September 2018
Volume 18, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2018
The effects of figure-ground segmentation on non-linear visual evoked potentials
Author Affiliations
  • Laila Hugrass
    Centre for Human Psychopharmacology, Swinburne University of Technology
  • David Crewther
    Centre for Human Psychopharmacology, Swinburne University of Technology
Journal of Vision September 2018, Vol.18, 333. doi:https://doi.org/10.1167/18.10.333
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      Laila Hugrass, David Crewther; The effects of figure-ground segmentation on non-linear visual evoked potentials. Journal of Vision 2018;18(10):333. https://doi.org/10.1167/18.10.333.

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

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Abstract

The neural correlates of figure-ground segmentation have been studied using single cell responses in primate thalamus and visual cortex, as well as fMRI in humans. In order to study the non-linear temporal structure of figure-ground responses in human observers, we recorded chromatic multifocal visual evoked potentials. The stimuli were radial gratings with the slightly elongated edges, which gave the appearance of an object on a background. The gratings were separated into inner and outer rings of patches that alternated between red and green in independent pseudorandom binary sequences (refresh rate = 60Hz). Hence, we were able to use Weiner kernel analyses to extract independent responses to each of the inner patches. When the red-green alternations were equiluminant, there was no clear figure-ground modulation of the multifocal VEP responses. When there was a small luminance difference between the red and green levels, we observed a decrease in the first-slice of the second order non-linear response to figure patches relative to ground patches. This difference was evident at latencies as early as 80ms. These results suggest that global analysis of a stimulus can influence responses to local luminance defined edges at very early stages of visual processing.

Meeting abstract presented at VSS 2018

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