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Large time step discrete-time modeling of sharp wave activity in hippocampal area CA3

机译:海马CA3区锐波活动的大时间步离散时间建模

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Reduced models of neuronal spiking activity simulated with a fixed integration time step are frequently used in studies of spatio-temporal dynamics of neurobiological networks. The choice of fixed time step integration provides computational simplicity and efficiency, especially in cases dealing with large number of neurons and synapses operating at a different level of activity across the population at any given time. A network model tuned to generate a particular type of oscillations or wave patterns is sensitive to the intrinsic properties of neurons and synapses and, therefore, commonly susceptible to changes in the time step of integration. In this study, we analyzed a model of sharp-wave activity in the network of hippocampal area CA3, to examine how an increase of the integration time step affects network behavior and to propose adjustments of intrinsic properties of neurons and synapses that help minimize or remove the damage caused by the time step increase. (C) 2018 Published by Elsevier B.V.
机译:具有固定积分时间步长模拟的神经元突跳活动的简化模型经常用于神经生物学网络的时空动力学研究。固定时间步长积分的选择提供了计算的简便性和效率,特别是在处理大量神经元和突触的情况下,在任何给定时间,这些神经元和突触在整个群体中以不同的活动水平运行。调整为生成特定类型的振荡或波动模式的网络模型对神经元和突触的内在属性敏感,因此通常容易受到积分时间步长变化的影响。在这项研究中,我们分析了海马区CA3网络中的尖波活动模型,以考察积分时间步长的增加如何影响网络行为,并提出调节神经元和突触的内在特性的方法,以帮助最小化或去除神经元和突触。时间步长造成的损害增加。 (C)2018由Elsevier B.V.发布

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