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Temperature effect on memristive ion channels.温度对忆阻离子通道的影响。
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Adaptive sparse coding based on memristive neural network with applications.基于忆阻神经网络的自适应稀疏编码及其应用
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Effect of spike-timing-dependent plasticity on stochastic burst synchronization in a scale-free neuronal network.脉冲时间依赖可塑性对无标度神经网络中随机爆发同步的影响。
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受高斯白噪声干扰的时延忆阻器神经元的电活动

Electric activities of time-delay memristive neuron disturbed by Gaussian white noise.

作者信息

Wang Zuolei, Shi Xuerong

机构信息

School of Mathematics and Statistics, Yancheng Teachers University, Yancheng, 224002 China.

出版信息

Cogn Neurodyn. 2020 Feb;14(1):115-124. doi: 10.1007/s11571-019-09549-6. Epub 2019 Aug 1.

DOI:10.1007/s11571-019-09549-6
PMID:32015770
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6974230/
Abstract

To study the effect of electromagnetic induction on the electric activities of neuron, memristive neuron models have been proposed by coupling membrane potential with magnetic flux. In this paper, on the basis of memristive Hindmarsh-Rose neuron model, time-delay memristive Hindmarsh-Rose neuron model is described and the responses of neuron in electrical activities are detected. The effect of time-delay on the dynamical behaviors of the neuron is discussed and the transition of electrical activities of the neuron is investigated with the change of noise intensity. It is found that, both the time-delay and the noise have effect on the electrical activities of the neuron. Especially, by selecting appropriate parameters, the noise not only can excite neuron from quiescent state to bursting state, but also can suppress the electrical activities in neuron during certain discharge period. Results mean that multiple modes and coherence resonance can be observed by changing the size of time-delay or the noise intensity, which could be associated with memory effect and self-adaption in neurons.

摘要

为研究电磁感应对神经元电活动的影响,通过将膜电位与磁通量耦合提出了忆阻神经元模型。本文在忆阻 Hindmarsh-Rose 神经元模型的基础上,描述了时延忆阻 Hindmarsh-Rose 神经元模型,并检测了神经元电活动中的响应。讨论了时延对神经元动力学行为的影响,并研究了随着噪声强度变化神经元电活动的转变。研究发现,时延和噪声均对神经元的电活动有影响。特别地,通过选择合适的参数,噪声不仅可以将神经元从静息状态激发到爆发状态,而且在特定放电期间还可以抑制神经元中的电活动。结果表明,通过改变时延大小或噪声强度可以观察到多种模式和相干共振,这可能与神经元中的记忆效应和自适应有关。