On the neurophysiological organization of binocular vision

Biological Cybernetics, 2002

Stereopsis is the ability to perceive threedimensional structure from disparities between the twodimensional 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.

The Journal of physiology, 1967

1. Binocularly driven units were investigated in the cat's primary visual cortex.2. It was found that a stimulus located correctly in the visual fields of both eyes was more effective in driving the units than a monocular stimulus, and much more effective than a binocular stimulus which was correctly positioned in only one eye: the response to the correctly located image in one eye is vetoed if the image is incorrectly located in the other eye.3. The vertical and horizontal disparities of the paired retinal images that yielded the maximum response were measured in 87 units from seven cats: the range of horizontal disparities was 6.6 degrees , of vertical disparities 2.2 degrees .4. With fixed convergence, different units will be optimally excited by objects lying at different distances. This may be the basic mechanism underlying depth discrimination in the cat.

The Journal of Neuroscience : The Official Journal of the Society for Neuroscience

Journal of Neuroscience, 1988

BMC Neuroscience, 2011

Stereo ''3D'' depth perception requires the visual system to extract binocular disparities between the two eyes' images. Several current models of this process, based on the known physiology of primary visual cortex (V1), do this by computing a piecewise-frontoparallel local cross-correlation between the left and right eye's images. The size of the ''window'' within which detectors examine the local cross-correlation corresponds to the receptive field size of V1 neurons. This basic model has successfully captured many aspects of human depth perception. In particular, it accounts for the low human stereoresolution for sinusoidal depth corrugations, suggesting that the limit on stereoresolution may be set in primary visual cortex. An important feature of the model, reflecting a key property of V1 neurons, is that the initial disparity encoding is performed by detectors tuned to locally uniform patches of disparity. Such detectors respond better to squarewave depth corrugations, since these are locally flat, than to sinusoidal corrugations which are slanted almost everywhere. Consequently, for any given window size, current models predict better performance for square-wave disparity corrugations than for sine-wave corrugations at high amplitudes. We have recently shown that this prediction is not borne out: humans perform no better with square-wave than with sine-wave corrugations, even at high amplitudes. The failure of this prediction raised the question of whether stereoresolution may actually be set at later stages of cortical processing, perhaps involving neurons tuned to disparity slant or curvature. Here we extend the local cross-correlation model to include existing physiological and psychophysical evidence indicating that larger disparities are detected by neurons with larger receptive fields (a size/disparity correlation). We show that this simple modification succeeds in reconciling the model with human results, confirming that stereoresolution for disparity gratings may indeed be limited by the size of receptive fields in primary visual cortex.

The Journal of Neuroscience : The Official Journal of the Society for Neuroscience

Journal of neurophysiology, 1999

The visual system uses binocular disparity to discriminate the relative depth of objects in space. Because the striate cortex is the first site along the central visual pathways at which signals from the left and right eyes converge onto a single neuron, encoding of binocular disparity is thought to begin in this region. There are two possible mechanisms for encoding binocular disparity through simple cells in the striate cortex: a difference in receptive field (RF) position between the two eyes (RF position disparity) and a difference in RF profiles between the two eyes (RF phase disparity). Although there is evidence that supports each of these schemes, both mechanisms have not been examined in a single study to determine their relative roles. In this study, we have measured RF position and phase disparities of individual simple cells in the cat's striate cortex to address this issue. Using a sophisticated RF mapping technique that employs binary m-sequences, we have obtained ...

Vision Research, 2004

Half-occluded points (visible only in one eye) are perceived at a certain depth behind the occluding surface without binocular rivalry, even though no disparity is defined at such points. Here we propose a stereo model that reconstructs 3D structures not only from disparity information of interocularly paired points but also from unpaired points. Starting with an array of depth detection cells, we introduce cells that detect unpaired points visible only in the left eye or the right eye (left and right unpaired point detection cells). They interact cooperatively with each other based on optogeometrical constraints (such as uniqueness, cohesiveness, occlusion) to recover the depth and the border of 3D objects. Since it is contradictory for monocularly visible regions to be visible in both eyes, we introduce mutual inhibition between left and right unpaired point detection cells. When input images satisfy occlusion geometry, the model outputs the depth of unpaired points properly. An interesting finding is that when we input two unmatched images, the model shows an unstable output that alternates between interpretations of monocularly visible regions for the left and the right eyes, thereby reproducing binocular rivalry. The results suggest that binocular rivalry arises from the erroneous output of a stereo mechanism that estimates the depth of half-occluded unpaired points. In this sense, our model integrates stereopsis and binocular rivalry, which are usually treated separately, into a single framework of binocular vision. There are two general theories for what the ''rivals'' are during binocular rivalry: the two eyes, or representations of two stimulus patterns. We propose a new hypothesis that bridges these two conflicting hypotheses: interocular inhibition between representations of monocularly visible regions causes binocular rivalry. Unlike the traditional eye theory, the level of the interocular inhibition introduced here is after binocular convergence at the stage solving the correspondence problem, and thus open to pattern-specific mechanisms.

Vision research, 1996

Neurophysiological data support two models for the disparity selectivity of binocular simple and complex cells in primary visual cortex. These involve binocular combinations of monocular receptive fields that are shifted in retinal position (the position-shift model) or in phase (the phase-shift model) between the two eyes. This article presents a formal description and analysis of a binocular energy model with these forms of disparity selectivity. We propose how one might measure the relative contributions of phase and position shifts in simple and complex cells. The analysis also reveals ambiguities in disparity encoding that are inherent in these model neurons, suggesting a need for a second stage of processing. We propose that linear pooling of the binocular responses across orientations and scales (spatial frequency) is capable of producing an unambiguous representation of disparity.

Vision Research, 1973

Progress in Biophysics and Molecular Biology, 2005

Stereoscopic depth perception is a fascinating ability in its own right and also a useful model of perception. In recent years, considerable progress has been made in understanding the early cortical circuitry underlying this ability. Inputs from left and right eyes are first combined in primary visual cortex (V1), where many cells are tuned for binocular disparity. Although the observation of disparity tuning in V1, combined with psychophysical evidence that stereopsis must occur early in visual processing, led to initial suggestions that V1 was the neural correlate of stereoscopic depth perception, more recent work indicates that this must occur in higher visual areas. The firing of cells in V1 appears to depend relatively simply on the visual stimuli within local receptive fields in each retina, whereas the perception of depth reflects global properties of the stimulus. However, V1 neurons appear to be specialized in a number of respects to encode ecologically relevant binocular disparities. This suggests that they carry out essential preprocessing underlying stereoscopic depth perception in higher areas. This article reviews recent progress in developing accurate models of the computations carried out by these neurons. We seem close to achieving a mathematical description of the initial stages of the brain's stereo algorithm. This is important in itself--for instance, it may enable improved stereopsis in computer vision--and paves the way for a full understanding of how depth perception arises.

Visual Cortex: Current Status and Perspectives, 2012

PLoS ONE, 2013

This work describes an approach inspired by the primary visual cortex using the stimulus response of the receptive field profiles of binocular cells for disparity computation. Using the energy model based on the mechanism of log-Gabor filters for disparity encodings, we propose a suitable model to consistently represent the complex cells by computing the wide bandwidths of the cortical cells. This way, the model ensures the general neurophysiological findings in the visual cortex (V1), emphasizing the physical disparities and providing a simple selection method for the complex cell response. The results suggest that our proposed approach can achieve better results than a hybrid model with phase-shift and positionshift using position disparity alone.

Journal of neurophysiology, 1996

1. Spatiotemporal receptive fields (RFs) for left and right eyes were studied for simple cells in the cat's striate cortex to examine the idea that stereoscopic depth information is encoded via structural differences of RFs between the two eyes. Traditional models are based on neurons that possess matched RF profiles for the two eyes. We propose a model that requires a subset of simple cells with mismatched RF profiles for the two eyes in addition to those with similar RF structure. 2. A reverse correlation technique, which allows a rapid measurement of detailed RF profiles in the joint space-time domains, was used to map RFs for isolated single neurons recorded extracellularly in the anesthetized paralyzed cat. 3. Approximately 30% of our sample of cells shows substantial differences between spatial RF structure for the two eyes. Nearly all of these neurons prefer orientations between oblique and vertical, and are therefore presumed to be involved in processing horizontal dispa...

Journal of Neurophysiology, 1999

The visual system integrates information from the left and right eyes and constructs a visual world that is perceived as single and three dimensional. To understand neural mechanisms underlying this process, it is important to learn about how signals from the two eyes interact at the level of single neurons. Using a sophisticated receptive field (RF) mapping technique that employs binary m-sequences, we have determined the rules of binocular interactions exhibited by simple cells in the cat's striate cortex in relation to the structure of their monocular RFs. We find that binocular interaction RFs of most simple cells are well described as the product of left and right eye RFs. Therefore the binocular interactions depend not only on binocular disparity but also on monocular stimulus position or phase. The binocular interaction RF is consistent with that predicted by a model of a linear binocular filter followed by a static nonlinearity. The static nonlinearity is shown to have a shape of a half-power function with an average exponent of ϳ2. Although the initial binocular convergence of signals is linear, the static nonlinearity makes binocular interaction multiplicative at the output of simple cells. This multiplicative binocular interaction is a key ingredient for the computation of interocular cross-correlation, an algorithm for solving the stereo correspondence problem. Therefore simple cells may perform initial computations necessary to solve this problem.