A. R. Bulsara, W. Jacobs
We consider a noisy bist.able single neuron model driven by a periodic external modulation. The modulation introduces a correlated switching between st.ates driven by the noise. The information flow through the sys(cid:173) tem from the modulation to the output switching events, leads to a succes(cid:173) sion 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 t.hrough a maximum, an effect which has been called stochastic resonance. We treat t.he problem wit.hin the framework of a recently developed approx(cid:173) imate theory, valid in the limits of weak noise intensity, weak periodic forc(cid:173) ing and low forcing frequency. A comparison of the results of this theory with those obtained from a linear syst.em FFT is also presented .