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.

Departamento de Estudios Psicológicos Universidad Icesi Cali Colombia

Departamento de Lingüística y Literatura Facultad de Humanidades Universidad de Santiago de Chile Santiago Chile

Department of Circuit Theory Faculty of Electrical Engineering Czech Technical University Prague Czech Republic

Department of Neurology Knappschaftskrankenhaus Ruhr University Bochum Germany

Department of Psychology Université de Montréal CRIUGM Research Center Montréal Canada

Department of Social Psychology University of Würzburg Würzburg Germany

IBM Research T J Watson Research Center New York USA

Instituto de Psicología Universidad del Valle Cali Colombia

National Institute of Mental Health Prague Czech Republic; Department of Psychology Faculty of Arts Charles University Prague Prague Czech Republic

National Scientific and Technical Research Council Buenos Aires Argentina

National Scientific and Technical Research Council Buenos Aires Argentina; Universidad de San Andrés Buenos Aires Argentina

National Scientific and Technical Research Council Mendoza Argentina

National Scientific and Technical Research Council School of Psychology Universidad Adolfo Ibáñez Santiago de Chile Chile; Global Brain Health Institute University of California San Francisco United States

Neuroscience Group Faculty of Medicine University of Antioquia Medellín Colombia

Pattern Recognition Lab Friedrich Alexander Universität Erlangen Nürnberg Germany

Pattern Recognition Lab Friedrich Alexander Universität Erlangen Nürnberg Germany; GITA Lab Faculty of Engineering University of Antioquia Medellín Colombia

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