Filling-in and suppression of visual perception from context: a Bayesian account of perceptual biases by contextual influences.

Visual object recognition and sensitivity to image features are largely influenced by contextual inputs. We study influences by contextual bars on the bias to perceive or infer the presence of a target bar, rather than on the sensitivity to image features. Human observers judged from a briefly prese...

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Main Authors: Li Zhaoping, Li Jingling
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2008-02-01
Series:PLoS Computational Biology
Online Access:https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.0040014&type=printable
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author Li Zhaoping
Li Jingling
author_facet Li Zhaoping
Li Jingling
author_sort Li Zhaoping
collection DOAJ
description Visual object recognition and sensitivity to image features are largely influenced by contextual inputs. We study influences by contextual bars on the bias to perceive or infer the presence of a target bar, rather than on the sensitivity to image features. Human observers judged from a briefly presented stimulus whether a target bar of a known orientation and shape is present at the center of a display, given a weak or missing input contrast at the target location with or without a context of other bars. Observers are more likely to perceive a target when the context has a weaker rather than stronger contrast. When the context can perceptually group well with the would-be target, weak contrast contextual bars bias the observers to perceive a target relative to the condition without contexts, as if to fill in the target. Meanwhile, high-contrast contextual bars, regardless of whether they group well with the target, bias the observers to perceive no target. A Bayesian model of visual inference is shown to account for the data well, illustrating that the context influences the perception in two ways: (1) biasing observers' prior belief that a target should be present according to visual grouping principles, and (2) biasing observers' internal model of the likely input contrasts caused by a target bar. According to this model, our data suggest that the context does not influence the perceived target contrast despite its influence on the bias to perceive the target's presence, thereby suggesting that cortical areas beyond the primary visual cortex are responsible for the visual inferences.
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spelling doaj-art-25680145c64b405cab7288fbd856fd6c2025-08-20T02:02:44ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582008-02-0142e1410.1371/journal.pcbi.0040014Filling-in and suppression of visual perception from context: a Bayesian account of perceptual biases by contextual influences.Li ZhaopingLi JinglingVisual object recognition and sensitivity to image features are largely influenced by contextual inputs. We study influences by contextual bars on the bias to perceive or infer the presence of a target bar, rather than on the sensitivity to image features. Human observers judged from a briefly presented stimulus whether a target bar of a known orientation and shape is present at the center of a display, given a weak or missing input contrast at the target location with or without a context of other bars. Observers are more likely to perceive a target when the context has a weaker rather than stronger contrast. When the context can perceptually group well with the would-be target, weak contrast contextual bars bias the observers to perceive a target relative to the condition without contexts, as if to fill in the target. Meanwhile, high-contrast contextual bars, regardless of whether they group well with the target, bias the observers to perceive no target. A Bayesian model of visual inference is shown to account for the data well, illustrating that the context influences the perception in two ways: (1) biasing observers' prior belief that a target should be present according to visual grouping principles, and (2) biasing observers' internal model of the likely input contrasts caused by a target bar. According to this model, our data suggest that the context does not influence the perceived target contrast despite its influence on the bias to perceive the target's presence, thereby suggesting that cortical areas beyond the primary visual cortex are responsible for the visual inferences.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.0040014&type=printable
spellingShingle Li Zhaoping
Li Jingling
Filling-in and suppression of visual perception from context: a Bayesian account of perceptual biases by contextual influences.
PLoS Computational Biology
title Filling-in and suppression of visual perception from context: a Bayesian account of perceptual biases by contextual influences.
title_full Filling-in and suppression of visual perception from context: a Bayesian account of perceptual biases by contextual influences.
title_fullStr Filling-in and suppression of visual perception from context: a Bayesian account of perceptual biases by contextual influences.
title_full_unstemmed Filling-in and suppression of visual perception from context: a Bayesian account of perceptual biases by contextual influences.
title_short Filling-in and suppression of visual perception from context: a Bayesian account of perceptual biases by contextual influences.
title_sort filling in and suppression of visual perception from context a bayesian account of perceptual biases by contextual influences
url https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.0040014&type=printable
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