Dynamics and synchronization of neural models with memristive membranes under energy coupling

doi:10.1088/1674-1056/ad1dcc

中国物理B ›› 2024, Vol. 33 ›› Issue (5): 50504-050504.doi: 10.1088/1674-1056/ad1dcc

Dynamics and synchronization of neural models with memristive membranes under energy coupling

Jingyue Wan(万婧玥)¹, Fuqiang Wu(吴富强)^1,2,†, Jun Ma(马军)³, and Wenshuai Wang(汪文帅)^1,2

1 School of Mathematics and Statistics, Ningxia University, Yinchuan 750021, China;
2 Ningxia Basic Science Research Center of Mathematics, Ningxia University, Yinchuan 750021, China;
3 Department of Physics, Lanzhou University of Technology, Lanzhou 730050, China

收稿日期:2023-12-06 修回日期:2023-12-29 接受日期:2024-01-12 出版日期:2024-05-20 发布日期:2024-05-20
通讯作者: Fuqiang Wu E-mail:alexwutian@nxu.edu.cn
基金资助:
This study was funded by the National Natural Science Foundation of China (Grant No. 12302070) and the Ningxia Science and Technology Leading Talent Training Program (Grant No. 2022GKLRLX04).

Dynamics and synchronization of neural models with memristive membranes under energy coupling

Jingyue Wan(万婧玥)¹, Fuqiang Wu(吴富强)^1,2,†, Jun Ma(马军)³, and Wenshuai Wang(汪文帅)^1,2

1 School of Mathematics and Statistics, Ningxia University, Yinchuan 750021, China;
2 Ningxia Basic Science Research Center of Mathematics, Ningxia University, Yinchuan 750021, China;
3 Department of Physics, Lanzhou University of Technology, Lanzhou 730050, China

Received:2023-12-06 Revised:2023-12-29 Accepted:2024-01-12 Online:2024-05-20 Published:2024-05-20
Contact: Fuqiang Wu E-mail:alexwutian@nxu.edu.cn
Supported by:
This study was funded by the National Natural Science Foundation of China (Grant No. 12302070) and the Ningxia Science and Technology Leading Talent Training Program (Grant No. 2022GKLRLX04).

摘要/Abstract

摘要： Dynamical modeling of neural systems plays an important role in explaining and predicting some features of biophysical mechanisms. The electrophysiological environment inside and outside of the nerve cell is different. Due to the continuous and periodical properties of electromagnetic fields in the cell during its operation, electronic components involving two capacitors and a memristor are effective in mimicking these physical features. In this paper, a neural circuit is reconstructed by two capacitors connected by a memristor with periodical mem-conductance. It is found that the memristive neural circuit can present abundant firing patterns without stimulus. The Hamilton energy function is deduced using the Helmholtz theorem. Further, a neuronal network consisting of memristive neurons is proposed by introducing energy coupling. The controllability and flexibility of parameters give the model the ability to describe the dynamics and synchronization behavior of the system.

关键词: memristor, neuronal model, energy, synchronization

Abstract: Dynamical modeling of neural systems plays an important role in explaining and predicting some features of biophysical mechanisms. The electrophysiological environment inside and outside of the nerve cell is different. Due to the continuous and periodical properties of electromagnetic fields in the cell during its operation, electronic components involving two capacitors and a memristor are effective in mimicking these physical features. In this paper, a neural circuit is reconstructed by two capacitors connected by a memristor with periodical mem-conductance. It is found that the memristive neural circuit can present abundant firing patterns without stimulus. The Hamilton energy function is deduced using the Helmholtz theorem. Further, a neuronal network consisting of memristive neurons is proposed by introducing energy coupling. The controllability and flexibility of parameters give the model the ability to describe the dynamics and synchronization behavior of the system.

Key words: memristor, neuronal model, energy, synchronization

中图分类号: (Numerical simulations of chaotic systems)

05.45.Pq

05.45.Xt (Synchronization; coupled oscillators) 05.45.Gg (Control of chaos, applications of chaos)

Jingyue Wan(万婧玥), Fuqiang Wu(吴富强), Jun Ma(马军), and Wenshuai Wang(汪文帅). Dynamics and synchronization of neural models with memristive membranes under energy coupling[J]. 中国物理B, 2024, 33(5): 50504-050504.

Jingyue Wan(万婧玥), Fuqiang Wu(吴富强), Jun Ma(马军), and Wenshuai Wang(汪文帅). Dynamics and synchronization of neural models with memristive membranes under energy coupling[J]. Chin. Phys. B, 2024, 33(5): 50504-050504.

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Dynamics and synchronization of neural models with memristive membranes under energy coupling

Dynamics and synchronization of neural models with memristive membranes under energy coupling

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