Stochastic Resonance in Neuronal Network Motifs with Ornstein-Uhlenbeck Colored Noise | Zendy

Xuyang Lou | Zendy

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Stochastic Resonance in Neuronal Network Motifs with Ornstein-Uhlenbeck Colored Noise

Author(s) -

Xuyang Lou

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/902395

Subject(s) - colors of noise , colored , motif (music) , stochastic resonance , noise (video) , stochastic process , statistical physics , biological system , computer science , control theory (sociology) , physics , mathematics , topology (electrical circuits) , acoustics , artificial intelligence , combinatorics , noise reduction , statistics , control (management) , biology , materials science , image (mathematics) , composite material

We consider here the effect of the Ornstein-Uhlenbeck colored noise on the stochastic resonance of the feed-forward-loop (FFL) network motif. The FFL motif is modeled through the FitzHugh-Nagumo neuron model as well as the chemical coupling. Our results show that the noise intensity and the correlation time of the noise process serve as the control parameters, which have great impacts on the stochastic dynamics of the FFL motif. We find that, with a proper choice of noise intensities and the correlation time of the noise process, the signal-to-noise ratio (SNR) can display more than one peak

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