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The Electrical Activity of Neurons Subject to Electromagnetic Induction and Gaussian White Noise

Department of Physics, Lanzhou University of Technology, Lanzhou 730050, P. R. China

School of Science, Chongqing University of Posts and Telecommunications, Chongqing 430065, P. R. China

NAAM-Research Group, Department of Mathematics, Faculty of Science, King Abdulaziz University, P. O. Box 80203, Jeddah 21589, Saudi Arabia

E-mail Address: hyperchaos@163.com

Corresponding author.

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Ying Xu

Department of Physics, Lanzhou University of Technology, Lanzhou 730050, P. R. China

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Fuqiang Wu

Department of Physics, Lanzhou University of Technology, Lanzhou 730050, P. R. China

E-mail Address: alextianming@126.com

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, and

Ping Zhou

School of Science, Chongqing University of Posts and Telecommunications, Chongqing 430065, P. R. China

E-mail Address: zhouping@cqupt.edu.cn

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https://doi.org/10.1142/S0218127417500304Cited by:138 (Source: Crossref)

Abstract

Neurons can give appropriate response to external electrical stimuli and the modes in electrical activities can be carefully selected. Most of the neuron models mainly emphasize on the ion channel currents embedded into the membrane and the properties in electrical activities can be produced in the theoretical models. Indeed, some physical effect should be considered during the model setting for neuronal activities. In fact, induced current and the electrical field will cause the membrane potential to change and an exchange of charged ions during the fluctuation of ion concentration in cell. As a result, the effect of electromagnetic induction should be seriously considered. In this paper, magnetic flux is proposed to describe the effect of electromagnetic field, and the memristor is used to realize coupling on membrane by inputting induced current based on consensus of physical unit. Noise is also considered to detect the dynamical response in electrical activities and stochastic resonance, it is found that multiple modes can be selected in the electrical activities and it could be associated with memory effect and self-adaption in neurons.

Keywords:

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