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Computational Modeling of Interventions for Developmental Disorders
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 deve...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Psychological Association
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6776073/ https://www.ncbi.nlm.nih.gov/pubmed/31169397 http://dx.doi.org/10.1037/rev0000151 |
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author | Thomas, Michael S. C. Fedor, Anna Davis, Rachael Yang, Juan Alireza, Hala Charman, Tony Masterson, Jackie Best, Wendy |
author_facet | Thomas, Michael S. C. Fedor, Anna Davis, Rachael Yang, Juan Alireza, Hala Charman, Tony Masterson, Jackie Best, Wendy |
author_sort | Thomas, Michael S. C. |
collection | PubMed |
description | 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 behavioral approaches to intervention. We review an extended program of modeling 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. |
format | Online Article Text |
id | pubmed-6776073 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | American Psychological Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-67760732019-10-15 Computational Modeling of Interventions for Developmental Disorders Thomas, Michael S. C. Fedor, Anna Davis, Rachael Yang, Juan Alireza, Hala Charman, Tony Masterson, Jackie Best, Wendy Psychol Rev Articles 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 behavioral approaches to intervention. We review an extended program of modeling 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. American Psychological Association 2019-06-06 2019-10 /pmc/articles/PMC6776073/ /pubmed/31169397 http://dx.doi.org/10.1037/rev0000151 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by/3.0/ This article has been published under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Copyright for this article is retained by the author(s). Author(s) grant(s) the American Psychological Association the exclusive right to publish the article and identify itself as the original publisher. |
spellingShingle | Articles Thomas, Michael S. C. Fedor, Anna Davis, Rachael Yang, Juan Alireza, Hala Charman, Tony Masterson, Jackie Best, Wendy Computational Modeling of Interventions for Developmental Disorders |
title | Computational Modeling of Interventions for Developmental Disorders |
title_full | Computational Modeling of Interventions for Developmental Disorders |
title_fullStr | Computational Modeling of Interventions for Developmental Disorders |
title_full_unstemmed | Computational Modeling of Interventions for Developmental Disorders |
title_short | Computational Modeling of Interventions for Developmental Disorders |
title_sort | computational modeling of interventions for developmental disorders |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6776073/ https://www.ncbi.nlm.nih.gov/pubmed/31169397 http://dx.doi.org/10.1037/rev0000151 |
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