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Neural model of disinhibitory interactions in the modified Poggendorff illusion.

Neural model of disinhibitory interactions in the modified Poggendorff illusion. Research Abstract Details 

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  • Neural model of disinhibitory interactions in the modified Poggendorff illusion. Abstract Text:

    yingwei yuYingwei Yu,yoonsuck choeYoonsuck Choe,

    Visual illusions can be strengthened or weakened with the addition of extra visual elements. For example, in the Poggendorff illusion, with an additional bar added, the illusory skew in the perceived angle can be enlarged or reduced. In this paper, we show that a nontrivial interaction between lateral inhibitory processes in the early visual system (i.e., disinhibition) can explain such an enhancement or degradation of the illusory effect. The computational model we derived successfully predicted the perceived angle in the Poggendorff illusion task that was modified to include an extra thick bar. The concept of disinhibition employed in the model is general enough that we expect it can be further extended to account for other classes of geometric illusions.

    Neural model of disinhibitory interactions in the modified Poggendorff illusion. Publishing Authors By Initials

    y yuY Yu,y choeY Choe,

    For similar abstracts research abstracts see: abstracts research

    PUBMED ID PMID:

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    Neural model of disinhibitory interactions in the modified Poggendorff illusion. Journal Published:

    PUBLICATION TYPE: Journal Article

    Journal: Biological cybernetics

    VOLUME: 98

    Page Numbers: 75-85

    Journal Abbreviation:

    ISSN: 0340-1200

    DAY: 24

    MONTH: 11

    YEAR: 2007

    Neural model of disinhibitory interactions in the modified Poggendorff illusion. Information

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    LANGUAGE: eng

    NlmUniqueID: 7502533

    Neural model of disinhibitory interactions in the modified Poggendorff illusion. Keywords Mesh Terms:

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    Grant and Affiliation Information for Neural model of disinhibitory interactions in the modified Poggendorff illusion.

    AFFILIATION: Department of Computer Science, Texas A&M University, College Station, TX, 77843-3112, USA, choe@tamu.edu.

    Country: Germany

    Germany Research PublicationGermany Research Publication

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    MEDLINETA: Biol Cybern

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