Neural Circuits Research Articles

Prefrontal and lateral entorhinal neurons co-dependently learn item-outcome rules.

The ability to learn novel items depends on brain functions that store information about items classified by their associated meanings and outcomes1-4, but the underlying neural circuit mechanisms of this process remain poorly understood. Here we show that deep layers of the lateral entorhinal cortex (LEC) contain two groups of 'item-outcome neurons': one developing activity for rewarded items during learning, and another for punished items. As mice learned an olfactory item-outcome association, we found that the neuronal population of LEC layers 5/6 (LECL5/6) formed an internal map of pre-learned and novel items, classified into dichotomic rewarded versus punished groups. Neurons in the medial prefrontal cortex (mPFC), which form a bidirectional loop circuit with LECL5/6, developed an equivalent item-outcome rule map during learning. When LECL5/6 neurons were optogenetically inhibited, tangled mPFC representations of novel items failed to split into rewarded versus punished groups, impairing new learning by mice. Conversely, when mPFC neurons were inhibited, LECL5/6 representations of individual items were held completely separate, disrupting both learning and retrieval of associations. These results suggest that LECL5/6 neurons and mPFC neurons co-dependently encode item memory as a map of associated outcome rules.

Oligodendrocytes and myelin limit neuronal plasticity in visual cortex.

Developmental myelination is a protracted process in the mammalian brain1. One theory for why oligodendrocytes mature so slowly posits that myelination may stabilize neuronal circuits and temper neuronal plasticity as animals age2-4. We tested this theory in the visual cortex, which has a well-defined critical period for experience-dependent neuronal plasticity5. During adolescence, visual experience modulated the rate of oligodendrocyte maturation in visual cortex. To determine whether oligodendrocyte maturation in turn regulates neuronal plasticity, we genetically blocked oligodendrocyte differentiation and myelination in adolescent mice. In adult mice lacking adolescent oligodendrogenesis, a brief period of monocular deprivation led to a significant decrease in visual cortex responses to the deprived eye, reminiscent of the plasticity normally restricted to adolescence. This enhanced functional plasticity was accompanied by a greater turnover of dendritic spines and coordinated reductions in spine size following deprivation. Furthermore, inhibitory synaptic transmission, which gates experience-dependent plasticity at the circuit level, was diminished in the absence of adolescent oligodendrogenesis. These results establish a critical role for oligodendrocytes in shaping the maturation and stabilization of cortical circuits and support the concept of developmental myelination acting as a functional brake on neuronal plasticity.

The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality

Scaling relationships are key in characterizing complex systems at criticality. In the brain, they are evident in neuronal avalanches—scale-invariant cascades of neuronal activity quantified by power laws. Avalanches manifest at the cellular level as cascades of neuronal groups that fire action potentials simultaneously. Such spatiotemporal synchronization is vital to theories on brain function yet avalanche synchronization is often underestimated when only a fraction of neurons is observed. Here, we investigate biases from fractional sampling within a balanced network of excitatory and inhibitory neurons with all-to-all connectivity and critical branching process dynamics. We focus on how mean avalanche size scales with avalanche duration. For parabolic avalanches, this scaling is quadratic, quantified by the scaling exponent, χ = 2, reflecting rapid spatial expansion of simultaneous neuronal firing over short durations. However, in networks sampled fractionally, χ is significantly lower. We demonstrate that applying temporal coarse-graining and increasing a minimum threshold for coincident firing restores χ = 2, even when as few as 0.1% of neurons are sampled. This correction crucially depends on the network being critical and fails for near sub- and supercritical branching dynamics. Using cellular 2-photon imaging, our approach robustly identifies χ = 2 over a wide parameter regime in ongoing neuronal activity from frontal cortex of awake mice. In contrast, the common ‘crackling noise’ approach fails to determine χ under similar sampling conditions at criticality. Our findings overcome scaling bias from fractional sampling and demonstrate rapid, spatiotemporal synchronization of neuronal assemblies consistent with scale-invariant, parabolic avalanches at criticality.

Kernel heterogeneity improves sparseness of natural images representations

Abstract Both biological and artificial neural networks inherently balance their performance with their operational cost, which characterizes their computational abilities. Typically, an efficient neuromorphic neural network is one that learns representations that reduce the redundancies and dimensionality of its input. For instance, in the case of sparse coding (SC), sparse representations derived from natural images yield representations that are heterogeneous, both in their sampling of input features and in the variance of those features. Here, we focused on this notion, and sought correlations between natural images’ structure, particularly oriented features, and their corresponding sparse codes. We show that representations of input features scattered across multiple levels of variance substantially improve the sparseness and resilience of sparse codes, at the cost of reconstruction performance. This echoes the structure of the model’s input, allowing to account for the heterogeneously aleatoric structures of natural images. We demonstrate that learning kernel from natural images produces heterogeneity by balancing between approximate and dense representations, which improves all reconstruction metrics. Using a parametrized control of the kernels’ heterogeneity of a convolutional SC algorithm, we show that heterogeneity emphasizes sparseness, while homogeneity improves representation granularity. In a broader context, this encoding strategy can serve as inputs to deep convolutional neural networks. We prove that such variance-encoded sparse image datasets enhance computational efficiency, emphasizing the benefits of kernel heterogeneity to leverage naturalistic and variant input structures and possible applications to improve the throughput of neuromorphic hardware.

Moment neural network and an efficient numerical method for modeling irregular spiking activity.

Continuous rate-based neural networks have been widely applied to modeling the dynamics of cortical circuits. However, cortical neurons in the brain exhibit irregular spiking activity with complex correlation structures that cannot be captured by mean firing rate alone. To close this gap, we consider a framework for modeling irregular spiking activity, called the moment neural network, which naturally generalizes rate models to second-order moments and can accurately capture the firing statistics of spiking neural networks. We propose an efficient numerical method that allows for rapid evaluation of moment mappings for neuronal activations without solving the underlying Fokker-Planck equation. This allows simulation of coupled interactions of mean firing rate and firing variability of large-scale neural circuits while retaining the advantage of analytical tractability of continuous rate models. We demonstrate how the moment neural network can explain a range of phenomena including diverse Fano factor in networks with quenched disorder and the emergence of irregular oscillatory dynamics in excitation-inhibition networks with delay.

Neural Development and Repair Induced by Femtosecond Laser Stimulation.

Dendritic spines function as postsynaptic sites, receiving excitatory signals from presynaptic axons. The synaptic plasticity of spines underlies the refinement of neuronal circuits. Neural cognitive disorders are commonly associated with the impairment and elimination of dendritic spines. In this study, we report an all-optical method to activate dendritic spine growth and regeneration by a single short flash of femtosecond laser stimulation. The inhibited development and loss of spines can be rescued by a transient illumination of the laser inside a micrometer region of the soma by activating the extracellular signal-regulated kinase (ERK) signaling pathway. The rescued neurons exhibit function. Hence we provide a potential noninvasive method for the regeneration of dendritic spines.

Effects of chronic insecticide exposure on neuronal network development in vitro in rat cortical cultures.

Developmental exposure to carbamates, organophosphates, and pyrethroids has been associated with impaired neurodevelopmental outcomes. Sex-specific differences following chronic insecticide exposure are rather common in vivo. Therefore, we assessed the chronic effects of in vitro exposure to different carbamates (carbaryl, methomyl and aldicarb), organophosphates [chlorpyrifos (CPF), chlorpyrifos-oxon (CPO), and 3,5,6,trichloropyridinol (TCP)], and pyrethroids [permethrin, alpha-cypermethrin and 3-phenoxy benzoic acid (3-PBA)] on neuronal network development in sex-separated rat primary cortical cultures using micro-electrode array (MEA) recordings. Our results indicate that exposure for 1week to carbaryl inhibited neurodevelopment in male cultures, while a hyperexcitation was observed in female cultures. Methomyl and aldicarb evoked a hyperexcitation after 2weeks of exposure, which was more pronounced in female cultures. In contrast to acute MEA results, exposure to ≥ 10µM CPF caused hyperexcitation in both sexes after 10days. Interestingly, exposure to 10µM CPO induced a clear hyperexcitation after 10days of exposure in male but not female cultures. Exposure to 100µM CPO strongly inhibited neuronal development. Exposure to the type I pyrethroid permethrin resulted in a hyperexcitation at 10µM and a decrease in neuronal development at 100µM. In comparison, exposure to ≥ 10µM of the type II pyrethroid alpha-cypermethrin decreased neuronal development. In female but not in male cultures, exposure to 1 and 10µM permethrin changed (network) burst patterns, with female cultures having shorter (network) bursts with fewer spikes per (network) burst. Together, these results show that MEA recordings are suitable for measuring sex-specific developmental neurotoxicity in vitro. Additionally, pyrethroid exposure induced effects on neuronal network development at human-relevant concentrations. Finally, chronic exposure has different effects on neuronal functioning compared to acute exposure, highlighting the value of both exposure paradigms.

Using DeepLabCut-Live to probe state dependent neural circuits of behavior with closed-loop optogenetic stimulation.

Closed-loop behavior paradigms enable us to dissect the state-dependent neural circuits underlying behavior in real-time. However, studying context-dependent locomotor perturbations has been challenging due to limitations in molecular tools and techniques for real-time manipulation of spinal cord circuits. We developed a novel closed-loop optogenetic stimulation paradigm that utilizes DeepLabCut-Live pose estimation to manipulate primary sensory afferent activity at specific phases of the locomotor cycle in mice. A compact DeepLabCut model was trained to track hindlimb kinematics in real-time and integrated into the Bonsai visual programming framework. This allowed an LED to be triggered to photo-stimulate sensory neurons expressing channelrhodopsin at user-defined pose-based criteria, such as during the stance or swing phase. Optogenetic activation of nociceptive TRPV1 + sensory neurons during treadmill locomotion reliably evoked paw withdrawal responses. Photoactivation during stance generated a brief withdrawal, while stimulation during swing elicited a prolonged response likely engaging stumbling corrective reflexes. Comparison with Existing Methods: This new method allows for high spatiotemporal precision in manipulating spinal circuits based on the phase of the locomotor cycle. Unlike previous approaches, this closed-loop system can control for the state-dependent nature of sensorimotor responses during locomotion. Integrating DeepLabCut-Live with optogenetics provides a powerful new approach to dissect the context-dependent role of sensory feedback and spinal interneurons in modulating locomotion. This technique opens new avenues for uncovering the neural substrates of state-dependent behaviors and has broad applicability for studies of real-time closed-loop manipulation based on pose estimation. Highlights: Closed-loop system probes state-dependent behaviors at pose-modulated instancesBonsai integrates DeepLabCut models for real-time pose estimation during locomotion Phase-dependent TRPV1 + sensory afferent photostimulation elicits context-specific withdrawal responses.

Chronic Neuronal Hyperexcitation Exacerbates Tau Propagation in a Mouse Model of Tauopathy.

The intracerebral spread of tau is a critical mechanism associated with functional decline in Alzheimer's disease (AD) and other tauopathies. Recently, a hypothesis has emerged suggesting that tau propagation is linked to functional neuronal connections, specifically driven by neuronal hyperactivity. However, experimental validation of this hypothesis remains limited. In this study, we investigated how tau propagation from the entorhinal cortex to the hippocampus, the neuronal circuit most susceptible to tau pathology in AD, is affected by the selective stimulation of neuronal activity along this circuit. Using a mouse model of seed-induced propagation combined with optogenetics, we found that the chronic stimulation of this neuronal connection over a 4-week period resulted in a significant increase in insoluble tau accumulation in both the entorhinal cortex and hippocampus. Importantly, the ratio of tau accumulation in the hippocampus relative to that in the entorhinal cortex, serving as an indicator of transcellular spreading, was significantly higher in mice subjected to chronic stimulation. These results support the notion that abnormal neuronal activity promotes tau propagation, thereby implicating it in the progression of tauopathy.

Spontaneous Emergence of Robustness to Light Variation in CNNs With a Precortically Inspired Module.

The analogies between the mammalian primary visual cortex and the structure of CNNs used for image classification tasks suggest that the introduction of an additional preliminary convolutional module inspired by the mathematical modeling of the precortical neuronal circuits can improve robustness with respect to global light intensity and contrast variations in the input images. We validate this hypothesis using the popular databases MNIST, FashionMNIST, and SVHN for these variations once an extra module is added.

Homeostatic Regulation of Spike Rate within Bursts in Two Distinct Preparations.

Homeostatic plasticity represents a set of mechanisms thought to stabilize some function of neural activity. Here, we identified the specific features of cellular or network activity that were maintained after the perturbation of GABAergic blockade in two different systems: mouse cortical neuronal cultures where GABA is inhibitory and motoneurons in the isolated embryonic chick spinal cord where GABA is excitatory (males and females combined in both systems). We conducted a comprehensive analysis of various spiking activity characteristics following GABAergic blockade. We observed significant variability in many features after blocking GABAA receptors (e.g., burst frequency, burst duration, overall spike frequency in culture). These results are consistent with the idea that neuronal networks achieve activity goals using different strategies (degeneracy). On the other hand, some features were consistently altered after receptor blockade in the spinal cord preparation (e.g., overall spike frequency). Regardless, these features did not express strong homeostatic recoveries when tracking individual preparations over time. One feature showed a consistent change and homeostatic recovery following GABAA receptor block. We found that spike rate within a burst (SRWB) increased after receptor block in both the spinal cord preparation and cortical cultures and then returned to baseline within hours. These changes in SRWB occurred at both single cell and population levels. Our findings indicate that the network prioritizes the burst spike rate, which appears to be a variable under tight homeostatic regulation. The result is consistent with the idea that networks can maintain an appropriate behavioral response in the face of challenges.

Cyclase-associated protein (CAP) inhibits inverted formin 2 (INF2) to induce dendritic spine maturation

The morphology of dendritic spines, the postsynaptic compartment of most excitatory synapses, decisively modulates the function of neuronal circuits as also evident from human brain disorders associated with altered spine density or morphology. Actin filaments (F-actin) form the backbone of spines, and a number of actin-binding proteins (ABP) have been implicated in shaping the cytoskeleton in mature spines. Instead, only little is known about the mechanisms that control the reorganization from unbranched F-actin of immature spines to the complex, highly branched cytoskeleton of mature spines. Here, we demonstrate impaired spine maturation in hippocampal neurons upon genetic inactivation of cyclase-associated protein 1 (CAP1) and CAP2, but not of CAP1 or CAP2 alone. We found a similar spine maturation defect upon overactivation of inverted formin 2 (INF2), a nucleator of unbranched F-actin with hitherto unknown synaptic function. While INF2 overactivation failed in altering spine density or morphology in CAP-deficient neurons, INF2 inactivation largely rescued their spine defects. From our data we conclude that CAPs inhibit INF2 to induce spine maturation. Since we previously showed that CAPs promote cofilin1-mediated cytoskeletal remodeling in mature spines, we identified them as a molecular switch that control transition from filopodia-like to mature spines.

Nogo Receptor Antagonist LOTUS Promotes Neurite Outgrowth through Its Interaction with Teneurin-4.

Neurite outgrowth is a crucial process for organizing neuronal circuits in neuronal development and regeneration after injury. Regenerative failure in the adult mammalian central nervous system (CNS) is attributed to axonal growth inhibitors such as the Nogo protein that commonly binds to Nogo receptor-1 (NgR1). We previously reported that lateral olfactory tract usher substance (LOTUS) functions as an endogenous antagonist for NgR1 in forming neuronal circuits in the developing brain and improving axonal regeneration in the adult injured CNS. However, another molecular and cellular function of LOTUS remains unknown. In this study, we found that cultured retinal explant neurons extend their neurites on the LOTUS-coating substrate. This action was also observed in cultured retinal explant neurons derived from Ngr1-deficient mouse embryos, indicating that the promoting action of LOTUS on neurite outgrowth may be mediated by unidentified LOTUS-binding protein(s). We therefore screened the binding partner(s) of LOTUS by using a liquid chromatography-tandem mass spectrometry (LC-MS/MS). LC-MS/MS analysis and pull-down assay showed that LOTUS interacts with Teneurin-4 (Ten-4), a cell adhesion molecule. RNAi knockdown of Ten-4 inhibited neurite outgrowth on the LOTUS substrate in retinoic acid (RA)-treated Neuro2A cells. Furthermore, a soluble form of Ten-4 attenuates the promoting action on neurite outgrowth in cultured retinal explant neurons on the LOTUS substrate. These results suggest that LOTUS promotes neurite outgrowth by interacting with Ten-4. Our findings may provide a new molecular mechanism of LOTUS to contribute to neuronal circuit formation in development and to enhance axonal regeneration after CNS injury.

Gliomagenesis, Epileptogenesis, and Remodeling of Neural Circuits: Relevance for Novel Treatment Strategies in Low- and High-Grade Gliomas.

Gliomas present a complex challenge in neuro-oncology, often accompanied by the debilitating complication of epilepsy. Understanding the biological interaction and common pathways between gliomagenesis and epileptogenesis is crucial for improving the current understanding of tumorigenesis and also for developing effective management strategies. Shared genetic and molecular mechanisms, such as IDH mutations and dysregulated glutamate signaling, contribute to both tumor progression and seizure development. Targeting these pathways, such as through direct inhibition of mutant IDH enzymes or modulation of glutamate receptors, holds promise for improving patient outcomes. Additionally, advancements in surgical techniques, like supratotal resection guided by connectomics, offer opportunities for maximally safe tumor resection and enhanced seizure control. Advanced imaging modalities further aid in identifying epileptogenic foci and tailoring treatment approaches based on the tumor's metabolic characteristics. This review aims to explore the complex interplay between gliomagenesis, epileptogenesis, and neural circuit remodeling, offering insights into shared molecular pathways and innovative treatment strategies to improve outcomes for patients with gliomas and associated epilepsy.

High-Frequency Imaging Reveals Synchronised Delta- and Theta-Band Ca2+ Oscillations in the Astrocytic Soma In Vivo.

One of the major breakthroughs of neurobiology was the identification of distinct ranges of oscillatory activity in the neuronal network that were found to be responsible for specific biological functions, both physiological and pathological in nature. Astrocytes, physically coupled by gap junctions and possessing the ability to simultaneously modulate the functions of a large number of surrounding synapses, are perfectly positioned to introduce synchronised oscillatory activity into the neural network. However, astrocytic somatic calcium signalling has not been investigated to date in the frequency ranges of common neuronal oscillations, since astrocytes are generally considered to be slow responders in terms of Ca2+ signalling. Using high-frequency two-photon imaging, we reveal fast Ca2+ oscillations in the soma of astrocytes in the delta (0.5-4 Hz) and theta (4-8 Hz) frequency bands in vivo in the rat cortex under ketamine-xylazine anaesthesia, which is known to induce permanent slow-wave sleep. The high-frequency astrocytic Ca2+ signals were not observed under fentanyl anaesthesia, excluding the possibility that the signals were introduced by motion artefacts. We also demonstrate that these fast astrocytic Ca2+ signals, previously considered to be exclusive to neurons, are present in a large number of astrocytes and are phase synchronised at the astrocytic network level. We foresee that the disclosure of these high-frequency astrocytic signals may help with understanding the appearance of synchronised oscillatory signals and may open up new avenues of treatment for neurological conditions characterised by altered neuronal oscillations.

Altered functional connectivity of primary olfactory cortex-hippocampus-frontal cortex in subjective cognitive decline during odor stimulation.

Subjective cognitive decline (SCD) is a high-risk population in the preclinical stage of Alzheimer's disease (AD), and olfactory dysfunction is a risk factor for dementia progression. The present study aimed to explore the patterns of functional connectivity (FC) changes in the olfactory neural circuits during olfactory stimulation in SCD subjects. A total of 56 SCD subjects and 56 normal controls (NCs) were included. All subjects were assessed with a cognitive scale, an olfactory behavior test, and olfactory task-based functional magnetic resonance imaging scanning. The FC differences in olfactory neural circuits between the two groups were analyzed by the generalized psychophysiological interaction. Additionally, we calculated and compared the activation of brain regions within the olfactory neural circuits during odor stimulation, the volumetric differences in brain regions showing FC differences between groups, and the correlations between neuroimaging indicators and olfactory behavioral and cognitive scale scores. During odor stimulation, the FC between the bilateral primary olfactory cortex (bPOC) and the right hippocampus in the SCD group was significantly reduced; while the FC between the right hippocampus and the right frontal cortex was significantly increased in the SCD group. The bPOC of all subjects showed significant activation, but no significant difference in activation between groups was found. No significant differences were observed in the volume of the brain regions within the olfactory neural circuits or in olfactory behavior between groups. The volume of the bPOC and right frontal cortex was significantly positively correlated with olfactory identification, and the volume of the right frontal cortex and right hippocampus was significantly correlated with cognitive functions. Furthermore, a significant correlation between the activation of bPOC and the olfactory threshold was found in the whole cohort. These results suggested that while the structure of the olfactory neural circuits and olfactory behavior in SCD subjects remained stable, there were significant changes observed in the FC of the olfactory neural circuits (specifically, the POC-hippocampus-frontal cortex neural circuits) during odor stimulation. These findings highlight the potential of FC alterations as sensitive imaging markers for identifying high-risk individuals in the early stage of AD.

Functional and structural maturation of auditory cortex from 2 months to 2 years old

BackgroundIn school-age children, the myelination of the auditory radiation thalamocortical pathway is associated with the latency of auditory evoked responses, with the myelination of thalamocortical axons facilitating the rapid propagation of acoustic information. Little is known regarding this auditory system function-structure association in infants and toddlers. Methods and ParticipantsThe present study tested the hypothesis that maturation of auditory radiation white-matter microstructure (e.g., fractional anisotropy (FA); measured using diffusion-weighted MRI) is associated with the latency of the infant auditory response (the P2m response, measured using magnetoencephalography, MEG) in a cross-sectional (N = 47, 2 to 24 months, 19 females) as well as longitudinal cohort (N = 18, 2 to 29 months, 8 females) of typically developing infants and toddlers. Of 18 longitudinal infants, 2 infants had data from 3 timepoints and 16 infants had data from 2 timepoints. ResultsIn the cross-sectional sample, non-linear maturation of P2m latency and auditory radiation diffusion measures were observed. Auditory radiation diffusion accounted for significant variance in P2m latency, even after removing the variance associated with age in both P2m latency and auditory radiation diffusion measures. In the longitudinal sample, latency and FA associations could be observed at the level of a single child. ConclusionsFindings provide strong support for the hypothesis that an increase in thalamocortical neural conduction velocity, due to increased axon diameter and/or myelin maturation, contributes to a decrease in the infant P2m auditory evoked response latency. SignificanceInfant multimodal brain imaging identifies brain mechanisms contributing to the rapid changes in neural circuit activity during the first two years of life.

The Neurobiology of Parenting and Infant-Evoked Aggression.

Parenting behavior comprises a variety of adult-infant and adult-adult interactions across multiple timescales that require an extensive reorganization of individual priorities and physiology. The state transition from non-parent to parent is facilitated by combinatorial hormone action on specific cell types that are integrated throughout interconnected and brain-wide neuronal circuits. In this review we take a comprehensive approach to integrate historical and current literature on each of these topics across multiple species, with a focus on rodents. New and emerging molecular, circuit based and computational technologies have recently been used to address outstanding gaps in our current framework of knowledge on infant-mediated behavior, mainly in murine models. This work is raising fundamental questions about the interplay between instinctive and learned components of parenting and the mutual regulation of parenting and anti-parenting behaviors in health and disease. Whenever possible, we point to how these technologies have helped gain novel insights, while opening new avenues of research into studies of parenting. We hope this review will serve as an introduction for those new to the field, a comprehensive resource for those already studying parenting, and a guidepost for designing future studies.

Inference on the Macroscopic Dynamics of Spiking Neurons.

The process of inference on networks of spiking neurons is essential to decipher the underlying mechanisms of brain computation and function. In this study, we conduct inference on parameters and dynamics of a mean-field approximation, simplifying the interactions of neurons. Estimating parameters of this class of generative model allows one to predict the system's dynamics and responses under changing inputs and, indeed, changing parameters. We first assume a set of known state-space equationsand address the problem of inferring the lumped parameters from observed time series. Crucially, we consider this problem in the setting of bistability, random fluctuations in system dynamics, and partial observations, in which some states are hidden. To identify the most efficient estimation or inversion scheme in this particular system identification, we benchmark against state-of-the-art optimization and Bayesian estimation algorithms, highlighting their strengths and weaknesses. Additionally, we explore how well the statistical relationships between parameters are maintained across different scales. We found that deep neural density estimators outperform other algorithms in the inversion scheme, despite potentially resulting in overestimated uncertainty and correlation between parameters. Nevertheless, this issue can be improved by incorporating time-delay embedding. We then eschew the mean-field approximation and employ deep neural ODEs on spiking neurons, illustrating prediction of system dynamics and vector fields from microscopic states. Overall, this study affords an opportunity to predict brain dynamics and responses to various perturbations or pharmacological interventions using deep neural networks.

Dissecting reactive astrocyte responses: lineage tracing and morphology-based clustering

Brain damage triggers diverse cellular and molecular events, with astrocytes playing a crucial role in activating local neuroprotective and reparative signaling within damaged neuronal circuits. Here, we investigated reactive astrocytes using a multidimensional approach to categorize their responses into different subtypes based on morphology. This approach utilized the StarTrack lineage tracer, single-cell imaging reconstruction and multivariate data analysis. Our findings identified three profiles of reactive astrocyte responses, categorized by their effects on cell size- and shape- related morphological parameters: “moderate”, “strong,” and “very strong”. We also examined the heterogeneity of astrocyte reactivity, focusing on spatial and clonal distribution. Our research revealed a notable enrichment of protoplasmic and fibrous astrocytes within the “strong” and “very strong” response subtypes. Overall, our study contributes to a better understanding of astrocyte heterogeneity in response to an injury. By characterizing the diverse reactive responses among astrocyte subpopulations, we provide insights that could guide future research aimed at identifying novel therapeutic targets to mitigate brain damage and promote neural repair.Graphical