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生物神经系统的编码特性和小世界特性
引用本文:谢彬,刘深泉,李炎烽,陈树春. 生物神经系统的编码特性和小世界特性[J]. 生物数学学报, 2009, 0(3): 507-512
作者姓名:谢彬  刘深泉  李炎烽  陈树春
作者单位:华南理工大学理学院,应用数学系,广东广州510640
摘    要:本文主要研究视网膜神经系统和七鳃鳗脊椎神经系统的电位发放特性和网络特性,首先利用抑制神经系统的Winner Less Competition(WLC)模型,分析视网膜和七鳃鳗脊椎神经系统的电位发放.得到视网膜神经元和脊椎神经元的电位发放模式.然后利用Watts-Strogatz小世界网络的特性,分析两个生物神经系统的群集系数和特征路长,说明这些生物系统神经元之间的信息传递具有小世界网络的特性.

关 键 词:小世界模型  视网膜  七鳃鳗  群集系数  特征路长

The Code Property of Biology Neural System and Small World Network
XIE Bin,LIU Shen-quan,LI Yan-feng,CHEN Shu-chun. The Code Property of Biology Neural System and Small World Network[J]. Journal of Biomathematics, 2009, 0(3): 507-512
Authors:XIE Bin  LIU Shen-quan  LI Yan-feng  CHEN Shu-chun
Affiliation:(Department of Mathematics, School of Science, South China University of Technology Guangzhou Guangdoug 510640 China)
Abstract:The paper studies action potential and network properties of retina neural system and lamprey neural system. The inhibited neural systems, WinnerLess Competition(WLC)model, are used here to study the potential spike of retina and lamprey neural system and we obtain the pattern of their electric spike. With help of properties of Watts-Strogatz small world network,the indexes of clustering coefficient and characteristic length of these two biology systems tell us the massage transmitting of these two neural systems have properties of small world network.
Keywords:Small world network  ltetina  Lamprey  Clustering coefficient  Characteristic length
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