Complex Behavior in a Selective Aging Neuron Model Based on Small World Networks

作     者：ZHANG Gui-Qing CHEN Tian-Lun 

作者机构：Department of Physics Nankai University Tianjin 300071 China 

出 版 物：《Communications in Theoretical Physics》 (理论物理通讯（英文版）)

年 卷 期：2008年第49卷第2期

页      面：409-413页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China under Grant No.10675060 

主　　题：selective aging self-organized criticality small world networks finite-size-scaling analysis power-law 

摘      要：Complex behavior in a selective aging simple neuron model based on small world networks is investigated. The basic elements of the model are endowed with the main features of a neuron function. The structure of the selective aging neuron model is discussed. We also give some properties of the new network and find that the neuron model displays a power-law behavior. If the brain network is small world-like network, the mean avalanche size is almost the same unless the aging parameter is big enough.