Abstract
Bursting is an important firing activity of neurons, which is caused by a slow process that modulates fast spiking activity. Based on the original second‐order Morris‐Lecar neuron model, an improved third‐order Morris‐Lecar neuron model can produce bursting activity is proposed, in which the effect of electromagnetic radiation is considered as a slow process and the original equation of Morris‐Lecar neuron model as a fast process. Extensive numerical simulation results show that the improved neuron model can produce different types of bursting, and bursting activity shows a deep dependence on system parameters and electromagnetic radiation parameters. In addition, synchronization transitions of identical as well as no‐identical coupled third‐order Morris‐Lecar neurons are studied, the results show that identical coupled neurons experience a complex synchronization process and reach complete synchronization finally with the increase of coupling intensity. For no‐identical coupled neurons, only anti‐phase synchronization and in‐phase synchronization can be reached. The studies of bursting activity of single neuron and synchronization transition of coupled neurons have important guiding significance for further understanding the information processing of neurons and collective behaviors in neuronal network under electromagnetic radiation environment.
Highlights
Being considered is constructed, in which the previous steady neural network can present abundant chaotic dynamics, and hidden attractors can be observed
References [28,29,30] have proved that the ionic channels of neuron models, e.g., Hodgkin–Huxley and Morris-Lecar neuron model, have memory e ect and they can be substituted by rst-order or second-order memristors
Synchronization, noise e ect, and spatiotemporal dynamics in neuron and neural networks under electromagnetic radiation were investigated [37,38,39,40,41]. e e ect of electromagnetic radiation can be described by time-varying magnetic ux, the coupling of electromagnetic eld between neurons can be described by exchange of magnetic ux as well, which results in another e ective way for coupling between neurons, i.e., eld coupling
Summary
Being considered is constructed, in which the previous steady neural network can present abundant chaotic dynamics, and hidden attractors can be observed. 2: Sampled time series for membrane potential when the angular frequency of external forcing currents is chosen as di erent values with xed intensity = 0.05.
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