基于变异系数的霍奇金-赫胥黎神经元模型相干共振分析

Chunxiao Han, Jiang Wang, Wenye Guan, Bin Deng, Feng Dong
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引用次数: 1

摘要

研究了无外部周期信号的Hodgkin- Huxley模型在极限环鞍节点分岔附近分别以高斯白噪声(GWN)和Ornstein-Uhlenbeck噪声(OUN)为突触电流时的非线性响应。根据膜电位和峰列峰间间隔的变异系数估计,在一定的噪声强度下,系统的相干性最小,从而发生相干共振。当GWN作为突触输入时,当噪声强度大于一定阈值时发生相干共振;当OUN作为突触输入时,只有扩散系数适中时才会发生相干共振,扩散系数过大时不会产生相干共振。这些发现进一步加深了我们对神经元如何对不同类型的噪音作出反应的理解。
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Coefficient of Variation Based Analysis of Coherence Resonance in Hodgkin-Huxley Neuron Model
We study the nonlinear response of the Hodgkin- Huxley model without external periodic signal to Gaussian white noise (GWN) and Ornstein-Uhlenbeck noise (OUN) as synaptic current respectively near the saddle-node bifurcation of limit cycles. The coherence of the system, estimated from the Coefficient of Variation of interspike interval of membrane potentials and spike trains, is minimal at certain noise intensity, so that the coherence resonance occurs. When GWN is served as synaptic input, coherence resonance occurs when noise intensity is greater than a certain threshold; when OUN is served as synaptic input, coherence resonance only occurs only with a moderate diffusion coefficient: too large diffusion coefficient will not generate coherence resonance. These findings further our understanding of how neurons respond to different types of noises.
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