Effects of channel noise on synchronization transitions in delayed scale-free network of stochastic Hodgkin-Huxley neurons

doi:10.1088/1674-1056/24/11/118702

Abstract We numerically study the effect of the channel noise on the spiking synchronization of a scale-free Hodgkin-Huxley neuron network with time delays. It is found that the time delay can induce synchronization transitions at an intermediate and proper channel noise intensity, and the synchronization transitions become strongest when the channel noise intensity is optimal. The neurons can also exhibit synchronization transitions as the channel noise intensity is varied, and this phenomenon is enhanced at around the time delays that can induce the synchronization transitions. It is also found that the synchronization transitions induced by the channel noise are dependent on the coupling strength and the network average degree, and there is an optimal coupling strength or network average degree with which the synchronization transitions become strongest. These results show that by inducing synchronization transitions, the channel noise has a big regulation effect on the synchronization of the neuronal network. These findings could find potential implications for the information transmission in neural systems.

Keywords: channel noise scale-free network time delay synchronization transition

Received: 11 May 2015
Revised: 18 June 2015
Accepted manuscript online:

PACS:	87.19.lc	(Noise in the nervous system)
	87.19.lm	(Synchronization in the nervous system)
	87.19.lj	(Neuronal network dynamics)

Fund: Project supported by the Natural Science Foundation of Shandong Province of China (Grant No. ZR2012AM013).

Corresponding Authors: Gong Yu-Bing
E-mail: gongyubing@ustc.edu

Cite this article:

Wang Bao-Ying (王宝英), Gong Yu-Bing (龚玉兵) Effects of channel noise on synchronization transitions in delayed scale-free network of stochastic Hodgkin-Huxley neurons 2015 Chin. Phys. B 24 118702

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Effects of channel noise on synchronization transitions in delayed scale-free network of stochastic Hodgkin-Huxley neurons

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