stimulus orientation on spatial frequency maps was similar: higher preferred spatial frequency for horizontal and cardinal orientations compared to vertical and oblique orientations in both studies. The extension to extrastriate maps revealed that the biggest change in tuning between maps was in bandwidth: the bandwidth in spatial frequency tuning increased by 70% from V1 to V2 and 100% from V1 to V3, paralleling known increases in receptive field size. Together, the results show robust reproducibility of visual fMRI experiments, and bring us closer to a systematic characterization of spatial encoding in the human visual system.

Working memory shapes neural geometry in human EEG over learning
Working memory has been traditionally studied as a passive storage for information. However, recent advances have suggested that working memory is prospective rather than retrospective, meaning that its content undergoes transformations that will support future behaviour. One perspective that underscores this notion conceptualises memory processes as a computational resource that can be used to reduce the complexity of computation at decision time. Here, we explore this perspective by examining whether the process of maintenance shapes neural geometry and leads to low-dimensional representations during storage and later decision time. We recorded EEG in 25 human participants who learnt to solve a XOR task. We hypothesised that separating task features by a working memory delay would result in participants temporally decomposing the XOR computation, by prospectively processing one of the task features early in trial time. In line with our predictions, participants transformed the first feature from a sensory to an abstract format and maintained this pre-processed information throughout the delay. This process was related to the low-dimensional representation required at decision time early in learning, a representation that has recently been shown to support later cross-generalisation. These results demonstrate that low-dimensional representations, elsewhere associated with slow learning, might also provide a mechanism for maintenance processes in working memory.

Inhibition of the angiotensin-converting enzyme N-terminal catalytic domain prevents endogenous opioid degradation in brain tissue
Angiotensin-converting enzyme (ACE) regulates blood pressure by cleaving angiotensin peptides in the periphery, and can also regulate endogenous opioid signaling by degrading enkephalin peptides in the brain. ACE has two catalytic domains, located in the N-terminal or C-terminal region of the protein, but little is known about the roles that these two catalytic domains play in regulating endogenous opioid degradation in brain tissue. Using acute brain slice preparations from mice of both sexes, we developed methods to study degradation of Met-enkephalin-Arg-Phe (MERF) by ACE, and investigated the role of each ACE catalytic domain in MERF degradation. Using mutant mouse lines with functional inactivation of either the N-terminal domain or the C-terminal domain, we incubated acute brain slices with exogenous MERF at a saturating concentration. The degradation MERF to produce Met-enkephalin was only reduced by N-terminal domain inactivation. Additionally, application of a selective N-terminal domain inhibitor (RXP 407) reduced degradation of both exogenously applied and endogenously released MERF, without affecting degradation of endogenously released Met-enkephalin or Leu-enkephalin. Taken together, our results suggest that the ACE N-terminal domain is the primary site of MERF degradation in brain tissue, and that N-terminal domain inhibition is sufficient to reduce degradation of this specific endogenous opioid peptide. Our results have exciting implications for the development of novel pharmacotherapies that target the endogenous opioid system to treat psychiatric and neurological disorders.

A single dorsal vagal complex circuit mediates the aversive and anorectic responses to GLP1R agonists
GLP-1 receptor agonists (GLP1RAs) effectively reduce feeding to treat obesity, although nausea and other aversive side effects of these drugs can limit their use. Brainstem circuits that promote satiation and that mediate the physiologic control of body weight can be distinguished from those that cause aversion. It remains unclear whether brainstem Glp1r neurons contribute to the normal regulation of energy balance and whether GLP1RAs control appetite via circuits distinct from those that mediate aversive responses, however. Hence, we defined roles for AP and NTS Glp1r-expressing neurons (APGlp1r and NTSGlp1r neurons, respectively) in the physiologic control of body weight, the GLP1RA-dependent suppression of food intake, and the GLP1RA-mediated stimulation of aversive responses. While silencing non-aversive NTSGlp1r neurons interfered with the physiologic restraint of feeding and body weight, restoring NTSGlp1r neuron Glp1r expression on an otherwise Glp1r-null background failed to enable long-term body weight suppression by GLP1RAs. In contrast, selective Glp1r expression in APGlp1r neurons restored both aversive responses and long-term body weight suppression by GLP1RAs. Thus, while non-aversive NTSGlp1r neurons control physiologic feeding, aversive APGlp1r neurons mediate both the anorectic and weight loss effects of GLP1RAs, dictating the functional inseparability of these pharmacologic GLP1RA responses at a circuit level.

Protective mechanisms against Alzheimer's Disease in APOE3-Christchurch homozygous astrocytes
The APOE3-Christchurch (APOE3-Ch) variant has been linked to reduced Alzheimer's Disease (AD) risk, but its protective mechanisms remain unclear. This study explores the neuroprotective phenotype of APOE3-Ch astrocytes, focusing on lipid metabolism and tau processing. APOE3-Ch astrocytes demonstrate enhanced tau oligomer uptake via HSPG- and LRP1-mediated pathways, facilitated by elevated HSPG expression, and achieve superior tau degradation through lysosomal pathways and proteasomal pathways, in contrast to wild-type astrocytes, which primarily use proteasomal mechanisms. Transcriptomic analysis reveals upregulation of genes involved in endocytosis and cell projection assembly, explaining enhanced tau uptake and clearance in APOE3-Ch astrocytes. Lipidomic profiling identifies reduced levels of pathological lipids such as ceramides and gamma-linolenic acid (GLA), potentially mitigating neuroinflammation. These findings provide insight into the protective mechanisms of APOE3-Ch astrocytes and underscore their potential as therapeutic targets for tauopathy and neurodegeneration in AD.

Mapping brain function underlying naturalistic motor observation and imitation using high-density diffuse optical tomography
Background: While autism spectrum disorder (ASD) is defined by deficits in social communication with restricted interests and repetitive behaviors, autistic individuals often show early impairments in motor imitation that persist through childhood and into adulthood. High-density diffuse optical tomography (HD-DOT) overcomes logistical challenges of functional magnetic resonance imaging (fMRI) to provide an open scanning environment conducive to neuroimaging during naturalistic motor imitation. Additionally, the mirror neuron system (MNS) is crucial for understanding and imitating actions, and its dysfunction is hypothesized to underlie key ASD features. Objective: We aim to investigate brain function underlying motor observation and motor imitation in adult autistic and non-autistic individuals (NAI). We hypothesize that HD-DOT will reveal greater MNS activity during motor imitation than motor observation, and that MNS activity will exhibit a negative correlation with autistic traits. Methods: We imaged brain function using HD-DOT in N=100 participants as they passively observed videos of an actor completing sequences of meaningless arm movements. Additionally, while being simultaneously recorded with both HD-DOT and Kinect 3D cameras for computer-vision-based assessment of motor imitation (CAMI), participants imitated different videos of an actor completing similar arm movements. Responses to the tasks were estimated using general linear models, and multiple regression was used to investigate brain-behavior associations with autistic traits, using the Social Responsiveness Scale, and imitation fidelity as measured with CAMI. Results: Both motor observation and imitation tasks elicited significant activations in visual, temporal, and MNS areas, with imitation showing stronger activation in motor regions. Notably, MNS regions exhibited greater activation during observation than imitation. Additionally, activity during observation in the right parietal lobe correlated with autistic traits assessed with the SRS. Conclusions: Our findings provide robust evidence of shared and task-specific neural mechanisms underlying motor observation and imitation, emphasizing the differential engagement of MNS regions during motor observation and imitation.

Perinatal circadian desynchronization disrupts sleep and prefrontal cortex function in adult offspring
Sleep and circadian (daily) rhythms impact nearly all aspects of physiology and are critical for optimal organismal function. Disruption of the clock can lead to significant metabolic disorders, neuropsychiatric illness, and cognitive dysfunction. Our lab has previously shown that environmental circadian desynchronization (ECD) in adults alters the anatomical structure and neurophysiological function of prefrontal cortex (PFC) neurons, PFC mediated behaviors, as well as sleep quality. As the PFC undergoes significant development in utero and early life, and maternal disturbances during this period can have significant long-term ramifications, we hypothesized that disrupting the circadian environment of dams during the perinatal period would alter sleep and PFC function in adult offspring. Using a mouse model of ECD we investigated how perinatal ECD (pECD) modulates sleep quality in adult offspring. We also determined how pECD impacts PFC neural function in adult offspring using ex vivo patch-clamp electrophysiology, exploring how pECD alters synaptic function and action potential dynamics. We found that male pECD mice trended toward increased total sleep during the inactive (light) period with shorter sleep bouts during the active (dark) period. pECD did not change sleep behavior in female mice. Independent of time of day, pECD altered post-synaptic dynamics of excitatory neurotransmitter release onto plPFC pyramidal neurons. There was also a loss of time-of-day effects on cell endogenous properties in male pECD mice. Thus, pECD clearly alters sleep behavior and PFC function in male mice. However, female mice appear protected against the effects of pECD in these measures. Together, these experiments form the foundation for future studies to understand the lifelong neurobehavioral impact of pECD.

Isolation and characterization of synaptic structures from human neural organoids
Synapses are essential for neuronal function and are central to numerous neurological disorders including developmental and neurodegenerative diseases. Synapses structurally constitute a very small proportion of a neuron, and their protein content is difficult to study using whole tissue preparations. Especially studying synapses on the functional level is challenging. To overcome this limitation, synapses can be captured as synaptosomes generated through enrichment of isolated nerve terminals. Such synaptosomes have a re-sealed plasma membrane and can regenerate their membrane potential and perform physiological function, for example neurotransmitter release. Synaptosomes are traditionally enriched from rodent or postmortem human brain tissue, but rodent models lack human-specific synaptic features, and the functionality of synaptosomes from postmortem tissues is limited by the postmortem interval and often only show disease endpoints. Furthermore, due to ethical issues and availability, only a few studies have been conducted on human samples. However, neural organoids (NOs) have emerged as a possible new source for isolation of intact and live human nerve terminals to study human-specific aspects of synaptic transmission. Further, the enrichment of synaptosomes is usually performed using density gradient centrifugation, which requires a lot of starting material. In the present study we developed a method for the enrichment of synaptic structures from human NOs applying a differential centrifugation protocol. We then used mass spectrometry-based quantitative proteomics to document the enrichment of synapse and growth cone specific proteins, and quantitative phosphoproteomics upon KCl stimulation to demonstrate viability and physiological function of the derived synaptic structures.

Small molecule-mediated targeted protein degradation of voltage-gated sodium channels involved in pain
The voltage-gated sodium channels (VGSC) NaV1.8 and NaV1.7 (NaVs) have emerged as promising and high-value targets for the development of novel, non-addictive analgesics to combat the chronic pain epidemic. In recent years, many small molecule inhibitors against these channels have been developed. The recent successful clinical trial of VX-548, a NaV1.8-selective inhibitor, has spurred much interest in expanding the arsenal of subtype-selective voltage-gated sodium channel therapeutics. Toward that end, we sought to determine whether NaVs are amenable to targeted protein degradation with small molecule degraders, namely proteolysis-targeting chimeras (PROTACs) and molecular glues. Here, we report that degron-tagged NaVs are potently and rapidly degraded by small molecule degraders harnessing the E3 ubiquitin ligases cereblon (CRBN) and Von Hippel Lindau (VHL). Using LC/MS analysis, we demonstrate that PROTAC-mediated proximity between NaV1.8 and CRBN results in ubiquitination on the 2nd intracellular loop, pointing toward a potential mechanism of action and demonstrating the ability of CRBN to recognize a VGSC as a neosubstrate. Our foundational findings are an important first step toward realizing the immense potential of NaV-targeting degrader analgesics to combat chronic pain.

A Shared Neural Network for Highly Liked and Disliked Music
Music research has increasingly focused on neural responses to naturalistic stimuli. The neural correlates of music-induced peak moments of pleasure (e.g., chills) have been well-studied; data on other types of aesthetic responses, such as judgments of beauty, goodness, or liking are sparse. Among these, liking is of particular interest given its complex nature and its ubiquity in everyday and musical experiences. In this functional magnetic resonance imaging (fMRI) study, 26 participants listened to musical excerpts while continuously rating how much they liked the music. In addition, subjects provided an overall liking judgment at the end of each musical piece. Participants' musical preferences manifested remarkably early and were sustained over time, with the value of the continuous rating at the end of each piece showing the strongest correlation with the overall ratings. At the neural level, highly liked and disliked musical pieces activated a shared neural network previously associated with the processing of both positive and negative emotional stimuli. This network encompassed the anterior cingulate cortex, limbic system, basal ganglia, and precuneus. These activations reflected individual differences, such that participants with greater trait-level responsiveness to artistic stimuli showed stronger engagement of this network while listening to music. Finally, the default-mode network was associated with the slope of the continuous ratings, suggesting that the faster participants liked a musical excerpt, the more disengaged this network became. In linking behavior and brain function to better characterize the way humans make aesthetic judgments of music the data support a model in which preferences and aesthetic choices are modulated by brain circuits associated with emotion and reward.

Derived motor neurons transplantation promotes nerve regeneration in a rodent model of a chronically denervated nerve through delayed adoption of a chronic denervation phenotype
After acute injury, the peripheral nervous system regenerates more efficiently than the central nervous system, but this advantage is not maintained with chronic injuries. In large animals like humans, the slow rate of axon growth and the long distance between the central nervous system and end organ result in the adoption of a chronically denervated nerve phenotype even in the setting of acute injury: distal areas of the nerve become unable to support regenerating axons, even as the proximal aspect of the acute injury may be appropriately supportive of regeneration. We hypothesized that motor neuron transplantation into the denervated distal stump would maintain the regenerative capacity by effectively reducing the time and distance necessary for regeneration through relay formation as well as by supporting the host Schwann cells responsible for guiding regenerating axons. Using an in vitro assays, we showed the feasibility of relay formation by demonstrating ventral horn to derived-motor neuron synaptogenesis as identified by calcium imaging. Pilot studies of transplantation of embryonic stem cell-derived mouse motor neurons into chronically denervated rat nerves demonstrated improved regenerative capacity in the chronically denervated nerve following a delayed repair paradigm. While host to graft synaptogenesis was not observed, the Schwann cells in the transplanted nerve stump were maintained in a pro-regenerative state despite chronic denervation. These pilot data suggest cell transplantation can delay the adoption of a chronically denervated phenotype primarily by maintaining Schwann cells in a pro-regenerative state.

Longitudinal Trajectories of Cognition and Neural Metrics as Predictors of Persistent Distressing Psychotic-Like Experiences Across Middle Childhood and Early Adolescence
Objectives: Psychotic-like experiences (PLEs) may arise from genetic and environmental risk leading to worsening cognitive and neural metrics over time, which in turn lead to worsening PLEs. Persistence and distress are factors that distinguish more clinically significant PLEs. Analyses used three waves of unique longitudinal Adolescent Brain Cognitive Development Study data (ages 9-13) to test whether changes in cognition and structural neural metrics attenuate associations between genetic and environmental risk with persistent distressing PLEs. Methods: Multigroup univariate latent growth models examined three waves of cognitive metrics and global structural neural metrics separately for three PLE groups: persistent distressing PLEs (n=356), transient distressing PLEs (n=408), and low-level PLEs (n=7901). Models then examined whether changes in cognitive and structural neural metrics over time attenuated associations between genetic liability (i.e., schizophrenia polygenic risk scores/family history) or environmental risk scores (e.g., poverty) and PLE groups. Results: Persistent distressing PLEs showed greater decreases (i.e., more negative slopes) of cognition and neural metrics over time compared to those in low-level PLE groups. Associations between environmental risk and persistent distressing PLEs were attenuated when accounting for lowered scores over time on cognitive (e.g., picture vocabulary) and to a lesser extent neural (e.g., cortical thickness, volume) metrics. Conclusions: Analyses provide novel evidence for extant theories that worsening cognition and global structural metrics may partially account for associations between environmental risk with persistent distressing PLEs.

Representation of conceptual affordances in eye movements and the entorhinal cortex
Structural representations in the entorhinal cortex are a crucial feature of cognitive maps. However, a complete understanding of task structure often requires knowledge of the actions available at each state (analogous to the moves of different pieces on a chessboard). Moreover, action representations are key to several models of the hippocampal-entorhinal system. In this study, we tested whether the entorhinal cortex represents the actions that allow transitioning between states of a conceptual space. In particular, participants learned to transition between numerically-labelled states using different mathematical operations. Behaviourally, participants learned and generalised action information across states. Action information was also reflected in eye movements, indicating the active processing of the possible actions for a given state during the trials. Importantly, we found that neural pattern similarity in the right entorhinal cortex scaled with the similarity of action affordances across the states. This affordance representation was not explained by other properties of the task space such as link distance between the states or action magnitude. In sum, this study provides first evidence for the integration of action information into ocular and entorhinal representations of conceptual spaces, suggesting that these may not just store experiences, but provide information about how to explore knowledge.

Is cultural context the crucial touch? Neurophysiological and self-reported responses to affective touch in women in South Africa and the United Kingdom.
Affective touch, involving touch-sensitive C-tactile (CT-) afferent nerve fibres, is integral to human development and wellbeing. Despite presumed cultural differences, affective touch research typically includes 'Western', minority-world contexts, with findings extrapolated cross-culturally. We report the first cross-cultural study to experimentally investigate subjective and neurophysiological correlates of affective touch in women in South Africa (SA) and the United Kingdom (UK) using (1) subjective touch ratings, and (2) cortical oscillations for slow CT-optimal (vs. faster non-CT-optimal) touch on two body regions (arm, palm). Cultural context modulated affective touch experiences: SA (vs. UK) participants rated touch as more positive and less intense, with enhanced differentiation in sensorimotor beta band oscillations, especially during palm touch. UK participants differentiated between stroking speeds, with opposite directions of effects at arm and palm for frontal theta oscillations. Results highlight the importance of cultural context in subjective experience and neural processing of affective touch.

The patient-specific mouse model with Foxg1 frameshift mutation provides insights into the pathophysiology of FOXG1 syndrome
Single allelic mutations in the forebrain-specific transcription factor gene FOXG1 lead to FOXG1 syndrome (FS). To decipher the disease mechanisms of FS, which vary depending on FOXG1 mutation types, patient-specific animal models are critical. Here, we report the first patient specific FS mouse model, Q84Pfs heterozygous (84Pfs-Het) mice, which emulates one of the most predominant FS variants. Remarkably, Q84Pfs-Het mice recapitulate various human FS phenotypes across cellular, brain structural, and behavioral levels, such as microcephaly, corpus callosum agenesis, movement disorders, repetitive behaviors, and anxiety. Q84Pfs-Het cortex showed dysregulations of genes controlling cell proliferation, neuronal projection and migration, synaptic assembly, and synaptic vesicle transport. Interestingly, the FS-causing Q84Pfs allele produced the N-terminal fragment of FOXG1, denoted as Q84Pfs protein, in Q84Pfs-Het mouse brains. Q84Pfs fragment forms intracellular speckles, interacts with FOXG1 full-length protein, and triggers the sequestration of FOXG1 to distinct subcellular domains. Q84Pfs protein also promotes the radial glial cell identity and suppresses neuronal migration in the cortex. Together, our study uncovered the role of the FOXG1 fragment derived from FScausing FOXG1 variants and identified the genes involved in FS-like cellular and behavioral phenotypes, providing essential insights into the pathophysiology of FS.

A self-supervised deep learning pipeline for segmentation in two-photon fluorescence microscopy
Two-photon fluorescence microscopy (TPFM) allows in situ investigation of the structure and function of the brain at a cellular level, but the conventional image analyses of TPFM data are labour-intensive. Automated deep learning (DL)-based image processing pipelines used to analyze TPFM data require large labeled training datasets. Here, we developed a self supervised learning (SSL) pipeline to test whether unlabeled data can be used to boost the accuracy and generalizability of DL models for image segmentation in TPFM. We specifically developed four pretext tasks, including shuffling, rotation, axis rotation, and reconstruction, to train models without supervision using the UNet architecture. We validated our pipeline on two tasks (neuronal soma and vasculature segmentation), using large 3D microscopy datasets. We introduced a novel density-based metric, which provided more sensitive evaluation to downstream analysis tasks. We further determined the amount of labeled data required to reach performance on par with fully supervised learning (FSL) models. SSL-based models that were fine-tuned with only 50% of data were on par or superior (e.g., Dice increase of 3% for neuron segmentation and Dice score of 0.88 +/- 0.09 for vessel segmentation) to FSL models. We demonstrated that segmentation maps generated by SSL models pretrained on the reconstruction and rotation tasks can be better translated to downstream tasks than can other SSL tasks. Finally, we benchmarked all models on a publicly available out-of-distribution dataset, demonstrating that SSL models outperform FSL when trained with clean data, and are more robust than FSL models when trained with noisy data.

Loss of the autism associated gene Tbr1 disrupts prediction and encoding by prefrontal ensembles during socioemotional behaviors
Disruptions in many genes linked to autism spectrum disorder (ASD) affect synaptic function and socioemotional behaviors in mice. However, exactly how synaptic dysfunction alters neural activity patterns underlying behavior remains unknown. We addressed this using mice lacking the high confidence ASD gene Tbr1 in cortical layer 5 (L5) projection neurons (Tbr1 cKO mice). These mice have known deficits in synaptic input to L5 neurons and social behavior. We also find some abnormalities in anxiety-related avoidance. Calcium imaging of prefrontal L5 neurons revealed that despite reduced overall activity, cKO mice recruit normal numbers of neurons into prefrontal ensembles encoding social and anxiety-related behaviors. However, the stability, inter-neuronal coordination, and reactivation of social ensembles were diminished in cKO mice. Furthermore, in cKO mice, ensembles no longer predicted approach-avoidance decisions. These results reveal new aspects of how prefrontal ensembles encode socioemotional behaviors, and malfunction in the setting of ASD-linked gene disruption.

Guess Who? Identifying individuals from their brain natural frequency fingerprints
Neural oscillations are critical for brain function and cognition. Thus, identifying the typical or natural oscillatory frequencies of the brain is an important first step for understanding its functional architecture. Recently, a data-driven algorithm has been developed for mapping the brains natural frequencies throughout the whole cortex, free of anatomical and frequency-band constraints. However, an important limitation of this methodology is that it yields robust results only at the group level. Here, we aimed to adapt this algorithm to improve the quality of the single-subject maps of natural frequencies obtained from magnetoencephalography (MEG) recordings. To achieve this goal, we incorporated two modifications to the original method: (1) increasing the number of individual power spectra to be assigned to each k-means cluster, and (2) smoothing across neighboring voxels. To assess the quality of the single-subject maps, we relied on the fingerprinting technique. Our results show a high degree of accuracy in individual identification, both within a single recording session and across separate sessions. Furthermore, we were able to identify individuals by their natural frequency fingerprints, even with a gap of over four years between sessions. This demonstrates the robustness of the single-subject mapping of natural frequencies and opens new opportunities for identification of pathological variations in intrinsic oscillatory activity in individual subjects.

Green Synthesis of Silver Nanoparticles Using Sudanese Candida parapsilosis: A Sustainable Approach to Combat Antimicrobial Resistance
BackgroundAntimicrobial resistance (AMR) is a major global health threat, particularly in Sudan, where the overuse and misuse of antibiotics have led to the emergence and spread of multidrug-resistant (MDR) pathogens. Traditional methods to address AMR often fail to provide sustainable solutions. Nanotechnology offers promising alternatives, with silver nanoparticles (AgNPs) demonstrating broad-spectrum antimicrobial properties. This study aims to develop an eco-friendly synthesis of AgNPs using Candida parapsilosis isolated from Sudanese soil, leveraging untapped fungal biodiversity to combat AMR.

ResultsThe Candida parapsilosis-mediated synthesis of AgNPs was successfully characterized using UV-Vis spectroscopy, X-ray diffraction (XRD), and high-resolution transmission electron microscopy (HRTEM), confirming the formation of well-defined nanoparticles. The biosynthesized AgNPs exhibited potent antimicrobial activity against Gram-positive and Gram-negative MDR pathogens. Medium concentrations of AgNPs demonstrated optimal activity, with inhibition zones up to 29 mm for Pseudomonas aeruginosa (ATCC27853). MIC and MBC assays revealed AgNPs bactericidal efficacy, particularly against Escherichia coli and Klebsiella pneumoniae at 0.3125 mg/mL. Synergistic effects with antibiotics, such as ceftazidime and colistin, significantly enhanced antimicrobial activity, with fold increases up to 9.46. AgNPs disrupted bacterial membranes, as evidenced by increased permeability and leakage of nucleic acids.

ConclusionsThis study presents a novel and sustainable approach to combating AMR by utilizing Sudanese fungal strains for the green synthesis of AgNPs. The findings highlight the potential of AgNPs as an effective antibacterial agent, particularly in combination with conventional antibiotics, to combat multidrug-resistant pathogens. This research not only offers a cost-effective and environmentally friendly solution to AMR but also underscores the significant potential of integrating microbiology and nanotechnology to address global health challenges. The results could pave the way for future applications in both public health and environmental sustainability.

Effects of shock on perceptual learning in a virtual reality environment
This study investigates two aspects of visual processing and perceptual learning: the impact of training on the human visual systems ability to integrate information across the visual field and the influence of aversive electrodermal stimulation on perceptual performance in an orientation averaging task. Through a ten-day training regimen that manipulated the set-size of Gabor element arrays, we observe consistent degradation in orientation averaging performance with increasing set-size, with training leading to overall improvements in accuracy and response times, but only a marginal interaction with set-size (for response times). This suggests that training-related enhancements likely operate at a post-integration and/or decisional stage of processing rather than at an early encoding stage. The second inquiry explores the effects of aversive stimuli on perceptual learning-based orientation averaging performance, with participants exposed to no shock, performance-contingent shock or random shock conditions. Our results show that while performance improved across training there was no discernible effect of the shock condition on task accuracy or response times and no evidence of an interaction with set size. State anxiety levels, measured by the State-Trait Anxiety Inventory, indicated that whilst anxiety was elevated in both shock conditions, this was not associated with variations on orientation averaging performance. We also find that visual performance feedback, represented by a health bar, significantly influenced accuracy, but not response times, regardless of the presence or absence of shock. This unexpected impact of visual feedback suggests potential roles for attention and motivation in perceptual performance.

Public significance statementThis study enhances our understanding of how training and stress influence visual processing and perceptual learning, revealing critical insights into the mechanisms that govern how we integrate visual information. By exploring the effects of acute stress and visual feedback, our findings suggest potential applications for improving learning outcomes in various contexts, from virtual to real-world environments.

Single-cell spatial transcriptome reveals pathological features of human hippocampus with sclerosis
More than half of epileptic patients ultimately turned to intractable epilepsy. Mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS), the most common type of intractable epilepsies, whose pathological mechanism remains elusive. Here, using 42 human hippocampal samples from surgical donors of MTLE (32 with and 10 without HS) through single-cell resolution Stereo-seq and histologcial experiments, we revealed spatially pathological changes of gene expression and cell type composition with HS systematically. After precise parcellation of hippocampal subregions and differentially expressed gene (DEG) analysis between each region with and without sclerosis, we found Cornu Ammonis (CA) subregions with higher number of DEGs were vulnerable to sclerosis, especially CA1 and CA3. Within CA1, we found that CA1-superficial and proximal areas were more vulnerable than CA1-deep and distal areas in sclerosis. Meanwhile, after analyzing 350,795 segmented cells from Stereo-seq, we found dramatically increasing density of astrocyte accompanied with significantly decreasing density of excitatory neurons in CA1, especially superficial and proximal CA1, and CA3 in sclerosis. In these two vulnerable subregions, proliferative astrocyte (P_astrocyte) and reactive astrocyte (R_astrocyte) were found to be enriched whereas apoptotic subtype of astrocyte (A_astrocyte), related with apoptotic pathway, was mainly located in alveus, which strengthened cell communication with reactive microglia (R_microglia) in HS, revealing the novel pathological feature in our work. The pseudotime analysis indicated that CA excitatory neurons underwent synaptic impairment, energy dysfunction, aging, and finally losing cell identity until death through autophagy or apoptosis. Besides, we also found a resilient subtype, EX_CA2-4.3, highly expressed extracellular matrix related genes including PDYN, and was increasing the interaction of BDNF-NTRK, NFASC-CNTN1 to withstand the damage from sclerosis. Together, our study provided a reference of human hippocampus with and without HS caused by MTLE, and highlighted the potential pathological mechanism on molecular and cellular level of MTLE-HS.

Doctoral Students as Carbon Accountants: Calculating Carbon Costs of a PhD in Neuroscience
PhD students are drivers of innovation in research; however, the carbon intensity of PhD work is often unclear, especially in specialised STEM disciplines. Empowering PhD students to engage in carbon accounting could provide a powerful force for decarbonization in key areas of production and consumption in research communities. Here, we present a comprehensive life-cycle assessment for PhD work in a cellular neuroscience laboratory as part of a larger strategic effort to encourage PhD students to engage in carbon accounting. We measured Scope 1 emissions associated with anaesthetising animals and research-related travel. We then used regional conversion data openly reported by the UK National Grid through the Carbon Intensity API to accurately document time-specific Scope 2 emissions associated with neuroscience research activities, including widely used techniques like calcium imaging, electrophysiology, and optogenetics. Finally, we estimated Scope 3 Emissions associated with procuring particular equipment and consumables using UK GOV 2024 reported conversion factors. Over 1 year, we accounted for 1.56 kg of direct carbon dioxide emissions (CO2), < 1942 kg carbon dioxide equivalent (CO2e) emissions associated with ground and air travel using radiative factor, 3.56 kg CO2e directly underpinning research activities, and 10.99 kg CO2e underlying indirect costs of laboratory facilities. Procurement of a subset of laboratory supplies were estimated to be in the range of < 543 kg CO2e. We discuss challenges of accurately estimating carbon footprints across disciplines in the UK and beyond. Here we propose a common framework for including carbon life cycle analyses in Carbon Appendices to PhD theses and other publications. Overall, this work demonstrates how PhD students can measure the carbon footprint of their work and catalyse community-led efforts to decarbonize research that are efficient, targeted, and accurate.

Virtual Brain Inference (VBI): A flexible and integrative toolkit for efficient probabilistic inference on virtual brain models
Network neuroscience has proven essential for understanding the principles and mechanisms underlying complex brain (dys)function and cognition. In this context, whole-brain network modeling-also known as virtual brain modeling-combines computational models of brain dynamics (placed at each network node) with individual brain imaging data (to coordinate and connect the nodes), advancing our understanding of the complex dynamics of the brain and its neurobiological underpinnings. However, there remains a critical need for automated model inversion tools to estimate control (bifurcation) parameters at large scales and across neuroimaging modalities, given their varying spatio-temporal resolutions. This study aims to address this gap by introducing a flexible and integrative toolkit for efficient Bayesian inference on virtual brain models, called Virtual Brain Inference (VBI). This open-source toolkit provides fast simulations, taxonomy of feature extraction, efficient data storage and loading, and probabilistic machine learning algorithms, enabling biophysically interpretable inference from non-invasive and invasive recordings. Through in-silico testing, we demonstrate the accuracy and reliability of inference for commonly used whole-brain network models and their associated neuroimaging data. VBI shows potential to improve hypothesis evaluation in network neuroscience through uncertainty quantification, and contribute to advances in precision medicine by enhancing the predictive power of virtual brain models.

Muscle Cathepsin B treatment improves behavioral and neurogenic deficits in a mouse model of Alzheimer's Disease
Muscle secretes factors during exercise that enhance cognition. Myokine Cathepsin B (Ctsb) is linked to memory function, but its role in neurodegenerative disease is unclear. Here we show that AAV-vector-mediated Ctsb overexpression in skeletal muscle in an Alzheimers Disease (AD) mouse model (APP/PS1), improves motor coordination, memory function and adult hippocampal neurogenesis, while plaque pathology and neuroinflammation remain unchanged. Additionally, in AD mice, Ctsb treatment modifies hippocampal, muscle and plasma proteomic profiles to resemble that of wildtype controls. Conversely, in wildtype mice, Ctsb expression causes memory deficits and results in protein profiles across tissues that are comparable to AD control mice. In AD mice, Ctsb treatment increases the abundance of hippocampal proteins involved in mRNA metabolism and protein synthesis, including those relevant to adult hippocampal neurogenesis and memory function. Furthermore, Ctsb treatment enhances plasma metabolic and mitochondrial processes, and reduces inflammatory responses. In muscle, Ctsb expression elevates protein translation in AD mice, whereas in wildtype mice mitochondrial proteins decrease. Overall, the biological changes in the treatment groups are consistent with effects on memory function. Thus, skeletal muscle Ctsb application has potential as an AD therapeutic intervention.

Parameterization of intraoperative human microelectroderecordings: Linking action potential morphology to brainanatomy
Deep brain stimulation (DBS) is a targeted manipulation of brain circuitry to treat neurological and neuropsychiatric conditions. Optimal DBS lead placement is essential for treatment efficacy. Current targeting practice is based on preoperative and intraoperative brain imaging, intraoperative electrophysiology, and stimulation mapping. Electrophysiological mapping using extracellular microelectrode recordings aids in identifying functional subdomains, anatomical boundaries, and disease-correlated physiology. The shape of single-unit action potentials may differ due to different biophysical properties between cell-types and brain regions. Here, we describe a technique to parameterize the structure and duration of sorted spike units using a novel algorithmic approach based on canonical response parameterization, and illustrate how it may be used on DBS microelectrode recordings. Isolated spike shapes are parameterized then compared using a spike similarity metric and grouped by hierarchical clustering. When spike morphology is associated with anatomy, we find regional clustering in the human globus pallidus. This method is widely applicable for spike removal and single-unit characterization and could be integrated into intraoperative array-based technologies to enhance targeting and clinical outcomes in DBS lead placement.

Sparks fade with distance: The effect of electric field distribution on global motion perception using different tES techniques
Previous evidence has shown that high frequency transcranial random noise stimulation (hf-tRNS) decreases motion coherence thresholds when a cephalic montage (i.e., return over Cz) is used. Extracephalic montages have also been employed to modulate behavioral performance, eliminating stimulation of regions under the return electrode. In this study, we examined the effects of different transcranial electrical stimulation (tES) protocols on visual motion discrimination, placing the return electrode on the ipsilateral arm. We assessed the impact of electrode localization using hf-tRNS, anodal, cathodal transcranial direct current stimulation (tDCS), and Sham stimulation over hMT+, a brain region involved in global motion perception. Motion direction discrimination was measured using random dot kinematograms (RDKs). Due to the increased distance between the stimulation and return electrodes in this montage, we expected a smaller reduction in motion discrimination thresholds compared to our previous study. The results suggest that increased interelectrode distance mitigates the efficacy of hf-tRNS. Additionally, no significant effects were observed with the other tES protocols tested. Our findings imply that the positioning of the two electrodes affects current flow characteristics, leading to reduced neuromodulation. These results underscore the importance of stimulation configuration, particularly the effect of interelectrode distance on performance. Given the widespread application of brain stimulation techniques in clinical and cognitive research, our results can guide future studies in carefully considering this further aspect of stimulation montage configurations.

Influence of neural network bursts on functional connectivity
Network bursts or synchronized burst events are a typical activity seen in most in vitro neural networks. Network bursts arise early in development and as networks mature, activity becomes dominated by bursts propagating across the entirety of the network. The reason for this developmental plateau in vitro is unknown, but to bypass it would confer a significant advantage in the use of in vitro networks for computation. As most neurons in a network participate in network bursts, burst onset supersedes any ongoing activity thereby placing a limit on short term computations equal to the recovery period between bursts. By assessing 521 multielectrode array recordings from day 4-39 in vitro we find that network bursts influence the connectivity, but this change is only weakly associated with the origin of the network bursts. The impacts of bursts on functional integration and segregation in neural networks are discussed along with approaches to mitigate the development and propagation of network bursts in vitro. Additionally, we hypothesize that burst initiation zones or pacemakers are viable targets for stimulation for computation in the context of control and reservoir computing.

Cannabinoid Modulation of Central Amygdala Population Dynamics During Threat Investigation
Cannabinoids modulate innate avoidance, threat-reactivity, and stress adaptations via modulation amygdala-associated circuits; however, the mechanisms by which cannabinoids modulate amygdala representation of threat-related behavior are not known. We show that cannabinoid administration increases the activity of central amygdala (CeA) somatostatin neurons (SOM) and alters basal network dynamics in a manner supporting generation of antagonistic sub-ensembles within the SOM population. Moreover, diverging neuronal population trajectory dynamics and enhanced antagonistic sub-ensemble representation of threat-related behaviors, and enhanced threat-related location representation, were also observed. Lastly, cannabinoid administration increased the proportion of SOM neurons exhibiting multidimensional representation of threat-related behaviors and behavior-location conjunction. While cannabinoid receptor activation ex vivo suppressed excitatory inputs to SOM neurons, our data suggest preferential suppression of local GABA release subserves cannabinoid activation of CeA SOM neurons. These data provide insight into how cannabinoid-mediated presynaptic suppression transforms postsynaptic population dynamics and reveal cellular mechanisms by which cannabinoids could affect threat-reactivity.

Reduced levels of synaptic vesicle protein 2A in the extracellular vesicles and brain of Alzheimer's disease- associations with Aβ, tau and synaptophysin
Background: Synaptic dysfunction plays an important role in Alzheimer's disease (AD) and is an emerging imaging and fluid biomarker. Here, we aimed to assess the regional expression of synaptic vesicle glycoprotein 2A (SV2A) in the brain and extracellular vesicles of AD patients and its associations with the APOE e4 allele, amyloid-, tau pathologies, and other synaptic markers. Methods: Mass spectrometry-based synaptosome proteomics was performed on brain-derived extracellular vesicles (BdEVs) isolated from the frontal cortex of 17 AD patients and 4 NCs. Immunohistochemical staining for SV2A, synaptophysin, amyloid-{beta} and phospho-tau was performed on postmortem tissue from the frontal, temporal, and entorhinal cortices and hippocampus of 40 AD patients and 44 nondemented controls (NCs). Results: Reduced levels of synaptic proteins, including synaptotagamin, GAP43, SYT1, SNAP25 and 14-3-3zeta, were positively correlated with SV2A and negatively correlated with GFAP and NEFL in BdEVs from AD patients and NCs. We detected lower levels of SV2A in the hippocampus and entorhinal cortex of AD compard to NCs, and in APOE e4 carriers than in noncarriers. SV2A levels were positively correlated with synaptophysin and negatively correlated with the levels of the amyloid-{beta}, phospho-tau, and Braak stages. Conclusions: This study provides postmortem evidence of synaptic markers and reduced regional levels of SV2A in brain tissue slices and BdEVs from AD patients compared with NCs and in APOE e4 carriers compared to non-carriers. SV2A could serve as a valuable marker for monitoring synaptic degeneration in AD.

Cisternostomy facilitates clearance of metabolic waste from cerebrospinal fluid in patients with traumatic brain injury
Decompressive craniotomy, a common intervention for traumatic brain injury (TBI), can fail to effectively alleviate patient symptoms. Cisternostomy, reported for cistern drainage in TBI patients, has shown efficacy in reducing intracranial pressure and clearing detritus resulting from brain hemorrhage. However, the mechanisms underlying its effectiveness remain largely unknown. Here, we utilized non-targeted metabolomics to analyze cerebrospinal fluid from cisterns alongside peripheral blood samples from TBI patients undergoing cisternostomy. Through a systematic comparison of the cisternal cerebrospinal fluid and blood plasma metabolomes, we identified multiple blood-enriched metabolites, including betaine, triethanolamine, and proline, that were efficiently cleared during the acute stage of TBI. Notably, two metabolites linked to arginine metabolism and the urea cycle, N8-acetylspermidine and N-acetylputrescine, showed significant reductions that correlated with improvements in the Glasgow Coma Scale. Our findings indicate that cisternostomy effectively removes blood-derived substances and aids the recovery of patients with acute-stage TBI.

Scg2 drives reorganization of the corticospinal circuit with spinal premotor interneurons to recover motor function after stroke
Brain injuries such as stroke damage neural circuitry and lead to functional deficits. Spared motor pathways are often reorganized and contribute to functional recovery; however, the connectivity and molecular mechanisms that drive the reorganization are largely unknown. Here, we demonstrate structural and functional connectivity reformed by spared corticospinal axons after stroke and determine a key secretory protein that drives the reorganization. We first found that corticospinal axons innervate specific areas of the denervated cervical cord after stroke. Anatomical and photometric analyses reveal that the axons reconnect to premotor V2a interneurons. Kinematic analyses of forelimb movements and chemogenetic silencing reveal their contribution to motor recovery. Translated mRNA expression analyses of V2a interneurons and astrocytes in the denervated cervical cord reveal diverse transcripts upregulated in the rewiring process. In particular, a secretory protein Scg2 is upregulated by injury-induced purinergic ATP signals and rehabilitative training-induced neural activity and possesses an ability to promote axon growth via cAMP and S6 signaling. Scg2 overexpression in the denervated cervical cord enhances axon rewiring, while the Scg2 knockdown attenuates it. The present data reveal the neural substrate and molecular mechanism essential to induce reorganization and recovery of the motor system, providing fundamental therapeutic targets for CNS injuries.

Fos expression in the periaqueductal gray, but not the ventromedial hypothalamus, is correlated with psychosocial stress-induced cocaine-seeking behavior in rats
Psychosocial stressors are known to promote cocaine craving and relapse in humans but are infrequently employed in preclinical relapse models. Consequently, the underlying neural circuitry by which these stressors drive cocaine seeking has not been thoroughly explored. Using Fos expression analyses, we sought to examine whether the ventromedial hypothalamus (VMH) or periaqueductal gray (PAG), two critical components of the brains hypothalamic defense system, are activated during psychosocial stress-induced cocaine seeking. Adult male and female rats self-administered cocaine (0.5 mg/kg/inf IV, fixed-ratio 1 schedule, 2 h/session) over 20 sessions. On sessions 11, 14, 17, and 20, a tactile cue was present in the operant chamber that signaled impending social defeat stress (n=16, 8/sex), footshock stress (n=12, 6/sex), or a no-stress control condition (n=12, 6/sex) immediately after the sessions conclusion. Responding was subsequently extinguished, and rats were tested for reinstatement of cocaine seeking during re-exposure to the tactile cue that signaled their impending stress/no-stress post-session event. All experimental groups displayed significant reinstatement of cocaine seeking, but Fos analyses indicated that neural activity within the rostrolateral PAG (rPAGl) was selectively correlated with cocaine-seeking magnitude in the socially-defeated rats. rPAGl activation was also associated with active-defense coping behaviors during social defeat encounters and with Fos expression in prelimbic prefrontal cortex and orexin-negative cells of the lateral hypothalamus/perifornical area in males, but not females. These findings suggest a potentially novel role for the rPAGl in psychosocial stress-induced cocaine seeking, perhaps in a sex-dependent manner.

Anxiety-associated behaviors following ablation of Miro1 from cortical excitatory neurons
Autism spectrum disorder, schizophrenia, and bipolar disorder are neuropsychiatric disorders that manifest early in life with a wide range of phenotypes, including repetitive behavior, agitation, and anxiety (American Psychological Association, 2013). While the etiology of these disorders is not completely understood, recent data implicate a role for mitochondrial dysfunction. To function optimally mitochondria must translocate to metabolically active intracellular compartments to support energetics and free-radical buffering; failure to achieve this localization results in cellular dysfunction (Picard et al., 2016). Mitochondrial Rho-GTPase 1 (Miro1) resides on the outer mitochondrial membrane and participates in neuronal microtubule-mediated mitochondrial motility and homeostasis (Fransson et al., 2003). Previous research implicates the loss of MIRO1 as a contributor to the onset/progression of neurodegenerative diseases including amyotrophic lateral sclerosis, Alzheimers disease, and Parkinsons disease (Kay et al., 2018). We have hypothesized that MIRO1 also has a role in nervous system development and function (Lin-Hendel et al., 2016). To test this, we ablated Miro1 from cortical excitatory progenitors by crossing floxed Miro1 mice with Emx1-cre mice. We found that mitochondrial mis-localization in migrating excitatory neurons was associated with reduced brain weight, decreased cortical volume, and subtle disruptions in cortical organization. Adult Miro1 conditional mutants exhibit agitative-like behaviors, including decreased nesting behavior and abnormal home cage activity. Open field testing revealed anxiety-like behavior and elevated plus maze and wide/narrow box testing found the mice avoided confined spaces. Our data link MIRO1 function with mitochondrial dynamics in the pathogenesis of several neuropsychiatric disorders and implicate mitochondrial localization in anxiety-like behaviors.

SignificanceNeuropsychological disorders such as autism spectrum disorder, schizophrenia, and bipolar disorder have overlapping symptoms and behaviors. While the mechanisms underlying these disorders are not completely understood, recent evidence suggests mitochondrial dysfunction and mis-localization within a cell could play a role. Mitochondria are organelles that provide energy and other self-regulating processes to the cell. Previous research from our lab has shown distinct dynamic localization patterns within migrating excitatory and inhibitory neurons may be important during development. To further examine the importance of mitochondrial localization, we ablated MIRO1, a protein important for coupling mitochondria to motor proteins, in excitatory neurons. Mitochondria mis-localize in migrating excitatory neurons, and this is associated with a loss of motor skills and anxiety-like behavior in post-natal mice.

Identifying mood instability and circadian rest-activity patterns using digital remote monitoring and actigraphy in participants at risk for bipolar disorder
Mood instability and circadian rhythm disruptions are both of increasing interest with regard to a number of psychiatric disorders, notably bipolar disorder (BD), but understanding of their nature and their interrelationship are incomplete. By definition, both have an integral temporal component and, as such, measuring them longitudinally and remotely is desirable. We conducted the Cognition and Mood Evolution across Time (COMET) study to assess the feasibility and value of digital devices to capture mood, its instability, and daily rest-activity patterns, over a 10-week period, in two groups of participants. The first group (n=37) were selected as scoring >7 on the Mood Disorder Questionnaire (MDQ) (high MDQ), thereby having a history of mood elevation and being at risk for BD. They were compared with a group (n=37) scoring <5 on the MDQ (low MDQ). Over a 10-week period, using a tablet, mood was rated daily, clinical ratings of depression, mania, and anxiety were captured weekly via the True Colours app, and a GENEactiv actigraph was worn to capture rest-activity pattern data. The main findings are that (1) MDQ score predicts mood instability; (2) high MDQ score is associated with more negative affect and mood symptoms than people with low MDQ, and with a different circadian activity profile; and (3) mood instability and circadian indices appear uncorrelated. The implications are that (1) remote monitoring of these domains is feasible and valuable; (2) selection of participants based on MDQ score is useful for studying mood (in)stability; and (3) the approach has potential for studies of clinical populations and for experimental medicine studies assessing interventions to reduce mood instability.

Automatic detection of fluorescently labeled synapses in volumetric in vivo imaging data
Synapses are submicron structures that connect and enable communication between neurons. Many forms of learning are thought to be encoded by synaptic plasticity, wherein the strength of specific synapses is regulated by modulating expression of neurotransmitter receptors. For instance, regulation of AMPA-type glutamate receptors is a central mechanism controlling the formation and recollection of long-term memories. A critical step in understanding how synaptic plasticity drives behavior is thus to directly observe, i.e., image, fluorescently labeled synapses in living tissue. However, due to their small size and incredible density - with one ~ 0.5 um diameter synapse every cubic micron - accurately detecting individual synapses and segmenting each from its closely abutting neighbors is challenging. To overcome this, we trained a convolutional neural network to simultaneously detect and separate densely labeled synapses. These tools significantly increased the accuracy and scale of synapse detection, enabling segmentation of hundreds of thousands of individual synapses imaged in living mice.

Proximity labeling of the Tau repeat domain enriches RNA-binding proteins that are altered in Alzheimer's disease and related tauopathies
In Alzheimer's disease (AD) and other tauopathies, tau dissociates from microtubules and forms toxic aggregates that contribute to neurodegeneration. Although some of the pathological interactions of tau have been identified from postmortem brain tissue, these studies are limited by their inability to capture transient interactions. To investigate the interactome of aggregate-prone fragments of tau, we applied an in vitro proximity labeling technique using split TurboID biotin ligase (sTurbo) fused with the tau microtubule repeat domain (TauRD), a core region implicated in tau aggregation. We characterized sTurbo TauRD co-expression, robust enzyme activity and nuclear and cytoplasmic localization in a human cell line. Following enrichment of biotinylated proteins and mass spectrometry, we identified over 700 TauRD interactors. Gene ontology analysis of enriched TauRD interactors highlighted processes often dysregulated in tauopathies, including spliceosome complexes, RNA-binding proteins (RBPs), and nuclear speckles. The disease relevance of these interactors was supported by integrating recombinant TauRD interactome data with human AD tau interactome datasets and protein co-expression networks from individuals with AD and related tauopathies. This revealed an overlap with the TauRD interactome and several modules enriched with RBPs and increased in AD and Progressive Supranuclear Palsy (PSP). These findings emphasize the importance of nuclear pathways in tau pathology, such as RNA splicing and nuclear-cytoplasmic transport and establish the sTurbo TauRD system as a valuable tool for exploring the tau interactome.

Characterising ongoing brain aging from cross-sectional data
"Brain age delta" is the difference between age estimated from brain imaging data and actual age. Positive delta in adults is normally interpreted as implying that an individual is aging (or has aged) faster than the population norm, an indicator of unhealthy aging. Unfortunately, from cross-sectional (single timepoint) imaging data, it is impossible to know whether a single individual's positive delta reflects a state of faster ongoing aging, or an unvarying trait (in other words, a "historical baseline effect" in the context of the population being studied). However, for a cross-sectional dataset comprising many individuals, one could attempt to disambiguate the overall relative contributions of varying aging rates vs. fixed baseline effects. We present a method for doing this, and show that for the most common approaches, which estimate a single delta per subject, baseline effects are likely to dominate. If instead one estimates multiple biologically distinct modes of brain aging, we find that some modes do reflect aging rates varying strongly across subjects. We demonstrate this, and verify our modelling, using longitudinal (two timepoint) data from 4,400 participants in UK Biobank. In addition, whereas previous work found incompatibility between cross-sectional and longitudinal brain aging, we show that careful data processing does show consistency between cross-sectional and longitudinal results.

Meta all the way down: An overview of neuroimaging meta-analyses
Meta-analyses are invaluable tools for navigating the rapidly expanding scientific literature. Given their high value, ensuring the quality of meta-analyses is paramount. We conducted a multifaceted overview, examining each step in a manual neuroimaging meta-analysis on a large scale. We used four novel datasets comprising over 14,000 papers, including fMRI meta-analyses, fMRI studies, studies included in meta-analyses, and studies associated with image data on NeuroVault. Regarding successes, two-thirds of meta-analyses stated that they followed PRISMA guidelines, and 65% included a flowchart describing their inclusion process. We point out several areas for improvement. Pre-registration was fairly rare (20%), and only half listed their exact search strategy. There could be a location bias in which papers are included, and many did not include enough studies to be robust against publication bias (68% of meta analyses have less than 30 studies included). We also offer ideas for future directions. As image based meta-analysis is the gold standard, we have indicated which topics have the most image data available. The potential redundancy of topics can be visualized in our paper, and we recommend future meta-analyses be in conversation with past ones by citing and discussing previous similar work. By addressing these findings, the neuroimaging community can collectively improve the field of neuroimaging meta-analyses.

Multimodal Neuroimaging Reveals Distinct Characteristics of Levodopa-Induced Dyskinesias in de novo Parkinsons Disease Patients
Levodopa-induced dyskinesia (LID) is a significant treatment complication that affects a substantial proportion of Parkinsons disease (PD) patients. Our understanding of the neural basis of LID remains limited, partly due to the small sample sizes in existing neuroimaging studies.

In this study, we utilized structural MRI data from the Parkinsons Progression Markers Initiative (PPMI) database, including de novo PD patients (104 non-dyskinetic for a least 3 years after diagnosis and 120 who developed dyskinesia) and 100 age- and sex-matched healthy controls. Additionally, we analyzed resting-state functional MRI data from a subset of these participants to investigate connectivity differences among the groups.

Our analysis revealed no significant baseline volumetric differences between dyskinetic and non-dyskinetic PD patients. However, the thickness of frontal and sensorimotor cortices were significantly greater in dyskinetic patients. In the subcortical regions, vertex-based shape analysis identified localized surface growth in the left caudate and left pallidum, as well as surface morphology changes in the bilateral pallidum in dyskinetics. Resting-state functional connectivity analysis revealed stronger connectivity between the putamen, inferior frontal gyrus, and sensory cortex in dyskinetic PD patients compared to non-dyskinetics.

These findings suggest that specific morphological and functional changes in the motor cortical-basal ganglia circuitry of de novo PD patients may predispose them to LID over time. Additionally, the altered functional connectivity patterns reinstate the role of the inferior frontal gyrus in the pathophysiology of dyskinesia and suggest that it might be a suitable target for neuromodulatory interventions, consistent with previous reports.