City Research Online

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. All our stimuli were squares (“fields”) of randomly selected gray levels. Horizontal strips of 16 pixels shifted rightwards with a velocity defined by a disk-shaped function of space. 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 binary texture and the difference between two 2-D Gaussian density functions.

Publication Type:	Article
Additional Information:	© 2024. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
Subjects:	R Medicine > RE Ophthalmology
Departments:	School of Health & Psychological Sciences School of Health & Psychological Sciences > Optometry & Visual Sciences
SWORD Depositor:	Symplectic Administrator

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