Anti-Interference of Neuronal Network Synchronization

Abstract

Abstract:

Abstract： To understand the underlying mechanism of reliable neural information processing in noise, the neuronal model was adopted to build neuronal network and its activities of synchronized firing and characteristics of antiinference were analyzed. The degree of synchronization and ability of antiinterference were quantified and the relation between them was discussed. The simulation results show that the scales of neuronal network and strength of coupling have remarkable effects both on synchronization and antiinterference; under some conditions, the ability of antiinference is almost linear with the degree of neuronal synchronization. Therefore, it is concluded that neuronal synchronization can reduce noise and execute reliable information coding and processing in the brain.

Key words: neuronal network, noise, synchronized firing, anti-inference, small-world network

CLC Number:

CHANG Xiaolonga,DING Guoliangb,LOU Jiananc. Anti-Interference of Neuronal Network Synchronization[J]. Journal of Shanghai Jiaotong University, 2014, 48(10): 1485-1490.

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