Neural Modelling of Disparity Influences in Optic-Flow Processing

Last year, we reported a new disparity effect on optic-flow perception. It occurs when a flow field of radially moving random dots is transparently superimposed by a unidirectional motion pattern. Subjects asked to locate the centre of the expansion pattern perceive it shifted away from its true position (Duffy and Wurtz, 1993 Vision Research 33 1481 – 1490). The magnitude of this shift depends on binocular disparity between the two superimposed patterns: presenting the translation in front of the expansion causes a massive reduction of the shift, presenting it behind the expansion yields only a slight reduction.

To determine possible mechanisms for this interaction, we tried to model our results by modifying a previously developed neural model for optic-flow processing (Lappe and Rauschecker, 1995 Vision Research 35 1619 – 1631). We compared three possible mechanisms of disparity influence. The first was based on the assumption that the absolute distance of the stimuli from the observer was known. The second was based on a disparity-based spatial integration, as found in ‘tuned’ neurons in primate visual area MT. Neither could account for our data.

Finally we included a disparity-dependent weighting function in the model, assuming that distant flow vectors contribute more strongly than near ones to the processing of optic flow. This reproduced the experimental findings. Surprisingly, the optimal weighting function was similar to the disparity-dependence of the so-called ‘far-neurons’ in area MT. We conclude that the visual system uses disparity in optic-flow processing by putting special emphasis on distant flow vectors, and that far-neurons in MT might serve as a neuronal substrate for this.