The use of spelling for variant classification in primary progressive aphasia: Theoretical and practical implications. (October 2019)

• Record Type: Journal Article
• Authors: Neophytou, Kyriaki; Wiley, Robert W.; Rapp, Brenda; Tsapkini, Kyrana
• Is Part Of: Neuropsychologia. Volume 133(2019)
• Publication Date: 2019-10
• Subjects: Primary progressive aphasia -- Spelling -- Variant classification -- Language -- Semantic variant -- Non-fluent variant -- Logopenic variant; Neuropsychology -- Periodicals; Neurology -- Periodicals; Psychophysiology -- Periodicals; Neuropsychologie -- Périodiques; Neuropsychology; Periodicals; Electronic journals; 616.8
• DOI: 10.1016/j.neuropsychologia.2019.107157
• Languages: English
• ISSNs: 0028-3932

Abstract

Abstract: Currently, variant subtyping in primary progressive aphasia (PPA) requires an expert neurologist and extensive language and cognitive testing. Spelling impairments appear early in the development of the disorder, and the three PPA variants (non-fluent - nfvPPA; semantic - svPPA; logopenic - lvPPA) reportedly show fairly distinct spelling profiles. Given the theoretical and empirical evidence indicating that spelling may serve as a proxy for spoken language, the current study aimed to determine whether spelling performance alone, when evaluated with advanced statistical analyses, allows for accurate PPA variant classification. A spelling to dictation task (with real words and pseudowords) was administered to 33 PPA individuals: 17 lvPPA, 10 nfvPPA, 6 svPPA. Using machine learning classification algorithms, we obtained pairwise variant classification accuracies that ranged between 67 and 100%. In additional analyses that assumed no prior knowledge of each case's variant, classification accuracies ranged between 59 and 70%. To our knowledge, this is the first time that all the PPA variants, including the most challenging logopenic variant, have been classified with such high accuracy when using information from a single language task. These results underscore the rich structure of the spelling process and support the use of a spelling task in PPA variant classification. Highlights: Spelling performance allows for high PPA variant classification accuracies. PPA variant classification using spelling is theoretically and empirically driven. Error types, lexical, sublexical and semantic variables distinguish PPA variants. Spelling can be used for developing a simpler PPA variant classification tool.