Research on suprathreshold stochastic resonance of FitzHugh-Nagumo neuron model

Nowadays, noise was considered to play a key role in the neural system, which improved the weak signal detection and enhanced the information transmission, as deeply research on stochastic resonance (SR). Traditionally, stochastic resonance was thought to be the result of the interaction between subthreshold signals with noise in nonlinear system. Particularly, the existence of noise was thought to be harmful to the response of system with suprathreshold signal input commonly. Observing the response of FitzHugh-Nagumo (FHN) neuron model to the suprathreshold input, it was improved gradually as the amplitude of input rising from subthreshold to suprathreshold. Signal-to-noise ratio and cross correlation coefficient were defined as performance evaluation functions separately, then the response of FHN neuron model to periodic and aperiodic suprathreshold signal input was studied. At the same time, the threshold characteristic was discussed, and some basic parameters for practical application were provided. The simulation result illustrates the information transmission can be enhanced by the noise even if input signal is suprathreshold in FHN neuron model.