Single Neuron Model: Response to Weak Modulation in the Presence of Noise

摘要

We consider a noisy bistable single neuron model driven by a periodic externalmodulation. The modulation introduces a correlated switching between states driven by the noise. The information flows through the system from the modulation to the output switching events, and leads to a succession of strong peaks in the power spectrum. The signal-to-noise ratio (SNR) obtained from this power spectrum is a measure of the information content in the neuron response. With increasing noise intensity, the SNR passes through a maximum, an effect which has been called stochastic resonance. We treat the problem within the framework of a recently developed approximate theory, valid in the limits of weak noise intensity, weak periodic forcing and low forcing frequency. A comparison of the results of this theory with those obtained from a linear system FFT is also presented.