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无树突电位重置的随机模型神经元:在嗅觉系统中的应用。

Stochastic model neuron without resetting of dendritic potential: application to the olfactory system.

作者信息

Rospars J P, Lánský P

机构信息

Laboratoire de Biométrie, Institut National de la Recherche Agronomique, Versailles, France.

出版信息

Biol Cybern. 1993;69(4):283-94. doi: 10.1007/BF00203125.

Abstract

A two-dimensional neuronal model, in which the membrane potential of the dendrite evolves independently from that at the trigger zone of the axon, is proposed and studied. In classical one-dimensional neuronal models the dendritic and axonal potentials cannot be distinguished, and thus they are reset to resting level after firing of an action potential, whereas in the present model the dendritic potential is not reset. The trigger zone is modelled by a simplified leaky integrator (RC circuit) and the dendritic compartment can be described by any of the classical one-dimensional neuronal models. The new model simulates observed features of the firing dynamics which are not displayed by classical models, namely positive correlation between interspike intervals and endogenous bursting. It gives a more natural account of features already accounted for in previous models, such as the absence of an upper limit for the coefficient of variation of intervals (i.e. irregular firing). It allows the first- and second-order neurons of the olfactory system to be described with the same basic assumptions, which was not the case in one-point models. Nevertheless it keeps the main qualitative properties found previously, such as the existence of three regimens of firing with increasing stimulus concentration and the sigmoid shape of the firing frequency of first-order neurons as a function of the logarithm of stimulus concentration.

摘要

提出并研究了一种二维神经元模型,其中树突的膜电位独立于轴突触发区的膜电位演化。在经典的一维神经元模型中,树突电位和轴突电位无法区分,因此在动作电位发放后它们会被重置为静息水平,而在当前模型中,树突电位不会被重置。触发区由一个简化的漏电积分器(RC电路)建模,树突部分可以用任何经典的一维神经元模型来描述。新模型模拟了经典模型未显示的放电动力学观测特征,即峰峰间期与内源性爆发之间的正相关。它对先前模型中已考虑的特征给出了更自然的解释,例如间期变异系数没有上限(即不规则放电)。它允许用相同的基本假设来描述嗅觉系统的一级和二级神经元,这在单点模型中是不存在的情况。然而,它保留了先前发现的主要定性特性,例如随着刺激浓度增加存在三种放电模式,以及一级神经元的放电频率作为刺激浓度对数的函数呈S形。

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