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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2025

The neurotrophin DNT-2 regulates cell survival and connectivity via the Toll-2 receptor during visual system development of Drosophila

During development, neurons are produced in excess and those that receive trophic support are maintained, whereas excess neurons are eliminated, enabling the establishment of appropriate neural circuits. In vertebrates, neurotrophin ligands promote cell survival during periods of naturally occurring cell death, by signalling through p75 and Trk receptors. In the Drosophila optic lobe, a wave of apoptosis occurs during neural circuit development; however, whether this also involves neurotrophism remains unresolved. Drosophila neurotrophins (DNTs) are encoded by spatzle (spz) paralogue genes and bind Toll receptors instead. Here, we focused on DNT-3 (previously known as spz-3) and DNT-2 (also known as spz-5) to ask whether they underlie neurotrophism in visual system development. We show that DNT-3 (spz-3) and DNT-2 (spz-5) are both expressed in the retina and in medulla neurons, and multiple Tolls are expressed across lamina and medulla neurons. Over-expression of DNT-3 (spz-3) and DNT-2 (spz-5) could rescue natural occurring cell death, whereas their loss of function caused cell death, showing that DNT-3 and DNT-2 can, and are required to, promote cell survival during optic lobe development. Importantly, DNT-2 is expressed in Mi1 neurons and Toll-2 in connecting L1 neurons. We show that DNT-2 functions in concert with Toll-2, as Toll-2 RNAi knock-down prevented the rescue of apoptosis by DNT-2 over-expression and all Toll-2+ neurons were lost in DNT-2 mutants. Furthermore, alterations in DNT-2 or Toll-2 expression levels impaired connectivity of L1 neurons at the M1 medulla layer and altered dendritic morphology of L1 neurons. These data suggest that L1 neurons could take up DNT-2 secreted from medulla neurons during the establishment of connectivity patterns. As DNT-3 (spz-3) and DNT-2 (spz-5) are expressed in the medulla and they could influence both lamina and medulla neurons, this suggests that their function maintaining cell survival could enable the stabilisation or alignment of connected neurons across medulla columns.

developmental biology↗
bioRxiv2025

Scratcher: An automated machine-vision tool for dissecting the neural basis of itch

Itch or pruritus invokes a specific reflexive and repetitive directed nocifensive behavioural response, known as scratching. Recent decades have revealed neural circuits that are involved in the sensory and affective-motivational aspects of itch-induced scratching. However, most of these studies relied on manual subjective methods of quantifying scratching in laboratory mice and rats. Recent advances in deep learning have opened avenues for the development of computational tools to analyze animal behaviour in a reliable and automated manner. Further, combined with optogenetic and chemogenetic strategies, these tools can accelerate our understanding of neural circuits underlying itch and scratching. To that end, we have developed Scratcher, a GUI-based computational tool based on a real-time object detection algorithm that allows semi-supervised automated analysis of scratching behaviour in mice in a computationally inexpensive manner. We recorded chloroquine-induced acute itch as it developed and determined the consequence of nail-trimming on acute-itch induced scratching with Scratcher. To probe the neural mechanisms underlying itch, we combined Scratcher with genetic circuit dissection using the Fos-TRAP mouse line. By targeting itch-activated neurons in the lateral parabrachial nucleus (LPBN) - a key brainstem hub for pruritic signal transmission - we demonstrated that LPBN activity modulates itch-evoked scratching. Together, we present a novel, easy-to-use computational tool to dissect molecular, cellular, and circuit mechanisms of itch and scratching.

neuroscience↗
bioRxiv2025

Specificity Protein 1 is essential for the limb trajectory of ephrin-mediated spinal motor axons

The precise organization of neural circuits requires highly specific axon guidance, facilitated by cell-surface guidance receptors on axonal growth cones that help neurons reach their target destinations. Despite a limited repertoire of known guidance receptors and ligands, neural systems achieve complex axonal networks, suggesting that additional regulatory mechanisms exist. One proposed strategy is the co-expression of ligands and their receptors on the same axons, allowing modulation of receptor responsiveness to guidance cues. To investigate this mechanism, we studied the spinal lateral motor column (LMC) motor neurons, which make a binary axon pathfinding decision toward limb targets. We hypothesized that specificity protein 1 (Sp1), a transcription factor, regulates ephrin expression in LMC neurons, thereby modulating receptor functions via cis-attenuation to ensure accurate axonal pathfinding. Our results show that Sp1 is indeed expressed in LMC neurons during critical axonal extension periods. Manipulating Sp1 activity disrupted LMC axon trajectory selection, and RNA-Seq analysis indicated that Sp1 regulates genes associated with axon guidance, including ephrins. We found that Sp1 knockdown affected ephrin/Eph cis-binding and trans-signaling, highlighting Sp1s role in controlling axonal projections through ephrin gene regulation. Additionally, coactivators p300 and CBP are essential for Sp1s regulatory function. These findings identify Sp1 as a key transcription factor in LMC neurons, essential for ephrin expression and ephrin/Eph-mediated axon guidance, providing insights into the molecular mechanisms of neural circuit formation.

neuroscience↗
bioRxiv2025

Disruption of GABA-Regulated Network Resilience in Human Cerebral Organoids Leads to Fragmented Small-World States and Reduced Connectivity

Neuronal network resilience, the ability of brain circuits to maintain and recover functional connectivity following perturbation, is fundamental to cognitive stability and adaptability. Using human cerebral organoids and multi-electrode arrays (MEAs), we investigated how mechanical stress disrupts network stability and identified key mechanisms regulating recovery. Blast overpressure exposure destabilized small-world network (SWN) organization, increasing network fragmentation and reducing overall integration. Merged SWNs, which exhibit high connectivity, were particularly vulnerable, while fragmented and single SWNs persisted for extended periods, indicating a shift toward less resilient network states. Optogenetic stimulation promoted network recovery, reducing the persistence of fragile states and facilitating transitions toward more cohesive network structures. GABAergic signaling emerged as a critical regulator of network resilience, with pharmacological inhibition exacerbating fragmentation and impairing network reorganization. These findings reveal fundamental principles of how inhibitory networks regulate circuit stability, with implications extending beyond mechanical injury to broader conditions characterized by network dysfunction, including anxiety, depression, PTSD, and neurodegenerative disorders. Understanding the mechanisms governing network adaptation and resilience could inform new therapeutic strategies aimed at stabilizing disrupted neural circuits across a range of neurological conditions. Significance statementNeuronal networks must dynamically adapt to maintain function in the face of disruption, yet the mechanisms that govern network resilience remain poorly understood. Using human cerebral organoids, we demonstrate that primary blast overpressure destabilizes small-world networks, increasing fragmentation and reducing overall connectivity. Critically, GABAergic signaling emerges as a key stabilizer, with inhibition of GABA receptors amplifying network fragmentation and impairing recovery. These findings provide fundamental insight into how neural circuits resist and recover from mechanical stress, bridging gaps between basic neuroscience, injury pathology, and potential therapeutic interventions. By identifying inhibitory signaling as a regulator of network resilience, our work informs not only traumatic brain injury treatment strategies but also broader efforts to restore functional connectivity in neurological disorders, from epilepsy to neurodegeneration.

neuroscience↗
bioRxiv2025

Computation-through-Dynamics Benchmark: Simulated datasets and quality metrics for dynamical models of neural activity

A primary goal of systems neuroscience is to discover how ensembles of neurons transform inputs into goal-directed behavior, a process known as neural computation. A powerful framework for understanding neural computation uses neural dynamics - the rules that govern how neural activity evolves over time - to explain how goal-directed input-output transformations occur. As dynamical rules are not directly observable, we need computational models that can infer neural dynamics from recorded neural activity. We typically validate such models using synthetic datasets with known ground-truth dynamics, but unfortunately existing synthetic datasets dont reflect fundamental features of neural computation and may therefore be poor proxies for neural systems. Further, the field lacks validated metrics for quantifying the accuracy of the dynamics inferred by models. The Computation-through-Dynamics Toolkit (CtDToolkit) addresses these critical gaps by providing: 1) synthetic datasets that reflect computational properties of biological neural circuits, 2) interpretable metrics for quantifying model performance, and 3) a standardized pipeline for training and evaluating models with or without known external inputs. In this manuscript, we demonstrate how CtDToolkit can help guide the development, tuning, and troubleshooting of neural dynamics models. In summary, CtDToolkit provides a necessary framework for model developers to better understand and characterize neural computation through the lens of dynamics. Author SummaryUnderstanding how the brain works requires interpretable accounts of how populations of neurons process information to produce behavior. One powerful approach is to study "neural dynamics", the patterns of how neural activity evolves over time. Scientists develop computational models to infer these dynamics from neural recordings, but it has been challenging to know when the inferred dynamics are trustworthy. Existing datasets often lack key features of biological neural circuits, and current performance metrics can provide an incomplete picture of model quality. We developed the Computation-through-Dynamics Toolkit (CtDToolkit) to solve these problems. Our toolkit provides three key resources: biologically motivated synthetic datasets, improved metrics that provide more holistic accounts of model performance, and a standardized workflow for training and evaluating models. We hope that CtDToolkit enables researchers to rigorously test, improve, and troubleshoot their models before applying them to real brain data. This work establishes a crucial foundation for developing better methods to understand neural computation, ultimately advancing our ability to decode how the brain transforms sensory information into thought and action.

neuroscience↗
bioRxiv2019

Anterograde Trans-Synaptic AAV Strategies for Probing Neural Circuitry

Elucidating the organization and function of neural circuits is greatly facilitated by viral tools that spread transsynaptically. Adeno-associated virus (AAV) has been shown to exhibit anterograde transneuronal spread. However, the synaptic specificity of the spread and its broad application in various neural circuits remain to be explored. Here, using anatomical, functional, and molecular approaches, we provide strong evidence for the specifically preferential spread of AAV1 to post-synaptically connected neurons. Besides glutamatergic synapses made onto excitatory and inhibitory neurons, AAV1 also transsynaptically spreads through GABAergic synapses and effectively tags spinal cord neurons receiving long-distance projections from various brain regions, but exhibits little or no spread through neuromodulatory projections (e.g. serotonergic, cholinergic, and noradrenergic). Combined with newly designed intersectional and sparse labeling strategies, AAV1 can be utilized to categorize neurons according to their input sources, morphological and molecular identities. These properties make AAV a unique anterograde transsynaptic tool for establishing a comprehensive cell-atlas of the brain.

neuroscience↗
bioRxiv2020

Recurrent circuit based neural population codes for stimulus representation and inference

A large part of the synaptic input received by cortical neurons comes from local cortico-cortical connectivity. Despite their abundance, the role of local recurrent connections in cortical function is unclear, and in simple coding schemes it is often the case that a circuit with no recurrent connections performs optimally. We consider a recurrent excitatory-inhibitory circuit model of a cortical hypercolumn which performs sampling-based Bayesian inference to infer latent hierarchical stimulus features. We show that local recurrent connections can store an internal model of the correlations between stimulus features that are present in the external world. When the resulting recurrent input is combined with feedforward input it produces a population code from which the posterior over the stimulus features can be linearly read out. Internal Poisson spiking variability provides the proper fluctuations for the population to sample stimulus features, yet the resultant population variability is aligned along the stimulus feature direction, producing differential correlations. Importantly, the amplitude of these internally generated differential correlations is determined by the associative prior in the model stored in the recurrent connections. This provides experimentally testable predictions for how population connectivity and response variability are related to the structure of latent external stimuli.

neuroscience↗
bioRxiv2018

Individual variability in behavior and functional networks predicts vulnerability using a predator scent model of PTSD

Only a minority of individuals who experience traumatic event(s) subsequently develop post-traumatic stress disorder (PTSD). However, whether differences in vulnerability to PTSD result from predisposition or a consequence of trauma exposure remains unclear. A major challenge in differentiating these possibilities is that clinical studies focus on individuals already exposed to traumatic experiences, and do not take into account pre-trauma conditions. Here using the predator scent model of PTSD in rats and a longitudinal design, we measured pre-trauma brain-wide neural circuit functional connectivity (FC), behavioral and corticosterone responses to trauma exposure, and post-trauma anxiety. Individual differences in freezing responses to predator scent exposure correlated with differences in pre-trauma FC in a set of neural circuits, especially in olfactory and stress-related systems, indicating that pre-existing function in these circuits could predispose animals to differential fearful responses to threats. Counterintuitively, rats with the lowest freezing showed more avoidance of the predator scent, a prolonged corticosterone response, and higher anxiety long after exposure. This study provides a comprehensive framework of pre-existing circuit function that determines threat response strategy, which might be directly related to the development of PTSD-like behaviors.

neuroscience↗
bioRxiv2022

Defective neuritogenesis in Abcd1/2 deficient rat neurons due to intrinsic and astrocyte-dependent mechanisms

X-linked adrenoleukodystrophy (X-ALD) is a rare neurometabolic and demyelinating disorder caused by loss of function mutations of the ABCD1 transporter that imports very-long-chain fatty acids (VLCFA) into the peroxisome for beta-oxidation. Impaired ABCD1 function results in VLCFA accumulation, which ultimately causes lethal forms of X-ALD in children (CCALD) and adults (CAMN). Because X-ALD is a genetic disorder, we looked for signs of altered neurodevelopmental pathways in the transcriptomes of brain cortical tissues free of pathology from patients that died of CALD or CAMN. Several categories related to brain development, axonal growth, synaptic signaling and synaptic compartments were significantly dysregulated in both CALD and CAMN, suggesting that congenital circuit abnormalities might be structural in brains of mutated ABCD1 carriers. We partially dissected the cellular origin of dysregulated pathways using rat neuronal and astrocytic cultures in which X-ALD was modeled by silencing of Abcd1 and Abcd2 by RNA interference. Abcd2 was silenced lest it compensated for Abcd1 loss. Abcd1/2 deficient neurons presented higher rates of death, reduced sizes and defective formation of spines, dendrites and axons. The aberrant neuron development was caused by cell-autonomous and astrocyte-dependent mechanisms, and involved Wnt signaling, as suggested by the rescue of the expression of a synaptic gene upon pharmacological activation of the Wnt pathway. As recently proposed for neurogenetic disorders such as Huntingtons disease, our data suggest that X-ALD has a neurodevelopmental component that may cause psychiatric alterations and prime neural circuits for neurodegeneration. If this is the case, therapies aimed at restoring neural-circuit function in neurodevelopmental disorders may be reprofiled for X-ALD therapeutics.

neuroscience↗
bioRxiv2017

Dystroglycan Maintains Inner Limiting Membrane Integrity To Coordinate Retinal Development

Proper neural circuit formation requires the precise regulation of neuronal migration, axon guidance and dendritic arborization. Mutations affecting the function of the transmembrane glycoprotein dystroglycan cause a form of congenital muscular dystrophy that is frequently associated with neurodevelopmental abnormalities. Despite its importance in brain development, the role for dystroglycan in regulating retinal development remains poorly understood. Using a mouse model of dystroglycanopathy (ISPDL79*) and conditional dystroglycan mutants of both sexes, we show that dystroglycan is critical for the proper migration, axon guidance and dendritic stratification of neurons in the inner retina. Using genetic approaches, we show that dystroglycan functions in neuroepithelial cells as an extracellular scaffold to maintain the integrity of the retinal inner limiting membrane (ILM). Surprisingly, despite the profound disruptions in inner retinal circuit formation, spontaneous retinal activity is preserved. These results highlight the importance of dystroglycan in coordinating multiple aspects of retinal development.\n\nSignificance StatementThe extracellular environment plays a critical role in coordinating neuronal migration and neurite outgrowth during neural circuit development. The transmembrane glycoprotein dystroglycan functions as a receptor for multiple extracellular matrix proteins, and its dysfunction leads to a form of muscular dystrophy frequently associated with neurodevelopmental defects. Our results demonstrate that dystroglycan is required for maintaining the structural integrity of the inner limiting membrane (ILM) in the developing retina. In the absence of functional dystroglycan, ILM degeneration leads to defective migration, axon guidance and mosaic spacing of neurons, and a loss of multiple neuron types during retinal development. These results demonstrate that disorganization of retinal circuit development is a likely contributor to visual dysfunction in patients with dystroglycanopathy.

neuroscience↗
bioRxiv2023

A rotational velocity estimate constructed through visuomotor competition updates the fly's neural compass

Navigating animals continuously integrate velocity signals to update internal representations of their directional heading and spatial location in the environment. How neural circuits combine sensory and motor information to construct these velocity estimates and how these self-motion signals, in turn, update internal representations that support navigational computations are not well understood. Recent work in Drosophila has identified a neural circuit that performs angular path integration to compute the flys head direction, but the nature of the velocity signal is unknown. Here we identify a pair of neurons necessary for angular path integration that encode the flys rotational velocity with high accuracy using both visual optic flow and motor information. This estimate of rotational velocity does not rely on a moment-to-moment integration of sensory and motor information. Rather, when visual and motor signals are congruent, these neurons prioritize motor information over visual information, and when the two signals are in conflict, reciprocal inhibition selects either the motor or visual signal. Together, our results suggest that flies update their head direction representation by constructing an estimate of rotational velocity that relies primarily on motor information and only incorporates optic flow signals in specific sensorimotor contexts, such as when the motor signal is absent.

neuroscience↗
bioRxiv2025

Methamphetamine Conditioned Place Preference in Adolescent Mice: Interaction Between Sex and Strain

BackgroundMethamphetamine (METH) use is higher in adolescent women than men. While rodent studies support a sex difference in the reinforcing effects of METH, few have investigated sex differences in the underlying neural circuits, none of which tested rodents during adolescence. AimsInvestigate whether there are sex differences in the rewarding effects of METH in two strains of adolescent mice that are commonly used to generate transgenic lines. Identify changes in associated neural circuits. MethodsWe tested METH-induced conditioned place preference (CPP) in male and female 129Sv/Ev and C57Bl/6 mice during middle adolescence using 1mg/kg of METH. Behaviorally-induced upregulation of c-Fos protein expression was quantified in the nucleus accumbens (NAc) and area CA1 of the hippocampus following the post-conditioning test. ResultsIn C57Bl/6 mice, METH induced CPP in females, but not males. Conversely, METH-induced CPP in 129Sv/Ev males, but not females. In both strains, groups that exhibited CPP had more c-Fos+ cells in the NAc and CA1 when compared to saline-treated control groups. The number of c-Fos+ cells in these two brain regions correlated in groups exhibiting CPP, indicating increased NAc-CA1 communication during retrieval of the conditioned memory. Finally, we found evidence of behavioral sensitization in 129Sv/Ev males only. ConclusionsOur study reveals that the rewarding effects of the METH in adolescent mice are both sex- and strain-dependent, indicating that METH response may result from an interaction between sex-specific and genetic mechanisms. Our findings will be informative when selecting an appropriate background strain in future studies using genetically modified mice.

neuroscience↗
bioRxiv2025

Fast Interneuron Dysfunction in Laminar Neural Mass Model Reproduces Alzheimer's Oscillatory Biomarkers

Alzheimers disease (AD) is characterized by a progressive cognitive decline underpinned by disruptions in neural circuit dynamics. Early-stage AD is associated with cortical hyperexcitability, whereas later stages exhibit oscillatory slowing and hypoactivity, a progression observable in electrophysiological spectral characteristics. While previous studies have linked these changes to the dysfunction of fast-spiking parvalbumin-positive (PV) interneurons and neuronal loss associated with amyloid-beta (A{beta}) and hyperphos-phorylated tau (hp-{tau}) pathology, the precise mechanistic relationship between cellular and altered electrophysiology remains unclear. To study this relationship, we employed a Laminar Neural Mass Model that integrates excitatory and inhibitory neural populations within a biophysically informed columnar framework. The connectivity constant from PV cells to pyramidal neurons was gradually reduced to simulate the progressive neurotoxic effects of A{beta} oligomers. Other model parameters were systematically varied to compare with existing modeling literature and also to simulate the effects of hp-{tau}. All model predictions were compared to empirical M/EEG findings in the literature. Our simulations of PV interneuron dysfunction successfully reproduced the biphasic electrophysiological progression observed in AD: an early phase of hyperexcitability with increased gamma and alpha power, followed by oscillatory slowing and reduced spectral power. Alternative mechanisms and model parameters, such as increased excitatory drive, failed to replicate the observed biomarker trajectory. Additionally, to reconcile the hypoactivity and decreased firing rates observed in advanced AD stages, we combined the PV dysfunction model with a disruption of the pyramidal cell populations that reflects the neurotoxicity induced by hp-{tau}. Although this additional mechanism is not necessary to reproduce oscillatory changes in the isolated neural mass, it is crucial for aligning the model with evidence of reduced firing rates, metabolic activity, and cell loss and will enhance its applicability in future whole-brain modeling studies. These results support the hypothesis that at the local level, PV interneuron dysfunction is a primary driver of cortical electrophysiological alterations, while pyramidal neuron loss underlies later-stage severe hypoactivity. Our model provides a mechanistic framework for interpreting excitation-inhibition imbalance across AD progression, demonstrating the value of biophysically constrained models for interpreting electrophysiological biomarkers. Author summaryAlzheimers disease (AD) is not just a disorder of memory--it is a disease of brain networks. Before widespread neuronal loss occurs, the brain enters a state of hyperexcitability, which may contribute to disease progression. This hyperactivity is thought to arise from the selective dysfunction of inhibitory interneurons, particularly parvalbumin-positive (PV) interneurons, which play a crucial role in maintaining balanced brain activity. However, as the disease advances, a dramatic shift occurs, with neurons becoming progressively less active, leading to network breakdown. Understanding how this transition unfolds is essential for identifying new targets for early intervention. In this study, we developed a computational model of AD that represents the effects of amyloid-beta (A{beta}) oligomers and hyperphosphorylated tau (hp-{tau}) on neural circuits in a biologically meaningful way. Our model reproduces key features of M/EEG biomarkers, demonstrating that PV interneuron dysfunction leads to early hyperexcitability and the electrophysiological oscillatory changes characteristic of AD, while pyramidal cell pathology is necessary to drive later hypoactivity and network failure. By bridging molecular pathology mechanisms with mesoscale neural activity, our model provides a powerful tool for studying AD-related circuit dysfunction. It also highlights the importance of PV interneurons as a potential therapeutic target, paving the way for biologically informed interventions that could alter the course of the disease.

neuroscience↗
bioRxiv2023

Laminar Specificity of the Auditory Perceptual Awareness Negativity: A Biophysical Modeling Study

How perception of sensory stimuli emerges from brain activity is a fundamental question of neuroscience. To date, two disparate lines of research have examined this question. On one hand, human neuroimaging studies have helped us understand the large-scale brain dynamics of perception. On the other hand, work in animal models (mice, typically) has led to fundamental insight into the micro-scale neural circuits underlying perception. However, translating such fundamental insight from animal models to humans has been challenging. Here, using biophysical modeling, we show that the auditory awareness negativity (AAN), an evoked response associated with perception of target sounds in noise, can be accounted for by synaptic input to the supragranular layers of auditory cortex (AC) that is present when target sounds are heard but absent when they are missed. This additional input likely arises from cortico-cortical feedback and/or non-lemniscal thalamic projections and targets the apical dendrites of layer-V pyramidal neurons (PNs). In turn, this leads to increased local field potential activity, increased spiking activity in layer-V PNs, and the AAN. The results are consistent with current cellular models of conscious processing and help bridge the gap between the macro and micro levels of perception-related brain activity. Author SummaryTo date, our understanding of the brain basis of conscious perception has mostly been restricted to large-scale, network-level activity that can be measured non-invasively in human subjects. However, we lack understanding of how such network-level activity is supported by individual neurons and neural circuits. This is at least partially because conscious perception is difficult to study in experimental animals, where such detailed characterization of neural activity is possible. To address this gap, we used biophysical modeling to gain circuit-level insight into an auditory brain response known as the auditory awareness negativity (AAN). This response can be recorded non-invasively in humans and is associated with perceptual awareness of sounds of interest. Our model shows that the AAN likely arises from specific cortical layers and cell types. These data help bridge the gap between circuit- and network-level theories of consciousness, and could lead to new, targeted treatments for perceptual dysfunction and disorders of consciousness.

neuroscience↗
bioRxiv2023

The classic psychedelic DOI induces a persistent desynchronized state in medial prefrontal cortex

Administration or consumption of classic psychedelics (CPs) leads to profound changes in experience which are often described as highly novel and meaningful. They have shown substantial promise in treating depressive symptoms and may be therapeutic in other situations. Although research suggests that the therapeutic response is correlated with the intensity of the experience, the neural circuit basis for the alterations in experience caused by CPs requires further study. The medial prefrontal cortex (mPFC), where CPs have been shown to induce rapid, 5-HT2A receptor-dependent structural and neurophysiological changes, is believed to be a key site of action. To investigate the acute neural circuit changes induced by CPs, we recorded single neurons and local field potentials in the mPFC of freely behaving mice after administration of the 5-HT2A/2C receptor-selective CP, 2,5-Dimethoxy-4-iodoamphetamine (DOI). We segregated recordings into active and rest periods in order to examine cortical activity during desynchronized (active) and synchronized (rest) states. We found that DOI induced a robust decrease in low frequency power and decoupled rhythmic activity from neural population dynamics when animals were at rest, attenuating the usual synchronization that occurs during less active behavioral states. DOI also increased broadband gamma power and suppressed activity in fast-spiking neurons in both active and rest periods. Together, these results show that the CP DOI induces persistent desynchronization in mPFC, including during rest when mPFC typically exhibits more synchronized activity. This shift in cortical dynamics may in part underlie the longer-lasting effects of CPs on plasticity, and may be critical to their therapeutic properties.

neuroscience↗
bioRxiv2024

Assembloid model to study loop circuits of the human nervous system

Neural circuits connecting the cerebral cortex, the basal ganglia and the thalamus are fundamental networks for sensorimotor processing and their dysfunction has been consistently implicated in neuropsychiatric disorders1-9. These recursive, loop circuits have been investigated in animal models and by clinical neuroimaging, however, direct functional access to developing human neurons forming these networks has been limited. Here, we use human pluripotent stem cells to reconstruct an in vitro cortico-striatal-thalamic-cortical circuit by creating a four-part loop assembloid. More specifically, we generate regionalized neural organoids that resemble the key elements of the cortico-striatal-thalamic-cortical circuit, and functionally integrate them into loop assembloids using custom 3D-printed biocompatible wells. Volumetric and mesoscale calcium imaging, as well as extracellular recordings from individual parts of these assembloids reveal the emergence of synchronized patterns of neuronal activity. In addition, a multi-step rabies retrograde tracing approach demonstrate the formation of neuronal connectivity across the network in loop assembloids. Lastly, we apply this system to study heterozygous loss of ASH1L gene associated with autism spectrum disorder and Tourette syndrome and discover aberrant synchronized activity in disease model assembloids. Taken together, this human multi-cellular platform will facilitate functional investigations of the cortico-striatal-thalamic-cortical circuit in the context of early human development and in disease conditions.

neuroscience↗
bioRxiv2025

Head stabilization behavior and underlying circuit mechanisms in larval zebrafish

Head stabilization is essential for animal survival, enabling stable sensory input and effective motor coordination. Animals stabilize their heads in response to vestibular stimuli through the vestibulo-collic reflex (VCR). While the VCR has been characterized in tetrapod vertebrates, it remains unknown whether fish, which lack an anatomical neck, employ a comparable behavior. Here, we demonstrate that larval zebrafish exhibit VCR-like behaviors: they adjust their head orientation relative to the body by rostral body flexion during pitch tilts. The rostral body flexed ventrally during head-up posture, whereas it flexed dorsally during head-down posture. These flexions partially compensated for the head pitch changes, thereby contributing to head stabilization. We also identified the muscles and neural circuits responsible for these two types of body flexions. Both the dorsal and ventral flexions were mediated by the same vestibular nucleus, but neural signals were transmitted through distinct pathways, either involving or bypassing a class of reticulospinal neurons. The dorsal and ventral flexions were ultimately produced by specialized dorsal and ventral muscles in the rostral body, respectively. The neural circuits underlying these body flexions in fish share similarities with those underlying the mammalian VCR. Together, our results demonstrate that fish exhibit a VCR-like behavior through comparable circuit mechanisms, suggesting that the VCR is evolutionarily conserved across vertebrates.

neuroscience↗
bioRxiv2023

Neural Mechanism Underlying NEergic Neurons-Modulated The Arousal Associated With Midazolam Anesthesia

The advent of midazolam holds profound implications for modern clinical practice. The hypnotic and sedative effects of midazolam afford it broad clinical applicability. However, the specific mechanisms underlying the modulation of altered consciousness by midazolam remain elusive. Herein, using pharmacology, optogenetics, chemogenetics, fiber photometry, and gene knockdown, we revealed the role of locus coeruleus (LC)-ventrolateral preoptic nucleus (VLPO) noradrenergic neural circuit in regulating midazolam-induced altered consciousness. This effect was mediated by 1 adrenergic receptors. Moreover, gamma-aminobutyric acid receptor type A (GABAA-R) represents a mechanistically crucial binding site in the LC for midazolam. Our findings will provide novel insights into the neural circuit mechanisms underlying the recovery of consciousness after midazolam administration and will help guide the timing of clinical dosing and propose effective intervention targets for timely recovery from midazolam-induced loss of consciousness.

neuroscience↗