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Abnormal discourse in semantic dementia: a data driven approach

Garrard, Peter and Forsyth, Richard (2009) Abnormal discourse in semantic dementia: a data driven approach Neurocase

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Structural and content-related deficits characterise connected discourse produced by patients with semantic dementia (SD). We used a principal components analysis to identify and characterise the sources of variation in word usage during picture description by healthy controls and SD patients. It was hypothesized that this data-driven approach would yield insights into the relationship between semantic degradation and any higher level structural deficits. Transcripts of Cookie Theft picture descriptions provided by 21 patients with SD and 21 controls were used to generate frequency tables of all word types (n=557) across participants. Frequency values of words with ?10 occurrences (n=81) were entered into a principal components analysis. Values on the emergent dimensions were compared with performance on tests of single word meaning. The first principal component accounted for 59% of the variance, and the second for a further 10%. Patient and control transcripts showed good separation within the resulting space. Factor loading scores indicated that control performance was characterized by function (factor 1) and content (factor 2) word usage, while patients showed a greater tendency to use pronouns, deictic and generic words, and the phrase “I do not know”. Tests of knowledge of single word meaning correlated with factor 1 but not with factor 2. Differences in word usage alone can differentiate passages of connected speech produced by patients with SD from controls using a rapid, automated, data driven algorithm. The distinction between the two groups reflects seemingly independent differences in both structure and lexical content

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Submitted date: April 2009
Accepted/In Press date: April 2009
Keywords: semantic dementia, discourse, principal components analysis


Local EPrints ID: 79961
ISSN: 1355-4794
PURE UUID: 261d73fe-d12a-4959-b719-89050c574146

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Date deposited: 23 Mar 2010
Last modified: 18 Jul 2017 23:15

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Author: Peter Garrard
Author: Richard Forsyth

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