bioRxiv Subject Collection: Neuroscience's Journal
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Saturday, April 5th, 2025
| Time |
Event |
| 2:45a |
A proteogenomic tool uncovers protein markers for human microglial states
Human microglial heterogeneity has been largely described using transcriptomic data. Here, we introduce a microglial proteomic data resource and a Cellular Indexing of Transcriptomes and Epitopes by Sequencing panel enhanced with antibodies targeting 17 microglial cell surface proteins (mCITE-Seq). We evaluated mCITE-Seq on HMC3 microglia-like cells, induced-pluripotent stem cell-derived microglia (iMG), and freshly isolated primary human microglia. We identified novel protein microglial markers such as CD51 and relate expression of 101 cell surface proteins to transcriptional programs. This results in the identification and validation of three protein marker combinations with which to purify microglia enriched with each of 23 transcriptional programs; for example, CD49D, HLA-DR and CD32 enrich for GPNMBhigh (disease associated) microglia. Further, we identify and validate proteins, SIRPA, PDPN and CD162, that differentiate microglia from infiltrating macrophages. The mCITE-Seq panel enables the transition from RNA-based classification and facilitates the functional characterization and harmonization of model systems. | | 2:45a |
Autonomic responses to proprioceptive and visual errors during single-trial reach adaptation
Recent evidence suggests that not only the implicit but also explicit cognitive learning processes play a significant role in acquiring sophisticated motor skills. How these processes interact with each other, or how we can quantify them without bias, are, however, still elusive. To tackle these issues, here we employ simultaneous measurement of peripheral autonomic signals during the short-term motor learning paradigm. Through extensive research in the cognitive learning field, autonomic measures, such as pupil diameter, have been shown to reflect various internal states associated with the adjustment of learning behavior, suggesting that they could also be an effective tool to assess cognitive processes during motor learning. In a series of experiments, we measured the multiple autonomic signals, including pupil diameter, skin conductance, and heart rate, while human participants of both sexes learned to reach under occasional proprioceptive or visual disturbances. We characterized the phasic autonomic responses to errors and evaluated their influence over motor learning, which was quantified by comparing the trials immediately before and after the error event. The results demonstrated the dose-dependent increase in the phasic autonomic responses to errors of both modalities, consistent with higher cognitive demand in large errors. Using a latent factor analysis, which combines the multimodal autonomic response data, we also found a statistical relationship between the latent autonomic states and the motor learning rate, the suppression of implicit motor adaptation at higher error-induced sympathetic state. These results provide a novel insight into how internal state change affects motor learning. | | 2:45a |
JACUZI-SD: An automated, high-throughput, minimally stressful approach to sleep depriving larval zebrafish.
While sleep deprivation broadly disrupts health and well-being, the neural and molecular mechanisms that signal increased sleep pressure remain poorly understood. A key obstacle to progress is the fact that traditional methods for inducing sleep deprivation (SD) in animal models often introduce confounding stress or disrupt circadian rhythms. Here, we present JACUZI-SD (Jetting Automated Currents Under Zebrafish to Induce Sleep Deprivation), a fully automated, high-throughput system designed to induce sleep deprivation in larval zebrafish with minimal stress. By delivering randomized water pulses via a custom milli-fluidic device integrated with a 96-well plate, JACUZI-SD promotes wakefulness during the natural dark cycle without the stress associated with existing SD methods. Our results demonstrate that JACUZI-SD reduces total sleep time by 41-64% and elicits a robust rebound sleep characterized by increased sleep bout length following deprivation. Importantly, this method avoids activating the hypothalamic-pituitary-interrenal (HPI) stress axis, as evidenced by reduced stress marker expression compared to other deprivation methods. Additionally, the system reliably activates established sleep pressure pathways, including the upregulation of galanin in the neurosecretory preoptic area, while also revealing biologically relevant inter-individual variability in homeostatic rebound responses. JACUZI-SD provides a powerful, minimally invasive platform for dissecting the neural and molecular underpinnings of sleep homeostasis in vertebrates. | | 10:50a |
Incorporating special interests to investigate the language system in autism: A feasibility pilot fMRI study
Most autistic individuals have sustained, focused interests in particular topics or activities. In some cases, these special interests have been shown to motivate communicative behaviors, a domain in which many autistic individuals experience challenges. We conducted a pilot study with 15 autistic children (ages 8.18 - 13.27 years, mean(SD)= 11.17(1.62), 3 female/11 male/1 nonbinary), comparing brain responses elicited by short narratives tailored to individuals' special interests to responses elicited by generic, non-tailored narratives. Using functional magnetic resonance imaging (fMRI), we found that autistic children did not show typical language responses to generic narratives. However, they did show heightened responses to the narratives that incorporated their special interests relative to the generic narratives in language regions and in regions associated with reward and self-reference. Brain responses for personalized narratives were also more consistent across children than responses for the generic narratives. These results suggest that personalizing stimuli by incorporating special interests might be a promising approach for neuroimaging in autistic participants. | | 10:50a |
Functional interrogation of neuronal connections by chemoptogenetic presynaptic ablation
Most neurons are embedded in multiple circuits, with signaling to distinct postsynaptic partners playing functionally different roles. The function of specific connections can be interrogated using synaptically localized optogenetic effectors, however these tools are often experimentally difficult to validate or produce paradoxical outcomes. We have developed a system for photoablation of synaptic connections originating from genetically defined neurons, based on presynaptic localization of the fluorogen activating protein dL5** that acts as a photosensitizer when bound to a cell-permeable dye. Using the well mapped zebrafish escape circuit as a readout, we first show that cytoplasmically expressed dL5** enables efficient spatially targeted neuronal ablation using near infra-red light. We then demonstrate that spatially patterned illumination of presynaptically localized dL5** can effectively disconnect neurons from selected downstream partners, producing precise behavioral deficits. This technique should be applicable to almost any genetically tractable neuronal circuit, enabling precise manipulation of functional connectivity within the nervous system. | | 10:50a |
Parametric Modulation of a Shared Midbrain Circuit Drives Distinct Vocal Modes in a Singing Mouse
Neural circuits capable of generating multiple outputs are essential for behavioral flexibility, yet their organizational principles remain poorly understood. Using vocal communication in singing mice (Scotinomys teguina), we investigated whether distinct vocal behaviors are controlled by separate pathways or by shared circuits operating under different parametric regimes. We developed a novel behavioral assay (PAIRId---Partial Acoustic Isolation Reveals Identity) that enables precise attribution of vocalizations during social interactions in singing mice. This approach revealed two major vocal modes: loud, temporally patterned songs used for long-distance communication and soft, unstructured ultrasonic vocalizations (USVs) employed during close-range interactions. Despite their dramatic acoustic and contextual differences, both vocal modes share peripheral sound production mechanisms and central neural control by the caudolateral periaqueductal gray (clPAG). We derived a simple mathematical model describing song rhythm as a linear progression of note rates, which captures song motor patterning with just three parameters and accurately predicts song duration across animals and conditions. Using this model, we demonstrate that progressive silencing of clPAG neurons systematically alters specific song parameters before eliminating all vocalizations. Notably, one of these parameters - which controls song termination - also accounts for natural sexual dimorphism in song production. Our findings reveal how differential amplitude and frequency modulation of shared neural circuits produces categorically distinct behavioral outputs and provide a mechanistic basis for how behavioral innovations can emerge through evolutionary tinkering of ancestral neural pathways. | | 10:50a |
Individual differences in sequential decision-making
People differ widely in how they make decisions in uncertain environments. While many studies leverage this variability to measure differences in specific cognitive processes and parameters, the key dimension(s) of individual variability in uncertain decision-making tasks has not been identified. Here, we analyzed behavioral data from 1001 participants performing a restless three-armed bandit task, where reward probabilities fluctuated unpredictably over time. Using a novel analytical approach that controlled for the stochasticity in this tasks, we identified a dominant nonlinear axis of individual variability. We found that this primary axis of variability was strongly and selectively correlated with the probability of exploration, as inferred by latent state modeling. This suggests that the major factor shaping individual differences in bandit task performance is the tendency to explore (versus exploit), rather than personality characteristics, reinforcement learning model parameters, or low-level strategies. Certain demographic characteristics also predicted variance along this principle axis: participants at the exploratory end tended to be younger than participants at the exploitative end, and self-identified men were overrepresented at both extremes. Together, these findings offer a principled framework for understanding individual differences in task behavior while highlighting the cognitive and demographic factors that shape individual differences in decision-making under uncertainty. | | 10:50a |
Glucocorticoid receptors mediate reprogramming of astrocytes in depression.
Psychiatric disorders are among the most pressing problems of the modern society, with various forms of depression affecting more than 300 millions of people worldwide. Dysfunction of glial cells has consistently been reported in major depressive disorder (MDD); however, no comprehensive resource detailing glial dysfunction is available. To provide insight into neurobiological mechanisms behind severe psychiatric symptoms, we performed transcriptional analysis of post-mortem samples from a subpopulation of suicide completers with previously reported glial abnormalities. We focused on BA25, a subregion of the prefrontal cortex prioritized for targeted medical interventions, due to its metabolic aberrations in disease. We found that a significant portion of genes deregulated in MDD is enriched in glia, with astrocyte-specific genes representing the highest fraction. Then we employed a novel protocol for enriching astrocytic nuclei to provide a detailed molecular signature of astrocytes in MDD. The analysis of the gene set revealed the glucocorticoid receptor (GR) as a key regulatory transcription factor. We found that astrocyte-specific elimination of the GR in mice largely prevented transcriptional, metabolic and behavioral changes elicited by chronic stress. We also demonstrated that regional manipulation of glutamate turnover in astrocytes suffices to elicit discrete traits of depressive-like behavior. Our data points to astrocytes as a key cellular site of convergence of multiple traits of depression and provide a resource for exploring novel targets for glia-focused therapeutic approaches. | | 10:50a |
Pyruvate kinase deficiency links metabolic perturbations to neurodegeneration and axonal protection
Neurons rely on tightly regulated metabolic networks to sustain their high-energy demands, particularly through the coupling of glycolysis and oxidative phosphorylation. Here, we investigate the role of pyruvate kinase (PyK), a key glycolytic enzyme, in maintaining axonal and synaptic integrity in the Drosophila melanogaster neuromuscular system. Using genetic deficiencies in PyK, we show that disrupting glycolysis induces progressive synaptic and axonal degeneration and severe locomotor deficits. These effects require the conserved dual leucine zipper kinase (DLK), Jun N-terminal kinase (JNK), and activator protein 1 (AP-1) Fos transcription factor axonal damage signaling pathway and the SARM1 NADase enzyme, a key driver of axonal degeneration. As both DLK and SARM1 regulate degeneration of injured axons (Wallerian degeneration), we probed the effect of PyK loss on this process. Consistent with the idea that metabolic shifts may influence neuronal resilience in context-dependent ways, we find that pyk knockdown delays Wallerian degeneration following nerve injury, suggesting that reducing glycolytic flux can promote axon survival under stress conditions. This protective effect is partially blocked by DLK knockdown and fully abolished by SARM1 overexpression. Together, our findings help bridge metabolism and neurodegenerative signaling by demonstrating that glycolytic perturbations causally activate stress response pathways that dictate the balance between protection and degeneration depending on the system's state. These results provide a mechanistic framework for understanding metabolic contributions to neurodegeneration and highlight the potential of metabolism as a target for therapeutic strategies. | | 10:50a |
MeCP2 controls dendritic morphogenesis via miR-199a-mediated Qki downregulation
Rett syndrome (RTT) (OMIM: 312750) is a severe neurodevelopmental disorder caused by mutations in the MECP2 gene. Although decreased dendritic morphogenesis has been observed in the brain of RTT patients and mouse models, the molecular mechanisms underlying these dendritic anomalies remain unclear. We have previously shown that MeCP2 facilitates specific microRNA (miRNA) processing by associating with the miRNA microprocessor Drosha complex. In this study, we show that MeCP2 positively regulates dendritic formation via miR-199a, a specific target of the MeCP2-Drosha complex. Overexpression of MeCP2 and miR-199a promotes dendritic development such as increases in dendrite length, branching number, and complexity. In contrast, blocking miR-199a inhibited dendrite formation and abolished enhanced dendritic development induced by MeCP2 expression. We also demonstrate that the decreased dendrite outgrowth observed in MeCP2-deficient neurons could be rescued by miR-199a expression. In addition, we found that miR-199a targets the 3' untranslated region of quaking (Qki), a negative regulator of dendritic development, and downregulates its protein expression level. Furthermore, we report an increase in the Qki protein expression level in miR-199a-2-deficient brains and show that Qki knockdown restores the dendritic morphology of miR-199a-2-Knockout (KO) neurons. Taken together, these results suggest that the MeCP2/miR-199a/Qki axis is critical for proper dendritic development and its dysregulation contributes to the dendritic pathology in RTT. | | 4:31p |
Whole-night gentle rocking improves sleep in poor sleepers with insomnia complaints.
Specific brain oscillations can be manipulated during sleep to improve sleep quality and memory performance. We previously demonstrated that continuous rocking stimulation (0.25Hz, lateral movement) applied to good sleepers during sleep enhanced stable deep sleep, boosted NREM oscillations (spindles and slow waves), and memory consolidation. Here, we investigated whether nocturnal rocking could benefit individuals suffering from sleep difficulties. We recruited sixteen young adults with subjective difficulties initiating and/or maintaining sleep and who presented with objective poor sleep quality. Each participant spent two nights of sleep at the laboratory, one rocking and one stationary, during which we assessed sleep and declarative memory consolidation. We found that a whole night of gentle rocking in individuals with poor sleep decreased sleep fragmentation, time spent awake and in light sleep (N1), with an associated increase in objective sleep efficiency and subjective sleep quality. Additionally, we replicated the neural entrainment or synchronizing effect of the rocking motion, yielding a boost in NREM fast spindles and slow oscillations. Yet, these changes in sleep did not modulate overnight memory performance. By alleviating some difficulties encountered in this population of poor sleepers (e.g., sleep maintenance and poor self-reported sleep), these findings provide preliminary evidence that rocking may represent an alternative or complementary intervention for the management of some forms of chronic insomnia. | | 5:46p |
Automated sleep scoring in hibernating and non-hibernating American black bears
Hibernating bears show remarkable metabolic suppression. Their decline in core body temperature (Tb) is moderate (from 38{degrees}C to 30-35{degrees}C), but their metabolism declines as much as 75%. To understand the role of sleep in this hypometabolic state, we recorded biotelemetrically EEG, EOG and EMG data over 3500 days from 16 captive American black bears in and out of hibernation under semi-natural conditions. This data set is too large to score manually for Wake, REM- and NREM sleep, so we tested two machine learning classifiers: (1) Somnotate trained on multiple one-day recordings, and (2) Somnivore, trained on a small subset from each recording. As automated scoring methods have not been applied to hibernating species before, a major concern is the effect changing brain temperature has on the EEG and on the machine learning based detection. Therefore, we selected reference data using consensus by 3 manual sleep scorers from each of 6 bears, two one-day recordings at the highest and lowest body temperatures during hibernation when Tb was oscillating in multiday cycles, and a non-hibernating one-day recording in summer. Somnotate results were excellent when trained separately for hibernating and non-hibernating data. Training Somnotate separately for high and low Tb within hibernation did not improve results further. Sleep times in hibernation were about 2x that in summer for both automated scores and manual scores (p<0.0001). There were no significant differences in occupancy of vigilance states between automated and manual scores in hibernation (p>0.05), but a small overestimate of sleep time in summer (p<0.05). Both applications yielded F-measures against manual scores in the 0.90-0.98 range. Outliers in the 0.67-0.88 range were correlated between the two applications, indicating that specific files are more challenging to annotate. We conclude that both applications have accuracies approaching that of manual scorers when trained on high quality data. |
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