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Role of the colored noise in a FitzHugh-Nagumo system driven by a periodic signal

机译:有色噪声在由周期信号驱动的FitzHugh-Nagumo系统中的作用

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摘要

During these last years the interest in neuronal dynamics increased. The study of this kind of system has been carried out by using the FitzHugh-Nagumo (FHN) model that is a simplified modification of the Hodgkin-Huxley model. Many interesting phenomena can be observed in the presence of fluctuations: modification of detection threshold by manipulation of noisy parameters (FHN model), noise-induced activation and coeherence resonance for suitable noise amplitude (absence of periodic signal), resonant activation for high periodic signals and noise reduction, intrinsic stochastic resonance (ISR) in Hodgkin-Huxley neuron and the enhancement of a weak signal by tuning the subthreshold intrinsic oscillation, Resonant Activation (RA) and Noise Enhanced Stability (NES) in FHN model [5], dependence of neuron firing on subthreshold periodic signal and additive noise and optimization of the interspike time, stochastic resonance maximized in the presence of coloured noise I/f^{beta} for beta = 1. In this work, by using coloured noise sources with correlation time tau, we investigate the effects of fluctuations on the FHN dynamics. In particular we study the mean response time (MRT) as a function both of noise intensity and correlation time.
机译:在最近几年中,对神经元动力学的兴趣增加了。使用FitzHugh-Nagumo(FHN)模型进行了此类系统的研究,该模型是Hodgkin-Huxley模型的简化修改。在波动的情况下可以观察到许多有趣的现象:通过控制噪声参数(FHN模型)来修改检测阈值,针对适当的噪声幅度(不存在周期性信号)的噪声诱发的激活和相干共振,针对高周期性信号的共振激活和噪声降低,霍奇金-赫克斯利神经元的内在随机共振(ISR)以及通过调整FHN模型中的亚阈值内在振荡,共振激活(RA)和噪声增强的稳定性(NES)来增强弱信号[5],在阈值以下的周期信号和加性神经元上激发神经元,并优化尖峰时间,在存在有色噪声I / f ^ {beta}(β= 1)的情况下,随机共振最大化。在这项工作中,通过使用具有相关时间tau的有色噪声源,我们研究了波动对FHN动力学的影响。特别是,我们研究了平均响应时间(MRT)与噪声强度和相关时间的关系。

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