复杂网络上耦合神经系统的非聚类相同步

Networked Non⁃Clustering Phase Synchronization in Coupled Neuron Systems

考虑了不同复杂网络结构(小世界、无标度和随机网络)条件下的耦合神经元系统,针对其进入相同步的同步化路径进行了建模与仿真,发现系统呈现出非聚类相同步现象,并对其形成原因进行了定性分析.结果表明:复杂网络上的耦合神经元系统与其在规则网络下有相同的同步行为,系统均不出现通常耦合相振子中的聚类成群现象,而表现为随着耦合强度的增加所有神经元渐进趋于同步.另外,随着放电尖峰的插入与弥合,最终导致系统个体平均频率先增强后衰减的变化.这些结果将丰富对于网络动力学行为(尤其是相同步)的认识,对理解神经认知科学具有一定意义.

The phase synchronization of coupled neurons under different complex network en⁃vironments(including classical small⁃world,scale⁃free and random networks)was studied.Differing from the clustering phase synchronization in coupled phase oscillators generally found and reported in previous literature,a novel non⁃clustering phase synchronization was uncov⁃ered.The global synchronization involves 2 different dynamical processes:the frequency in⁃crease and the frequency decrease,where the frequency increase is induced by the spike inser⁃tion,and the frequency decrease is induced by the spike merge.Therefore,the neuron’s fre⁃quency variation mainly depends on the change of spike numbers,and the usual phase cluste⁃ring phenomenon cannot be found here.The findings could enrich the understanding of net⁃worked dynamical behaviors including the phase synchronization and the computational neuron dynamics.