November 2002
Volume 2, Issue 7
Free
Vision Sciences Society Annual Meeting Abstract  |   November 2002
An ideal observer approach to simple visual reaction time
Author Affiliations
  • William A. Simpson
    Glasgow Caledonian University
Journal of Vision November 2002, Vol.2, 190. doi:https://doi.org/10.1167/2.7.190
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      William A. Simpson, Kellyanne Findlay, Velitchko Manahilov; An ideal observer approach to simple visual reaction time. Journal of Vision 2002;2(7):190. https://doi.org/10.1167/2.7.190.

      Download citation file:


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

      ×
  • Supplements
Abstract

The ideal observer approach has been used to reveal the causes of human limitations in detecting simple visual patterns at near threshold contrasts. In everyday situations, however, the patterns to be detected often have very high contrasts. We studied the sources of visual inefficiency in detecting high contrast Gabor patches in dynamic Gaussian noise by measuring simple reaction time (RT) and by comparing the results to predictions from an ideal observer model. The ideal observer in a simple RT task must form an estimate of the time of arrival of the signal and hit the button at that time. For an ideal observer, the variance of this time of arrival estimate increases linearly as the variance of the external Gaussian noise increases. The human observer's RT variance behaves in a similar way, but humans have low sampling efficiency and add internal noise.

Simpson, W. A., Findlay, K., Manahilov, V.(2002). An ideal observer approach to simple visual reaction time [Abstract]. Journal of Vision, 2( 7): 190, 190a, http://journalofvision.org/2/7/190/, doi:10.1167/2.7.190. [CrossRef] [PubMed]
Footnotes
 Supported by a grant from the Engineering and Physical Sciences Research Council (UK) to WS.
×
×

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.

×