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What kind of empirical evidence is needed for probabilistic mental representations? An example from visual perception.

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Title: What kind of empirical evidence is needed for probabilistic mental representations? An example from visual perception.
Authors: Tanrıkulu, Ömer Dağlar1 (AUTHOR) daglar83@gmail.com, Chetverikov, Andrey1,2,3 (AUTHOR), Hansmann-Roth, Sabrina1 (AUTHOR), Kristjánsson, Árni1,4 (AUTHOR)
Source: Cognition. Dec2021, Vol. 217, pN.PAG-N.PAG. 1p.
Subject Terms: *Visual perception, *Cognition, *Cognitive science, *Research, *Research methodology, *Evaluation research, *Comparative studies, Mental representation, Distribution (Probability theory), Medical cooperation, Vision, Probability theory
Abstract: Recent accounts of perception and cognition propose that the brain represents information probabilistically. While this assumption is common, empirical support for such probabilistic representations in perception has recently been criticized. Here, we evaluate these criticisms and present an account based on a recently developed psychophysical methodology, Feature Distribution Learning (FDL), which provides promising evidence for probabilistic representations by avoiding these criticisms. The method uses priming and role-reversal effects in visual search. Observers' search times reveal the structure of perceptual representations, in which the probability distribution of distractor features is encoded. We explain how FDL results provide evidence for a stronger notion of representation that relies on structural correspondence between stimulus uncertainty and perceptual representations, rather than a mere co-variation between the two. Moreover, such an account allows us to demonstrate what kind of empirical evidence is needed to support probabilistic representations as posited in current probabilistic Bayesian theories of perception. [ABSTRACT FROM AUTHOR]
Copyright of Cognition is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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DbLabel: Education Research Complete
An: 152846709
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PubTypeId: academicJournal
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  Data: What kind of empirical evidence is needed for probabilistic mental representations? An example from visual perception.
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  Data: Recent accounts of perception and cognition propose that the brain represents information probabilistically. While this assumption is common, empirical support for such probabilistic representations in perception has recently been criticized. Here, we evaluate these criticisms and present an account based on a recently developed psychophysical methodology, Feature Distribution Learning (FDL), which provides promising evidence for probabilistic representations by avoiding these criticisms. The method uses priming and role-reversal effects in visual search. Observers' search times reveal the structure of perceptual representations, in which the probability distribution of distractor features is encoded. We explain how FDL results provide evidence for a stronger notion of representation that relies on structural correspondence between stimulus uncertainty and perceptual representations, rather than a mere co-variation between the two. Moreover, such an account allows us to demonstrate what kind of empirical evidence is needed to support probabilistic representations as posited in current probabilistic Bayesian theories of perception. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Cognition is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.cognition.2021.104903
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      – Code: eng
        Text: English
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        Type: general
      – SubjectFull: Cognition
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      – SubjectFull: Cognitive science
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      – SubjectFull: Evaluation research
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      – SubjectFull: Comparative studies
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      – SubjectFull: Mental representation
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      – SubjectFull: Distribution (Probability theory)
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      – SubjectFull: Medical cooperation
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      – SubjectFull: Vision
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      – SubjectFull: Probability theory
        Type: general
    Titles:
      – TitleFull: What kind of empirical evidence is needed for probabilistic mental representations? An example from visual perception.
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          Name:
            NameFull: Tanrıkulu, Ömer Dağlar
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            NameFull: Chetverikov, Andrey
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            NameFull: Hansmann-Roth, Sabrina
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            NameFull: Kristjánsson, Árni
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            – D: 01
              M: 12
              Text: Dec2021
              Type: published
              Y: 2021
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              Value: 217
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