August 2016
Volume 16, Issue 12
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2016
Binocular summation of chromatic information
Author Affiliations
  • Hsiao-Yuan Lin
    Department of Psychology, National Taiwan University
  • Chien-Chung Chen
    Department of Psychology, National Taiwan University
Journal of Vision September 2016, Vol.16, 1214. doi:10.1167/16.12.1214
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      Hsiao-Yuan Lin, Chien-Chung Chen; Binocular summation of chromatic information . Journal of Vision 2016;16(12):1214. doi: 10.1167/16.12.1214.

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      © 2017 Association for Research in Vision and Ophthalmology.

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Abstract

While there are studies for binocular summation of luminance contrast, how the visual system integrates chromatic information from the two eyes is not well understood. We designed a matching experiment to measure the binocular summation of isoluminance colors. The stimuli were dichoptically viewed squares (2 by 2 degree) modulated in one of the six color directions (L-M, M-L, +S, –S, L+M+S and –L-M-S). In each trial, an observer would see a test square, which was a combination of the squares presented to the left and the right eyes in different contrast, and a match square, in which the contrasts of the left and the right eye squares were the same. The ranges of contrast, expressed in dB (20*log10C, where C is Michelson contrast), were ,from -42 to -18 dB for L-M, -18 to -2 dB for S and -32 to -8 dB for L+M+S directions.. The observers' task was to adjust the contrast of the match stimulus to match the test stimulus. In general, the matched contrast increased with test contrast. When the test contrast difference between the two eyes was small, the match was approximately the average of the patch contrasts of both eyes with slightly greater weighting for the dominant eye. However, when the contrast difference between the two eyes was large, the match result was dominated by the higher contrast, regardless of the eye origin. Such change of relative contribution from the two eyes by contrast cannot be explained by a linear model in which the perceived binocular contrast was predicted by the linear combination of two monocular contrasts. Instead, a nonlinear model is necessary to explain the data.

Meeting abstract presented at VSS 2016

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