Small-World Connections to Induce Firing Activity and Phase Synchronization in Neural Networks  

作　　者：覃英华 罗晓曙 

机构地区：[1]College of Electronic Engineering, Guangxi Normal University, Guilin 541004

出　　处：《Chinese Physics Letters》2009年第7期380-383,共4页中国物理快报（英文版）

基　　金：Supported by the National Natural Science Foundation of China under Grant Nos 10862001 and 70571017.

摘　　要：We investigate how the firing activity and the subsequent phase synchronization of neural networks with smallworld topological connections depend on the probability p of adding-links. Network elements are described by two-dimensional map neurons （2DMNs） in a quiescent original state. Neurons burst for a given coupling strength when the topological randomness p increases, which is absent in a regular-lattice neural network. The bursting activity becomes frequent and synchronization of neurons emerges as topological randomness further increases. The maximal firing frequency and phase synchronization appear at a particular value of p. However, if the randomness p further increases, the firing frequency decreases and synchronization is apparently destroyed.We investigate how the firing activity and the subsequent phase synchronization of neural networks with smallworld topological connections depend on the probability p of adding-links. Network elements are described by two-dimensional map neurons （2DMNs） in a quiescent original state. Neurons burst for a given coupling strength when the topological randomness p increases, which is absent in a regular-lattice neural network. The bursting activity becomes frequent and synchronization of neurons emerges as topological randomness further increases. The maximal firing frequency and phase synchronization appear at a particular value of p. However, if the randomness p further increases, the firing frequency decreases and synchronization is apparently destroyed.

关 键 词：sea surface nonliear interaction numerical method 

分 类 号：TP302.8[自动化与计算机技术—计算机系统结构] TP18[自动化与计算机技术—计算机科学与技术]