Parameter dependence of stochastic resonance in the FitzHugh-Nagumo neuron model driven by trichotomous noise

We investigate the stochastic resonance in a FitzHugh-Nagumo neuron model driven by trichotomous noise and periodic signal, focusing on the dependence of properties of stochastic resonance (SR) on system parameters. The stochastic resonance is shown through several different measures: system response, power spectrum and signal-to-noise ratio. Firstly, it is found that whether the neuron can fire regularly depends on the cooperative effect of the signal frequency and the signal amplitude for the deterministic FHN neuron. When the forcing amplitude alone is insufficient to cause the neuron firing, the neuron can fire with the addition of trichotomous noise. Secondly, we show that power spectrum is maximized for an optimal value of the noise correlation time, which is the signature of SR. Finally, from studying SNR, the specific system parameters are found to optimize the SR phenomenon.