期刊
PHYSICAL REVIEW E
卷 79, 期 5, 页码 -出版社
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevE.79.051921
关键词
brain models; neural nets; neurophysiology; stochastic processes
资金
- National Natural Science Foundation of China (NSFC) [6087109]
- Foundation for the Author of National Excellent Doctoral Dissertation of PR China
- Youth Foundation of Sichuan Province [07ZQ026-019]
The relationships between noise and complex dynamic behaviors of neuronal ensembles are key questions in computational neuroscience, particularly in understanding some basic signal transmission mechanisms of the brain. Here we systemically investigate both the stochastic resonance (SR) and coherence resonance (CR) in the triple-neuron feed-forward-loop (FFL) network motifs by computational modeling. We use the Izhikevich neuron model as well as the chemical coupling to build the FFL motifs, and consider all possible motif types. The simulation results demonstrate that these motifs can exploit noise to enrich its dynamic performance. With a proper choice of noise intensities, both the SR and CR can be exhibited in many types of the FFLs. On the other hand, our results also indicate that the coupling strength serves as a control parameter, which has great impacts on the stochastic dynamics of the FFL motifs. Additionally, biological implications of presented results in the field of neuroscience are outlined.
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