Suppression of noise in FitzHugh-Nagumo model driven by a strong periodic signal

The response time of a neuron in the presence of a strong periodic driving in the stochastic FitzHugh-Nagumo model is investigated. We analyze two cases: (i) the variable that corresponds to membrane potential is subjected to fluctuations, and (ii) the recovery variable associated with the refractory properties of a neuron is noisy. The influence of noise sources on the delay of the response of a neuron is analyzed. In both cases we observe a resonant activation-like phenomenon and suppression of noise: the negative effect of fluctuations on the process of spike generation is minimal near the resonance region. The phenomenon of noise enhanced stability is also observed in both cases. The role of the initial phase of the periodic driving is examined.