September 2019
Volume 19, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2019
Using dynamic contrast estimation to assess interocular summation for non-rivalrous stimuli
Author Affiliations & Notes
  • Kimberly Meier
    Department of Psychology, University of Washington
  • Kristina Kristina Tarczy-Hornoch
    Department of Ophthalmology, Seattle Children’s Hospital
  • Ione Fine
    Department of Psychology, University of Washington
  • Geoffrey M Boynton
    Department of Psychology, University of Washington
Journal of Vision September 2019, Vol.19, 80. doi:https://doi.org/10.1167/19.10.80
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      Kimberly Meier, Kristina Kristina Tarczy-Hornoch, Ione Fine, Geoffrey M Boynton; Using dynamic contrast estimation to assess interocular summation for non-rivalrous stimuli. Journal of Vision 2019;19(10):80. doi: https://doi.org/10.1167/19.10.80.

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

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Abstract

Purpose: Interocular summation has been measured using a wide variety of stimuli, measurements, and models. Our goal was to develop an intuitive and robust measure of interocular summation that reflects naturalistic (non-rivalrous) conditions and provides a direct measure of the perceptual experience of the observer. Methods: Observers fixated a Gabor (2 cpd; 4 deg radius, orientation rotating at 1 deg/sec to minimize adaptation effects) through a stereoscope. Gabor contrast was slowly modulated at 1/8 Hz in one eye, and 1/6 Hz in the other. Subjects dynamically reported perceived contrast over time by manipulating a Thrustmaster Pro joystick. In a separate task, we quantified each observer’s interocular contrast ratio by asking subjects to estimate the apparent phase of 100% contrast Gabor stimuli that were phase-offset across the two eyes (Kwon et al. 2014). Results: Using dynamic contrast estimation, with less than an hour of data per subject it was possible to estimate individual contrast response functions for each eye, and robustly fit a model of binocular summation. Data were well fit by a very simple model of binocular summation: R = (KL*CLn + KR*CRn)(1/n), where CL and CR are the stimulus contrast response functions and KL and KR are gain parameters for left (L) and right (R) eyes. Exponential parameters n show that binocular summation varied across individuals, ranging from approximately quadratic summation to a max rule. The interocular contrast ratio was estimated from best fitting model parameters as KL/KR. Interocular contrast ratios from dynamic model fits were closely correlated with those measured using the phase-offset technique. Conclusions: Our dynamic perceived contrast task provides an intuitive, rapid and robust method for assessing the binocular visual system that is likely to be useful in characterizing binocular dysfunction across a wide variety of disorders, including amblyopia and strabismus.

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