bioRxiv Subject Collection: Neuroscience's Journal
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Friday, October 25th, 2024
| Time |
Event |
| 8:16a |
GABAergic neurons can facilitate the propagation of cortical spreading depolarization: experiments in mouse neocortical slices and a novel neural field computational model
Cortical spreading depolarization (CSD) is a wave of depolarization with local onset and extended propagation implicated in several pathological conditions. Its mechanisms have been extensively investigated, including our recent studies showing with experimental and computational approaches that the hyperactivity of GABAergic neurons can initiate migraine-related CSD because of spiking-generated extracellular potassium (K+) build-up. However, less is known about the role played by GABAergic neurons in CSD propagation. Here we studied mechanisms of CSD propagation, focusing on the role of GABAergic neurons, with experiments performed in mouse brain slices and with a new spatially extended neural field computational model. Experimentally, we induced CSD by applying brief puffs of potassium chloride (KCl) in somatosensory cortex slices from wild type and VGAT-ChR2-tdtomato mice, which specifically express the excitatory opsin channelrhodopsin (ChR2) in GABAergic neurons. We evaluated the role of GABAergic neurons in CSD propagation by modulating their activity with optogenetic illumination and their synaptic connections with pharmacological tools. We have developed the computational model to obtain realistic simulations of both initiation and propagation of CSD. It includes large populations of interconnected excitatory and inhibitory neurons, as well as the effect of extracellular ion concentrations on their features. We found that the decrease of the synaptic activity of GABAergic neurons can enhance CSD propagation, because of the reduction of the inhibitory synaptic weight, whereas their spiking activity can enhance CSD propagation because of extracellular K+ upload. However, differently from for CSD initiation, the latter effect is normally hidden by the action of GABAergic synaptic transmission. A reduction of GABAergic synaptic transmission, which can be observed in pathological states, can reveal the potentiating effect of the K+ upload induced by GABAergic activation. The neural field model that we implemented can generate accurate simulations of CSD, providing testable hypotheses on mechanisms, and can also be used for modeling other (patho)-physiological activities of neuronal networks. | | 8:16a |
Cortical norepinephrine-astrocyte signaling critically mediates learned behavior
Updating behavior based on feedback from the environment is a crucial means by which organisms learn and develop optimal behavioral strategies. Norepinephrine (NE) release from the locus coeruleus (LC) has been shown to mediate learned behaviors such that in a task with graded stimulus uncertainty and performance, a high level of NE released after an unexpected outcome causes improvement in subsequent behavior. Yet, how the transient activity of LC-NE neurons, lasting tens of milliseconds, influences behavior several seconds later, is unclear. Here, we show that NE acts directly on cortical astrocytes via Adra1a adrenergic receptors to elicit sustained increases in intracellular calcium. Chemogenetic blockade of astrocytic calcium elevation prevents the improvement in behavioral performance. NE-activated calcium invokes purinergic pathways in cortical astrocytes that signal to neurons; pathway-specific astrocyte gene expression is altered in mice trained on the task, and blocking neuronal adenosine-sensitive A1 receptors also prevents post-reinforcement behavioral gain. Finally, blocking either astrocyte calcium dynamics or A1 receptors alters encoding of the task in prefrontal cortex neurons, preventing the post-reinforcement change in discriminability of rewarded and unrewarded stimuli underlying behavioral improvement. Together, these data demonstrate that astrocytes, rather than indirectly reflecting neuronal drive, play a direct, instrumental role in representing task-relevant information and signaling to neurons to mediate a fundamental component of learning in the brain. | | 8:16a |
Gene therapy for targeting a prenatally enriched potassium channel associated with severe childhood epilepsy and premature death
Dysfunction of the sodium-activated potassium channel KNa1.1 (encoded by KCNT1) is associated with a severe condition characterized by frequent seizures (up to hundreds per day) and is often fatal by age three years. We defined the early developmental onset of KNa1.1 channels in prenatal and neonatal brain tissue, establishing a timeline for pathophysiology and a window for therapeutic intervention. Using patch-clamp electrophysiology, we observed age-dependent increases in KNa1.1 K+ conductance. In neurons derived from a child with a gain-of-function KCNT1 pathogenic variant (p.R474H), we detected abnormal excitability and action potential afterhyperpolarization kinetics. In a clinical trial, two individuals with the p.R474H variant showed dramatic reductions in seizure occurrence and severity with a first-in-human antisense oligonucleotide (ASO) RNA therapy. ASO-treated p.R474H neurons in vitro exhibited normalized spiking and burst properties. Finally, we demonstrated the feasibility of ASO knockdown of KNa1.1 in mid-gestation human neurons, suggesting potential for early therapeutic intervention before the onset of epileptic encephalopathy. | | 8:16a |
Synaptic input architecture of visual cortical neurons revealed by large-scale synapse imaging without backpropagating action potentials
How neurons integrate thousands of synaptic inputs to compute sharply tuned outputs is a critical question in sensory information processing. To answer this question, it is essential to record the location and activity of synaptic inputs in vivo. However, back-propagating action potential (BAP) calcium signals invade dendrites and spines, making accurate recording of spine responses difficult. In this study, we first developed a new method to record spine calcium responses without BAP signals. Using this method, we performed large-scale imaging of visually evoked spine activity from layer 2/3 pyramidal neurons and revealed three patterns of dendritic functional architectures of synaptic inputs: dendrites with clusters of spines of similar responses, dendrites with spines of diverse responses, and dendrites with spines where the majority of them show no visual response. Our model suggests that only a small fraction of spines on dendrites of clustered architectures are sufficient to generate sharply tuned output. | | 8:16a |
Sex differences in deep brain shape and asymmetry persist across schizophrenia and healthy individuals: A meta-analysis from the ENIGMA-Schizophrenia Working Group
Background: Schizophrenia (SCZ) is characterized by a disconnect from reality that manifests as various clinical and cognitive symptoms, and persistent neurobiological abnormalities. Sex-related differences in clinical presentation imply separate brain substrates. The present study characterized deep brain morphology using shape features to understand the independent effects of diagnosis and sex on the brain, and to determine whether the neurobiology of schizophrenia varies as a function of sex. Methods: This study analyzed multi-site archival data from 1,871 male (M) and 955 female (F) participants with SCZ, and 2,158 male and 1,877 female healthy controls (CON) from twenty-three cross-sectional samples from the ENIGMA Schizophrenia Workgroup. Harmonized shape analysis protocols were applied to each site's data for seven deep brain regions obtained from T1-weighted structural MRI scans. Effect sizes were calculated for the following main contrasts: 1) Sex effects; 2) Diagnosis-by-Sex interaction; 3) within sex tests of diagnosis; 4) within diagnosis tests of sex differences. Meta-regression models between brain structure and clinical variables were also computed separately in men and women with schizophrenia. Results: Mass univariate meta-analyses revealed more concave-than-convex shape differences in all regions for women relative to men, across diagnostic groups (d = -0.35 to 0.20, SE = 0.02 to 0.07); there were no significant diagnosis-by-sex interaction effects. Within men and women separately, we identified more-concave-than-convex shape differences for the hippocampus, amygdala, accumbens, and thalamus, with more-convex-than-concave differences in the putamen and pallidum in SCZ (d = -0.30 to 0.30, SE = 0.03 to 0.10). Within CON and SZ separately, we found more-concave-than-convex shape differences in the thalamus, pallidum, putamen, and amygdala among females compared to males, with mixed findings in the hippocampus and caudate (d = -0.30 to 0.20, SE = 0.03 to 0.09). Meta-regression models revealed similarly small, but significant relationships, with medication and positive symptoms in both SCZ-M and SCZ-F. Conclusions: Sex-specific variation is an overriding feature of deep brain shape regardless of disease status, underscoring persistent patterns of sex differences observed both within and across diagnostic categories, and highlighting the importance of including it as a critical variable in studies of neurobiology. Future work should continue to explore these dimensions independently to determine whether these patterns of brain morphology extend to other aspects of neurobiology in schizophrenia, potentially uncovering broader implications for diagnosis and treatment. | | 8:16a |
Dendritome Mapping Unveils Spatial Organization of Striatal D1/D2-Neuron Morphology
Morphology is a cardinal feature of a neuron that mediates its functions, but profiling neuronal morphologies at scale remains a formidable challenge. Here we describe a generalizable pipeline for large-scale brainwide study of dendritic morphology of genetically-defined single neurons in the mouse brain. We generated a dataset of 3,762 3D-reconstructed and reference-atlas mapped striatal D1- and D2- medium spiny neurons (MSNs). Integrative morphometric analyses reveal distinct impacts of anatomical locations and D1/D2 genetic types on MSN morphologies. To analyze striatal regional features of MSN dendrites without prior anatomical constraints, we assigned MSNs to a lattice of cubic boxes in the reference brain atlas, and summarized morphometric representation ("eigen-morph") for each box and clustered boxes with shared morphometry. This analysis reveals 6 modules with characteristic dendritic features and spanning contiguous striatal territories, each receiving distinct corticostriatal inputs. Finally, we found aging confers robust dendritic length and branching defects in MSNs, while Huntington's disease (HD) mice exhibit selective length-related defects. Together, our study demonstrates a systems-biology approach to profile dendritic morphology of genetically-defined single-neurons; and defines novel striatal D1/D2-MSN morphological territories and aging- or HD-associated pathologies. | | 11:45a |
A universal hippocampal memory code across animals and environments
How learning is affected by context is a fundamental question of neuroscience, as the ability to generalize learning to different contexts is necessary for navigating the world. An example of swift contextual generalization is observed in conditioning tasks, where performance is quickly generalized from one context to another. A key question in identifying the neural substrate underlying this ability is how the hippocampus (HPC) represents task-related stimuli across different environments, given that HPC cells exhibit place-specific activity that changes across contexts (remapping). In this study, we used calcium imaging to monitor hippocampal neuron activity as animals performed a conditioning task across multiple spatial contexts. We investigated whether hippocampal cells, which encode both spatial locations (place cells) and task-related information, could maintain their task representation even when their spatial encoding remapped in a new spatial context. To assess the consistency of task representations, we used advanced dimensionality reduction techniques combined with machine learning to develop manifold representations of population level HPC activity. The results showed that task-related neural representations remained stable even as place cell representations of spatial context changed, thus demonstrating similar embedding geometries of neural representations of the task across different spatial contexts. Notably, these patterns were not only consistent within the same animal across different contexts but also significantly similar across different animals, suggesting a standardized neural encoding or 'neural syntax' in the hippocampus. These findings bridge a critical gap between memory and navigation research, revealing how the hippocampus maintains cognitive consistency across different spatial environments. These findings also suggest that hippocampal function is governed by a neural framework shared between animals, an observation that may have broad implications for understanding memory, learning, and related cognitive processes. Looking ahead, this work opens new avenues for exploring the fundamental principles underlying hippocampal encoding strategies. | | 3:19p |
Fragmentation and Multithreading of Experience in the Default-Mode Network
Reliance on internal predictive models of the world is central to many theories of human cognition. Yet it is unknown whether humans acquired multiple separate internal models, each evolved for a specific domain, or maintain a globally unified representation. Using fMRI, we show that during naturalistic experiences (during movie watching or narrative listening), adult participants selectively engage three topographically distinct midline prefrontal cortical regions, for different forms of predictions. Regions responded selectively to abstract spatial, referential (social), and temporal domains during model updates implying separate representations for each. Prediction-error-driven neural transitions in these regions, indicative of model updates, preceded subjective belief changes in a domain-specific manner. We find these parallel top-down predictions are unified and selectively integrated with sensory streams in the Precuneus, shaping participants' ongoing experience. Results generalized across sensory modalities and content, suggesting humans recruit abstract, modular predictive models for both vision and language. Our results highlight a key feature of human world modeling: fragmenting information into abstract domains before global integration. | | 3:19p |
Proteomic associations with cognitive variability as measured by the Wisconsin Card Sorting Test in a healthy Thai population: A machine learning approach
Cognitive function is the term for the higher-order mental processes in the brain that gather and process information, and it mirrors brain activity. Cognitive function in adults exhibits variability as a result of genetic and environmental components such as gender, age, and lifestyle factors to name a few. Interindividual variability in cognitive trajectories has been observed in community-dwelling older adults across different cognitive domains. Inter-individual variations in cognitive response to identical physical exercise are also evident. This study aimed to explore the association between serum protein expression profiles and one measure of cognitive variability, as measured by the Wisconsin Card Sorting Test (WCST), in a healthy Thai population using a machine learning approach. This study included 199 healthy Thai subjects, ranging in age from 20 to 70 years. Cognitive performance was measured by the WCST, and the WCST % Errors was used to define the lower and higher cognitive ability groups. Serum protein expression profiles were studied by the label-free proteomics method. The Linear Model for Microarray Data (LIMMA) approach in R was utilized to assess differentially expressed proteins (DEPs) between groups; subsequently bioinformatic analysis was performed for the functional enrichment and interaction network analysis of DEPs. A random forest model was built to classify subjects from the lower and higher cognitive ability groups. Cross-validation was used for model performance evaluation. The results showed that, there were 213 DEPs identified between the poor and higher cognition groups, with 155 DEPs being upregulated in the poor cognition group. Those DEPs were significantly enriched in the IL-17 signaling pathway. Furthermore, the analysis of protein-protein interaction (PPI) network revealed that most of the selected DEPs were linked to neuroinflammation-related cognitive impairment. The random forest model achieved a test classification accuracy of 81.5%. The model's sensitivity (true positive rate) was estimated to be 65%, and the specificity (true negative rate) was 85.9%. The AUC (0.79) indicates good binary classification performance. The results suggested that a measure of poor WCST performance in healthy Thai subjects might be attributed to higher levels of neuroinflammation. |
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