A NEURONAL MODEL WITH VARIABLE SYNAPTIC INPUT EFFECT

被引：6
作者：
MUSILA, M
LANSKY, P
机构：
[1] Institute of Biophysics, Medical School of Charles University, Prague
[2] Institute of Physiology, Czech. Academy of Sciences, Prague
来源：
CYBERNETICS AND SYSTEMS | 1992年 / 23卷 / 01期
关键词：
D O I：
10.1080/01969729208927448
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The amplitude of a postsynaptic potential attenuates as it spreads from the synapse to the trigger zone, where spike generation is initiated. Thus, especially in neurons with a large dendritic structure, great variability in synaptically evoked changes of the membrane potential at the trigger zone can be expected. Therefore the randomly distributed magnitudes of jumps caused by input processes were assumed in Stein's neuronal model with reversal potentials. Two distributions, normal and exponential, were applied for this purpose. The normal distribution has no influence on statistical characteristics of the interspike interval (ISI). For the exponential distribution the mean ISI, as well as the coefficient of variation, increases nonlinearly with the parameter of the distribution. The coefficient of variation is limited by the value 1. The estimation of the mean ISI by the method of Smith and Smith (1984) is not applicable for the investigated model.
引用
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页码：29 / 40
页数：12
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