Literature DB >> 11431496

Modeling V1 disparity tuning to time-varying stimuli.

Y Chen1, Y Wang, N Qian.   

Abstract

Most models of disparity selectivity consider only the spatial properties of binocular cells. However, the temporal response is an integral component of real neurons' activities, and time-varying stimuli are often used in the experiments of disparity tuning. To understand the temporal dimension of V1 disparity representation, we incorporate a specific temporal response function into the disparity energy model and demonstrate that the binocular interaction of complex cells is separable into a Gabor disparity function and a positive time function. We then investigate how the model simple and complex cells respond to widely used time-varying stimuli, including motion-in-depth patterns, drifting gratings, moving bars, moving random-dot stereograms, and dynamic random-dot stereograms. It is found that both model simple and complex cells show more reliable disparity tuning to time-varying stimuli than to static stimuli, but similarities in the disparity tuning between simple and complex cells depend on the stimulus. Specifically, the disparity tuning curves of the two cell types are similar to each other for either drifting sinusoidal gratings or moving bars. In contrast, when the stimuli are dynamic random-dot stereograms, the disparity tuning of simple cells is highly variable, whereas the tuning of complex cells remains reliable. Moreover, cells with similar motion preferences in the two eyes cannot be truly tuned to motion in depth regardless of the stimulus types. These simulation results are consistent with a large body of extant physiological data, and provide some specific, testable predictions.

Mesh:

Year:  2001        PMID: 11431496     DOI: 10.1152/jn.2001.86.1.143

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  6 in total

1.  Effect of interocular delay on disparity-selective v1 neurons: relationship to stereoacuity and the pulfrich effect.

Authors:  Jenny C A Read; Bruce G Cumming
Journal:  J Neurophysiol       Date:  2005-03-23       Impact factor: 2.714

2.  Pulfrich phenomena are coded effectively by a joint motion-disparity process.

Authors:  Ning Qian; Ralph D Freeman
Journal:  J Vis       Date:  2009-05-27       Impact factor: 2.240

3.  Neural representation of motion-in-depth in area MT.

Authors:  Takahisa M Sanada; Gregory C DeAngelis
Journal:  J Neurosci       Date:  2014-11-19       Impact factor: 6.167

4.  V1 orientation plasticity is explained by broadly tuned feedforward inputs and intracortical sharpening.

Authors:  Andrew F Teich; Ning Qian
Journal:  Vis Neurosci       Date:  2010-04-16       Impact factor: 3.241

5.  A computational study of how orientation bias in the lateral geniculate nucleus can give rise to orientation selectivity in primary visual cortex.

Authors:  Levin Kuhlmann; Trichur R Vidyasagar
Journal:  Front Syst Neurosci       Date:  2011-10-11

6.  Dynamics of orientation tuning in cat v1 neurons depend on location within layers and orientation maps.

Authors:  James Schummers; Beau Cronin; Klaus Wimmer; Marcel Stimberg; Robert Martin; Klaus Obermayer; Konrad Koerding; Mriganka Sur
Journal:  Front Neurosci       Date:  2007-10-15       Impact factor: 4.677

  6 in total

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