Literature DB >> 8888610

Binocular receptive field models, disparity tuning, and characteristic disparity.

Y D Zhu1, N Qian.   

Abstract

Disparity tuning of visual cells in the brain depends on the structure of their binocular receptive fields (RFs). Freeman and coworkers have found that binocular RFs of a typical simple cell can be quantitatively described by two Gabor functions with the same gaussian envelope but different phase parameters in the sinusoidal modulations (Freeman and Ohzawa 1990). This phase-parameter-based RF description has recently been questioned by Wagner and Frost (1993) based on their identification of a so-called characteristic disparity (CD) in some cells' disparity tuning curves. They concluded that their data favor the traditional binocular RF model, which assumes on overall positional shift between a cell's left and right RFs. Here we set to resolve this issue by studying the dependence of cells' disparity tuning on their underlying RF structures through mathematical analyses and computer simulations. We model the disparity tuning curves in Wagner and Frost's experiments and demonstrate that the mere existence of approximate CDs in real cells cannot be used to distinguish the phase-parameter-based RF description from the traditional position-shift-based RF description. Specifically, we found that model simple cells with either type RF description do not have a CD. Model complex cells with the position-shift-based RF description have a precise CD, and those with the phase-parameter-based RF description have an approximate CD. We also suggest methods for correctly distinguishing the two types of RF descriptions. A hybrid of the two RF models may be required to fit the behavior of some real cells, and we show how to determine the relative contributions of the two RF models.

Entities:  

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Year:  1996        PMID: 8888610     DOI: 10.1162/neco.1996.8.8.1611

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  10 in total

1.  The subregion correspondence model of binocular simple cells.

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4.  Neural mechanisms underlying binocular fusion and stereopsis: position vs. phase.

Authors:  A Anzai; I Ohzawa; R D Freeman
Journal:  Proc Natl Acad Sci U S A       Date:  1997-05-13       Impact factor: 11.205

5.  Solving stereo transparency with an extended coarse-to-fine disparity energy model.

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Review 6.  Disparity processing in primary visual cortex.

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Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2016-06-19       Impact factor: 6.237

7.  Orientation-specific computation in stereoscopic vision.

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8.  Understanding the cortical specialization for horizontal disparity.

Authors:  Jenny C A Read; Bruce G Cumming
Journal:  Neural Comput       Date:  2004-10       Impact factor: 2.026

9.  From disparity to depth: how to make a grating and a plaid appear in the same depth plane.

Authors:  Yu-Chin Chai; Bart Farell
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10.  Event-driven proto-object based saliency in 3D space to attract a robot's attention.

Authors:  Suman Ghosh; Giulia D'Angelo; Arren Glover; Massimiliano Iacono; Ernst Niebur; Chiara Bartolozzi
Journal:  Sci Rep       Date:  2022-05-10       Impact factor: 4.996

  10 in total

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