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

作　　者：万婧玥 吴富强 马军 汪文帅 Jingyue Wan;Fuqiang Wu;Jun Ma;Wenshuai Wang(School of Mathematics and Statistics,Ningxia University,Yinchuan 750021,China;Ningxia Basic Science Research Center of Mathematics,Ningxia University,Yinchuan 750021,China;Department of Physics,Lanzhou University of Technology,Lanzhou 730050,China)

机构地区：[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

出　　处：《Chinese Physics B》2024年第5期316-322,共7页中国物理B（英文版）

基　　金：funded by the National Natural Science Foundation of China(Grant No.12302070);the Ningxia Science and Technology Leading Talent Training Program(Grant No.2022GKLRLX04)。

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 

分 类 号：TN60[电子电信—电路与系统] O175[理学—数学]