Abstract Details

Title Characterizing Expressive Language Deficit Patterns in Primary Progressive Aphasia using NLP

Topic Aging, Dementia, and Behavioral Neurology

Presentation(s) Behavioral and Cognitive Neurology Posters (7:00 AM-5:00 PM)

Poster/Presentation
Number 010

Objective We aimed to investigate spontaneous production in the three PPA variants and normal controls and to identify linguistic markers that classify the variants, using NLP.

Background Expressive language impairments are frequently described clinical features associated with the three variants of primary progressive aphasia (PPA): nonfluent/agrammatic PPA, logopenic variant PPA, and semantic variant PPA. The limited scope of currently available standardized tasks limits the timely and accurate detection of deficits in the three PPA variants.

Design/Methods

We obtained spontaneous speech samples from 120 participants with PPA, and 25 normal controls. Participants were asked to describe a black and white drawing of a picnic scene while three minutes of speech were recorded, transcribed, and later analyzed for content using NLP. Two types of features are extracted from statistically-tagged transcripts: (1) morpho-syntax knowledge: types of pronouns (e.g., subjective/possessive), verb tenses (e.g., present, past, be + progressive “-ing”), sentence forms (e.g., coordination/subordination), and (2) thematic knowledge: arguments and adjuncts (e.g., the man is flying [a kite]_ARGUMENT [at the beach]_ADJUNCT). To account for variation in lengths of speech produced by participants, these features are divided by total number of non-stop words, evaluated as a metric for classifying three PPA variants using a Support Vector Machine (SVM) classifier.

Results The SVM analyses revealed that the nonfluent/agrammatic patients are classified by the morphosyntactic features with 88% accuracy, and showed reduction in production of verbs, verb tenses and sentence forms. All three PPA variants are classified by the arguments and adjuncts features with over 75% accuracy, with nfvPPA participants producing a lower proportion of arguments compared to adjuncts. No differences in producing arguments and adjuncts were found for logopenic or semantic PPA patients.

Conclusions

Our findings highlight specific expressive language deficit patterns in the three PPA variants using an automated analysis of expressive language.

Authors/Disclosures
Sladjana Lukic, PhD (UCSF) PRESENTER	Dr. Lukic has nothing to disclose.
Zekai Fan	Mr. Fan has nothing to disclose.
	No disclosure on file
Zachary Miller, MD (UCSF Memory and Aging Center)	Dr. Miller has nothing to disclose.
Bruce L. Miller, MD, FAAN (University of California, San Francisco)	Dr. Miller has nothing to disclose.
	No disclosure on file
Maria Luisa Gorno Tempini, MD, PhD (UCSF Memory and Aging Center)	The institution of Dr. Gorno Tempini has received research support from the NIH.

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