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    Representation in Cognitive Science

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    Author(s)
    Shea, Nicholas
    Collection
    European Research Council (ERC); EU collection
    Language
    English
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    Abstract
    "Our thoughts are meaningful. We think about things in the outside world; how can that be so? This is one of the deepest questions in contemporary philosophy. Ever since the 'cognitive revolution', states with meaning-mental representations-have been the key explanatory construct of the cognitive sciences. But there is still no widely accepted theory of how mental representations get their meaning. Powerful new methods in cognitive neuroscience can now reveal information processing in the brain in unprecedented detail. They show how the brain performs complex calculations on neural representations. Drawing on this cutting-edge research, Nicholas Shea uses a series of case studies from the cognitive sciences to develop a naturalistic account of the nature of mental representation. His approach is distinctive in focusing firmly on the 'subpersonal' representations that pervade so much of cognitive science. The diversity and depth of the case studies, illustrated by numerous figures, make this book unlike any previous treatment. It is important reading for philosophers of psychology and philosophers of mind, and of considerable interest to researchers throughout the cognitive sciences."
    URI
    http://library.oapen.org/handle/20.500.12657/28350
    Keywords
    contemporary philosophy; cognitive sciences; mental representations; cognitive neuroscience
    DOI
    10.1093/oso/9780198812883.001.0001
    ISBN
    9780198812883
    OCN
    1053888145
    Publisher
    Oxford University Press
    Publisher website
    https://global.oup.com/
    Publication date and place
    Oxford, UK, 2018
    Grantor
    • H2020 European Research Council - 681422 - MetCogCon Research grant informationFind all documents
    Classification
    Cognitive studies
    Pages
    304
    Rights
    http://creativecommons.org/licenses/by-nc-nd/4.0
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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