Suppr超能文献

受高斯白噪声干扰的自突触艾克米维奇神经元的动力学响应。

Dynamical response of Autaptic Izhikevich Neuron disturbed by Gaussian white noise.

作者信息

Feali Mohammad Saeed, Hamidi Abdolsamad

机构信息

Department of Electrical Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.

Electrical Engineering Department, Lorestan University, Khorramabad, Lorestan, Iran.

出版信息

J Comput Neurosci. 2023 Feb;51(1):59-69. doi: 10.1007/s10827-022-00832-w. Epub 2022 Aug 30.

Abstract

Using the improved memristive Izhikevich neuron model, the effects of autaptic connection as well as electromagnetic induction are studied on the dynamical behavior of neuronal spiking. Using bifurcation analysis for membrane potentials, the effects of autaptic and electromagnetic parameters on the mode transition in electrical activities of the neuron model are investigated. Furthermore, white Gaussian noise is considered in the neuron model, to evaluate the effect of electromagnetic disturbance on the firing pattern of the neuron using the coefficient of variation. The bifurcation diagram versus autaptic conductance and time delay has been extensively studied. The results show that the effects of autaptic connection as well as electromagnetic induction on the spiking behavior of neurons can be well demonstrated by using the Izhikevich model. The electrical activities of the Izhikevich neuron model become more complex when the effects of autaptic connection and electromagnetic induction are considered in the neuron model. Using the Izhikevich neuron model, the high variety of spiking/bursting patterns is represented in the bifurcation diagram of inter-spike interval versus autaptic or electromagnetic parameters. Noise can have distinct effects on the spiking activity of the neuron, for the subthreshold input current, increasing the intensity of the electromagnetic noise increases the regularity of the neuron spiking, but for the suprathreshold input current, the regularity of spiking decreases with noise.

摘要

利用改进的忆阻型艾兹海默神经元模型,研究了自突触连接以及电磁感应对神经元放电动力学行为的影响。通过对膜电位进行分岔分析,研究了自突触和电磁参数对神经元模型电活动模式转变的影响。此外,在神经元模型中考虑了高斯白噪声,以使用变异系数评估电磁干扰对神经元放电模式的影响。广泛研究了分岔图与自突触电导和时间延迟的关系。结果表明,利用艾兹海默模型可以很好地证明自突触连接以及电磁感应对神经元放电行为的影响。当在神经元模型中考虑自突触连接和电磁感应的影响时,艾兹海默神经元模型的电活动变得更加复杂。利用艾兹海默神经元模型,在峰峰间隔与自突触或电磁参数的分岔图中呈现出高度多样的放电/爆发模式。噪声对神经元的放电活动可能有不同的影响,对于阈下输入电流,增加电磁噪声强度会增加神经元放电的规律性,但对于阈上输入电流,放电的规律性会随着噪声而降低。

相似文献

8
Firing-rate models for neurons with a broad repertoire of spiking behaviors.具有广泛放电行为的神经元的发放率模型。
J Comput Neurosci. 2018 Oct;45(2):103-132. doi: 10.1007/s10827-018-0693-9. Epub 2018 Aug 27.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验