A Simple Visual Model Accounts for Drift Illusion and Reveals Illusory Patterns

Abstract

Computational models of vision should not only be able to reproduce experimentally obtained results; such models should also be able to predict the input–output properties of vision. We assess whether a simple computational model of neurons in the Middle Temporal (MT) visual area proposed by the authors can account for illusory perception of “rotating drift patterns,” by which humans perceive illusory rotation (clockwise or counterclockwise) depending on the background luminance. Moreover, to predict whether a pattern causes visual illusion or not, we generate an enormous set of possible visual patterns as inputs to the MT model: $8^{8} = 16,777,216,$ possible input patterns. Numerical quantities of model outputs by computer simulation for 8⁸ inputs were used to estimate human illusory perception. Using psychophysical experiments, we show that the model prediction is consistent with human perception.