Research on Electrical Activity and Synchronization Behavior of Electromagnetic Coupled FHN Neural Networks
Yuancheng Jing, Yanhua Xian · 2024
This paper proposes three models based on FHN neurons: a neuron model introducing a magnetic field variable through a magnetoresistive memristor, a neuron model introducing an external electric field, and a chain neural network model under the combined action of an electromagnetic field. (1) Detailed numerical simulations were performed on the two neuron models. The results show that under the action of a magnetic field, different external DC current stimulations and different feedback gains can lead to various discharge modes of neurons, such as resting state, spike discharge, and periodic spike discharge; while under the action of an electric field, different external DC current stimulations and different charge sizes can cause neurons to exhibit cluster discharges of different periods. (2) An in-depth analysis of the electromagnetic coupled neural network was conducted. The results found that increasing the synaptic coupling strength can enhance the synchronization effect of the neural network. However, changing the charge size and memristor feedback gain does not change the synchronization effect of the network. These findings provide new perspectives and methods for understanding and designing neural computing systems.