Synchronization study in ring-like and grid-like neuronal networks.
In this paper, we study the synchronization status of both two gap-junction coupled neurons and neuronal network with two different network connectivity patterns. One of the network connectivity patterns is a ring-like neuronal network, which only considers nearest-neighbor neurons. The other is a grid-like neuronal network, with all nearest neighbor couplings. We show that by varying some key parameters, such as the coupling strength and the external current injection, the neuronal network will exhibit various patterns of firing synchronization. Different types of firing synchronization are diagnosed by means of a mean field potential, a bifurcation diagram, a correlation coefficient and the ISI-distance method. Numerical simulations demonstrate that the synchronization status of multiple neurons is much dependent on the network patters, when the number of neurons is the same. It is also demonstrated that the synchronization status of two coupled neurons is similar with the grid-like neuronal network, but differs radically from that of the ring-like neuronal network. These results may be instructive in understanding synchronization transitions in neuronal systems.
Department of Mathematics, Institute for Cognitive Neurodynamics, School of Science, School of Information Science and Engineering, East China University of Science and Technology, Meilong 130, Shanghai, 200237 China.
Jingyi
J
Qu
Rubin
R
Wang
Ying
Y
Du
Jianting
J
Cao
Bifuration diagram; Correlation coefficient; ISI-distance; Mean field potential; Ring-like and grid-like neuronal network