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A Neuronal Model with Excitatory and Inhibitory Inputs Governed by a Birth-Death Process

机译:具有兴奋和抑制输入的出生死亡过程控制的神经元模型

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A stochastic model for the firing activity of a neuronal unit has been recently proposed in [4]. It includes the decay effect of the membrane potential in the absence of stimuli, and the occurrence of excitatory inputs driven by a Poisson process. In order to add the effects of inhibitory stimuli, we now propose a Stein-type model based on a suitable exponential transformation of a bilateral birth-death process on Z and characterized by state-dependent nonlinear birth and death rates. We perform an analysis of the probability distribution of the stochastic process describing the membrane potential and make use of a simulation-based approach to obtain some results on the firing density.
机译:最近在[4]中提出了一种神经元单位放电活动的随机模型。它包括在没有刺激的情况下膜电位的衰减效应,以及由泊松过程驱动的兴奋性输入的发生。为了增加抑制性刺激的作用,我们现在提出一种Stein型模型,该模型基于Z上双边生死过程的适当指数转换,并具有与状态有关的非线性生灭率。我们对描述膜电位的随机过程的概率分布进行分析,并使用基于模拟的方法来获得有关燃烧密度的一些结果。

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