Spatial summation for motion detection

Abstract

We used the psychophysical summation paradigm to reveal some spatial characteristics of the mechanism responsible for detecting a motion-defined visual target in central vision. There has been much previous work on spatial summation for motion detection and direction discrimination, but none has assessed it in terms of the velocity threshold or used velocity noise to provide a measure of the efficiency of the velocity processing mechanism. Motion-defined targets were centered within square fields of randomly selected gray levels. The motion was produced within the disk-shaped target region by shifting the pixels rightwards for 0.2 s. The uniform target motion was perturbed by Gaussian motion noise in horizontal strips of 16 pixels. Independent variables were field size, the diameter of the disk target, and the variance of an independent perturbation added to the (signed) velocity of each 16-pixel strip. The dependent variable was the threshold velocity for target detection. Velocity thresholds formed swoosh-shaped (descending, then ascending) functions of target diameter. Minimum values were obtained when targets subtended approximately 2 degrees of visual angle. The data were fit with a continuum of models, extending from the theoretically ideal observer through various inefficient and noisy refinements thereof. In particular, we introduce the concept of sparse sampling to account for the relative inefficiency of the velocity thresholds. The best fits were obtained from a model observer whose responses were determined by comparing the velocity profile of each stimulus with a limited set of sparsely sampled “DoG” templates, each of which is the product of a random binary array and the difference between two 2-D Gaussian density functions.