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Autor/inn/enDell, Gary S.; Martin, Nadine; Schwartz, Myrna F.
TitelA Case-Series Test of the Interactive Two-Step Model of Lexical Access: Predicting Word Repetition from Picture Naming
QuelleIn: Journal of Memory and Language, 56 (2007) 4, S.490-520 (31 Seiten)
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0749-596X
DOI10.1016/j.jml.2006.05.007
SchlagwörterAphasia; Word Recognition; Phonology; Prediction; Error Analysis (Language); Models; Language Research; Pictorial Stimuli
AbstractLexical access in language production, and particularly pathologies of lexical access, are often investigated by examining errors in picture naming and word repetition. In this article, we test a computational approach to lexical access, the two-step interactive model, by examining whether the model can quantitatively predict the repetition-error patterns of 65 aphasic subjects from their naming errors. The model's characterizations of the subjects' naming errors were taken from the companion paper to this one (Schwartz, M. F., Dell, G. S., Martin, N., Gahl, S., & Sobel, P. (2006). A case-series test of the interactive two-step model of lexical access: evidence from picture naming. "Journal of Memory and Language, 54," 228-264), and their repetition was predicted from the model on the assumption that naming involves two error prone steps, word and phonological retrieval, whereas repetition only creates errors in the second of these steps. A version of the model in which lexical-semantic and lexical-phonological connections could be independently lesioned was generally successful in predicting repetition for the aphasics. An analysis of the few cases in which model predictions were inaccurate revealed the role of input phonology in the repetition task. (Author).
AnmerkungenElsevier. 6277 Sea Harbor Drive, Orlando, FL 32887-4800. Tel: 877-839-7126; Tel: 407-345-4020; Fax: 407-363-1354; e-mail: usjcs@elsevier.com; Web site: http://www.elsevier.com
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2017/4/10
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