July 2013
Volume 13, Issue 9
Free
Vision Sciences Society Annual Meeting Abstract  |   July 2013
A unified framework for multiple-alternative detection in birds and primates
Author Affiliations
  • Devarajan Sridharan
    Department of Neurobiology, Stanford University School of Medicine, Stanford, California
  • Nicholas Steinmetz
    Department of Neurobiology, Stanford University School of Medicine, Stanford, California
  • Tirin Moore
    Department of Neurobiology, Stanford University School of Medicine, Stanford, California
  • Eric Knudsen
    Department of Neurobiology, Stanford University School of Medicine, Stanford, California
Journal of Vision July 2013, Vol.13, 629. doi:10.1167/13.9.629
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to Subscribers Only
      Sign In or Create an Account ×
    • Get Citation

      Devarajan Sridharan, Nicholas Steinmetz, Tirin Moore, Eric Knudsen; A unified framework for multiple-alternative detection in birds and primates. Journal of Vision 2013;13(9):629. doi: 10.1167/13.9.629.

      Download citation file:


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

      ×
  • Supplements
Abstract

Studies of spatial vision and attention seek to measure sensitivity to visual stimuli at multiple locations within a single experimental session. A key challenge for behavioral psychophysics is to decouple the contributions of perceptual sensitivity from those of response bias at each location. Signal detection theory (SDT) is a powerful approach for decoupling sensitivity from bias in two alternative forced-choice (discrimination) and Yes-No (detection) tasks. However, conventional SDT cannot be readily applied to tasks with more than two response alternatives. Here we introduce a theoretical framework that extends SDT to a detection task with multiple (more than two) alternatives. In multiple-alternative detection tasks, targets are presented at one among several potential locations, and the subject is rewarded for detecting and indicating the location of the target (when it occurred), or for not responding when no target was presented ("catch" trials). Based on a structural model and decision rule, our framework permits principled estimation of sensitivity and bias at each location from observed response probabilities. We applied this framework to estimate sensitivity and bias for chickens (Gallus domesticus) and monkeys (Macaca mulatta) performing four-alternative visual detection tasks. In each task, the target could occur at one of four locations (one in each visual quadrant) or not at all (catch), generating a 5x5 contingency table of response probabilities. For both species, the theory demonstrated remarkable predictive ability: with parameters estimated from only 8 contingencies (the 4 miss and 4 false-alarm rates) response probabilities for all remaining 17 contingencies could be predicted with less than 3% deviation. Our results demonstrate that a common model accounts for spatial detection behaviors in these diverse species. This framework will find important application in assessing the differential effects of neural manipulations (microstimulation or inactivation) on sensitivity and bias in multialternative detection tasks of spatial vision and attention.

Meeting abstract presented at VSS 2013

×
×

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.

×