Department of Mathematics and Statistics and Neuroscience Institute, Georgia State University, 30 Pryor Street, Atlanta, Georgia 30303, USA.
Chaos. 2011 Mar;21(1):016106. doi: 10.1063/1.3563581.
We study the role of network architecture in the formation of synchronous clusters in synaptically coupled networks of bursting neurons. We give a simple combinatorial algorithm that finds the largest synchronous clusters from the network topology. We demonstrate that networks with a certain degree of internal symmetries are likely to have cluster decompositions with relatively large clusters, leading potentially to cluster synchronization at the mesoscale network level. We also address the asymptotic stability of cluster synchronization in excitatory networks of Hindmarsh-Rose bursting neurons and derive explicit thresholds for the coupling strength that guarantees stable cluster synchronization.
我们研究了网络结构在爆发神经元突触耦合网络中同步簇形成中的作用。我们给出了一个简单的组合算法,可从网络拓扑中找到最大的同步簇。我们证明,具有一定程度内部对称性的网络可能具有相对较大的簇分解,从而可能在介观网络水平上实现簇同步。我们还研究了 Hindmarsh-Rose 爆发神经元兴奋性网络中簇同步的渐近稳定性,并推导出保证稳定簇同步的耦合强度的显式阈值。