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    Mechanisms of developmental change in infant categorization

    Westermann, Gert and Mareschal, Denis (2012) Mechanisms of developmental change in infant categorization. Cognitive Development , ISSN 0885-2014.

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    Computational models are tools for testing mechanistic theories of learning and development. Formal models allow us to instantiate theories of cognitive development in computer simulations. Model behavior can then be compared to real performance. Connectionist models, loosely based on neural information processing, have been successful in capturing a range of developmental phenomena, in particular on-line within-task category learning by young infants. Here we describe two new models. One demonstrates how age dependent changes in neural receptive field sizes can explain observed changes in on-line category learning between 3 and 10 months of age. The other aims to reconcile two conflicting views of infant categorization by focusing on the different task requirements of preferential looking and manual exploration studies. A dual-memory hypothesis posits that within-task category learning that drives looking time behaviors is based on a fast-learning memory system, whereas categorization based on background experience and assessed by paradigms requiring complex motor behavior relies on a second, slow-learning system. The models demonstrate how emphasizing the mechanistic causes of behaviors leads to discovery of deeper, more explanatory accounts of learning and development.


    Item Type: Article
    Keyword(s) / Subject(s): Infancy, Categorization, Learning, Development, Mechanism, Connectionist modeling
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Psychological Sciences
    Research Centres and Institutes: Educational Neuroscience, Centre for, Brain and Cognitive Development, Centre for (CBCD)
    Depositing User: Administrator
    Date Deposited: 11 Sep 2012 10:03
    Last Modified: 02 Aug 2023 16:58


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