文献类型：期刊文献

英文题名：Analysis of stability of neural network with inhibitory neurons

作者：Liu, Yan[1];Wang, Rubin[1];Zhang, Zhikang[1];Jiao, Xianfa[1,2]

机构：[1]E China Univ Sci & Technol, Inst Cognit Neurodynam, Shanghai 200237, Peoples R China;[2]Hefei Univ Technol, Dept Math, Sch Sci, Hefei, Peoples R China

年份：2010

卷号：4

期号：1

起止页码：61

外文期刊名：COGNITIVE NEURODYNAMICS

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000274455800004)】；

基金：The work was supported by the National Natural Science Foundation of China (NSFC) under Grant No. 10872068 and No. 10672057.

语种：英文

外文关键词：Inhibitory neural population; Excitatory neural population; Average number density; Critical state

摘要：Phase coding in a neural network composed of neural oscillators with inhibitory neurons was studied based on the theory of stochastic phase dynamics. We found that with increasing the coupling coefficients of inhibitory neural oscillators, the firing density in excitatory population transits to a critical state. In this case, when we increase the inhibitory coupling, the firing density will come into dynamic balance again and tend to a fixed value gradually. According to the phenomenon, in the paper we found parameter regions to exhibit those different population states, called dividing zones including flat fading zone, rapid fading zone and critical zone. Based on the dividing zones we can choose the number ratio between inhibitory neurons and excitatory neurons in the neural network, and estimate the coupling action of inhibitory population and excitatory population. Our research also shows that the balance value, enabling the firing density to reach the dynamic balance, does not depend on initial conditions. In addition, the critical value in critical state is only related to the number ratio between inhibitory neurons and excitatory neurons, but is independent of inhibitory coupling and excitatory coupling.