September 2019
Volume 19, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2019
Decoding chromaticity and luminance information with multivariate EEG
Author Affiliations & Notes
  • David W Sutterer
    Vanderbilt University
  • Andrew Coia
    Institute for Mind and Biology, University of Chicago
    Department of Psychology, University of Chicago
  • Vincent Sun
    Chinese Culture University
  • Steven Shevell
    Institute for Mind and Biology, University of Chicago
    Department of Psychology, University of Chicago
    Depart-ment of Ophthalmology & Visual Science, The University of Chicago
  • Edward Awh
    Institute for Mind and Biology, University of Chicago
    Department of Psychology, University of Chicago
Journal of Vision September 2019, Vol.19, 70. doi:https://doi.org/10.1167/19.10.70
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      David W Sutterer, Andrew Coia, Vincent Sun, Steven Shevell, Edward Awh; Decoding chromaticity and luminance information with multivariate EEG. Journal of Vision 2019;19(10):70. doi: https://doi.org/10.1167/19.10.70.

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

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Abstract

Recent work suggested that it is possible to decode which chromaticity an observer is viewing from the multi-electrode pattern of low frequency EEG activity on the scalp (Bocincova and Johnson, 2018). However, chromatic stimuli may vary also in luminance, and there has been debate about whether differences in the visual evoked potentials (VEPs) from stimuli of different chromaticities are driven by differences in the luminance or the chromaticity of the stimuli (Skiba et al., 2014). Thus, an open question is whether the chromaticity of a stimulus can be decoded even when differences in luminance do not inform the classification. To answer this question, we conducted two experiments in which we systematically varied both the luminance and the chromaticity of a centrally presented disk. In experiment one, we presented two chromaticities (appearing red and green) at three luminance levels (6.5, 10.8, and 17.4 cd/m2, on a 5 cd/m2 background) on separate trials. In experiment 2 we presented 4 chromaticities (appearing red, orange, yellow, and green) at two luminance levels (6.5 and 10.8 cd/m2, on a 5 cd/m2 background). For each observer, we first performed heterochromatic flicker photometry to equate each chromaticity at each luminance level. Next, observers monitored centrally presented chromatic discs (150ms stimulus duration) while EEG was recorded. Using a pattern classifier and the multivariate topography of scalp EEG activity we were able to accurately decode the chromaticity of observed stimuli. We could also decode the luminance level of each stimulus. Critically, we were able to decode the chromaticity of the stimuli when we trained the classifier on the chromaticities presented at one luminance level and tested at a different luminance level. Thus, the multivariate topography of EEG activity can be used to decode which chromaticity is being viewed, even when chromaticity is decoupled from variation in luminance.

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