Binocular stereopsis is the ability to use differences between the images? presented to the two eyes (binocular disparities) to perceive the three? dimensional structure of the outside world. In order to detect that an object? has a binocular disparity, it is first necessary to correctly match up the? images of that object in the two eyes (the stereo correspondence problem).? Humans are able to do this very robustly, even when the two eyes are shown random patterns generated by computers (random dot stereograms). Understanding how this correspondence problem is solved by cortical neurons is excellent model system for studying how neuronal processing generates useful perceptual representations. ? ? We studied this with a combination of neuronal recordings and computer simulations. First, simulations showed that our current understanding of the mechanisms that generate disparity selective neurons make a curious prediction: the optimum stimulus for these cells never occurs in natural viewing. We tested this prediction in neurons recorded from the visual cortex of awake fixating monkeys, and found it to be true of approximately half the neurons. ? ? This striking failure to reflect the natural structure of binocular images may serve a useful function: these neurons are most activated when a stimulus falls on the two retinae that cannot be produced by a real 3D object. For exactly this reason these responses may help solve the correspondence problem. When these neurons are activated, the match at that disparity must be a false match. We were able to develop a very simple algorithm, based on this principle, that could be implemented simply using only model neurons with realistic behavior. We derived a proof that this algorithm always finds the correct match for simple cases in which the disparity is uniform. The algorithm also performed well on real stereo images. This work therefore provides an explanation for the observed nature of disparity coding in visual cortex, and shows how significant computational problems can be solved by interactions between cortical neurons.

National Institute of Health (NIH)
National Eye Institute (NEI)
Intramural Research (Z01)
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U.S. National Eye Institute
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Bredfeldt, C E; Read, J C A; Cumming, B G (2009) A quantitative explanation of responses to disparity-defined edges in macaque V2. J Neurophysiol 101:701-13
Haefner, Ralf M; Cumming, Bruce G (2008) Adaptation to natural binocular disparities in primate V1 explained by a generalized energy model. Neuron 57:147-58
Read, Jenny C A; Cumming, Bruce G (2007) Sensors for impossible stimuli may solve the stereo correspondence problem. Nat Neurosci 10:1322-8
Nienborg, Hendrikje; Cumming, Bruce G (2007) Psychophysically measured task strategy for disparity discrimination is reflected in V2 neurons. Nat Neurosci 10:1608-14
Bredfeldt, Christine E; Cumming, Bruce G (2006) A simple account of cyclopean edge responses in macaque v2. J Neurosci 26:7581-96
Nienborg, Hendrikje; Cumming, Bruce G (2006) Macaque V2 neurons, but not V1 neurons, show choice-related activity. J Neurosci 26:9567-78
Read, Jenny C A; Cumming, Bruce G (2005) Effect of interocular delay on disparity-selective v1 neurons: relationship to stereoacuity and the pulfrich effect. J Neurophysiol 94:1541-53
Read, Jenny C A; Cumming, Bruce G (2005) The stroboscopic Pulfrich effect is not evidence for the joint encoding of motion and depth. J Vis 5:417-34
Read, Jenny (2005) Early computational processing in binocular vision and depth perception. Prog Biophys Mol Biol 87:77-108
Read, Jenny C A; Cumming, Bruce G (2004) Understanding the cortical specialization for horizontal disparity. Neural Comput 16:1983-2020

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