Learning direction in global motion: two classes of psychophysically-motivated models

Part of Advances in Neural Information Processing Systems 7 (NIPS 1994)

Authors

V. Sundareswaran, Lucia Vaina

Abstract

Perceptual learning is defined as fast improvement in performance and retention of the learned ability over a period of time. In a set of psy(cid:173) chophysical experiments we demonstrated that perceptual learning oc(cid:173) curs for the discrimination of direction in stochastic motion stimuli. Here we model this learning using two approaches: a clustering model that learns to accommodate the motion noise, and an averaging model that learns to ignore the noise. Simulations of the models show performance similar to the psychophysical results.