Dynamical behaviour of FitzHugh-Nagumo neuron model driven by harmonic noise

Abstract

The FitzHugh-Nagumo neuron model driven by a harmonic noise is investigated, whose dynamic behaviours are influenced by the frequency and the damping parameters of noise. The spikes train varies with these two parameters changing. The FitzHugh-Nagumo neuron has resonance characteristic and exhibits stronger response to noise with a given frequency. Undernoise with this frequency parameter, the spikes train is more regular and the coefficient of coherent resonance reaches the minimum. The larger the damping parameter of the noise is, the more the different ingredients are, thus the synchronization between neuron and noise becomes more imperfect and the coefficient of coherent resonance is larger.