December 2010
Volume 10, Issue 15
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OSA Fall Vision Meeting Abstract  |   December 2010
The role of contrast in shape discrimination of radial frequency patterns
Author Affiliations
  • Iliya V. Ivanov
    McGill Vision Research Unit Department of Ophthalmology, McGill University
  • Kathy T. Mullen
    McGill Vision Research Unit Department of Ophthalmology, McGill University
Journal of Vision December 2010, Vol.10, 39. doi:10.1167/10.15.39
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      Iliya V. Ivanov, Kathy T. Mullen; The role of contrast in shape discrimination of radial frequency patterns. Journal of Vision 2010;10(15):39. doi: 10.1167/10.15.39.

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

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Abstract

Shape processing involves a progression from a local to global analysis. A key aspect of this progression is the binding of distributed local features into an overall form, followed by the extraction of the shape independently of its local contrasts and spatial scales. Here we use radial frequency (RF) patterns in a shape discrimination task, which is thought to be based on a global processing stage of form analysis that has reached contrast and scale invariance. We compare performance across different spatial scales (contour spatial frequencies of 0.75-10.0 cpd and pattern radii of 0.5-10.0 degs) with contrast matched in multiples of stimulus detection threshold. For each possible combination of radius and spatial frequency we first measured contrast thresholds for the detection of a circular RF pattern using a 2AFC staircase procedure. We then measured shape discrimination as a function of contrast.

Our results reveal an effect of spatial frequency and pattern radius on discrimination thresholds, with no scale invariance. Our results are at odds with earlier work showing no effect of scaling of radius and spatial frequency on discrimination thresholds. We also find an effect of contrast on shape discrimination for scaled contrasts below 100%. We conclude that our results do not support the assumption of a global processing stage for these stimuli. Instead, we suggest they indicate the importance of local curvature analyses. We develop a local curvature model that can predict our shape discrimination thresholds for foveal and peripheral vision.

Acknowledgments
This study was funded by a CIHR grant to K.T. Mullen (MOP-10819). 
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