bioRxiv Subject Collection: Neuroscience's Journal

Precision Functional Mapping of the Individual Human Brain Near Birth
Cortical areas are a fundamental organizational property of the brain, but their development in humans is not well understood. Key unanswered questions include whether cortical areas are fully established near birth, the extent of individual variation in the arrangement of cortical areas, and whether any such individual variation in cortical area location is greater in later-developing association areas as compared to earlier-developing sensorimotor areas. To address these questions, we used functional MRI to collect precision functional mapping (PFM) data in eight individual neonates (mean 42.7 weeks postmenstrual age) over 2-5 days (mean 77.9 minutes of low motion data per subject [framewise displacement <0.1]). Each subjects dataset was split into two roughly equal halves of data from different days of data collection to measure within-subject reliability and across-subject similarity. Whole-brain patterns of functional connectivity (FC) reached a mean within-subject, across-day reliability of r=0.78 with 41.9 minutes of data. Across subject similarity of whole-brain FC was r=0.62 on average and significantly lower than within-subject similarity (t=5.9, p<0.001). Using established methods to identify transitions in FC across the cortical surface, we identified sets of cortical areas for each individual that were subject-specific and highly reliable across split-halves (mean z=4.4, SD=1.4). The arrangement of cortical areas was thus individually specific across the entire cortical surface, and this individual specificity did not vary as a function of the sensorimotor-association axis. This study establishes the feasibility of neonatal PFM and suggests that cortical area arrangement is individually specific and largely established shortly following birth.

Calbindin Stratifies Midbrain Dopaminergic Neurons Governing Distinct Aspects of Locomotion
Despite advances in delineating the molecular diversity and projection patterns of midbrain dopaminergic (DA) neurons, their specific contributions to locomotion and motor learning remain poorly defined. Here, we applied intersectional ablation and chemogenetic approaches to dissect the distinct roles of calbindin-expressing (CALB1+) and non-expressing (CALB1-) DA neurons in locomotion. Using newly engineered intersectional constructs, we ablated CALB1+ or CALB1- DA neurons in the mouse midbrain. Loss of either subtype led to pronounced deficits in the initiation and vigor of voluntary movements, as demonstrated by a reduction in peak speed, acceleration and deceleration of locomotor bouts. Notably, only CALB1- ablation disrupted locomotor learning. Beyond these functional effects, we observed that selective ablation of CALB1 DA neurons induced local microglial activation and was followed by a non-cell-autonomous loss of CALB1- DA neurons, suggesting that CALB1- neurons are more vulnerable to inflammation triggered by CALB1 neuron loss. We then confirmed these findings by performing acute inhibition of either population using inhibitory DREADD hM4Di. CALB1- DA neurons inhibition impaired the initial acquisition of locomotor learning, whereas inhibition of CALB1+ DA neurons disrupted the retention of acquired motor skills from previous days. Moreover, inhibition of CALB1+ DA neurons further impaired the initiation and amplitude of voluntary movements, as well as the velocity and acceleration/deceleration of locomotor bouts. Together, these findings provide causal evidence for functional specialization among molecularly distinct midbrain DA subtypes and reveal new aspects of mesostriatal circuit organization underlying locomotion and motor memory.

Administration of barcoded AAV capsid library to the putamen of non-human primates identifies variants with efficient retrograde transport
Adeno-associated viral vectors have become a leading choice for gene therapy in the central nervous system due to their safety profile, efficient neuronal transduction, and capacity for sustained transgene expression. We previously reported that AAV2-derived capsids developed using the BRAVE (Barcoded Rational AAV Vector Evolution) approach have enhanced retrograde transport properties in the rodent brain, compared to parental AAV2. Retrograde transport enables broader coverage of connected brain regions after a single focal intraparenchymal brain injection and is therefore a powerful tool for delivery of vectors to distant sites with potentially higher specificity, transduction efficacy and safety. Because transport properties can vary among species, we further characterized a barcoded library of 25 BRAVE-derived AAV2 capsid variants, along with the parental AAV2 serotype and benchmark AAV capsids, in brains of adult cynomolgus monkeys after intraputaminal dosing. Based on RNA and DNA amplicon sequencing, single-nucleus RNA sequencing, and histological assessment, we report here capsid variants with enhanced retrograde transport and expression compared to the parental AAV2 capsid. These properties make them potentially useful for disease indications in which broader brain coverage is desirable beyond the injection site.

Contributions from Long-Term Memory Explain Superior Visual Working Memory Performance with Meaningful Objects
Visual working memory (WM) capacity has recently been claimed to be higher for meaningful objects compared to simple visual features, possibly due to richer and more distinctive representations. However, prior demonstrations of this advantage have typically compared performance with meaningful stimuli that are trial-unique to performance with a small set of repeated simple stimuli (e.g., colors). This design creates a confound between the strength of proactive interference (PI) and meaningfulness, such that PI is minimized for meaningful items compared to colors. Thus, improved WM performance with meaningful objects could reflect enhanced contributions from episodic long term memory (LTM), a memory system that is highly vulnerable to PI, rather than an increase in WM capacity. To examine this issue, Experiment 1 measured WM capacity for repeated colors, repeated meaningful objects, and trial-unique meaningful objects. We replicated the previously observed advantage for trial-unique objects over colors. Critically, this advantage was eliminated entirely with repeated meaningful objects that equated PI across the meaningful and simple stimuli, suggesting that minimal PI, not meaningfulness, drove this behavioral effect. In line with this hypothesis, hierarchical Bayesian dual-process signal detection modeling suggested that the advantage for trial-unique objects was due to enhanced familiarity-based LTM signals rather than recollection-based WM processes. To directly measure online storage in WM, Experiment 2 measured contralateral delay activity (CDA), an electrophysiological marker of the number of items stored in working memory. Although we saw the typical performance benefits for trial-unique objects over repeated colors, CDA activity across increasing set sizes revealed a common plateau for trial-unique meaningful objects and repeated colors, indicating a WM storage limit that is independent of stimulus meaningfulness. Thus, past demonstrations of superior memory performance with meaningful stimuli can be explained by a task design that minimized PI for meaningful compared to simple stimuli. When PI is equated, WM storage limits for simple and meaningful stimuli are equivalent.

Intertemporal choice across short and long time horizons: an fMRI study
This preregistered fMRI study investigates the neural mechanisms underlying intertemporal choices involving waiting and postponing. On a behavioral level, choices made regarding rewards available in seconds that require waiting compared to choices about rewards postponed to a number days are surprisingly similar. The explanation to this short/long time scales gap is lacking even after considering time perception and external factors, such as stress. To address that this study is the first to examine the overlapping and distinct neural circuitry involved in the intertemporal choices over seconds and days, and the waiting period within subject. Our results revealed considerable overlap in brain activation during choices that consider seconds and days delays to reward in the executive control (dACC, dlPFC) and prospection (PCC/precuneus, dmPFC) networks, but not in the valuation network. Consistent with existent literature we found the valuation network activation (both vmPFC and ventral striatum) being parametrically modulated by individual subjective values of delayed rewards. Overall, the key network determined through representational similarity and decoding analyses was prospection accounting for similarity in activation during decision making across time scales of delays and discriminating between waiting and postponing the reward. These findings enhance our understanding of the neural underpinnings of intertemporal choices and their implications for real-life decisions occurring across varying time horizons, such as paying to skip advertisements while watching videos or deciding on the next-day delivery service.

Tonic GABAA receptor currents in Cerebellar Purkinje cells of wild-type and DMDmdx mice
Cerebellar Purkinje cells (PCs) fire spontaneously in the absence of excitatory input and depend heavily on inhibition to modify their firing activity. Previous work in the field has described phasic inhibition arising primarily from molecular layer interneuron-PC (MLI-PC) synapses extensively, however little work explores other sources of inhibition in PCs. Several types of neurons throughout the brain and within the cerebellum receive significant inhibition through tonic currents, a low amplitude current resulting from ambient GABA acting upon extrasynaptic GABAA receptors. Through the use of ex vivo electrophysiology and single cell RNA analysis, we investigated the role of tonic inhibition in PCs. We find that PCs have a significant tonic current mediated by {delta}-subunit containing GABAA receptors, which accounts for roughly half of the total inhibitory current. We also examined PC tonic GABA currents in DMDmdx mice, a mouse model of Duchenne Muscular Dystrophy with ~50% reduction in phasic inhibitory currents. We find that tonic inhibition is dramatically upregulated in DMDmdx PCs, suggesting a possible compensatory mechanism to account for the loss in phasic inhibition. Furthermore, roughly 80% of the total inhibition is derived from tonic currents in this condition. These data suggest that under physiological conditions, PCs are subject to both tonic and phasic inhibition, and that adjustments in the balance of inhibition may be a physiological mechanism for PC function. These data reveal an expanded range of inhibitory currents in PC which may be critical to regulating PC activity in both normal and pathophysiological states.

Identification of functional neural networks of human brains with fMRI
The highly evolved human brain comprises numerous functional systems, ranging from essential sensory, motor, attention and memory networks to higher-order cognitive functions like reasoning and language. Although these neural systems and cognitive functions are separately distributed across the entire brain, they are functionally integrated together to perform a task. Decision-making and executive functioning may also be involved in performing the task. While studying task-evoked brain networks is important, investigating whole-brain activity could be crucial for understanding the neural underpinnings of individual behavioral and clinical traits. Even when the brain is not actively engaged in a task, the intrinsic neural activity, i.e., the resting-state (rs) activity, maintains the operations of the brain that involve the acquisition and maintenance of information for interpreting, responding to, and predicting environmental demands. This intrinsic activity is also functionally organized into networks like the brain default mode network. Investigating its whole-brain activity could also be crucial for understanding the neural underpinnings of the operations of the brain at rest. We report a novel data-driven method to objectively and automatically identify functional neural networks (FNNs) across the entire brain for both brain states measured with rs- and task-fMRI, respectively. The identified FNNs characterize the whole-brain activity holistically for each brain state and each individual subject.

Altered lysosomal biology impairs motor neuron survival via TFEB dysregulation in spinal muscular atrophy
Spinal muscular atrophy (SMA) is a devastating motor neuron disease, caused by recessive mutations or deletions of the SMN1 gene, representing the leading genetic cause of infant mortality. Available therapies, aimed at increasing SMN protein levels, can only partially halt motor neuron (MN) degeneration in a select number of patients, reinforcing the need for combinatorial treatments to improve clinical outcomes. We previously showed that mTORC1 overactivation and impaired autophagosome clearance in SMA MNs lead to the accumulation of protein aggregates, contributing to MN degeneration. However, the mechanistic link between SMN protein deficiency and autophagy-lysosomal dysfunction remained unknown. Here, using patient iPSC-derived MNs along with isogenic and healthy controls, we show that SMA MNs exhibit reduced lysosome numbers and impaired functionality. Furthermore, the master regulator of lysosomal biogenesis and autophagy, TFEB, is downregulated, and its nuclear translocation compromised upon SMN deficiency. We further propose the upregulation of the mTORC1 positive modulator TPT1 as contributor to TFEB dysregulation. Notably, TFEB overexpression ameliorates protein aggregate accumulation in SMA MNs and enhances MN survival both in vitro and in a zebrafish SMA model. Our findings identify lysosomal dysfunction as a key player in SMA pathology and highlight TFEB activation as a potential therapeutic strategy for SMA treatment.

One Sentence SummaryTFEB activation restores lysosomal function and improves motor neuron survival in SMA, highlighting its potential as a therapeutic target.

High-pass noise suppression in the mosquito auditory system
Mosquitoes detect sound with their antennae, which transmit vibrations to mechanosensory neurons in Johnston's organ. However, their auditory system is exposed to low-frequency noise from external sources, such as convective and thermal noise, and internal sources, such as flight-induced noise, which could impair sensitivity. High-pass filters (HPFs) may mitigate this issue by suppressing low-frequency interference before it is transformed into neuronal signals. We investigated HPF mechanisms in Culex pipiens mosquitoes by analyzing the phase-frequency characteristics of the primary sensory neurons in the Johnston's organ. Electrophysiological recordings from male and female mosquitoes revealed phase shifts consistent with high-pass filtering. Initial modeling suggested a single HPF; however, experimental data required revising the model to include two serially connected HPFs to account for phase shifts exceeding -90{degrees}. The results showed that male mosquitoes exhibit stronger low-frequency suppression (~32 dB at 10 Hz) compared to females (~21 dB), with some female neurons showing negligible filtering. The estimated delay in signal transmission was ~7 ms for both sexes. These findings suggest that HPFs enhance noise immunity, particularly in males, whose auditory sensitivity is critical for mating. The diversity in female neuronal tuning may reflect broader auditory functions in addition to mating, such as host detection. This study provides indirect evidence for HPFs in mosquito hearing and highlights sex-specific adaptations in auditory processing. The proposed dual-HPF model improves our understanding of how mosquitoes maintain high auditory sensitivity in noisy environments.

Robust Neural Decoding with low density EEG
High-density EEG recording enhances spatial resolution for neural signal decoding, yet the relationship between electrode density and decoding performance, as well as the minimum number of electrodes required for effective decoding, remains unclear. To address this, we systematically investigated the decoding accuracy of neural signals across varying electrode densities (16, 32, 64, 96, and 128 electrodes) using visual grating stimuli characterized by orientation, contrast, spatial frequency, and color. Our findings showed that accurate decoding of these visual grating features was achievable even with as few as 16 electrodes, highlighting the robustness of decodable neural signals. To test the generalization of these results to more complex natural stimuli, we conducted a similar analysis with a diverse set of naturalistic images categorizable into living/non-living and moving/non-moving. The results consistently showed that effective decoding persists even with only 16 electrodes, demonstrating robust decoding efficacy even for complex naturalistic stimuli. This work provides valuable insights into the efficient neural decoding offered by low-density EEG and robustness of neural signal representation.

Global error signal guides local optimization in mismatch calculation
Corollary discharge denotes internal signals about the expected sensory consequences of one's own actions, leading to attenuation of sensory responses caused by self-produced stimulation. To investigate the underlying neural circuit mechanism, here we introduce a biologically plausible three-factor learning rule, where a global signal guides the updating of local inhibitory synapses to enable the computation of mismatch between a stimulus and its expectation or prediction. We show that our network model, endowed with positive and negative prediction error neurons, accounts for the salient physiological observations of motor-visual and motor-auditory mismatch responses in mice. Moreover, the model predicts that learning induces a bimodal distribution in activity correlation with stimulus and movement-induced prediction, supported by our analysis of neural data from a recent experiment. These results link global modulation to local learning for predictive error computation in the sensory areas, and shed insights into how disrupting inhibition impairs mismatch computation in specific ways.

β-adrenergic receptors modulate CA1 population coding during cumulative spatial memory formation and updating
Hippocampal neuronal ensembles are likely to support the acquisition, stabilization and updating of spatial experience. Spatial learning is typically cumulative, but little is known about how neuronal ensembles are manifested during this process. Here, we used wide-field Ca2+-imaging to monitor CA1 pyramidal cells during cumulative item-place learning in adult male CBA/CaOlaHsd mice. In control mice, initial learning prompted activity in a population of CA1 neurons, some of which re-appeared during re-exposure to the same item-place configuration 60 min after 1st exposure. Item-place reconfiguration (60 min later) caused a change in population dynamics as reflected by alterations in neuronal recruitment and reactivation patterns. Place cell-like properties, population burst activity, and functional connectivity were consistent with the encoding and updating of item-place memory. To examine the role of noradrenergic neuromodulation on these processes, we pharmacologically antagonized {beta}-adrenergic receptors({beta}-AR) prior to the 1st item-place exposure. This led to reduced cellular recruitment, disrupted ensemble reactivation, reduced spatial tuning, dampened population bursts, and altered functional connectivity within neurons. This was accompanied by impaired spatial learning compared to controls. Our results reveal the population activity of CA1 neurons during item-place learning and show that {beta}-AR support memory function by influencing both neuronal and network-level dynamics.

Alterations in Electroencephalography Signals in Female Fragile X Syndrome Mouse Model on a C57Bl/6J Background
Background: Fragile X Syndrome (FXS), the most common monogenic cause of autism spectrum disorder, arises from FMR1 gene silencing and exhibits pronounced sex differences in prevalence and phenotypic severity. Electroencephalography (EEG) has emerged as a promising translational biomarker for FXS pathophysiology, yet prior research has predominantly focused on male cohorts. In the widely used C57Bl/6J (B6) mouse strain, male Fmr1 knockout (KO) models show increased absolute gamma power at both juvenile and adult stages, which may reflect cortical hyperexcitability. In contrast, little is known about female Fmr1 KO mice, except that they exhibit no gamma alterations in adulthood. This gap hinders understanding of sex-specific neurodevelopmental trajectories of EEG profile in FXS. Leveraging the genetic stability and translational relevance of the B6 strain, this study compares EEG profiles between juvenile female Fmr1 KO and wild-type (WT) B6 mice to address this critical gap. Methods: Frontal-parietal differential EEG was recorded in freely behaving mice using the Open-Source Electrophysiology Recording system for Rodents. Neural activity was analyzed across three recording conditions: in the home cage, light-dark arena, and open field arena. Computed metrics included absolute/relative power, peak alpha frequency, theta-beta ratio, phase-amplitude coupling, amplitude-amplitude coupling, and multiscale entropy to assess signal complexity. Results: In all recording conditions, Fmr1 KO mice exhibited reduced absolute power in theta, alpha, and beta frequency bands compared to WT controls. Relative power analysis revealed decreased alpha activity alongside increased gamma-band power, including both low and high gamma, in the KO mice. Cross-frequency coupling was disrupted, with diminished alpha-gamma phase-amplitude coupling. Amplitude-amplitude coupling between theta or alpha and gamma power displayed distinct changes in different recording conditions. Peak alpha frequency and theta-beta ratio were both reduced or unchanged in the KO mice, depending on the recording condition. Finally, EEG signal complexity remained comparable between the two genotypes across the conditions. Behaviorally, KO mice displayed hyper-exploration in the open field test, characterized by increased center time and entries. However, no overall robust correlations between EEG power in different frequency bands and behavioral parameters in the open field test were observed. Discussion and Conclusion: Our results demonstrate that juvenile female Fmr1 KO mice on a B6 background exhibit EEG alterations highly consistent with those reported in FXS patients, particularly increased gamma and reduced alpha power. The robust increase in gamma activity reinforces its status as a reliable biomarker across preclinical and clinical studies, while alpha reductions and slowed peak alpha frequency implicate thalamocortical network involvement. Together, these findings highlight the translational value of this model for studying core circuit dysfunctions in FXS.

Altered Stress and Fear Responses in the VPA Rat Model of Autism: Behavioral Dissociation Across Tactile, Nociceptive, and Social Contexts
Sensitivity to environmental stimuli is a fundamental aspect of human behavior, and its dysregulation is associated with stress-related and anxiety disorders. In autism spectrum disorder (ASD), altered sensory processing may contribute to increased vulnerability to such conditions. To better understand this relationship, we evaluated autonomic and behavioral responses to tactile, nociceptive, and social stressors in juvenile Wistar rats prenatally exposed to valproic acid (VPA), a widely used animal model of ASD. VPA-treated and saline-treated control (CTL) rats underwent a battery of stress-related behavioral tests. Defecation, freezing and vocalization behaviors were analyzed in response to handling, electro-tactile stimulation, nociceptive foot shock (fear conditioning) and social stress stimuli (emotional contagion). VPA-treated rats maintained increased defecation during handling and a higher prevalence of defecation during electro-tactile stimulation, without corresponding changes in freezing. During fear conditioning, these animals showed delayed onset and heightened freezing responses. Furthermore, unlike CTL rats, VPA-treated rats lacked correlations among freezing, defecation, and vocalization. In the emotional contagion paradigm, observation of shock in the partner increased the prevalence of animals freezing and reduced the prevalence of animals vocalizing in both VPA and CTL groups (oV+ and oC+) compared to their respective controls (oV- and oC-). However, these effects were more sustained in oV+ rats, which also exhibited prolonged freezing behavior and an earlier reduction in vocalization rate. These findings indicate that VPA-treated rats display heightened stress reactivity, habituation deficit and disrupted coordination of fear responses, supporting the VPA model as a relevant tool for investigating the neurobiological basis of stress vulnerability and social dysfunction in ASD.

Multiple event segmentation mechanisms in the human brain
The human brain segments continuous experience into discrete events, with theoretical accounts proposing two distinct mechanisms: creating boundaries at points of high prediction error (mismatch between expected and observed information) or high prediction uncertainty (reduced precision in predictions). Using fMRI and computational modeling, we investigated the neural correlates of error-driven and uncertainty-driven boundaries. We developed computational models that generate boundaries based on prediction error or prediction uncertainty, and examined how both types of boundaries, and human-identified boundaries, related to fMRI pattern shifts and evoked responses. Multivariate analysis revealed a specific temporal sequence of neural pattern changes around human boundaries: early pattern shifts in anterior temporal regions (-11.9s), followed by shifts in parietal areas (-4.5s), and subsequent whole-brain pattern stabilization (+11.8s). The core of this dynamic response was associated with both error-driven and uncertainty-driven boundaries. Critically, both error- and uncertainty-driven boundaries were associated with unique pattern shifts. Error-driven boundaries were associated with early pattern shifts in ventrolateral prefrontal areas, followed by pattern stabilization in prefrontal and temporal areas. Uncertainty-driven boundaries were linked to shifts in parietal regions within the dorsal attention network, with minimal subsequent stabilization. In addition, within the core regions responsive to both types of boundaries, the timing differed significantly. These findings provide evidence for two overlapping brain networks that maintain and update representations of the environment, controlled by two distinct prediction quality signals: prediction error and prediction uncertainty.

Modeling Laryngeal Dystonia through Spectral Analyses of Vocalizations in a Dystonia Mouse Model
Laryngeal dystonia is a task-specific, focal dystonia that disrupts vocal-motor control and significantly alters quality of life through impaired communication. Despite its early onset in many hereditary dystonias, effective treatments remain limited, in part due to the lack of a preclinical model that captures its circuit-level pathophysiology. Our experiment evaluates ultrasonic vocalizations (USVs) in Ptf1aCre/+;Vglut2fl/fl mice, a cerebellum-specific generalized dystonia model, to assess translational relevance for laryngeal dystonia. At postnatal day 9, mutant mice demonstrated statistically significant reductions in total USV count, relative count of complex calls, and key spectral parameters--especially frequency modulation and power--mirroring phonatory abnormalities seen in human patients. Cluster analyses further revealed impaired vocal burst initiation, suggesting disrupted cerebellar coordination of temporal vocal-motor output. These findings support the model's construct and face validity for cerebellar contributions to disordered phonation. By revealing these potential translational biomarkers, our study establishes a foundational platform for future mechanistic and interventional research in laryngeal dystonia.

Neurocomputational impairments in disambiguation of context as a key determinant of post-traumatic psychopathology
We combine theoretical biology and systems neuroscience to relate the mechanisms of post-traumatic stress disorder (PTSD) models to biopsychosocial complexity. Moving beyond fear conditioning, extinction and habits formed by associative learning, we consider conserved neuromodulatory mechanisms related to harm expectation, defensive mobilisation, and context (in)sensitivity. Our account of harm-mitigating, neurobehavioural responses furnishes a mechanistic understanding of maladaptive behaviour and impaired belief-updating, which are often underspecified in conceptual analyses. Grounded in neurobiological evidence, we specify PTSD-related impairment in terms of Bayesian belief-updating, and establish an adaptive/maladaptive boundary using active inference and simulation studies. The ensuing model plausibly illustrates PTSD pathogenesis, which remains understudied relative to aetiology. We locate pathogenesis in maladaptive precision following traumatic learning, characterised by aberrant Bayesian credit assignment. Future scientific and clinical studies can test the validity of these insights, which could underwrite our understanding of the phenomenology, diagnostics and ultimately treatment intervention in post-traumatic disorders.

Brain-Informed Fine-Tuning for Improved Multilingual Understanding in Language Models
Recent studies have demonstrated that fine-tuning language models with brain data can improve their semantic understanding, although these findings have so far been limited to English. Interestingly, similar to the shared multilingual embedding space of pretrained multilingual language models, human studies provide strong evidence for a shared semantic system in bilingual individuals. Here, we investigate whether fine-tuning language models with bilingual brain data changes model representations in a way that improves them across multiple languages. To test this, we fine-tune monolingual and multilingual language models using brain activity recorded while bilingual participants read stories in English and Chinese. We then evaluate how well these representations generalize to the bilingual participants' first language, their second language, and several other languages that the participant is not fluent in. We assess the fine-tuned language models on brain encoding performance and downstream NLP tasks. Our results show that bilingual brain-informed fine-tuned language models outperform their vanilla (pretrained) counterparts in both brain encoding performance and most downstream NLP tasks across multiple languages. These findings suggest that brain-informed fine-tuning improves multilingual understanding in language models, offering a bridge between cognitive neuroscience and NLP research.

Astrocytic mGluR5 signaling tunes emotional and cognitive processing in the adult brain
The hippocampus is a brain region involved in both emotion regulation and higher cognitive functions. Astrocytes have emerged as active modulators of synaptic activity, capable of sensing, integrating, and responding to neuronal signals. At glutamatergic synapses, astrocytes detect glutamate through the activation of the metabotropic glutamate receptor 5 (mGluR5). However, most existing research has focused on the role of mGluR5 in developing rodents or in pathological contexts, likely because of the reported lower astrocytic mGluR5 expression levels in adulthood compared to postnatal stages. Importantly, prior studies and our preliminary data have demonstrated mGluR5-mediated signaling in astrocytes of adult mice, supporting a role for this receptor. Therefore, the main objectives of this study were (1) to determine whether these lower levels of mGluR5 are sufficient to activate astrocytes in the adult brain and (2) to investigate whether this activation is involved in regulating circuit function and behavior. To address these objectives, we evaluated adult mice employing a combination of calcium-imaging in astrocytes, and loss- and gain-of-function manipulations to assess synaptic plasticity and behavior in adult mice. First, we found that astrocytes of adult mice display fully functional mGluR5-dependent calcium activity. To examine the role of this activity, we induced the deletion of mGluR5 in astrocytes across the entire brain of adult mice. These mice developed anxious- and depression-like behaviors, along with reduced sociability and recognition memory, but showed increased behavioral flexibility. These results highlighted the hippocampus as a key region for mGluR5-mediated astrocytic influence on behavior, leading us to specifically target hippocampal astrocytes. A viral-driven ablation in this area demonstrated that astrocytic mGluR5 plays a role in both basal transmission and the regulation of synaptic plasticity. Behaviorally, the deletion of astrocytic mGluR5 in the hippocampus recapitulated anxious-like behaviors, social deficits, and impaired long-term recognition memory. Surprisingly, it improved place recognition memory but reduced behavioral flexibility. Lastly, overexpressing this receptor to enhance mGluR5 signaling specifically in hippocampal astrocytes impaired place recognition memory but improved behavioral flexibility, revealing a role for astrocytic mGluR5 in regulating these behaviors. Overall, our results confirmed the biological relevance of astrocytic mGluR5 during adulthood, specifically in modulating hippocampal function.

Cortical and white matter T1w/T2w development proceed in concert during early infancy
The infant brain undergoes rapid myelin growth that is critical for healthy brain function. This development has been characterized for gray and white matter independently, but the link between gray and white matter myelination remains unexplored. To close this knowledge gap, we processed large-scale (N=279) Developing Human Connectome Project data with automated software to identify 26 white matter bundles and map their cortical terminations, before evaluating T1w/T2w development in individuals. We found that mean T1w/T2w as well as the slope of T1w/T2w development are correlated across tissues. This synchrony of brain T1w/T2w is impacted by birth age and postnatal experience, whereas inter-individual differences in this synchrony predict motor outcomes at 17 - 25 months of age. As T1w/T2w is associated with myelin content, our results reveal an intricate relationship between gray and white matter myelination, highlighting the importance of conjointly evaluating both tissues.

GPR17 modulates oligodendrocyte precursor cell maturation during development but has limited impact on myelin regeneration following demyelinating insults
Pharmacological enhancement of myelin regeneration is broadly recognized as the next frontier in therapeutic approaches for demyelinating diseases of the CNS such as multiple sclerosis. However, although several molecular targets for remyelination have been tested preclinically and in clinical trials, an efficacious and safe myelin repair treatment is yet to be developed. One promising molecular target to enhance myelin repair is the G protein-coupled receptor (GPCR) GPR17, which has been proposed to play a central role in the transition from early oligodendrocyte progenitor cells (OPC) into pre-myelinating oligodendrocytes. These findings are largely supported by studies using transgenic mice where GPR17 deletion results in developmental hypermyelination. Additionally, pharmacological modulation of GPR17 activity has been reported to enhance oligodendrocyte precursor cell (OPC) maturation and myelination. In our studies aimed to characterize and pharmacologically validate GPR17 as a viable target for drug development, we established by means of transcriptional profiling of GPR17 knockout versus wild type OPCs, that absence of this GPCR results in a gene signature revealing minor changes in myelin protein gene expression. Furthermore, blocking GPR17 receptor activity in OPC cultures using selective and potent antagonists or inverse agonists, results in limited enhancement of maturation and myelination in vitro. Importantly, remyelination in both the cuprizone and lysolecithin-induced demyelination models was not enhanced in the absence of GPR17. Our data demonstrate that GPR17 plays a minor role in OPC differentiation during development, and pharmacological modulation of its activity has a marginal effect on oligodendrocyte precursor maturation and myelin regeneration after injury.

Development of convolutional neural networks for automated brain-wide histopathological analysis in mouse models of synucleinopathies
Preclinical animal models are indispensable for uncovering disease mechanisms and developing novel therapeutic interventions in synucleinopathies. Key readouts including neuronal cell death, neuroinflammation and alpha-synuclein protein aggregation, are routinely assessed by histological methods. However, traditional characterization of histological samples is labor-intensive and time-consuming. There is a growing need for reproducible and high-throughput tools to capture region- and cell type-specific changes, ultimately improving the predictive value of preclinical studies. To address this, our study introduces a pipeline using convolutional neural networks (CNNs) for high-throughput, unbiased analysis of immunohistological data in mouse brains. We have trained five CNN-based models to autonomously identify brain regions and detect markers of neurodegeneration, neuroinflammation, and alpha-synuclein aggregation. These models provide accurate, region-specific insights at cellular resolution without manual annotation, significantly speeding up analysis time from weeks to minutes. Our approach enhances the precision and efficiency of histological assessments, providing robust, brain-wide results in various animal models of synucleinopathies.