bioRxiv Subject Collection: Neuroscience's Journal

A versatile miniature two-photon microscope enabling multicolor deep-brain imaging
Here we present the FHIRM-TPM 3.0, a 2.6 g miniature two-photon microscope capable of multicolor deep-brain imaging in freely behaving mice. The system was integrated with a broadband anti-resonant hollow-core fiber featuring low transmission loss, minimal dispersion from 700-1060 nm, and high tolerance of laser power. By correcting chromatic and spherical aberrations and optimizing the fluorescence collection aperture, we achieved cortical neuronal imaging at depths exceeding 820 m and, using a GRIN lens, hippocampal Ca2+ imaging at single dendritic spine resolution. Moreover, we engineered three interchangeable parfocal objectives, allowing for a tenfold scalable field-of-view up to 1x0.8 mm2, with lateral resolutions ranging from 0.68 to 1.46 m. By multicolor imaging at excitation wavelengths of 780 nm, 920 nm and 1030 nm, we investigated mitochondrial and cytosolic Ca2+ activities relative to the deposition of amyloid plaques in the cortex of awake APP/PS1 transgenic mice. Thus, the FHIRM-TPM 3.0 provides a versatile imaging system suitable for diverse brain imaging scenarios.

Deep generation of personalized connectomes based on individual attributes
An individual's connectome is unique. Interindividual variation in connectome architecture associates with disease status, cognition, lifestyle factors, and other personal attributes. While models to predict personal attributes from a person's connectome are abundant, the inverse task-inferring connectome architecture from an individual's personal profile-has not been widely studied. Here, we introduce a deep model to generate a person's entire connectome exclusively based on their age, sex, body phenotypes, cognition, and lifestyle factors. Using the richly phenotyped UK Biobank connectome cohort (N=8,086), we demonstrate that our model can generate network architectures that closely recapitulate connectomes mapped empirically using diffusion MRI and tractography. We find that age, sex, and body phenotypes exert the strongest influence on the connectome generation process, with an impact approximately four times greater than that of cognition and lifestyle factors. Regional differences in the importance of measures were observed, including an increased importance of cognition in the association cortex relative to the visual system. We further show that generated connectomes can improve the training of machine learning models and reduce their predictive errors. Our work demonstrates the feasibility of inferring brain connectivity from an individual's personal data and enables future applications of connectome generation such as data augmentation and anonymous data sharing.

Dual process impairments in reinforcement learning and working memory systems underlie learning deficits in physiological anxiety
Anxiety has been robustly linked to deficits in frontal executive function including working memory (WM) and attentional control processes. However, although anxiety has also been associated with impaired performance on learning tasks, computational investigations of reinforcement learning (RL) impairment in anxiety have yielded mixed results. WM processes are known to contribute to learning behavior in parallel to RL processes and to modulate the effective learning rate as a function of load. However, WM processes have typically not been modeled in investigations of anxiety and RL. In the current study, we leveraged an experimental paradigm (RLWM) which manipulates the relative contributions of WM and RL processes in a reinforcement learning and retention task using multiple stimulus set sizes. Using a computational model of interactive RL and WM processes, we investigated whether individual differences in physiological or cognitive anxiety impacted task performance via deficits in RL or WM. Elevated physiological, but not cognitive, anxiety scores were strongly associated with worse performance during learning and retention testing across all set sizes. Computationally, higher physiological anxiety scores were significantly related to reduced learning rate and increased rate of WM decay. To highlight the importance of modeling WM contributions to learning, we considered the effect of fitting RL models without WM modules to the data. Here we found that reduced learning performance for higher physiological anxiety was at least partially misattributed to stochastic decision noise in 9 out of 10 RL-only models considered. These findings reveal a dual-process impairment in learning in anxiety that is linked to a more physiological than cognitive anxiety phenotype. More broadly, this work also points to the importance of accounting for the contribution of WM to RL when investigating psychopathology-related deficits in learning.

The Evolving Landscape of Neuroscience
Neuroscience emerged as a distinct academic discipline during the 20th century and has undergone rapid expansion since then. However, a comprehensive analysis of its evolving landscape remains lacking. The present study provides a large-scale, data-driven, mapping of neuroscience research. Leveraging large language models and clustering techniques to analyze 461,316 articles published between 1999 and 2023, this study reveals the field's structural organization and highlights dominant themes. Citation network analysis uncovers a surprisingly integrated picture and key intellectual hubs that shape the broader research landscape. An analysis of how research clusters align with pre-defined dimensions demonstrates a strong experimental focus, widespread reliance on micro theories, and a growing emphasis on applied and translational research. At the same time, fundamental research is at the risk of decline while theoretical work and cross-scale integration remain limited. This study provides a framework for understanding neuroscience's trajectory and identifies potential avenues for strengthening the field.

Transcranial Magnetic Stimulation Reduces Non-Decision Time in Perceptual Decisions
Perceptual decision-making enables humans to process sensory information and translate it into goal-directed actions. A critical component of this process is response time, which declines with age due to the slowing of both non-decision processes and evidence accumulation. While perceptual learning has been shown to counteract these declines, it remains unclear whether non-decision processes can be accelerated through direct neural stimulation, bypassing the need for long training sessions. Here, we propose that Transcranial Magnetic Stimulation (TMS) can enhance perceptual decision-making by specifically reducing non-decision time. To test this hypothesis, we tracked response times during a perceptual learning task while recording brain activity. Using the Drift Diffusion Model, we quantified the effects of TMS on mental speed and non-decision time. Our findings reveal that perceptual learning decreases response time by simultaneously increasing mental speed and reducing non-decision time. Crucially, TMS application to brain regions associated with perceptual learning further shortened non-decision time without altering mental speed. These results demonstrate that TMS can selectively accelerate non-decision processes, offering a promising intervention for mitigating age-related cognitive slowing and enhancing decision efficiency.

Magnetoencephalography Reveals Neuroprotective Effects of COVID-19 Vaccination in Non-Human Primates
COVID-19, caused by the SARS-CoV-2 virus, can lead to widespread neurological complications, including cognitive deficits and neurodegenerative symptoms, even in the absence of significant structural brain abnormalities. The potential neuroprotective effects of SARS-CoV-2 vaccination remain underexplored. Here, we demonstrate the neuroprotective effects of a psoralen-inactivated SARS-CoV-2 vaccine in a non-human primate model using resting-state magnetoencephalography (MEG), a non-invasive neurophysiological recording technique with sub-millisecond temporal and submillimeter spatial resolution. MEG scans demonstrated substantial preservation of neural activity across multiple brain regions in vaccinated subjects compared to unvaccinated controls following viral challenge. This approach not only underscores the role of vaccination in mitigating severe neurological outcomes but also highlights the capability of MEG to detect subtle yet significant changes in brain function that may be overlooked by other imaging modalities. These findings advance our understanding of vaccine-induced neuroprotection and establish MEG as a powerful tool for monitoring brain function in the context of viral infections.

TGIF2 is a major regulator of neural stem cell fate and neurogenic priming
During brain development, neural stem cells (NSCs) must balance self-renewal with differentiation and ensure lineage progression. To identify novel regulators of NSCs during neurogenesis, we isolated NSCs by FACS from the mouse cerebral cortex and ganglionic eminence at mid-neurogenesis, and at birth, when gliogenesis starts in both, but neurogenesis only continues in the latter region. RNA-seq and ATAC-seq revealed major transcriptional and chromatin changes between these stages and identified TGFB-Induced Homeobox Factor 2 (TGIF2) as a key candidate factor in neurogenic NSCs. In vitro and in vivo experiments demonstrated a potent role of TGIF2 controlling NSC fate maintenance mediated by its interaction with the SIN3A/HDAC repressor complex suppressing neuronal differentiation genes. Multiomic comparison of NSC and neuron gene expression allowed the comprehensive analysis of neurogenic priming in cortical NSCs, identifying TGIF2 as its major regulator by restraining neuronal differentiation gene activation in NSCs.

Implicit Emotional Biases in Anxiety and Depression: A Fast Periodic Visual Stimulation Study
Anxiety and depression are among the leading global causes of disability, yet their underlying neural mechanisms remain poorly understood. Traditional event-related potential (ERP) studies have shown attentional biases in anxiety and blunted responses to positive stimuli in depression, but limitations in sensitivity and interpretability hinder their clinical application. Fast Periodic Visual Stimulation (FPVS) offers an objective, high signal-to-noise ratio (SNR) approach to measuring neural responses to emotional stimuli. In this study, we applied FPVS with affective images to assess differences in emotional processing between individuals with anxiety and healthy controls across two experimental phases, optimizing stimulus presentation parameters. The results revealed that individuals with anxiety exhibited increased neural responses to negative stimuli compared to positive stimuli, as well as reduced responses to high-arousal stimuli, particularly in occipito-temporal and central-parietal regions. Additionally, individuals with comorbid depression showed blunted responses to high-arousal stimuli across multiple brain regions, consistent with reduced emotional reactivity. These findings support the feasibility of FPVS as a rapid and reliable tool for assessing emotional processing differences in clinical populations, with potential applications in translational research and psychiatric screening.

Nitrous oxide modulates cortical activity, wake-sleep oscillations, and produces antidepressant-like effects in mice
Emerging evidence suggests that nitrous oxide (N2O), a gaseous NMDA receptor antagonist and dissociative anesthetic, exerts rapid antidepressant effects akin to subanesthetic ketamine. However, its cellular, molecular, and behavioral effects remain poorly understood. Using in vivo two-photon imaging through cortical microprisms, we demonstrate that 50% N2O/O2 rapidly increases neuronal calcium activity in the mouse medial prefrontal cortex (mPFC). This was corroborated by elevated c-Fos expression at both protein and mRNA levels in mPFC lysates. Cortical EEG recordings revealed that N2O increased subsequent wake-associated gamma oscillations and enhanced slow-wave activity during sleep, suggestive of cortical activation and synaptic potentiation. In a chronic corticosterone stress model, N2O elicited antidepressant-like behavioral effects in several, though not all, domains. Together, these findings indicate that a single treatment with N2O rapidly enhances cortical activity, modulates sleep and wake EEG oscillations, and produces antidepressant-like effects, paralleling key actions associated with subanesthetic ketamine.

Genetic targeting of astrocytes associated with specific neuronal circuit in adult Drosophila
Astrocytes are the major glial population of the brain and have been associated with a vast number of functions. To probe this diversity and to reach a similar level of understanding about astrocyte physiology that we have about neurons, we need genetic tools to target specific astrocytic subpopulations. In Drosophila, we are restricted to using driver lines that drive expression in astrocytes throughout the brain. To target specific astrocytes, we have optimized the genetic tool TRACT (and refer to it as astro-TRACT), allowing effector expression specifically in local astrocytes of a given neuronal circuit. We analyzed specificity, sensitivity and reproducibility of the tool across various MB split-Gal4 drivers. We found that the number of pre-synapses correlates positively with the success of the tool. Applying the tool to characterize morphology of individual astrocytes revealed that local astrocytes around MB medial compartments project into the ellipsoid body. Astro-TRACT will be a valuable resource to investigate both mechanistic astrocyte-neuron signaling and functional and structural astrocytic diversity across the adult Drosophila brain.

EEG Microstates reveal distinct network dynamics in lucid and non-lucid REM sleep
During lucid dreaming, the dreamer is aware that they are dreaming. In past years, numerous studies have explored the characteristics of lucid dreams, which link lucid dreams to vivid visual perception, positive emotions, and wake-like metacognition and executive functions. To determine brain network activity associated with the conscious experience during lucid dreaming, we analyzed 39 sleep recordings (non-lucid REM vs. lucid REM) with 32-channel polysomnography from 8 lucid dreamers, using EEG microstate analysis. We found that microstates A and G dominated during lucid REM sleep compared to non-lucid REM sleep, and microstates B, C, and D dominated during non-lucid REM sleep compared to lucid REM sleep. We explored the correlation of our microstate maps with previous findings based on topographical similarities of the microstate maps in our study. This suggests that in our study, microstate A might be associated with emotional processing, microstate B with visual processing, microstate C with salience network activity, microstate D with executive functions, and microstate G with the default mode network. Our results suggest that lucidity during REM sleep is associated with increased self-visualization, metacognition, and executive processing, along with decreased emotional processing and reduced default mode network activity. Additionally, we found the inverse relationship between the presence of microstates/networks associated with regions that serve specific functions and evidence for the function being used. This might indicate the inhibitory function of the EEG microstates during sleep. Our study provides novel insight into the distinct network dynamics in lucid and non-Lucid REM sleep.

A Clinically Aligned Murine Model of Electroconvulsive Stimulation Reverses Social Aversion and Displays Fear Memory Impairment After Chronic Social Defeat Stress
Electroconvulsive therapy (ECT) remains the most effective treatment for patients with major depression, bipolar depression, mania, catatonia, and severe psychosis. Nonetheless, the mechanisms underlying the therapeutic effects of ECT largely remain unknown. While previous preclinical studies have noted a role for neurotropic signaling, neurogenesis, and alterations in monoamine neurotransmitter systems, these models were largely conducted using procedures that deviate from clinical practice. Therefore, we sought to develop a clinically relevant murine model of electroconvulsive stimulation (ECS), a model of ECT, which more closely replicates current clinical approaches and then employ this model to explore ECS mechanisms. Using the well-established chronic social defeat stress (CSDS) paradigm, known to disrupt reward and motivated behaviors, we investigated whether the behavioral changes after CSDS could be reversed following a clinically related course of ECS. Additionally, we observed induction of plasticity-related genes in the nucleus accumbens (NAcc) and amygdala, regions responsible for reward- and fear-related memory, respectively. Lastly, we investigated ECS-related changes in the NAcc with RNA-sequencing. This approach revealed a gene expression profile associated with ECS-related changes in NAcc. Pathway analysis demonstrated cellular changes primarily involved in regulating cell migration and differentiation. Therefore, utilizing our novel and clinically relevant model of ECS, we have begun to elucidate mechanisms that contribute to ECTs therapeutic outcomes by examining murine behavior and RNA from brain regions associated with stress-induced states that model anxiety and depression and the impact of ECS.

Neurons in auditory cortex integrate information within constrained temporal windows that are invariant to the stimulus context and information rate
Much remains unknown about the computations that allow animals to flexibly integrate across multiple timescales in natural sounds. One key question is whether multiscale integration is accomplished by diverse populations of neurons, each of which integrates information within a constrained temporal window, or whether individual units effectively integrate across many different temporal scales depending on the information rate. Here, we show that responses from neurons throughout the ferret auditory cortex are nearly completely unaffected by sounds falling beyond a time-limited "integration window". This window varies substantially across cells within the auditory cortex (~15 to ~150 ms), increasing substantially from primary to non-primary auditory cortex across all cortical layers, but is unaffected by the information rate of sound. These results indicate that multiscale computation is predominantly accomplished by diverse and hierarchically organized neural populations, each of which integrates information within a highly constrained temporal window.

Connectome-seq: High-throughput Mapping of Neuronal Connectivity at Single-Synapse Resolution via Barcode Sequencing
Understanding neuronal connectivity at single-cell resolution remains a fundamental challenge in neuroscience, with current methods particularly limited in mapping long-distance circuits and preserving cell type information. Here we present Connectome-seq, a high-throughput method that combines engineered synaptic proteins, RNA barcoding, and parallel single-nucleus and single-synaptosome sequencing to map neuronal connectivity at single-synapse resolution. This AAV-based approach enables simultaneous capture of both synaptic connections and molecular identities of connected neurons. We validated this approach in the mouse pontocerebellar circuit, identifying both established projections and potentially novel synaptic partnerships. Through integrated analysis of connectivity and gene expression, we identified molecular markers enriched in connected neurons, suggesting potential determinants of circuit organization. By enabling systematic mapping of neuronal connectivity across brain regions with single-cell precision and gene expression information, Connectome-seq provides a scalable platform for comprehensive circuit analysis across different experimental conditions and biological states. This advance in connectivity mapping methodology opens new possibilities for understanding circuit organization in complex mammalian brains.

Decoding auditory working memory load from EEG alpha oscillations
Working memory (WM) enables temporary retention of task-relevant information for imminent use. Increases in visual WM load are accompanied by elevated contralateral delay activity (CDA), and EEG alpha-band power. While most WM research focuses on the visual domain, it remains unknown whether similar EEG responses also reflect WM load in the auditory domain. Using EEG, we set out to establish such neuro-markers of auditory WM load. Participants memorized the pitches of 1 to 4 pure tones presented to one ear, with 1 to 4 consistent distractor tones presented to the other ear. Behaviorally, auditory WM capacity plateaued between set-sizes two and three. Unlike for visual WM, auditory WM load was not reflected in lateralized EEG responses. This shows that the CDA is a vision-specific rather than domain-general neuro-marker of WM load. Applying multivariate pattern analyses on the delay activity revealed that auditory WM load is reflected in (mostly temporal) patterns of alpha-band oscillations. Surprisingly, a temporal generalization analysis revealed that the alpha patterns reflecting specific load conditions changed throughout the maintenance period (despite load being inherently constant), revealing dynamic coding of auditory WM load.

Deep Sound Synthesis Reveals Novel Category-Defining Sound Features in the Human Auditory Cortex
The human auditory system extracts meaning from the environment by transforming acoustic input signals into semantic categories. Specific acoustic features give rise to distinct categorical percepts, such as speech or music, and to spatially distinct preferential responses in the auditory cortex. These responses contain category-relevant information, yet their representational level and role within the acoustic-to-semantic transformation process remain unclear. We combined neuroimaging, a deep neural network, a brain-based sound synthesis, and psychophysics to identify the sound features that are internally represented in the speech- and music-selective human auditory cortex and test their functional role in sound categorization. We found that the synthetized sounds exhibit unnatural features distinct from those normally associated with speech and music, yet they elicit categorical cortical and behavioral responses resembling those of natural speech and music. Our findings provide new insights into the fundamental sound features underlying speech and music categorization in the human auditory cortex.

Genetic and pharmacological correction of impaired mitophagy in retinal ganglion cells rescues glaucomatous neurodegeneration
Progressive loss of retinal ganglion cells (RGCs) and degeneration of optic nerve axons are the pathological hallmarks of glaucoma. Ocular hypertension (OHT) and mitochondrial dysfunction are linked to neurodegeneration and vision loss in glaucoma. However, the exact mechanism of mitochondrial dysfunction leading to glaucomatous neurodegeneration is poorly understood. Using multiple mouse models of OHT and human eyes from normal and glaucoma donors, we show that OHT induces impaired mitophagy in RGCs, resulting in the accumulation of dysfunctional mitochondria and contributing to glaucomatous neurodegeneration. Using mitophagy reporter mice, we show that impaired mitophagy precedes glaucomatous neurodegeneration. Notably, the pharmacological rescue of impaired mitophagy via Torin-2 or genetic upregulation of RGC-specific Parkin expression restores the structural and functional integrity of RGCs and their axons in mouse models of glaucoma and ex-vivo human retinal-explant cultures. Our study indicates that impaired mitophagy contributes to mitochondrial dysfunction and oxidative stress, leading to glaucomatous neurodegeneration. Enhancing mitophagy in RGCs represents a promising therapeutic strategy to prevent glaucomatous neurodegeneration.

Gene Editing for ATXN3 Inactivation in Machado-Joseph disease: CRISPR-Cas9 as a Therapeutic Alternative to TALEN-Induced Toxicity
Machado-Joseph disease (MJD) is an autosomal dominantly-inherited neurodegenerative disorder, caused by an over-repetition of the polyglutamine-codifying region in the ATXN3 gene. Strategies based on the suppression of the deleterious gene products have demonstrated promising results in pre-clinical studies. Nonetheless, these strategies do not target the root cause of the disease. In order to prevent the downstream toxic pathways, our goal was to develop gene editing-based strategies to permanently inactivate the human ATXN3 gene. TALENs and CRISPR-Cas9 systems were designed to target exon 2 of this gene and functional characterization was performed in a human cell line. After the demonstration of TALEN and CRISPR-Cas9 efficiency on gene disruption, a sequence of each system was selected for further in vivo experiments. Although both TALENs and CRISPR-Cas9 systems led to a drastic reduction of ATXN3 aggregates in the striatum of a lentiviral-based mouse model of MJD/SCA3, only CRISPR-Cas9 system allowed the improvement of key neuropathological markers of the disease. Importantly, the administration of the engineered system in YAC-MJD84.2/84.2 mice mediated a delay in disease progression, when compared with non-treated littermates. These data provide the first in vivo evidence of the efficacy of a CRISPR-Cas9-based approach to permanently inactivate the ATXN3 gene in the brain of two mouse models of the disease, supporting its potential as a new therapeutic avenue in the context of MJD/SCA3.