Stochastic resonance in the perceptual interpretation of ambiguous figures: A neural network model

Abstract

We describe the results of computer simulations of the dynamical behavior of an autoassociative network with a two-dimensional energy landscape. Such a network can model some aspects of the phenomenon of perceptual bistability in the presence of ambiguous figures. The network can be operated at either zero or nonzero temperatures which represent an internal system noise. Our results show that, under the influence of a weak periodic external signal, the network exhibits a maximum in the signal-to-noise ratio at an optimum noise level: the characteristic signature of stochastic resonance.