Mechanism of stochastic resonance enhancement in neuronal models driven by1/f noise

Noise can assist neurons in the detection of weak signals via a mechanism k nown 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 a dded to the FitzHugh-Nagumo (FHN) neuronal model, the optimal noise varianc e for SR could be minimized with beta approximate to 1. In this study, we i nvestigate analytically how the noise color (beta) affects the SR profile i n a linearized version of the FHN model. We demonstrate that the aforementi oned 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 o f the membrane capacitance, and the high-pass filtering effect of the recov ery variable. [S1063-651X(99)11110-3].