Literature DB >> 28545983

Feedback from higher to lower visual areas for visual recognition may be weaker in the periphery: Glimpses from the perception of brief dichoptic stimuli.

Li Zhaoping1.   

Abstract

Eye movements bring attended visual inputs to the center of vision for further processing. Thus, central and peripheral vision should have different functional roles. Here, we use observations of visual perception under dichoptic stimuli to infer that there is a difference in the top-down feedback from higher brain centers to primary visual cortex. Visual stimuli to the two eyes were designed such that the sum and difference of the binocular input from the two eyes have the form of two different gratings. These gratings differed in their motion direction, tilt direction, or color, and duly evoked ambiguous percepts for the corresponding feature. Observers were more likely to perceive the feature in the binocular summation rather than the difference channel. However, this perceptual bias towards the binocular summation signal was weaker or absent in peripheral vision, even when central and peripheral vision showed no difference in contrast sensitivity to the binocular summation signal relative to that to the binocular difference signal. We propose that this bias can arise from top-down feedback as part of an analysis-by-synthesis computation. The feedback is of the input predicted using prior information by the upper level perceptual hypothesis about the visual scene; the hypothesis is verified by comparing the feedback with the actual visual input. We illustrate this process using a conceptual circuit model. In this framework, a bias towards binocular summation can arise from the prior knowledge that inputs are usually correlated between the two eyes. Accordingly, a weaker bias in the periphery implies that the top-down feedback is weaker there. Testable experimental predictions are presented and discussed.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Analysis-by-synthesis; Central vision; Dichoptic stimuli; Peripheral vision; Primary visual cortex (V1); Top-down feedback; Visual decoding

Mesh:

Year:  2017        PMID: 28545983     DOI: 10.1016/j.visres.2017.05.002

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  10 in total

1.  Central-peripheral dichotomy: color-motion and luminance-motion binding show stronger top-down feedback in central vision.

Authors:  Keyan Bi; Yifei Zhang; Yan-Yu Zhang
Journal:  Atten Percept Psychophys       Date:  2022-03-18       Impact factor: 2.199

2.  Mechanisms for shaping receptive field in monkey area TE.

Authors:  Keitaro Obara; Kazunori O'Hashi; Manabu Tanifuji
Journal:  J Neurophysiol       Date:  2017-08-02       Impact factor: 2.714

3.  Seeing fruit on trees: enhanced perceptual dissimilarity from multiple ambiguous neural representations.

Authors:  Jaelyn R Peiso; Steven K Shevell
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2020-04-01       Impact factor: 2.129

4.  Conflict-sensitive neurons gate interocular suppression in human visual cortex.

Authors:  Sucharit Katyal; Mark Vergeer; Sheng He; Bin He; Stephen A Engel
Journal:  Sci Rep       Date:  2018-01-19       Impact factor: 4.379

5.  Ocularity Feature Contrast Attracts Attention Exogenously.

Authors:  Li Zhaoping
Journal:  Vision (Basel)       Date:  2018-02-24

6.  Late disruption of central visual field disrupts peripheral perception of form and color.

Authors:  Kimberly B Weldon; Alexandra Woolgar; Anina N Rich; Mark A Williams
Journal:  PLoS One       Date:  2020-01-30       Impact factor: 3.240

7.  The central-peripheral dichotomy and metacontrast masking.

Authors:  Li Zhaoping; Yushi Liu
Journal:  Perception       Date:  2022-07-18       Impact factor: 1.695

8.  Robust natural depth for anticorrelated random dot stereogram for edge stimuli, but minimal reversed depth for embedded circular stimuli, irrespective of eccentricity.

Authors:  Paul B Hibbard; Jordi M Asher
Journal:  PLoS One       Date:  2022-09-22       Impact factor: 3.752

9.  Object detection through search with a foveated visual system.

Authors:  Emre Akbas; Miguel P Eckstein
Journal:  PLoS Comput Biol       Date:  2017-10-09       Impact factor: 4.475

Review 10.  A review of interactions between peripheral and foveal vision.

Authors:  Emma E M Stewart; Matteo Valsecchi; Alexander C Schütz
Journal:  J Vis       Date:  2020-11-02       Impact factor: 2.240

  10 in total

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