August 2012
Volume 12, Issue 9
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2012
Reciprocal inhibition between binocular energy-model units can account for the reduced response to disparities in anti-correlated stereograms
Author Affiliations
  • Fredrik Allenmark
    Institute of Neuroscience, Newcastle University
  • Jenny Read
    Institute of Neuroscience, Newcastle University
Journal of Vision August 2012, Vol.12, 46. doi:https://doi.org/10.1167/12.9.46
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      Fredrik Allenmark, Jenny Read; Reciprocal inhibition between binocular energy-model units can account for the reduced response to disparities in anti-correlated stereograms. Journal of Vision 2012;12(9):46. https://doi.org/10.1167/12.9.46.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract
 

Our 3D stereo depth perception depends on disparities between the two eyes’ images, arising from their different views on the world. This process is believed to begin in primary visual cortex, V1, where many neurons are tuned for binocular disparity. Their response is well described by the binocular energy model (Ohzawa et al. 1990, Science 249:1037). Because the energy model effectively implements cross-correlation of the left and right eye images, it makes a specific prediction about what happens when one eye’s image is polarity-inverted, i.e. replaced with its photographic negative, so that black pixels become white and vice versa. For these anti-correlated stimuli, the energy model predicts that the disparity tuning should simply invert; i.e. the disparity tuning curve should undergo a phase change of π with no change in amplitude. In fact, although disparity tuning curves of real V1 do usually invert for anti-correlated stimuli, they are also reduced in amplitude (Cumming & Parker 1997, Nature 389:280). Several modifications to the energy model have been put forward to account for this (Read et al. 2002, Vis Neurosci 19:735; Lippert & Wagner 2001, Neuroreport 12:3205; Haefner & Cumming 2008, Neuron 57:147). However, recent evidence suggests that none of these models is sufficient on its own (Tanabe et al. 2011, J Neurosci 31:8295). Rather, the latest evidence points to reciprocal connections between V1 neurons with different disparity tuning. Here, we present our first attempts to build a quantitative model along these lines which can account for the dynamics of the physiology data.

 

Meeting abstract presented at VSS 2012

 
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