Literature DB >> 14598624

Are developmental disorders like cases of adult brain damage? Implications from connectionist modelling.

Michael Thomas1, Annette Karmiloff-Smith.   

Abstract

It is often assumed that similar domain-specific behavioural impairments found in cases of adult brain damage and developmental disorders correspond to similar underlying causes, and can serve as convergent evidence for the modular structure of the normal adult cognitive system. We argue that this correspondence is contingent on an unsupported assumption that atypical development can produce selective deficits while the rest of the system develops normally (Residual Normality), and that this assumption tends to bias data collection in the field. Based on a review of connectionist models of acquired and developmental disorders in the domains of reading and past tense, as well as on new simulations, we explore the computational viability of Residual Normality and the potential role of development in producing behavioural deficits. Simulations demonstrate that damage to a developmental model can produce very different effects depending on whether it occurs prior to or following the training process. Because developmental disorders typically involve damage prior to learning, we conclude that the developmental process is a key component of the explanation of endstate impairments in such disorders. Further simulations demonstrate that in simple connectionist learning systems, the assumption of Residual Normality is undermined by processes of compensation or alteration elsewhere in the system. We outline the precise computational conditions required for Residual Normality to hold in development, and suggest that in many cases it is an unlikely hypothesis. We conclude that in developmental disorders, inferences from behavioural deficits to underlying structure crucially depend on developmental conditions, and that the process of ontogenetic development cannot be ignored in constructing models of developmental disorders.

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Year:  2002        PMID: 14598624     DOI: 10.1017/s0140525x02000134

Source DB:  PubMed          Journal:  Behav Brain Sci        ISSN: 0140-525X            Impact factor:   12.579


  38 in total

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3.  Exploring the impact of plasticity-related recovery after brain damage in a connectionist model of single-word reading.

Authors:  Stephen R Welbourne; Matthew A Lambon Ralph
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Authors:  Gary S Dell; Franklin Chang
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2013-12-09       Impact factor: 6.237

5.  To Model or Not to Model? A Dialogue on the Role of Computational Modeling in Developmental Science.

Authors:  Vanessa R Simmering; Jochen Triesch; Gedeon O Deák; John P Spencer
Journal:  Child Dev Perspect       Date:  2010-08

6.  Computational modeling of interventions for developmental disorders.

Authors:  Michael S C Thomas; Anna Fedor; Rachael Davis; Juan Yang; Hala Alireza; Tony Charman; Jackie Masterson; Wendy Best
Journal:  Psychol Rev       Date:  2019-06-06       Impact factor: 8.934

7.  Developmental prosopagnosics have widespread selectivity reductions across category-selective visual cortex.

Authors:  Guo Jiahui; Hua Yang; Bradley Duchaine
Journal:  Proc Natl Acad Sci U S A       Date:  2018-06-25       Impact factor: 11.205

Review 8.  From loci to networks and back again: anomalies in the study of autism.

Authors:  Ralph-Axel Müller
Journal:  Ann N Y Acad Sci       Date:  2008-12       Impact factor: 5.691

9.  Age-related brain structural alterations in children with specific language impairment.

Authors:  Carles Soriano-Mas; Jesús Pujol; Héctor Ortiz; Joan Deus; Anna López-Sala; Anna Sans
Journal:  Hum Brain Mapp       Date:  2009-05       Impact factor: 5.038

10.  Brain classification reveals the right cerebellum as the best biomarker of dyslexia.

Authors:  Cyril R Pernet; Jean Baptiste Poline; Jean François Demonet; Guillaume A Rousselet
Journal:  BMC Neurosci       Date:  2009-06-25       Impact factor: 3.288

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