Title of article
Subtypes of developmental dyslexia: Testing the predictions of the dual-route and connectionist frameworks
Author/Authors
Peterson، نويسنده , , Robin L. and Pennington، نويسنده , , Bruce F. and Olson، نويسنده , , Richard K.، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2013
Pages
19
From page
20
To page
38
Abstract
We investigated the phonological and surface subtypes of developmental dyslexia in light of competing predictions made by two computational models of single word reading, the Dual-Route Cascaded Model (DRC; Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001) and Harm and Seidenberg’s connectionist model (HS model; Harm & Seidenberg, 1999). The regression-outlier procedure was applied to a large sample to identify children with disproportionately poor phonological coding skills (phonological dyslexia) or disproportionately poor orthographic coding skills (surface dyslexia). Consistent with the predictions of the HS model, children with “pure” phonological dyslexia, who did not have orthographic deficits, had milder phonological impairments than children with “relative” phonological dyslexia, who did have secondary orthographic deficits. In addition, pure cases of dyslexia were more common among older children. Consistent with the predictions of the DRC model, surface dyslexia was not well conceptualized as a reading delay; both phonological and surface dyslexia were associated with patterns of developmental deviance. In addition, some results were problematic for both models. We identified a small number of individuals with severe phonological dyslexia, relatively intact orthographic coding skills, and very poor real word reading. Further, a subset of controls could read normally despite impaired orthographic coding. The findings are discussed in terms of improvements to both models that might help better account for all cases of developmental dyslexia.
Keywords
Reading disability , Phonological dyslexia , Surface dyslexia , Phonological coding , Orthographic coding , computational models
Journal title
Cognition
Serial Year
2013
Journal title
Cognition
Record number
2077579
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