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 Discriminating nonfluent/agrammatic and logopenic PPA variants with automatically extracted morphosyntactic measures from connected speech

 Discriminating nonfluent/agrammatic and logopenic PPA variants with automatically extracted morphosyntactic measures from connected speech - https://www.sciencedirect.com/science/article/pii/S001094522400011X?via%3Dihub

Morphosyntactic assessments are important for characterizing individuals with nonfluent/agrammatic variant <a href="https://www.sciencedirect.com/topics/neuroscience/primary-progressive-aphasia">primary progressive aphasia</a> (nfvPPA). Yet, standard tests are subject to examiner bias and often fail to differentiate between nfvPPA and logopenic variant PPA (lvPPA). Moreover, relevant neural signatures remain underexplored. Here, we leverage <a href="https://www.sciencedirect.com/topics/neuroscience/natural-language-processing">natural language processing</a> tools to automatically capture morphosyntactic disturbances and their neuroanatomical correlates in 35 individuals with nfvPPA relative to 10 healthy controls (HC) and 26 individuals with lvPPA.

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Discriminating nonfluent/agrammatic and logopenic PPA variants with automatically extracted morphosyntactic measures from connected speech