Literature DB >> 22160819

Substitution and pooling in crowding.

Jeremy Freeman1, Ramakrishna Chakravarthi, Denis G Pelli.   

Abstract

Unless we fixate directly on it, it is hard to see an object among other objects. This breakdown in object recognition, called crowding, severely limits peripheral vision. The effect is more severe when objects are more similar. When observers mistake the identity of a target among flanker objects, they often report a flanker. Many have taken these flanker reports as evidence of internal substitution of the target by a flanker. Here, we ask observers to identify a target letter presented in between one similar and one dissimilar flanker letter. Simple substitution takes in only one letter, which is often the target but, by unwitting mistake, is sometimes a flanker. The opposite of substitution is pooling, which takes in more than one letter. Having taken only one letter, the substitution process knows only its identity, not its similarity to the target. Thus, it must report similar and dissimilar flankers equally often. Contrary to this prediction, the similar flanker is reported much more often than the dissimilar flanker, showing that rampant flanker substitution cannot account for most flanker reports. Mixture modeling shows that simple substitution can account for, at most, about half the trials. Pooling and nonpooling (simple substitution) together include all possible models of crowding. When observers are asked to identify a crowded object, at least half of their reports are pooled, based on a combination of information from target and flankers, rather than being based on a single letter.

Entities:  

Mesh:

Year:  2012        PMID: 22160819      PMCID: PMC3283763          DOI: 10.3758/s13414-011-0229-0

Source DB:  PubMed          Journal:  Atten Percept Psychophys        ISSN: 1943-3921            Impact factor:   2.199


  40 in total

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Review 7.  The uncrowded window of object recognition.

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9.  A neurophysiologically plausible population code model for feature integration explains visual crowding.

Authors:  Ronald van den Berg; Jos B T M Roerdink; Frans W Cornelissen
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  23 in total

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2.  Macaque monkeys experience visual crowding.

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Journal:  J Vis       Date:  2015       Impact factor: 2.240

3.  Image correlates of crowding in natural scenes.

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4.  Radial-tangential anisotropy of crowding in the early visual areas.

Authors:  MiYoung Kwon; Pinglei Bao; Rachel Millin; Bosco S Tjan
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5.  Visual crowding cannot be wholly explained by feature pooling.

Authors:  Edward F Ester; Daniel Klee; Edward Awh
Journal:  J Exp Psychol Hum Percept Perform       Date:  2013-12-23       Impact factor: 3.332

6.  Variations in crowding, saccadic precision, and spatial localization reveal the shared topology of spatial vision.

Authors:  John A Greenwood; Martin Szinte; Bilge Sayim; Patrick Cavanagh
Journal:  Proc Natl Acad Sci U S A       Date:  2017-04-10       Impact factor: 11.205

7.  Perceptual and Cognitive Factors Imposing "Speed Limits" on Reading Rate: A Study with the Rapid Serial Visual Presentation.

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8.  A Comparison of Foveal and Peripheral Contour Interaction and Crowding.

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Journal:  Optom Vis Sci       Date:  2021-01-01       Impact factor: 2.106

9.  A New Font, Specifically Designed for Peripheral Vision, Improves Peripheral Letter and Word Recognition, but Not Eye-Mediated Reading Performance.

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Journal:  PLoS One       Date:  2016-04-13       Impact factor: 3.240

10.  Typical magnitude and spatial extent of crowding in autism.

Authors:  Jan Freyberg; Caroline E Robertson; Simon Baron-Cohen
Journal:  J Vis       Date:  2016       Impact factor: 2.240

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