From discourse to pathology: Automatic identification of Parkinson's disease patients via morphological measures across three languages
Open accessAbstract
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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Morphosyntactic patterns differentiated Parkinson's disease patients from healthy persons in German, Spanish and Czech, but the most discriminatory features diverged across these languages.
“Furthermore, while morphosyntactic patterns differ entiated Parkinson's disease patients from healthy persons in German, Spanish and Czech, the most discriminatory features diverged across these languages”
From Speech and language markers of neurodegeneration: a call for global equity (2023) · cites this paper as [19]
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The Neuroscience of Parkinson's Disease
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Self-citationFunctional correlates of strategy formation and verbal suppression in Parkinson's disease
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Disruptions of frontostriatal language functions in Parkinson's disease
García, A. M., Bocanegra, Y., Birba, A., Orozco-Arroyave, J. R., Sedeño, L., & Ibáñez, A. (2020) · Genetics, Neurology, Behavior, and Diet in Parkinson's Disease · doi:10.1016/b978-0-12-815950-7.00026-6 · Cited by 2 · see citing works
Self-citation
Flagged first, then by citations
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Cited by
Sorted by citations
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Self-citationSpeech and language markers of neurodegeneration: a call for global equity
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Cho, S., Cousins, K. A. Q., Shellikeri, S., Ash, S., Irwin, D. J., Liberman, M. Y., Grossman, M., & Nevler, N. (2022) · Neurology · doi:10.1212/wnl.0000000000200581 · Cited by 51 · see citing works
Ibáñez, A., Kühne, K., Miklashevsky, A., Monaco, E., Muraki, E., Ranzini, M., Speed, L., & Tuena, C. (2023) · Journal of Cognition · doi:10.5334/joc.228 · Cited by 53 · see citing works
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Garofalo, G., Magliocco, F., Silipo, F., Riggio, L., & Buccino, G. (2022) · Journal of Neuropsychology · doi:10.1111/jnp.12270 · Cited by 9 · see citing works
Language in behavioral variant frontotemporal dementia: Another stone to be turned in Latin America
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Speech and language outcome measures in clinical trials of Alzheimer’s and Parkinson’s diseases
Berthier, M. L., Welford, A. S., Orozco‐Arroyave, J. R., López-Barroso, D., Torres‐Prioris, M. J., Dávila, G., & García, A. M. (2025) · Expert Review of Neurotherapeutics · doi:10.1080/14737175.2025.2600616 · Cited by 4 · see citing works
Self-citationEmotional State Modeling for the Assessment of Depression in Parkinson’s Disease
Pérez-Toro, P. A., Vásquez-Correa, J. C., Arias‐Vergara, T., Klumpp, P., Schuster, M., Nöth, E., & Orozco‐Arroyave, J. R. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-83527-9_39 · Cited by 4 · see citing works
Self-citationPinto, S., Cardoso, R., Atkinson-Clément, C., Guimarães, I., Sadat, J., Santos, H., Mercier, C., Carvalho, J., Cuartero, M., Oliveira, P., et al. (2024) · Journal of Speech Language and Hearing Research · doi:10.1044/2024_jslhr-23-00525 · Cited by 3 · see citing works
Kogan, B., Birba, A., Rivera, M. D., Santibáñez, C. G., & García, A. M. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1637855 · Cited by 2 · see citing works
Self-citationTF-FusNet: A Novel Framework for Parkinson’s Disease Detection via Time-Frequency Domain Fusion
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Mercado, J., Escobar-Grisales, D., Ríos-Urrego, C. D., García, A. M., Bocanegra, Y., Moreno, L., Nöth, E., & Orozco‐Arroyave, J. R. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-02551-7_25 · Cited by 1 · see citing works
Self-citationLanguage in Parkinson’s disease
Basirat, A. (2025) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198888482.013.0013 · Cited by 1 · see citing works
Escobar-Grisales, D., Ríos-Urrego, C. D., & Orozco‐Arroyave, J. R. (2025) · Springer eBooks · doi:10.1007/978-3-031-95878-6_1
Self-citationVerb specificity effects on semantic processing in Parkinson's disease.
Salmazo-Silva, H., Toro-Hernández, F., Parente, M. A. D. M. P., Lunardi, B., Cravo, A., Weekes, B., Sato, J., Godinho, F., Rocha, M., & Carthery-Goulart, M. (2026) · Cortex; a journal devoted to the study of the nervous system and behavior · doi:10.1016/j.cortex.2026.05.006
Digital profiling of dysarthria in late- and early-onset Parkinson's disease
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Self-citationCross-Attention Fusion of Acoustic and Linguistic Features for Parkinson’s Disease Detection
Mercado, J., Escobar-Grisales, D., Ríos-Urrego, C. D., Gallo-Aristizábal, J. D., & Orozco‐Arroyave, J. R. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-37249-9_30
Self-citation
- Authors
- Eyigoz, E., Courson, M., Sedeño, L., Rogg, K., Orozco-Arroyave, J. R., Nöth, E., Skodda, S., Trujillo, N., Rodríguez, M., Rusz, J., Muñoz, E., Cardona, J. F., Herrera, E., Hesse, E., Ibáñez, A., Cecchi, G., & García, A. M.
- Affiliations
- Consejo Nacional de Investigaciones Científicas y Técnicas (AR)
- University of Würzburg (DE)
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- Universitätsklinikum Knappschaftskrankenhaus Bochum (DE)
- Universidad de Antioquia (CO)
- Charles University (CZ)
- Czech Technical University in Prague (CZ)
- Universidad del Valle (CO)
- Universidad Icesi (CO)
- IBM (United States) (US)
- Universidad de Santiago de Chile (CL)
- Corresponding author
- García, Adolfo M.
- ORCID
- Venue
- Cortex
- Publisher
- Elsevier BV
- Published
- 2020-11
- Volume
- 132
- Pages
- 191-205
- ISSN
- 0010-9452 (ISSN-L)
- PMC
- PMC7655620
- OpenAlex
- W3084199884
- Cited by
- 44
- References
- 96
- Citations by year
- 2026: 3 · 2025: 9 · 2024: 9 · 2023: 6 · 2022: 8 · 2021: 9
- FWCI
- 2.49
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Cortex (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- CONICET Digital (CONICET) (submittedVersion, cc-by-nc-sa)
- Funders
- Sistema General de Regalías de Colombia
- Universidad del Valle
- Global Brain Health Institute
- Fondo para la Investigación Científica y Tecnológica
- Horizon 2020
- Alzheimer's Association (SG-20-725707-ReDLat)
- Comisión Nacional de Investigación Científica y Tecnológica
- Ministerstvo Zdravotnictví Ceské Republiky
- Departamento Administrativo de Ciencia, Tecnología e Innovación
- Rainwater Charitable Foundation
- Universidad de Antioquia
- Consejo Nacional de Investigaciones Científicas y Técnicas
- Fondo Nacional de Desarrollo Científico y Tecnológico (1170010, 15150012, FONCYT-PICT 2017-1818, FONCYT-PICT 2017-1820)
- National Institutes of Health
- H2020 Marie Skłodowska-Curie Actions (766287)
- National Institute on Aging (R01AG057234)
- Topics
- Health Sciences › Medicine › Neurology › Parkinson's Disease Mechanisms and Treatments
- Health Sciences › Medicine › Physiology › Voice and Speech Disorders
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Keywords
- Parkinson's disease, morphological processing, embodied cognition, morphological tagging, Spanish language, German, Czech, motor impairment
- MeSH terms
- Machine Learning, Cognition, Humans, Language, Parkinson Disease, Speech
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