ArticleCortex; a journal devoted to the study of the nervous system and behavior2024
Discriminating nonfluent/agrammatic and logopenic PPA variants with automatically extracted morphosyntactic measures from connected speech.
Article in Cortex; a journal devoted to the study of the nervous system and behavior, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 12 citations in OpenAlex.
- The Effects of Personalized Observation, Execution, and Mental Imagery (POEM) Therapy in Logopenic Primary Progressive Aphasia: A Telepractice-Based Single-Case Study.Brain sciences · 2026Article
- Speech-based digital biomarkers for early etiological stratification of Alzheimer's disease and frontotemporal degeneration: a biomarker-confirmed prospective study.The journal of prevention of Alzheimer's disease · 2026Article
- Digital language measures capture episodic memory disruptions in people with human immunodeficiency virus: A machine learning study.The Clinical neuropsychologist · 2026Article
- The Production of Clitics in Serbian Speakers with Stroke Aphasia.Brain sciences · 2026Article
- Identifying neuropathologic disease in primary progressive aphasia using narrative speech.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Review of Artificial Intelligence for Clinical Use in Alzheimer's Disease and Related Dementias.Seminars in neurology · 2026Review
- Written picture descriptions distinguish variants of primary progressive aphasia.Journal of Alzheimer's disease : JAD · 2025Article
- Picture Description and Functional Communication Rating Correlates in Variants of Primary Progressive Aphasia.Aphasiology · 2025Article
- Distinct neural correlates of morphosyntactic and thematic comprehension processes in aphasia.Brain communications · 2025Article
- Automated analysis of expressive prosody in Dutch patients with behavioral variant frontotemporal dementia and primary progressive aphasia.Alzheimer's & dementia (Amsterdam, Netherlands)Article
- Automated differentiation of non-fluent and logopenic primary progressive aphasia in Italian speakers using acoustic and linguistic speech measures.Alzheimer's & dementia (Amsterdam, Netherlands)Article
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Authors and funding
13 authors at 6 institutions in 4 countries.
Funding
Abstract
Morphosyntactic assessments are important for characterizing individuals with nonfluent/agrammatic variant primary progressive aphasia (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 natural language processing 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. Participants described a picture, and ensuing transcripts were analyzed via part-of-speech tagging to extract sentence-related features (e.g., subordinating and coordinating conjunctions), verbal-related features (e.g., tense markers), and nominal-related features (e.g., subjective and possessive pronouns). Gradient boosting machines were used to classify between groups using all features. We identified the most discriminant morphosyntactic marker via a feature importance algorithm and examined its neural correlates via voxel-based morphometry. Individuals with nfvPPA produced fewer morphosyntactic elements than the other two groups. Such features robustly discriminated them from both individuals with lvPPA and HCs with an AUC of .95 and .82, respectively. The most discriminatory feature corresponded to subordinating conjunctions was correlated with cortical atrophy within the left posterior inferior frontal gyrus across groups (p
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.