Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/5368
Title: Propagation of spiking regularity and double coherence resonance in feedforward networks
Authors: Men, C
Wang, J
Qin, YM
Deng, B
Tsang, KM 
Chan, WL 
Keywords: Neural nets
Noise
Synchronisation
Issue Date: Mar-2012
Publisher: American Institute of Physics
Source: Chaos, Apr. 2012, v. 22, no. 1, 013104, p. 1-7 How to cite?
Journal: Chaos 
Abstract: We investigate the propagation of spiking regularity in noisy feedforward networks (FFNs) based on FitzHugh-Nagumo neuron model systematically. It is found that noise could modulate the transmission of firing rate and spiking regularity. Noise-induced synchronization and synfire-enhanced coherence resonance are also observed when signals propagate in noisy multilayer networks. It is interesting that double coherence resonance (DCR) with the combination of synaptic input correlation and noise intensity is finally attained after the processing layer by layer in FFNs. Furthermore, inhibitory connections also play essential roles in shaping DCR phenomena. Several properties of the neuronal network such as noise intensity, correlation of synaptic inputs, and inhibitory connections can serve as control parameters in modulating both rate coding and the order of temporal coding.
URI: http://hdl.handle.net/10397/5368
ISSN: 1054-1500
EISSN: 1089-7682
DOI: 10.1063/1.3676067
Rights: © 2012 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in Cong Men et al., Chaos: an interdisciplinary journal of nonlinear science 22, 013104 (2012) and may be found at http://link.aip.org/link/?cha/22/013104
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