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Nonlinear Dynamics

, Volume 85, Issue 3, pp 1479–1490 | Cite as

Model of electrical activity in a neuron under magnetic flow effect

  • Mi Lv
  • Chunni Wang
  • Guodong Ren
  • Jun Ma
  • Xinlin Song
Original Paper

Abstract

The electric activities of neurons are dependent on the complex electrophysiological condition in neuronal system, and it indicates that the complex distribution of electromagnetic field could be detected in the neuronal system. According to the Maxwell electromagnetic induction theorem, the dynamical behavior in electric activity in each neuron can be changed due to the effect of internal bioelectricity of nervous system (e.g., fluctuation of ion concentration inside and outside of cell). As a result, internal fluctuation of electromagnetic field is established and the effect of magnetic flux across the membrane should be considered during the emergence of collective electrical activities and signals propagation among a large set of neurons. In this paper, the variable for magnetic flow is proposed to improve the previous Hindmarsh–Rose neuron model; thus, a four-variable neuron model is designed to describe the effect of electromagnetic induction on neuronal activities. Within the new neuron model, the effect of magnetic flow on membrane potential is described by imposing additive memristive current on the membrane variable, and the memristive current is dependent on the variation of magnetic flow. The dynamics of this modified model is discussed, and multiple modes of electric activities can be observed by changing the initial state, which indicates memory effect of neuronal system. Furthermore, a practical circuit is designed for this improved neuron model, and this model could be suitable for further investigation of electromagnetic radiation on biological neuronal system.

Keywords

Electrical activity Magnetic flow Memristor  Electromagnetic induction Neuron 

Notes

Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grant Nos. 11265008 (MJ) and 11365014 (WCN).

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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Department of PhysicsLanzhou University of TechnologyLanzhouChina

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