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    Computational modelling of interventions for developmental disorders

    Thomas, Michael S.C. and Fedor, Anna and Davis, Rachael and Yang, Juan and Alireza, Hala and Charman, T. and Masterson, J. and Best, W. (2019) Computational modelling of interventions for developmental disorders. Psychological Review 126 (5), pp. 693-726. ISSN 0033-295X.

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    Abstract

    We evaluate the potential of connectionist models of developmental disorders to offer insights into the efficacy of interventions. Based on a range of computational simulation results, we assess factors that influence the effectiveness of interventions for reading, language, and other cognitive developmental disorders. The analysis provides a level of mechanistic detail that is generally lacking in behavioural approaches to intervention. We review an extended programme of modelling work in four sections. In the first, we consider long-term outcomes and the possibility of compensated outcomes and resolution of early delays. In the second section, we address methods to remediate atypical development in a single network. In the third section, we address interventions to encourage compensation via alternative pathways. In the final section, we consider the key issue of individual differences in response to intervention. Together with advances in understanding the neural basis of developmental disorders and neural responses to training, formal computational approaches can spur theoretical progress to narrow the gap between the theory and practice of intervention.

    Metadata

    Item Type: Article
    Additional Information: ©American Psychological Association 2019. This paper is not the copy of record and may not exactly replicate the authoritative document published in the APA journal. Please do not copy or cite without author's permission. The final article is available, upon publication, at the DOI cited above.
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Psychological Sciences
    Research Centres and Institutes: Educational Neuroscience, Centre for
    Depositing User: Michael Thomas
    Date Deposited: 18 Mar 2019 10:08
    Last Modified: 02 Aug 2023 17:49
    URI: https://eprints.bbk.ac.uk/id/eprint/26689

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