In the context of natural scenes, we applied the pattern-masking paradigm to investigate how image structure and phase alignment affect contrast-gain control in binocular vision. We measured the discrimination thresholds of bandpass-filtered natural-scene images (targets) under various types of pedestals. Our first experiment had four pedestal types: bandpass-filtered pedestals, unfiltered pedestals, notch-filtered pedestals (which enabled removal of the spatial frequency), and misaligned pedestals (which involved rotation of unfiltered pedestals). Our second experiment featured six types of pedestals: bandpass-filtered, unfiltered, and notch-filtered pedestals, and the corresponding phase-scrambled pedestals. The thresholds were compared for monocular, binocular, and dichoptic viewing configurations. The bandpass-filtered pedestal and unfiltered pedestals showed classic dipper shapes; the dipper shapes of the notch-filtered, misaligned, and phase-scrambled pedestals were weak. We adopted a two-stage binocular contrast-gain control model to describe our results. We deduced that the phase-alignment information influenced the contrast-gain control mechanism before the binocular summation stage and that the phase-alignment information and structural misalignment information caused relatively strong divisive inhibition in the monocular and interocular suppression stages. When the pedestals were phase-scrambled, the elimination of the interocular suppression processing was the most convincing explanation of the results. Thus, our results indicated that both phase-alignment information and similar image structures cause strong interocular suppression.
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http://dx.doi.org/10.1016/j.visres.2018.02.012 | DOI Listing |
bioRxiv
November 2024
Oregon Hearing Research Center, Oregon Health and Science University, Portland, OR 97239, USA.
Sci Rep
November 2024
Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
J Vis
November 2024
Department of Psychology, University of York, York, UK.
Much progress has been made in understanding how the brain combines signals from the two eyes. However, most of this work has involved achromatic (black and white) stimuli, and it is not clear if the same processes apply in color-sensitive pathways. In our first experiment, we measured contrast discrimination ("dipper") functions for four key ocular configurations (monocular, binocular, half-binocular, and dichoptic), for achromatic, isoluminant L-M and isoluminant S-(L+M) sine-wave grating stimuli (L: long-, M: medium-, S: short-wavelength).
View Article and Find Full Text PDFJ Neurophysiol
November 2024
Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, California, United States.
Neurons in primary visual cortex (area V1) adapt in varying degrees to the average contrast of the environment, suggesting that the representation of visual stimuli may interact with the state of cortical gain control in complex ways. To investigate this possibility, we measured and analyzed the responses of neural populations in mouse V1 to visual stimuli as a function of contrast in different environments, each characterized by a unique distribution of contrast values. Our findings reveal that, for a fixed stimulus, the population response can be described by a vector function (), where the gain is a decreasing function of the mean contrast of the environment.
View Article and Find Full Text PDFbioRxiv
July 2024
Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles Los Angeles, CA 90095.
Neurons in primary visual cortex (area V1) adapt in different degrees to the average contrast of the environment, suggesting that the representation of visual stimuli may interact with the state of cortical gain control in complex ways. To investigate this possibility, we measured and analyzed the responses of neural populations to visual stimuli as a function of contrast in different environments, each characterized by a unique distribution of contrast. Our findings reveal that, for a given stimulus, the population response can be described by a vector function , where the gain is a decreasing function of the mean contrast of the environment.
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