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Suppression of noise in FitzHugh-Nagumo model driven by a strong periodic signal

机译:强周期信号驱动下的FitzHugh-Nagumo模型中的噪声抑制

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The response time of a neuron in the presence of a strong periodic driving in the stochastic FitzHugh-Nagumo model is investigated. We analyze two cases: (i) the variable that corresponds to membrane potential is subjected to fluctuations, and (ii) the recovery variable associated with the refractory properties of a neuron is noisy. The influence of noise sources on the delay of the response of a neuron is analyzed. In both cases we observe a resonant activation-like phenomenon and suppression of noise: the negative effect of fluctuations on the process of spike generation is minimal near the resonance region. The phenomenon of noise enhanced stability is also observed in both cases. The role of the initial phase of the periodic driving is examined. (c) 2005 Elsevier B.V. All rights reserved.
机译:研究了随机FitzHugh-Nagumo模型中存在强周期性驱动的神经元的响应时间。我们分析了两种情况:(i)与膜电位相对应的变量受到波动影响;(ii)与神经元的难治性相关的恢复变量很吵。分析了噪声源对神经元反应延迟的影响。在这两种情况下,我们都观察到类似共振的激活现象并抑制了噪声:在共振区域附近,波动对尖峰生成过程的负面影响很小。在两种情况下,也都观察到了噪声增强稳定性的现象。检查了周期性驱动的初始阶段的作用。 (c)2005 Elsevier B.V.保留所有权利。

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