title: Propagation of spiking regularity and double coherence resonance in feedforward networks.
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.
authors.affiliation: School of Electrical Engineering and Automation, Tianjin University, Tianjin, China.
authors.forename: Cong
authors.initials: C
authors.lastname: Men
authors.forename: Jiang
authors.initials: J
authors.lastname: Wang
authors.forename: Ying-Mei
authors.initials: YM
authors.lastname: Qin
authors.forename: Bin
authors.initials: B
authors.lastname: Deng
authors.forename: Kai-Ming
authors.initials: KM
authors.lastname: Tsang
authors.forename: Wai-Lok
authors.initials: WL
authors.lastname: Chan
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D001683:Biological Clocks / Q000502:physiology*; D003198:Computer Simulation; D025461:Feedback, Physiological / Q000502:physiology; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009433:Neural Inhibition / Q000502:physiology*; D009435:Synaptic Transmission / Q000502:physiology*