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A simple model accounts for the response of disparity-tuned V1 neurons to anticorrelated images

  • JENNY C.A. READ (a1) (a2), ANDREW J. PARKER (a1) and BRUCE G. CUMMING (a1) (a2)

Disparity-tuned cells in primary visual cortex (V1) are thought to play a significant role in the processing of stereoscopic depth. The disparity-specific responses of these neurons have been previously described by an energy model based on local, feedforward interactions. This model fails to predict the response to binocularly anticorrelated stimuli, in which images presented to left and right eyes have opposite contrasts. The original energy model predicts that anticorrelation should invert the disparity tuning curve (phase difference π), with no change in the amplitude of the response. Experimentally, the amplitude tends to be reduced with anticorrelated stimuli and a spread of phase differences is observed, although phase differences near π are the most common. These experimental observations could potentially reflect a modulation of the V1 signals by feedback from higher visual areas (because anticorrelated stimuli create a weaker or nonexistent stereoscopic depth sensation). This hypothesis could explain the effects on amplitude, but the spread of phase differences is harder to understand. Here, we demonstrate that changes in both amplitude and phase can be explained by a straightforward modification of the energy model that involves only local processing. Input from each eye is passed through a monocular simple cell, incorporating a threshold, before being combined at a binocular simple cell that feeds into the energy computation. Since this local feedforward model can explain the responses of complex cells to both correlated and anticorrelated stimuli, there is no need to invoke any influence of global stereoscopic matching.

Corresponding author
Address correspondence and reprint requests to: Jenny C.A. Read, Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, 49 Convent Drive, Bethesda, MD 20892-4435, USA.
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Visual Neuroscience
  • ISSN: 0952-5238
  • EISSN: 1469-8714
  • URL: /core/journals/visual-neuroscience
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