Paradoxical psychometric functions ("swan functions") are explained by dilution masking in four stimulus dimensions

Daniel H. Baker, Tim S. Meese, Mark A. Georgeson

Research output: Contribution to journalArticle

Abstract

The visual system dissects the retinal image into millions of local analyses along numerous visual dimensions. However, our perceptions of the world are not fragmentary, so further processes must be involved in stitching it all back together. Simply summing up the responses would not work because this would convey an increase in image contrast with an increase in the number of mechanisms stimulated. Here, we consider a generic model of signal combination and counter-suppression designed to address this problem. The model is derived and tested for simple stimulus pairings (e.g. A + B), but is readily extended over multiple analysers. The model can account for nonlinear contrast transduction, dilution masking, and signal combination at threshold and above. It also predicts nonmonotonic psychometric functions where sensitivity to signal A in the presence of pedestal B first declines with increasing signal strength (paradoxically dropping below 50% correct in two-interval forced choice), but then rises back up again, producing a contour that follows the wings and neck of a swan. We looked for and found these "swan" functions in four different stimulus dimensions (ocularity, space, orientation, and time), providing some support for our proposal.
Original languageEnglish
Pages (from-to)17-35
Number of pages19
Journali-Perception
Volume4
Issue number1
DOIs
Publication statusPublished - 2013

Bibliographical note

Copyright is retained by the author(s) of this article. This open-access article is distributed under a Creative Commons Licence, which permits noncommercial use, distribution, and reproduction, provided the original author(s) and source are credited and no alterations are made.

Keywords

  • masking
  • paradoxical
  • swan function
  • psychometric function
  • dilution masking
  • contrast detection

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