bioRxiv Subject Collection: Neuroscience's Journal

A factor-based analysis of individual human microglia uncovers regulators of an Alzheimer-related transcriptional signature
Human microglial heterogeneity is only beginning to be appreciated at the molecular level. Here, we present a large, single-cell atlas of expression signatures from 441,088 live microglia broadly sampled across a diverse set of brain regions and neurodegenerative and neuroinflammatory diseases obtained from 161 donors sampled at autopsy or during a neurosurgical procedure. Using single-cell hierarchical Poisson factorization (scHPF), we derived a 23-factor model for continuous gene expression signatures across microglia which capture specific biological processes (e.g., metabolism, phagocytosis, antigen presentation, inflammatory signaling, disease-associated states). Using external datasets, we evaluated the aspects of microglial phenotypes that are encapsulated in various in vitro and in vivo microglia models and identified and replicated the role of two factors in human postmortem tissue of Alzheimer's disease (AD). Further, we derived a complex network of transcriptional regulators for all factors, including regulators of an AD-related factor enriched for the mouse disease-associated microglia 2 (DAM2) signature: ARID5B, CEBPA, MITF, and PPARG. We replicated the role of these four regulators in the AD-related factor and then designed a multiplexed MERFISH panel to assess our microglial factors using spatial transcriptomics. We find that, unlike cells with high expression of the interferon-response factor, cells with high expression of the AD DAM2-like factor are widely distributed in neocortical tissue. We thus propose a novel analytic framework that provides a taxonomic approach for microglia that is more biologically interpretable and use it to uncover new therapeutic targets for AD.

A therapeutic role for a regulatory glucose transporter1 (Glut1)-associated natural antisense transcript
The mammalian brain relies primarily on glucose for its energy needs. Delivery of this nutrient to the brain is mediated by the glucose transporter-1 (Glut1) protein. Low Glut1 thwarts glucose entry into the brain, causing an energy crisis and, triggering, in one instance, the debilitating neurodevelopmental condition, Glut1 deficiency syndrome (Glut1DS). Current treatments for Glut1DS are sub-optimal, as none address the root cause, low Glut1, of the condition. Levels of this transporter must respond rapidly to the brain's changing energy requirements. This necessitates fine-tuning its expression. Here we describe a long-noncoding RNA (lncRNA) antisense to Glut1 and show that it is involved in such regulation. Raising levels of the lncRNA had a concordant effect on Glut1 in cultured human cells and transgenic mice; reducing levels elicited the opposite effect. Delivering the lncRNA to Glut1DS model mice via viral vectors induced Glut1 expression, enhancing brain glucose levels to mitigate disease. Direct delivery of such a lncRNA to combat disease has not been reported previously and constitutes a unique therapeutic paradigm. Moreover, considering the importance of maintaining homeostatic Glut1 levels, calibrating transporter expression via the lncRNA could become broadly relevant to the myriad conditions, including Alzheimer's disease, wherein Glut1 concentrations are perturbed.

Vulnerability to memory decline in aging. A mega-analysis of structural brain change.
Brain atrophy is a key factor behind episodic memory loss in aging, but the nature and ubiquity of this relationship remains poorly understood. This study leveraged 13 longitudinal datasets, including 3,737 cognitively healthy adults (10,343 MRI scans; 13,460 memory assessments), to determine whether brain change-memory change associations are more pronounced with age and genetic risk for Alzheimer's Disease. Both factors are associated with accelerated brain decline, yet it remains unclear whether memory loss is exacerbated beyond what atrophy alone would predict. Additionally, we assessed whether memory decline aligns with a global pattern of atrophy or stems from distinct regional contributions. Our mega-analysis revealed a nonlinear relationship between memory decline and brain atrophy, primarily affecting individuals with above-average brain structural decline. The associations were stronger in the hippocampus but also spread across diverse cortical and subcortical regions. The associations strengthened with age, reaching moderate associations in participants in their eighties. While APOE {varepsilon}4 carriers exhibited steeper brain and memory loss, genetic risk had no effect on the change-change associations. These findings support the presence of common biological macrostructural substrates underlying memory function in older age which are vulnerable to multiple age-related factors, even in the absence of overt pathological changes.

Aggregation of the constitutively active K296E rhodopsin mutant contributes to retinal degeneration
A K296E mutation in rhodopsin causes autosomal dominant retinitis pigmentosa, a progressive retinal degenerative disease. Early in vitro characterizations of this mutation studied on a bovine rhodopsin background indicated that the mutation causes the receptor to be constitutively active. This molecular defect has been the primary focus when considering the pathogenic mechanism of the mutation. Knockin mice expressing the K296E rhodopsin mutant were generated and characterized to better understand the pathogenic mechanism of the mutation. Knockin mice exhibited progressive retinal degeneration characteristic of retinitis pigmentosa. The K296E rhodopsin mutant mislocalized in photoreceptor cells and, surprisingly, appeared to aggregate, as indicated by the dye PROTEOSTAT, which binds protein aggregates. The propensity of the K296E rhodopsin mutant to aggregate was tested and confirmed in vitro but was dependent on the species background of rhodopsin. The K296E mutation on either murine or human rhodopsin backgrounds exhibited similar propensities to aggregate. The same mutation on a bovine rhodopsin background, however, exhibited a lower propensity to aggregate, indicating this species background does not adequately model the effects of the K296E mutation. In contrast to previous expectations, we demonstrate here that aggregation of the K296E rhodopsin mutant can promote photoreceptor cell loss.

Dynamic structural connectivity changes in cortical and cortico-striatal strokes in mice
Stroke is a primary global health concern, leading to significant mortality and long-term disability. Beyond immediate neuronal damage, functional and structural connectivity is altered brain-wide with implications for functional deficits and recovery. It remains unclear, however, if the level of degeneration, i.e. reduced myelination and axonal damage, as well as compensatory plasticity, i.e., axonal sprouting and remyelination, depend on the lesion size and topology. This study compares for the first time two different stroke models in adult male mice, with the aim of uncovering the dynamics in white matter changes. Repetitive diffusion magnetic resonance imaging (dMRI) over four weeks post photothrombotic cortical (1.41+/-0.92% of brain volume), and middle cerebral artery occlusion (MCAO) cortico-striatal (11.53+/-2.8% of brain volume), strokes were used to map structural connectivity changes at the whole-brain level. We quantified inter- and intra-hemispheric seed strength changes over time, with seed strength reflecting how strongly each region is connected to the rest of the brain. Differences between groups and time points were assessed using a mixed model corrected for multiple comparisons. In conclusion, large cortico-striatal lesions led increased structural connectivity in sensorimotor regions, whereas small cortical lesions induced asymmetric connectivity changes: an increase extending globally from the ischemic hemisphere and a decrease expanding globally from the healthy hemisphere. These findings highlight that stroke severity and lesion size significantly affect the temporal dynamics and spatial distribution of connectivity disruptions, emphasizing the need for targeted monitoring of neural changes post-stroke.

Hsp90 buffers behavioral plasticity by regulating Pdf transcription in clock neurons of Drosophila melanogaster
Circadian rhythms are prevalent on Earth and temporally organize behaviour and physiology of organisms to occur in species-specific 'temporal niches'. However, species differ in how strictly individuals are controlled by their circadian clock, suggesting that it may offer a selective advantage for an individual to extend its temporal niche under certain circumstances, for example during stressful environmental conditions. A potential mechanism controlling temporal niche adherence involves the evolutionary capacitor and chaperon protein HSP90, known to assist the proper folding of important signalling molecules. If HSP90 becomes rate limiting (e.g., under environmental stress) hidden genetic variation will be expressed, producing novel and potentially beneficial phenotypes for the individual. While this role of HSP90 is well established for morphological traits, we show here that it extends to regulation of temporal behavioural patterns. We show that within a small subset of clock neurons in the fly brain, HSP83, the fly homologue of HSP90, mitigates inter-individual behavioural plasticity. We provide evidence for the requirement of HSP83 for efficient transcription of the gene encoding the circadian neuropeptide Pigment Dispersing Factor (PDF), and for correct PDF accumulation in central clock neurons. Strikingly, Hsp83 mutants affect synchronized oscillations of the clock protein PERIOD (PER) in subsets of circadian clock neurons in the same way as flies without PDF, further supporting a role of Hsp83 in regulating Pdf. Our findings therefore provide a mechanistic explanation for HSP83 function in regulation of behavioural plasticity, and offer an explanation for how to restrict temporal niche extension to stressful environmental conditions.

Sensitivity analysis enlightens effects of connectivity in a Neural Mass Model under Control-Target mode
Biophysical models of human brain represent the latter as a graph of inter-connected neural regions. Building from the model by Naskar et al. [1], our motivation was to understand how these brain regions can be connected at neural level to implement some inhibitory control, which calls for inhibitory connectivity rarely considered in such models. In this model, regions are made of inter connected excitatory and inhibitory pools of neurons, but are long-range connected only via excitatory pools (mutual excitation). We thus extend this model by generalizing connectivity, and we analyse how connectivity affects the behaviour of this model. Focusing on the simplest paradigm made of a Control area and a Target area, we explore four typical kinds of connectivity: mutual excitation, Target inhibition by Control, Control inhibition by Target, and mutual inhibition. For this, we build an analytical sensitivity framework, nesting up sensitivities of isolated pools, of isolated regions, and of the full system. We show that inhibitory control can emerge only in Target inhibition by Control and mutual inhibition connectivities. We next offer an analysis of how the model sensitivities depends on connectivity structure, depending on a parameter controling the strength of the self inhibition within Target region. Finally, we illustrate the effect of connectivity structure upon control effectivity in response to an external forcing in the Control area. Beyond the case explored here, our methodology to build analytical sensitivities by nesting up levels (pool, region, system) lays the groundwork for expressing nested sensitivities for more complex network configurations, either for this model or any other one.

Long-term, age-associated activity quantification in the DE50-MD dog model of Duchenne muscular dystrophy (DMD)
Animal models with a clinically relevant phenotype remain important for robust evaluation of novel therapeutics for the fatal, X-linked genetic disorder, Duchenne Muscular Dystrophy (DMD). Demonstration of functional improvement is crucial for both patients and regulatory authorities. DMD is associated with a decline in musculoskeletal function with progressive paresis, muscle atrophy and fibrosis: phenotypic features that are also seen in the DE50-MD canine model of DMD. Here we investigate non-invasive methods to quantify changes in activity and behaviour in DE50-MD dogs, using collar-based, tri-axial accelerometers. We measured activity in affected DE50-MD male dogs (3-8 per age point) and littermate wild-type (WT) male controls (3-13 per age point) at monthly intervals from 3 to 18 months of age using Axivity-AX3 accelerometers attached ventrally on each dog's collar. Data were recorded for 48 hours while dogs remained in their kennels with outside runs following their normal routine. Acceleration vector magnitudes were used to derive various activity indicators over a 24-hour period. Mixed model analyses were used to examine differences between affected and WT groups at different ages. DE50-MD dogs' activity indicators were significantly higher for % time spent at rest (p<0.001) and significantly lower for all other activity indicators (all p<0.05), when compared to age-matched WT dogs. Sample size calculations reveal that these non-invasive, unbiased and objective biomarkers offer significant promise for preclinical testing of therapeutics in this model of DMD. Our approach reveals opportunities for cross-model standardisation of activity monitoring methods, applicable to both research and companion animal settings.

Genomic and Transcriptomic Signatures of SETD1A Disruption in Human Excitatory Neuron Development and Psychiatric Disease Risk
Genetic disruption of SETD1A markedly increases the risk for schizophrenia. To elucidate the underlying mechanisms, we generated isogenic organoid models of the developing human cerebral cortex harboring a SETD1A loss-of-function schizophrenia risk mutation. Employing chromatin profiling combined with RNA sequencing, we identified high-confidence SETD1A target genes, analyzed the impact of the mutation on SETD1A binding and transcriptional regulation and validated key findings with orthogonal approaches. Disruption of SETD1A function disturbs the finely tuned temporal gene expression in the excitatory neuron lineage, yielding an aberrant transcriptional program that compromises key regulatory and metabolic pathways essential for neurodevelopmental transitions. Although overall SETD1A binding remains unchanged in mutant neurons, we identified localized alterations in SETD1A binding that correlate with shifts in H3K4me3 levels and gene expression. These changes are enriched at enhancer regions, suggesting that enhancer-regulated genes are especially vulnerable to SETD1A reduction. Notably, target genes with enhancer-bound SETD1A are primarily linked to neuronal functions while those with promoter-bound SETD1A are enriched for basic cellular functions. By mapping the SETD1A binding landscape in excitatory neurons of the human fetal frontal cortex and integrating multimodal neuroimaging and genetic datasets, we demonstrate that the genomic context of SETD1A binding differentially correlates with macroscale brain organization and establish a link between SETD1A-bound enhancers, schizophrenia-associated brain alterations and genetic susceptibility. Our study advances our understanding of the role of SETD1A binding patterns in schizophrenia pathogenesis, offering insights that may guide future therapeutic strategies.

Sensory and action neural tuning explains how priors guide human visual decisions
Prior expectations bias how we perceive the world. Despite well-characterized behavioral effects of priors, such as confirmation bias, their neural mechanisms remain unclear. Contemporary theories postulate conflicting predictions: does the brain enhance expected sensory information (sharpening the expected representation) or rather prioritize unexpected information (dampening the expected representations)? Here, we combined reversal learning with a noisy motion discrimination task to investigate how priors impact sensory and action information processing. Using behavioral modeling to infer participants' latent priors and EEG to track neural dynamics, we demonstrated that priors differentially impact sensory and action representations over time. While priors introduced long-lasting biases on action coding irrespective of their validity, sensory information was selectively enhanced with confirmatory evidence. Critically, dampening of action representations predicted confirmation biases, whereas sensory tuning dynamics tracked speed-accuracy trade-offs. These findings reveal a dissociable and temporally dynamic influence of priors in visual decisions, reconciling competing theories of predictive perception.

Serotonergic and noradrenergic interactions in pupil-linked arousal
Changes in central arousal state shape cortical computations underlying perception, thought, and action. Variations in arousal are accompanied by fluctuations in pupil size. In turn, pupil dynamics are often used as a marker of noradrenaline release from neurons of the locus coeruleus. The serotonergic system of the dorsal raphe also contributes to the brainstem control of waking states. However, little is known about its relationship to noradrenergic activity and arousal dynamics in awake animals. Here, we simultaneously accessed both systems in awake mice and unraveled their unique and joint contributions to pupil-linked arousal. Serotonergic and noradrenergic systems co-fluctuated, and serotonergic dorsal raphe neurons affected pupil size partly via noradrenergic populations in the locus coeruleus. Yet, part of the serotonergic control of pupil dynamics was independent of the locus coeruleus. Our findings challenge common assumptions about the neuromodulatory control of pupil dynamics and illuminate the interplay between distinct neurochemical systems within the arousal network of the brainstem.

A dynamic gene regulatory code drives synaptic development of hippocampal granule cells
Connecting neurons into functional circuits requires the formation, maturation, and plasticity of synapses. While advances have been made in identifying individual genes regulating synapse development, the molecular programs orchestrating their action during circuit integration of neurons remain poorly understood. Here, we take a multiomic approach to reconstruct gene regulatory networks (GRNs), comprising transcription factors (TFs), regulatory regions, and predicted target genes, in hippocampal granule cells (GCs). We find a dynamic gene regulatory code, with early and late postnatal GRNs regulating cell morphogenesis and synapse organization and plasticity, respectively. Our results predict sequential regulations, with early-active TFs delaying the activation of later GRNs and their putative synaptic targets. Using a loss-of-function approach, we identify Bcl6 as a regulator of pre- and postsynaptic structural maturation, and Smad3 as a modulator of inhibitory synaptic transmission, in GCs. Together, these findings highlight the networks of key TFs and target genes orchestrating GC synapse development.

A cortical-hippocampal communication undergoes rebalancing after new learning
The brain's ability to consolidate a wide range of memories while maintaining their distinctiveness across experiences remains poorly understood. Sharp-wave ripples, neural oscillations that occur predominantly within CA1 of the hippocampus during immobility and sleep, have been shown to play a critical role in the consolidation process. More recently, evidence has uncovered functional heterogeneity of pyramidal neurons within distinct sublayers of CA1 that display unique properties during ripples, potentially contributing to memory specificity. Despite this, it remains unclear exactly how ripples shift the activity of CA1 neuronal populations to accommodate the consolidation of specific memories and how sublayer differences manifest. Here, we studied interactions between the anterior cingulate cortex (ACC) and CA1 neurons during ripples and discovered a reorganization of their communication following learning. Notably, this reorganization appeared specifically for CA1 superficial (CA1sup) sublayer neurons. Utilizing a generalized linear model decoder, we demonstrate the pre-existence of ACC-to-CA1sup communication, which is suppressed during new learning and subsequent sleep suggesting that ACC activity may reallocate the contribution of CA1sup neurons during memory acquisition and consolidation. Further supporting this notion, we found that optogenetic stimulations of the ACC preferentially suppressed CA1sup interneurons while activating a unique subset of CA1 interneurons. Overall, these findings highlight a possible role of the ACC in rebalancing CA1 neuronal populations' contribution to ripple contents surrounding learning.

Meta-analysis of the brain transcriptomes of multiple genetic mouse models of schizophrenia highlights dysregulation in striatum and thalamus
Schizophrenia is a severe mental illness with high heritability, but its underlying mechanisms are poorly understood. We meta-analyzed large-scale brain transcriptomic data from mice harboring individual loss-of-function mutations in seven schizophrenia risk genes (Akap11, Dagla, Gria3, Grin2a, Sp4, Srrm2, Zmym2). While all studied brain regions were affected, the striatum and the thalamus emerged as key brain regions of convergence. Striatum showed downregulation of synapse- and oxidative phosphorylation-related gene sets in all models. In the thalamus, mutants separated into two groups based on transcriptomic phenotype: synapse-related gene sets were upregulated in mutants with only schizophrenia and bipolar association, and were downregulated in mutants that are associated with developmental delay/intellectual disability in addition to schizophrenia. Overall, our meta-analysis reveals convergence and divergence in brain transcriptomic phenotype in these schizophrenia genetic models, supports the involvement of striatal disturbance and synapse dysfunction in schizophrenia, and points to a key role of the thalamus.

Cognition is associated with task - related brain network reconfiguration in late childhood
In order to transition between a resting state and carrying out cognitively-demanding processes the brain makes a host of subtle changes to its network organization. In adults, less reconfiguration relates to better task performance, suggesting a preconfigured brain organization at rest is beneficial, such that only minute changes are required to execute task demands. Here, we take a developmental lens to this phenomenon, examining reconfiguration in late childhood by leveraging a large sample of 9-11 year olds from the Adolescent Brain and Cognitive Development Study. We find more reconfiguration between the resting state and two executive function tasks is related to better task performance, as well as better crystalized and fluid cognition in some cases. These relationships hold even when accounting for network segregation. These findings suggest a less-preconfigured, and thus more flexible, brain organization that enacts more reconfiguration to move from the resting state into a task state is beneficial in children. This aligns with theories positioning late childhood and the beginning of adolescence as a period of increased brain plasticity where functional brain networks are still undergoing refinement, and thus preconfiguration may be less beneficial and, instead, may place premature constraints on brain organization.

Functional populations in prefrontal cortex related to working memory encoding and maintenance
Nonlinear mixed selectivity, with neurons responding to diverse combinations of task-relevant variables, has been proposed as a key mechanism to enable flexible behavior and cognition. However, it is debated whether the structure of neural population responses in fronto-parietal cortices is better described as random mixed-selective or as non-random, that is, in terms of multiple subpopulations with stereotypical response profiles. Here, we show that neural activity in the macaque prefrontal cortex during a working memory and a visual response task is organized into subpopulations that provide a comprehensive description of the low-dimensional population dynamics. First, analysis of the demixed Principal Components shows that the neural code faithfully represents stimulus identity, task condition, and elapsed time during the trial. Second, a model-free analysis of the population structure reveals a significant degree of clustering, implying a non-random distribution of feature selectivity that is incompatible with random mixed selectivity. Closer inspection shows that stimulus-selective neurons also tend to be task-selective. Third, examining the contribution of stimulus-selective neurons to task-condition-related variance reveals two contrasting activity profiles that correspond to functionally different populations. One population responds during visual stimulation while the other activates during memory maintenance. Finally, the observed neural geometry explains how stable task and stimulus information can be read out from the population response using a linear decoder. Our results highlight that despite the heterogeneity of prefrontal responses during working memory, neurons do not represent random mixtures of task features but are structured according to neural subpopulations.

Cortical functional connectivity across the adult lifespan and its relation to sensorimotor integration
The operation of the human brain relies on functional networks enabled by inter-areal oscillatory synchronization between neuronal populations. Although disruptions in this functional connectivity are associated with brain disorders, evidence on its healthy age-dependent variation and behavioral relevance remains limited. Utilizing magnetoencephalography (MEG) recordings from 576 adults, we investigated the evolution of resting-state functional connectivity (rs-FC) across the healthy adult lifespan. We observed age-related, frequency-specific changes in widespread cortical networks. Alpha-band (8-13 Hz) rs-FC decreased and theta-band (4-8 Hz) rs-FC increased with age, while beta-band (13-30 Hz) rs-FC followed a non-linear trajectory, peaking in middle age. These patterns differed from concurrent changes in oscillatory power, underscoring their dissociable contributions. Notably, reduced beta-band rs-FC was associated with increased sensorimotor attenuation, indicating that changes in rs-FC are behaviorally relevant. These findings advance our understanding of healthy brain aging and highlight a link between resting-state brain activity and sensorimotor integration.

Auditory regulation of hippocampal locomotion circuits by a non-canonical reticular-limbic pathway
The ability to rapidly detect and respond to unexpected auditory stimuli is critical for adaptive behavior, especially during locomotion. Since movement suppresses auditory cortical activity, it remains unclear how salient auditory information influences locomotor circuits. In this work, using in vivo calcium imaging, electrophysiology, chemo- and optogenetics, we investigate the path that relays loud broadband sounds to the dorsal hippocampus (dHPC) and modulates theta oscillations. We demonstrate that noise accelerates theta frequency and decreases its power, effects mediated by entorhinal cortex (EC) and medial septum (MS) inputs while independent of the primary auditory cortex. Activation of dorsal cochlear nucleus (DCN) neurons projecting to the pontine reticular nucleus (PRN) mimics noise-driven hippocampal responses, supporting a brainstem-limbic auditory processing route. Furthermore, noise selectively modulates CA1 pyramidal neuron and interneuron activity, reflecting diverse circuit dynamics. Finally, loud broadband noise stimulus increased theta coherence between the dHPC and the medial prefrontal cortex (mPFC), enhancing interregional synchronization. These results highlight the mechanisms in which the DCN filters behaviorally relevant sounds promoting acoustic motor integration in the hippocampus during locomotion, without direct influence of the auditory cortex.

Neural correlates in basolateral and central amygdala during reward seeking in the face of punishment
The inability to suppress actions despite adverse consequences is a hallmark of compulsive behaviors and is amygdala dependent. To study the amygdala's role in responding despite adverse consequences, we compared single-unit activity in the basolateral (BLA) or central (CeA) amygdala before and after reward-seeking under punishment threat. Rats started each trial by pressing an initial lever, which triggered an outcome-specific 5-s auditory cue (white noise, pure tone, or clicker), signaling one of three reinforcement conditions: 100% sucrose reward, 20% reward/80% omission, or 80% reward/20% footshock punishment. Next, the active and inactive levers were extended, and pressing on the active lever terminated the auditory cue and triggered an outcome-specific 1-s visual cue predicting either reward, reward omission, or shock. After training, we implanted eight tetrodes in the BLA (n=7) or CeA (n=5) and recorded single-unit activity of ~100 neurons per region during task performance. CeA neurons, and to a lesser extent BLA neurons, responded differently to the distinct auditory cues and outcomes. The discrimination between conditions partially explained the capacity of neuronal activity to predict the latency to lever press to complete the trial. The failure to suppress reward-seeking behavior in the face of punishment coincided with the reactivation of reward-seeking-sensitive and the loss of inhibition of punishment-sensitive neuronal populations. In conclusion, we found that after extended training, opposing populations of activated and inhibited neurons in CeA, and to a lesser extent in BLA, control completion of reward-seeking despite punishment.

Synaptic editing of frontostriatal circuitry prevents excessive grooming in SAPAP3-deficient mice
Synaptic dysfunction has been implicated as a key mechanism underlying the pathophysiology of psychiatric disorders. Most pharmacological therapeutics for schizophrenia, autism spectrum disorder, obsessive-compulsive disorder, and major depressive disorder temporarily augment chemical synapse function. Nevertheless, medication non-compliance is a major clinical challenge, and behavioral dysfunction often returns following pharmacotherapeutic discontinuation. Here, we deployed a designer electrical synapse to edit a single class of chemical synapses in a genetic mouse model of obsessive-compulsive disorder (OCD). Editing these synapses in juvenile mice normalized circuit function and prevented the emergence of pathological repetitive behavior in adulthood. Thus, we establish precision circuit editing as a putative strategy for preventative psychotherapeutics.

Dissecting the Crosstalk Between Dopaminergic and Serotonergic Systems in the Striatum
Dopamine (DA) and serotonin (5-HT) are neuromodulators implicated in reward processing, decision-making, and motivated behavior. While often viewed as opposing or complementary systems, how DA and 5-HT release are integrated in the striatum remains elusive. Using optogenetics, fiber photometry and slice electrophysiology we found that ventral tegmental area (VTA) DA neuron stimulation increased DA release without affecting 5-HT release. Dorsal raphe nucleus (DRN) 5-HT neuron activation, on the other hand, induced serotonin release and a modest, transient increase in DA in the NAc, likely via glutamate co-release onto VTA DA neurons. These findings suggest that DA and 5-HT operate largely independently in the striatum, with selective circuit-dependent interactions. This work refines our understanding of DA-5HT interactions and provides a foundation for future research into their roles in motivated behaviors and neuropsychiatric disorders.

Flexible tapping synchronization in macaques: dynamic switching of timing strategies within rhythmic sequences
The ability to synchronize bodily movements with regular auditory rhythm across a broad range of tempos underlies humans' capacity for playing music and dancing. This capability is prevalent across human cultures but relatively uncommon among non-human species. Recent research indicates that monkeys can predictively synchronize to regular, isochronous metronomes, exhibiting a preference for visual rather than auditory sequences. In this study, we trained macaques to perform a visual synchronization tapping task, testing their synchronization abilities over a wide tempo range and characterizing their precision and accuracy in timing intervals throughout rhythmic sequences. Additionally, we investigated whether the macaques employed priors or error correction strategies to maintain synchrony with the metronome. Our findings demonstrate that, following sufficient training, macaques exhibit a remarkable capability to synchronize across diverse tempos. Through an inference model analysis, we identified two distinct timing control strategies used by the macaques: an initial strong regression-to-the-mean effect transitioning dynamically into a more precise error correction approach at their preferred tempo. These results provide compelling evidence that primates possess sophisticated rhythmic timing mechanisms, effectively leveraging internal and external cues to regulate their tapping behavior according to task demands.

The neurocomputational mechanisms of hierarchical linguistic predictions during narrative comprehension
Language comprehension requires a listener to predict the upcoming inputs of linguistic units with multiple timescales based on previous contexts, but how the prediction process is hierarchically represented and implemented in the human brain remains unclear. Combining the natural language processing (NLP) approach and functional Magnetic Resonance Imaging (fMRI) in a narrative comprehension task, we first applied the group-based general linear model (gGLM) to identify the neural underpinnings associated with the language prediction on word and sentence. Our results revealed a cortical architecture supporting the prediction, extending from the superior temporal cortices to the regions in the default mode network. Then, we investigated how these adjacent levels interact with each other by testing two rival hypotheses: the continuous updating hypothesis posits that the higher level of the representational hierarchy is continuously updated as inputs unfold over time, while the sparse updating hypothesis states that the higher level is only updated at the end of their preferred timescales of linguistic units. By conducting computational modeling and autocorrelation analysis, we found the sparse model outperformed the continuous model and the updating might occur at the sentence boundaries. Together, our results extend the linguistic prediction from the small timescales such as words to large timescales such as sentences, providing novel insights into the neurocomputational mechanisms of information updating within the linguistic prediction hierarchy.

Deletion of the voltage-gated calcium channel gene, CaV1.3, reduces Purkinje cell dendritic complexity without altering cerebellar-mediated eyeblink conditioning
Genetic variation in CACNA1D, the gene that encodes the pore-forming subunit of the L-type calcium channel CaV1.3, has been associated with increased risk for neuropsychiatric disorders that display abnormalities in cerebellar structures. We sought to clarify if deletion of CaV1.3 in mice would induce abnormalities in cerebellar cortex cytoarchitecture or synapse morphology. Since CaV1.3 is highly expressed in cerebellar molecular layer interneurons (MLIs) and L-type channels appear to regulate GABA release from MLIs, we hypothesized that loss of CaV1.3 would alter GABAergic synapses between MLIs and Purkinje cells (PCs) without altering MLI numbers or PC structure. As expected, we did not observe changes in the numbers of MLIs or PCs. Surprisingly, CaV1.3 KO mice do have decreased complexity of PC dendritic arbors without differences in the number or structure of GABAergic synapses onto PCs. Loss of CaV1.3 was not associated with impaired acquisition of delay eyeblink conditioning. Therefore, our data suggest that CaV1.3 expression is important for PC structure but does not affect other measures of cerebellar cortex morphology or cerebellar function as assessed by delay eyeblink conditioning.