Binocular combination of phase and contrast explained by a gain-control and gain-enhancement model
Author(s) -
Jian Ding,
Stanley A. Klein,
Dennis M. Levi
Publication year - 2013
Publication title -
journal of vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.126
H-Index - 113
ISSN - 1534-7362
DOI - 10.1167/13.2.13
Subject(s) - contrast (vision) , stimulus (psychology) , monocular , sine wave , binocular vision , psychology , optics , artificial intelligence , computer science , physics , cognitive psychology , quantum mechanics , voltage
We investigated suprathreshold binocular combination, measuring both the perceived phase and perceived contrast of a cyclopean sine wave. We used a paradigm adapted from Ding and Sperling (2006, 2007) to measure the perceived phase by indicating the apparent location (phase) of the dark trough in the horizontal cyclopean sine wave relative to a black horizontal reference line, and we used the same stimuli to measure perceived contrast by matching the binocular combined contrast to a standard contrast presented to one eye. We found that under normal viewing conditions (high contrast and long stimulus duration), perceived contrast is constant, independent of the interocular contrast ratio and the interocular phase difference, while the perceived phase shifts smoothly from one eye to the other eye depending on the contrast ratios. However, at low contrasts and short stimulus durations, binocular combination is more linear and contrast summation is phase-dependent. To account for phase-dependent contrast summation, we incorporated a fusion remapping mechanism into our model, using disparity energy to shift the monocular phases towards the cyclopean phase in order to align the two eyes' images through motor/sensory fusion. The Ding-Sperling model with motor/sensory fusion mechanism gives a reasonable account of the phase dependence of binocular contrast combination and can account for either the perceived phase or the perceived contrast of a cyclopean sine wave separately; however it requires different model parameters for the two. However, when fit to both phase and contrast data simultaneously, the Ding-Sperling model fails. Incorporating interocular gain enhancement into the model results in a significant improvement in fitting both phase and contrast data simultaneously, successfully accounting for both linear summation at low contrast energy and strong nonlinearity at high contrast energy.
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