Computational dynamics and synchronization in nonequilibrium networks consisting of interacting multistable elements
Vladimir Chinarov, Tamás Gergely · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1998
A neural network model that may give phase synchronization of activity patterns in ensembles with different types of complexity is described and simulated. This model is used to study the dynamic behavior of coupled phase oscillators with cosine interaction between them. Different schemes of the network architecture such as mean-field and nearest-neighbor interaction, symmetric and asymmetric types of coupling among elements are provided to deal with the processes of synchronization patterns formation. Dynamic pattern formation related to neural oscillations, patterns of phase an anti- phase synchronization of activities of elements within clusters remote from one another as well as clustering of different attractors are studied.