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A simple stochastic model of spatially complex neurons

机译:空间复杂神经元的简单随机模型

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摘要

A method for studying the coding properties of a multicompartmental integrate-and-fire neuron of arbitrary geometry is presented. Depolarization at each compartment evolves like a leaky integrator with an after-firing reset imposed only at the trigger zone. The frequency of firing at the steady-state regime is related to the properties of the multidimensional input. The decreasing variability of subthreshold depolarization from the dendritic tree to the trigger zone is shown for an input that is corrupted by a white noise. The role of a Poissonian noise is also investigated. The proposed method gives an estimate of the mean interspike interval that can be used to study the input-output transfer function of the system. Both types of the stochastic inputs result in broadening the transfer function with respect to the deterministic case. (C) 2000 Elsevier Science Ireland Ltd. All rights reserved. [References: 19]
机译:提出了一种研究任意几何形状的多室积分并发射神经元的编码特性的方法。每个隔室的去极化都像泄漏的积分器一样演变,仅在触发区域施加发射后复位。稳态状态下的发射频率与多维输入的属性有关。对于由白噪声破坏的输入,显示了从树状树到触发区域的亚阈值去极化的减小的可变性。还研究了泊松噪声的作用。所提出的方法给出了平均尖峰间隔的估计,可用于研究系统的输入输出传递函数。相对于确定性情况,两种类型的随机输入都会导致传递函数的扩展。 (C)2000 Elsevier Science Ireland Ltd.保留所有权利。 [参考:19]

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