Transition from double coherence resonances to single coherence resonance in a neuronal network with phase noise
Transition from double coherence resonances to single coherence resonance in a neuronal network with phase noise
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DOI：
10.1063/1.4938733
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发表时间：
2015-12-01
期刊：
影响因子：
2.9
通讯作者：
Gu, Huaguang
中科院分区：
文献类型：
--
作者：
Jia, Yanbing;Gu, Huaguang
研究了相位噪声对FitzHugh-Nagumo（FHN）神经元网络相干动力学的影响。对于不同的耦合强度区域，相位噪声会引起不同的相干共振（CR）效应。当耦合强度较小时，相位噪声会引起双CR。一个对应于相位噪声的平均频率，另一个对应于FHN神经元的固有激发频率。当耦合强度足够大时，相位噪声只能引起单个CR，CR对应于FHN神经元的固有放电频率。结果表明，随着耦合强度的增加，从双CR到单CR的过渡。基于由相位噪声和耦合电流刺激的单个神经元的动力学，可以很好地解释这种转变。当耦合强度较小时，耦合电流较弱，相位噪声主要决定神经元的动力学特性。此外，神经元网络中的相位噪声诱导的双CR类似于孤立的FHN神经元中的相位噪声诱导的双CR。当耦合强度足够大时，耦合电流很强，对网络中单个CR的发生起着关键作用。这些结果提供了一种新的现象，并可能对理解神经元网络的动力学具有重要意义。(C)2015 AIP Publishing LLC.
The effect of phase noise on the coherence dynamics of a neuronal network composed of FitzHugh-Nagumo (FHN) neurons is investigated. Phase noise can induce dissimilar coherence resonance (CR) effects for different coupling strength regimes. When the coupling strength is small, phase noise can induce double CRs. One corresponds to the average frequency of phase noise, and the other corresponds to the intrinsic firing frequency of the FHN neuron. When the coupling strength is large enough, phase noise can only induce single CR, and the CR corresponds to the intrinsic firing frequency of the FHN neuron. The results show a transition from double CRs to single CR with the increase in the coupling strength. The transition can be well interpreted based on the dynamics of a single neuron stimulated by both phase noise and the coupling current. When the coupling strength is small, the coupling current is weak, and phase noise mainly determines the dynamics of the neuron. Moreover, the phase-noise-induced double CRs in the neuronal network are similar to the phase-noise-induced double CRs in an isolated FHN neuron. When the coupling strength is large enough, the coupling current is strong and plays a key role in the occurrence of the single CR in the network. The results provide a novel phenomenon and may have important implications in understanding the dynamics of neuronal networks. (C) 2015 AIP Publishing LLC.