Dynamic response and control of neuros based on electromagnetic field theory

被引:22
作者
An Xin-Lei [1 ,2 ]
Qiao Shuai [1 ]
Zhang Li [3 ]
机构
[1] Lanzhou Jiaotong Univ, Sch Math & Phys, Lanzhou 730070, Peoples R China
[2] Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou 730050, Peoples R China
[3] Lanzhou Inst Technol, Basic Courses Dept, Lanzhou 730050, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
electromagnetic fields; Hopf bifurcation analysis; hidden attractor; two-parameter bifurcation; mixed mode discharge; PHASE SYNCHRONIZATION; ELECTRICAL-ACTIVITY; MODEL; OSCILLATIONS; SPIKING; NETWORK; SYSTEM;
D O I
10.7498/aps.70.20201347
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The time-varying electric fields generated by continuously pumping and transmitting calcium, potassium and sodium ions in cells not only affect the discharge activity of neurons, but also induce time-varying magnetic fields to further regulate the fluctuation of ions. According to the Maxwell's electromagnetic field theory, time-varying electric field and magnetic field can stimulate each other in the electrophysiological environment inside and outside the cells to produce electromagnetic field. In order to explore the discharge rhythm transition of neurons under the influence of electromagnetic fields, a five-dimensional (5D) HR neuron model (EMFN model for short) is established by introducing magnetic flux variable and electric field variable into a three-dimensional (3D) Hindmarsh-Rose (HR) neuron model. Firstly, the equilibrium distribution and global bifurcation properties of EMFN model are analyzed by Matcont software, then the existence of subcritical Hopf bifurcation, hidden discharge, coexistence of periodic discharge and resting state are found and analyzed. Secondly, by using the tools of two-parameter and one-parameter bifurcation, ISI bifurcation and the maximum Lyapunov exponent for numerical simulation, the period-adding bifurcation with and without chaos, mixed mode discharge and coexistence mode discharge in the EMFN model are analyzed in detail. At the same time, the transition law of discharge rhythm with the influence of electric field and magnetic field intensity is revealed. Finally, the Washout controller is used to convert the subcritical Hopf bifurcation into supercritical Hopf bifurcation, so the topological structure of EMFN model near the bifurcation point is changed for eliminating the hidden discharge. The research results of this paper confirm that the novel neuron model has rich discharge rhythm, which will affect the information transmission and coding, and provide some ideas for improving the neuron models, revealing the influence of electromagnetic field on biological nervous system, and exploring the pathogenic mechanism of some neurological diseases.
引用
收藏
页数:20
相关论文
共 46 条
[1]   Dynamics analysis and Hamilton energy control of a generalized Lorenz system with hidden attractor [J].
An Xin-lei ;
Zhang Li .
NONLINEAR DYNAMICS, 2018, 94 (04) :2995-3010
[2]  
[安新磊 An Xinlei], 2020, [力学学报, Chinese Journal of Theoretical and Applied Mechanics], V52, P1174
[3]  
[Anonymous], 2014, ENCY COMPUTATIONAL N
[4]   A spiking and bursting neuron circuit based on memristor [J].
Babacan, Yunus ;
Kacar, Brat ;
Gurkan, Koray .
NEUROCOMPUTING, 2016, 203 :86-91
[5]   Symbolic dynamical unfolding of spike-adding bifurcations in chaotic neuron models [J].
Barrio, R. ;
Lefranc, M. ;
Martinez, M. A. ;
Serrano, S. .
EPL, 2015, 109 (02)
[6]   Three-Dimensional Memristive Hindmarsh-Rose Neuron Model with Hidden Coexisting Asymmetric Behaviors [J].
Bao, Bocheng ;
Hu, Aihuang ;
Bao, Han ;
Xu, Quan ;
Chen, Mo ;
Wu, Huagan .
COMPLEXITY, 2018,
[7]  
Cassidy Andrew S., 2013, The 2013 International Joint Conference on Neural Networks (IJCNN), P1
[9]   Mixed-Mode Oscillations with Multiple Time Scales [J].
Desroches, Mathieu ;
Guckenheimer, John ;
Krauskopf, Bernd ;
Kuehn, Christian ;
Osinga, Hinke M. ;
Wechselberger, Martin .
SIAM REVIEW, 2012, 54 (02) :211-288
[10]   Explanation to negative feedback induced-enhancement of neural electronic activities with phase response curve [J].
Ding Xue-Li ;
Jia Bing ;
Li Yu-Ye .
ACTA PHYSICA SINICA, 2019, 68 (18)