Firing patterns in a fractional-order FithzHugh-Nagumo neuron model

Various neuron models and circuits have been developed to explore how neurons detect and encode different stimuli. However, relevant researches failed to consider edge effects and nonuniformity of realistic electronic components. In this paper, a fractional-order FithzHugh-Nagumo neuron circuit constructed by fractional-order capacitor and inductor is investigated based on Adomain decomposition method. The impacts on firing patterns and Hamilton energy are also discussed with the variation of fractional orders. The variation of the order induces the shifting between bursting firing and chaotic firing, and also between spiking firing and chaotic firing. Simulation results indicate that the fractional-order FHN neural model is more suitable and experimental to model neural behaviors, and it provides a promising application in construction of the artificial neural network.

Automated summary

This paper investigates a fractional-order FithzHugh-Nagumo neuron circuit constructed by fractional-order capacitor and inductor based on Adomain decomposition method. The impacts on firing patterns and Hamilton energy are also discussed with the variation of fractional orders. The simulation results suggest that the fractional-order FHN neural model is more suitable for modeling neural behaviors and has promising applications in constructing artificial neural networks.