爆裂
生物神经元模型
混乱的
生物系统
记忆电阻器
物理
非线性系统
计算机科学
神经元
分叉
统计物理学
控制理论(社会学)
人工智能
神经科学
生物
控制(管理)
量子力学
作者
Guoyuan Qi,Yu Wu,Jianbing Hu
标识
DOI:10.1142/s0218127421501704
摘要
Improving the neuron model and studying its electrical activities according to the real biophysical environment are significant in human cognitive brain activity and neural behavior. The complex transmembrane motion of ions on the neuronal cell membrane can establish time-varying electromagnetic fields and affect the transition firing patterns of neurons. In this paper, a threshold memristor is used to describe the electromagnetic induction and magnetic field effects of neuron cell membrane ion exchange to improve the neuron model, and a memristive Morris–Lecar (mM–L) neuron model is proposed. Numerical simulation confirms that different intensities of electromagnetic fields can produce distinct pattern transitions in electrical activities of the neuron, such as periodic bursting, periodic spiking, chaotic bursting. From the perspective of neuron’s interspike interval (ISI), the ISIs bifurcation in the multiparameter planes, ISIs firing periods, the variance of ISIs and other methods are used to find the trend of the mM–L neuron firing pattern transition. Finally, based on the 4D nonlinear differential equation of the mM–L neuron model, the complete electronic implementation of the model is designed. The output of the designed circuit is consistent with the theoretical prediction, which is extremely useful for studying the dynamics of a single neuron.
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