Application of the dual stream model to neurodegenerative disease: evidence from a multivariate classification tool in primary progressive aphasia. Issue 5 (4th May 2022)

• Record Type: Journal Article
• Authors: Keator, Lynsey M.; Yourganov, Grigori; Faria, Andreia V.; Hillis, Argye E.; Tippett, Donna C.
• Is Part Of: Aphasiology. Volume 36:Issue 5(2022)
• Page Start: 618
• Page End: 647
• Publication Date: 2022-05-04
• Subjects: (6): primary progressive aphasia -- dual stream -- atrophy -- diffusion tensor imaging (DTI) -- automated multivariate classification -- support vector machines (SVM) -- PPAprimary progressive aphasia -- lvPPA -- logopenic variant PPA -- nfaPPA -- nonfluent/agrammatic variant PPA -- svPPA -- semantic variant PPA -- roi -- region of interest -- wm -- white matter; Aphasia -- Periodicals; Aphasia; 616.8552
• DOI: 10.1080/02687038.2021.1897079
• Languages: English
• ISSNs: 0268-7038

Abstract

ABSTRACT: Background: A clinical diagnosis of primary progressive aphasia relies on behavioral characteristics and patterns of atrophy to determine a variant: logopenic; nonfluent/agrammatic; or semantic. The dual stream model is a contemporary paradigm that has been applied widely to understand brain-behavior relationships; however, applications to neurodegenerative diseases like primary progressive aphasia are limited. Aims: The primary aim of this study is to determine if the dual stream model can be applied to a neurodegenerative disease, such as primary progressive aphasia, using both behavioral and neuroimaging data. Methods & Procedures: We analyzed behavioral and neuroimaging data to apply a multivariate classification tool (support vector machines) to determine if the dual stream model extends to primary progressive aphasia. Sixty-four individuals with primary progressive aphasia were enrolled (26 logopenic variant, 20 nonfluent/agrammatic variant, and 18 semantic variant) and administered four behavioral tasks to assess three linguistic domains (naming, repetition, and semantic knowledge). We used regions of interest from the dual stream model and calculated the cortical volume for gray matter regions and white matter structural volumes and fractional anisotropy. We applied a multivariate classification tool (support vector machines) to distinguish variants based on behavioral performance and patterns of atrophy. Outcomes & Results: Behavioral performance discriminates logopenic from semantic variant and nonfluent/agrammatic from semantic variant. Cortical volume distinguishes all three variants. White matter structural volumes and fractional anisotropy primarily distinguish nonfluent/agrammatic from semantic variant. Regions of interest that contribute to each classification in cortical and white matter analyses demonstrate alignment of logopenic and nonfluent/agrammatic variants to the dorsal stream, while the semantic variant aligns with the ventral stream. Conclusions: A novel implementation of an automated multivariate classification suggests that the dual stream model can be extended to primary progressive aphasia. Variants are distinguished by behavioral and neuroanatomical patterns and align to the dorsal and ventral streams of the dual stream model. Application of the dual stream model to PPA