August 2023
Volume 23, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2023
Spatial summation for motion detection
Author Affiliations
  • Joshua Solomon
    City, University of London
  • Christopher Tyler
    City, University of London
Journal of Vision August 2023, Vol.23, 5422. doi:https://doi.org/10.1167/jov.23.9.5422
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Joshua Solomon, Christopher Tyler; Spatial summation for motion detection. Journal of Vision 2023;23(9):5422. https://doi.org/10.1167/jov.23.9.5422.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

The psychophysical summation paradigm is a powerful tool capable of revealing the effective receptive field structure underlying visual processing for a given stimulus domain, based on the form of summation prevailing in any given spatial range. Negative summation is predicted when the receptive field structure contains inhibitory components. 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. All stimuli were squares of randomly selected graylevels. Graylevels within each 16 (horizontal) x 1 (vertical) group of pixels shifted rightwards with a velocity defined by a disk-shaped function of space. Independent variables were stimulus size, the diameter of the disk target, and the variance of an independent perturbation added to the (signed) velocity of each 16-pixel group. The dependent variable was the threshold amplitude for target detection. Minimum velocity thresholds were obtained when targets subtended approximately 1 degree of visual angle centered at the fovea. Thresholds were higher for both smaller and larger targets. Satisfactory fits to the data were obtained from a model observer whose responses were determined by comparing the velocity profile of each stimulus with a set of “DoG” templates, each of which is the product between a binary texture and the sum of a smaller positive and a larger negative 2-D Gaussian density function.

×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×