Paper
17 March 1994 Monocular and binocular mechanisms of contrast gain control
Izumi Ohzawa, Ralph D. Freeman
Author Affiliations +
Proceedings Volume 2054, Computational Vision Based on Neurobiology; (1994) https://doi.org/10.1117/12.171149
Event: Computational Vision Based on Neurobiology, 1993, Park Grove, CA, United States
Abstract
Prolonged stimulation by temporally modulated sinusoidal gratings causes a decrease in the contrast sensitivity and response of neurons in the visual cortex. We have studied the dynamic aspects of this contrast gain control mechanism and how its temporal properties affect the determination of neural contrast response functions. In addition, we have considered the possibility that a single mechanism is sufficient to explain monocular and binocular properties of contrast gain control. We find that neural contrast response functions are highly susceptible to the measurement procedure itself, so that the data obtained in some studies seriously underestimate the slope of the function and overestimate the threshold. Therefore, careful selection of the experimental data is required for general use and for constructing models of visual cortical function. Comparisons of monocular and binocular properties of contrast gain control provide insights concerning the neural origin of the mechanism. Monocularly induced gain reductions are transferrable to the other eye, suggesting that gain control originates in part at a site following binocular convergence. However, binocular experiments conducted with interocular contrast mismatches indicate that the gain of the monocular pathways for each eye may be controlled independently. These results suggest that a single-gain control mechanism is not sufficient to account for the properties exhibited by cortical neurons.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Izumi Ohzawa and Ralph D. Freeman "Monocular and binocular mechanisms of contrast gain control", Proc. SPIE 2054, Computational Vision Based on Neurobiology, (17 March 1994); https://doi.org/10.1117/12.171149
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