ArticleCortex; a journal devoted to the study of the nervous system and behavior2020
From discourse to pathology: Automatic identification of Parkinson's disease patients via morphological measures across three languages.
Article in Cortex; a journal devoted to the study of the nervous system and behavior, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Review: Genetic, Neuroimaging, and Fluids Biomarkers for Frontotemporal Dementia Across Latin America Countries.Frontiers in neurology · 2021Pooled it
- Speech and language outcome measures in clinical trials of Alzheimer's and Parkinson's diseases.Expert review of neurotherapeutics · 2026Review
- Digital phenotyping of Parkinson's disease via natural language processing.NPJ Parkinson's disease · 2025Article
- Dynamics of language grounding: on the time course, durability, adaptability, and vulnerability of embodied effects.Frontiers in psychology · 2025Review
- Motor symptoms of Parkinson's disease: critical markers for early AI-assisted diagnosis.Frontiers in aging neuroscience · 2025Review
- Automatic classification of AD pathology in FTD phenotypes using natural speech.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Discriminating nonfluent/agrammatic and logopenic PPA variants with automatically extracted morphosyntactic measures from connected speech.Cortex; a journal devoted to the study of the nervous system and behavior · 2024Article
- Unveiling the Diagnostic Potential of Linguistic Markers in Identifying Individuals with Parkinson's Disease through Artificial Intelligence: A Systematic Review.Brain sciences · 2024Review
- A bibliometric analysis of speech and language impairments in Parkinson's disease based on Web of Science.Frontiers in psychology · 2024Article
- Automated free speech analysis reveals distinct markers of Alzheimer's and frontotemporal dementia.PloS one · 2024Article
- Speech and language markers of neurodegeneration: a call for global equity.Brain : a journal of neurology · 2023Review
- Narrative discourse production in Parkinson's disease: Decoupling the role of cognitive-linguistic and motor speech changes.Heliyon · 2023Article
- Deep Learning and Artificial Intelligence Applied to Model Speech and Language in Parkinson's Disease.Diagnostics (Basel, Switzerland) · 2023Article
- Ecological Meanings: A Consensus Paper on Individual Differences and Contextual Influences in Embodied Language.Journal of cognition · 2023Article
- Detecting Parkinson's disease and its cognitive phenotypes via automated semantic analyses of action stories.NPJ Parkinson's disease · 2022Article
- Automated text-level semantic markers of Alzheimer's disease.Alzheimer's & dementia (Amsterdam, Netherlands) · 2022Article
- Effects of Sleep on Language and Motor Consolidation: Evidence of Domain General and Specific Mechanisms.Neurobiology of language (Cambridge, Mass.) · 2022Article
- Early detection of Parkinson's disease from multiple signal speech: Based on Mandarin language dataset.Frontiers in aging neuroscience · 2022Article
- Language in Behavioral Variant Frontotemporal Dementia: Another Stone to Be Turned in Latin America.Frontiers in neurology · 2021Review
- Predicting and Characterizing Neurodegenerative Subtypes with Multimodal Neurocognitive Signatures of Social and Cognitive Processes.Journal of Alzheimer's disease : JAD · 2021Article
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Authors and funding
17 authors.
Funding
Abstract
Embodied cognition research on Parkinson's disease (PD) points to disruptions of frontostriatal language functions as sensitive targets for clinical assessment. However, no existing approach has been tested for crosslinguistic validity, let alone by combining naturalistic tasks with machine-learning tools. To address these issues, we conducted the first classifier-based examination of morphological processing (a core frontostriatal function) in spontaneous monologues from PD patients across three typologically different languages. The study comprised 330 participants, encompassing speakers of Spanish (61 patients, 57 matched controls), German (88 patients, 88 matched controls), and Czech (20 patients, 16 matched controls). All subjects described the activities they perform during a regular day, and their monologues were automatically coded via morphological tagging, a computerized method that labels each word with a part-of-speech tag (e.g., noun, verb) and specific morphological tags (e.g., person, gender, number, tense). The ensuing data were subjected to machine-learning analyses to assess whether differential morphological patterns could classify between patients and controls and reflect the former's degree of motor impairment. Results showed robust classification rates, with over 80% of patients being discriminated from controls in each language separately. Moreover, the most discriminative morphological features were associated with the patients' motor compromise (as indicated by Pearson r correlations between predicted and collected motor impairment scores that ranged from moderate to moderate-to-strong across languages). Taken together, our results suggest that morphological patterning, an embodied frontostriatal domain, may be distinctively affected in PD across languages and even under ecological testing conditions.
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