Project description:This is a model of one presynaptic and one postsynaptic cell, as described in the article: Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model. Wang XJ, Buzsáki G. J Neurosci. 1996 Oct 15;16(20):6402-13. PMID:8815919; Abstract: Fast neuronal oscillations (gamma, 20-80 Hz) have been observed in the neocortex and hippocampus during behavioral arousal. Using computer simulations, we investigated the hypothesis that such rhythmic activity can emerge in a random network of interconnected GABAergic fast-spiking interneurons. Specific conditions for the population synchronization, on properties of single cells and the circuit, were identified. These include the following: (1) that the amplitude of spike afterhyperpolarization be above the GABAA synaptic reversal potential; (2) that the ratio between the synaptic decay time constant and the oscillation period be sufficiently large; (3) that the effects of heterogeneities be modest because of a steep frequency-current relationship of fast-spiking neurons. Furthermore, using a population coherence measure, based on coincident firings of neural pairs, it is demonstrated that large-scale network synchronization requires a critical (minimal) average number of synaptic contacts per cell, which is not sensitive to the network size. By changing the GABAA synaptic maximal conductance, synaptic decay time constant, or the mean external excitatory drive to the network, the neuronal firing frequencies were gradually and monotonically varied. By contrast, the network synchronization was found to be high only within a frequency band coinciding with the gamma (20-80 Hz) range. We conclude that the GABAA synaptic transmission provides a suitable mechanism for synchronized gamma oscillations in a sparsely connected network of fast-spiking interneurons. In turn, the interneuronal network can presumably maintain subthreshold oscillations in principal cell populations and serve to synchronize discharges of spatially distributed neurons. The presynaptic and postsynaptic cell have identical parameters and the variables in each cell are identified by using _pre or _post as a postfix to their names. The presynaptic cell influences the postsynaptic one via the synapse (variables and parameters: I_syn, E_syn, g_syn, F, theta_syn, alpha, beta). The applied current to the presynaptic cell, I_app_pre, is set to 2 microA/cm2 for 10 ms as in figure 1C of the article. The dependence of the postsynaptic cell on directly applied current can be investigated in isolation by setting I_app_pre to 0 and altering I_app_post. Originally created by libAntimony v1.4 (using libSBML 3.4.1)

Project description:Genome-wide association studies (GWAS) have identified many risk genes for neuropsychiatric disorders (NPD) such as schizophrenia (SCZ). However, functional interpretation of these GWAS findings remains challenging; a major hurdle is that polygenic risk may manifest its effect conditionally upon neural activation, i.e., context-dependent. Human induced pluripotent stem cell (hiPSC)-derived neurons are a tractable cellular model for ascertaining context-dependent polygenic effects, e.g., neural activation that may mimic the physiological effects of environmental stimuli. Here, we modelled neural activation by depolarisation using high potassium chloride (KCl) in co-cultured excitatory/inhibitory neurons of 100 hiPSC lines (28 from SCZ donors), followed by assaying single-cell multiomes (scRNA/ATAC-seq) of over 700,000 nuclei from neurons at 0 hr (unstimulated), 1 hr (early response), and 6 hr (later response) of high KCI exposure. We linked genes with open chromatin peaks for each main neural subtype (GABAergic inhibitory, NEFM+ or NEFM-excitatory neurons) and confirmed a significant correlation between peak accessibility and target gene expression. Compared to static genes/peaks, dynamic ones, specifically those activity-upregulated, were more enriched for NPD GWAS risk, with the most robust enrichment for SCZ. Based on the dynamic gene expression pattern across the three time points, we found NPD risk genes tend to be continuously upregulated (i.e., with up-up dynamics). We further analysed context-specific SCZ-associated differentially expressed genes (DEGs) using MAST for single neurons of 28 SCZ cases and 72 controls. We found that 3-5%, 4-6%, and 15-23% of genes were SCZ-associated DEGs in NEFM+ excitatory, NEFM- excitatory, and GABAergic neurons, respectively, most of which were cell activity-specific. Notably, we found that SCZ-associated DEGs in high-activity neurons were more enriched for synapse-related GO terms and NPD risk genes. Interestingly, upstream regulatory sequences of the stimulation-specific SCZ-associated DEGs were enriched for binding sites of TCF4, which is a strong GWAS risk gene and was considered the master regulator of other SCZ-related genes. Moreover, the upregulated genes in SCZ cases in the stimulated (only at 6hr) NEFM+ excitatory neurons showed strong enrichment for GO terms related to cholesterol synthesis. Single-neuron DEG analysis for 28 SCZ cases and 28 matched controls gave similar results. Our study suggests that many NPD genes may only elicit disease-relevant effects upon neuronal activation, providing novel insights into how polygenic risk factors interact with environmental stimuli for NPD.

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Aberrant Neuronal Connectivity and Network Activity of Neurons Derived from Patients with Idiopathic Schizophrenia

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