Mechanism of stochastic resonance enhancement in neuronal models driven by 1/f noise.

Noise can assist neurons in the detection of weak signals via a mechanism known as stochastic resonance (SR). In a previous study [Phys. Lett. A 243, 281 (1998)], we showed that when colored noise with 1/f(beta) spectrum is added to the FitzHugh-Nagumo (FHN) neuronal model, the optimal noise variance for SR could be minimized with beta approximately 1. In this study, we investigate analytically how the noise color (beta) affects the SR profile in a linearized version of the FHN model. We demonstrate that the aforementioned effect of 1/f noise is related to the dynamical characteristics of the model neuron, i.e., the refractory period, the low-pass filtering effect of the membrane capacitance, and the high-pass filtering effect of the recovery variable.

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