Abstract.
Stereopsis is the ability to perceive three-dimensional structure from disparities between the two-dimensional retinal images. Although disparity-sensitive neurons have been proposed as a neural representation of this ability many years ago, it is still difficult to link all qualities of stereopsis to properties of the neural correlate of binocular disparities. The present study wants to support efforts directed at closing the gap between electrophysiology and psychophysics. Populations of disparity-sensitive neurons in V1 were simulated using the energy-neuron model. Responses to different types of stimuli were evaluated with an efficient statistical estimator and related to psychophysical findings. The representation of disparity in simulated population responses appeared to be very robust. Small populations allowed good depth discrimination. Two types of energy neurons (phase- and position-type models) that are discussed as possible neural implementations of disparity-selectivity could be compared to each other. Phase-type coding was more robust and could explain a tendency towards zero disparity in degenerated stimuli and, for high-pass stimuli, exhibited the breakdown of disparity discrimination at a maximum disparity value. Contrast-inverted stereograms led to high variances in disparity representation, which is a possible explanation of the absence of depth percepts in large contrast-inverted stimuli. Our study suggests that nonlocal interactions destroy depth percepts in large contrast-inverted stereograms, although these percepts occur for smaller stimuli of the same class.
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Received: 21 December 2001 / Accepted: 29 April 2002
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ID="*" Present address: Bayer AG BTS-PT-MVT-MKM, Geb. K9, 51368 Leverkusen, Germany
Acknowledgement. This work was supported by a scholarship from the Studienstiftung des deutschen Volkes to J.L.
Correspondence to: J. Lippert (e-mail: joerg.lippert.jl@bayer-ag.de)
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Lippert, J., Wagner, H. Visual depth encoding in populations of neurons with localized receptive fields. Biol Cybern 87, 249–261 (2002). https://doi.org/10.1007/s00422-002-0338-x
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DOI: https://doi.org/10.1007/s00422-002-0338-x