Synchronization in Memristive Small-World Neural Networks Under Electromagnetic Radiation

The human brain is composed of a large number of neurons that work together to process the generation, transmission, reception, and processing of information. The topological structure of the human brain has small-world characteristics, and the synchronization and neuron firing are influenced by the electromagnetic field. In this paper, we use four-stable discrete memristors to simulate the external electromagnetic field, and construct a memristive small-world neural network (MSNN) model based on Rulkov neurons, and conduct numerical simulations. We have found that the MSNN exhibits multiple coexisting behaviors of synchronous, asynchronous, and chimeric states under different initial conditions of the discrete memristors. At the same time, changing the strength of electromagnetic induction can affect the synchronization performance of the MSNN. Finally, we find that increasing the electromagnetic induction strength can enhance the neuron firing action potential.