September 2024
Volume 24, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2024
Dichoptic contrast integration across the human visual cortex hierarchy using functional MRI
Author Affiliations & Notes
  • Kelly Chang
    University of Washington
  • Xiyan Li
    University of Washington
    University of California, San Diego
  • Kimberly Meier
    University of Washington
    University of Houston
  • Kristina Tarczy-Hornoch
    University of Washington
  • Geoffrey M. Boynton
    University of Washington
  • Ione Fine
    University of Washington
  • Footnotes
    Acknowledgements  Knights Templar Eye Foundation, Research to Prevent Blindness, UW Center for Human Neuroscience, Unrestricted grant from Research to Prevent Blindness to UW Department of Ophthalmology
Journal of Vision September 2024, Vol.24, 1100. doi:https://doi.org/10.1167/jov.24.10.1100
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      Kelly Chang, Xiyan Li, Kimberly Meier, Kristina Tarczy-Hornoch, Geoffrey M. Boynton, Ione Fine; Dichoptic contrast integration across the human visual cortex hierarchy using functional MRI. Journal of Vision 2024;24(10):1100. https://doi.org/10.1167/jov.24.10.1100.

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

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Abstract

Introduction: A recent behavioral study by Meier et al. (2023) showed that when the contrast of a non-rivalrous grating is modulated independently in the two eyes, the perceived contrast of the combined stimulus roughly follows the maximum contrast over the two eyes. Here, in a similar paradigm using fMRI, we investigated the neural locus of this behavioral result. Methods: We measured BOLD fMRI signals in early visual cortex (V1 – V3) while participants (n = 10) viewed non-rivalrous dichoptic gratings (2-cpd) that varied slowly in contrast over time in each eye independently at 1/6 and 1/8 Hz. Observers provided a continuous report of perceived contrast over time by positioning a joystick lever. We fit a Minkowski mean [ (L(t)^m + R(t)^m) / 2 ] ^ (1/m) to the behavioral and fMRI time-courses, where L(t) and R(t) are the contrast time-courses in each eye. An exponent parameter of m = 1 is simple averaging, and as m → ∞ the model increases towards a max response in which neural responses or perceived contrast is driven by the eye presented with the highest contrast. Results: The magnitude of m was smallest in V1 (m = 2.00) and increased across the visual hierarchy toward a max model in V2 (m = 5.19) and V3 (m = 8.12). Behavioral responses measured during scanning were consistent with a max model (m = 6.55) and the later stages of the visual hierarchy. Conclusion: Our fMRI results in V1 are similar to a previous fMRI study that used a normalization model (Moradi & Heeger, 2009) to predict V1 BOLD responses. However, the integration of contrast in V1 differs systematically from perceived contrast. BOLD signals in V2 and V3 were consistent with behavioral measurements, implicating these higher visual areas as the neural locus of perceived contrast.

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