Faculty of Physics, University of Belgrade, P.O. Box 44, 11001 Belgrade, Serbia.
Chaos. 2012 Sep;22(3):033147. doi: 10.1063/1.4753919.
Properties of spontaneously formed clusters of synchronous dynamics in a structureless network of noisy excitable neurons connected via delayed diffusive couplings are studied in detail. Several tools have been applied to characterize the synchronization clusters and to study their dependence on the neuronal and the synaptic parameters. Qualitative explanation of the cluster formation is discussed. The interplay between the noise, the interaction time-delay and the excitable character of the neuronal dynamics is shown to be necessary and sufficient for the occurrence of the synchronization clusters. We have found the two-cluster partitions where neurons are firmly bound to their subsets, as well as the three-cluster ones, which are dynamical by nature. The former turn out to be stable under small disparity of the intrinsic neuronal parameters and the heterogeneity in the synaptic connectivity patterns.
详细研究了通过延迟扩散耦合连接的无结构噪声兴奋神经元网络中自发形成的同步动力学簇的特性。应用了几种工具来描述同步簇,并研究它们对神经元和突触参数的依赖性。讨论了簇形成的定性解释。结果表明,噪声、相互作用时间延迟和神经元动力学的兴奋特性之间的相互作用是同步簇发生的必要和充分条件。我们发现了两种聚类划分,其中神经元牢固地绑定到它们的子集,以及三种聚类划分,它们本质上是动态的。前者在内在神经元参数的微小差异和突触连接模式的异质性下保持稳定。