Field coupling-induced wave propagation and pattern stability in a two-layer neuronal network under noise

Abstract

Synapse coupling is critical for information encoding of neurons. The effect of electromagnetic induction in cell becomes distinct when the exchange of charged ions across membrane is frequently triggered by external electric field or synapse current from adjacent neurons. In this paper, Gaussian white noise is imposed on a two-layer network composed of neurons with electromagnetic induction. The gap junction coupling is applied to connect the adjacent neurons and external stimulus with diversity is applied to keep different excitabilities of neurons in each layer. Neurons on the second layer are activated and modulated by using field coupling rather than channel coupling. It is found that the pattern formation on the network is much dependent on the initial setting due to the memory effect based on induction current via memristive synapse. Furthermore, field coupling intensity (D0) and noise intensity (D1) are changed to detect the development of spiral waves, target waves on the network in presence of noise. It confirms that noise can be helpful for pattern selection and synchronization approach on the two-layer network under field coupling, while field coupling can suppress the self-organization for pattern formation.