DocumentCode :
507849
Title :
Stochastic Evolution Model of Neuronal Oscillator Population under the Condition of the Higher Order Coupling
Author :
Xiaodan, Zhang ; Rubin, Wang ; Zhikang, Zhang ; Xianfa, Jiao
Author_Institution :
Inst. for Cognitive Neurodynamics, East China Univ. of Sci. & Technol., Shanghai, China
Volume :
2
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
439
Lastpage :
443
Abstract :
The activities of coupled neuronal oscillator population in the presence of both external stimulation and noise were studied in this paper, and the dynamical evolution of the average number density of the neuronal oscillator population was studied when the coupling among oscillators contains higher harmonics. The results of the study indicate that under the condition of higher order coupling, if the initial condition of average number density contains the same harmonics with the higher order coupling and the coupling strength is greater than its critical value, the action of higher order coupling can maintain the already formed multiple-cluster synchronization state of the neuronal oscillator population. Under the condition of stimulation, the effect of phase neural coding is the correlative result of the coupling and the stimulation.
Keywords :
neural nets; oscillators; stochastic processes; coupled neuronal oscillator population; higher harmonics; higher order coupling; multiple-cluster synchronization state; neuronal oscillator population; phase neural coding; stochastic evolution model; Brain modeling; Computational biology; Computational modeling; Electronic mail; Evolution (biology); Mutual coupling; Neurodynamics; Oscillators; Stochastic processes; Stochastic resonance; average number density; external stimulation; higher order coupling; neuronal oscillator population; phase neural coding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
Type :
conf
DOI :
10.1109/ICNC.2009.664
Filename :
5363449
Link To Document :
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