Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia

Author:

Ferrante Franco J.123,Migeot Joaquín45,Birba Agustina167,Amoruso Lucía189,Pérez Gonzalo123,Hesse Eugenia110,Tagliazucchi Enzo411,Estienne Claudio12,Serrano Cecilia13,Slachevsky Andrea14151617,Matallana Diana1819,Reyes Pablo2021,Ibáñez Agustín12422,Fittipaldi Sol1422,Campo Cecilia Gonzalez12,García Adolfo M.142223

Affiliation:

1. Centro de Neurociencias Cognitivas Universidad de San Andrés Victoria Provincia de Buenos Aires Argentina

2. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Ciudad Autónoma de Buenos Aires Argentina

3. Facultad de Ingeniería Universidad de Buenos Aires (FIUBA) CABA Argentina

4. Latin American Brain Health (BrainLat) Institute Universidad Adolfo Ibáñez Peñalolén Región Metropolitana Chile

5. Center for Social and Cognitive Neuroscience (CSCN) School of Psychology Universidad Adolfo Ibáñez Las Condes Chile

6. Instituto Universitario de Neurociencia Universidad de La Laguna La Laguna Tenerife España

7. Cognitive Department of Psychology Universidad de La Laguna La Laguna Tenerife España

8. Basque Center on Cognition Brain and Language (BCBL) San Sebastián Gipuzkoa España

9. Ikerbasque Basque Foundation for Science Bilbao Spain

10. Departamento de Matemática y Ciencias Universidad de San Andrés Victoria Provincia de Buenos Aires Argentina

11. Departamento de Física Universidad de Buenos Aires and Instituto de Física de Buenos Aires (IFIBA‐CONICET) CABA Argentina

12. Instituto de Ingeniería Biomédica Universidad de Buenos Aires Buenos Aires Argentina

13. Unidad de Neurología Cognitiva Hospital César Milstein CABA Argentina

14. Neuropsychology and Clinical Neuroscience Laboratory (LANNEC) Physiopathology Department ‐ ICBM Neurocience and East Neuroscience Departments Faculty of Medicine University of Chile Providencia Santiago Chile

15. Geroscience Center for Brain Health and Metabolism (GERO) Faculty of Medicine University of Chile Providencia Santiago Chile

16. Memory and Neuropsychiatric Clinic (CMYN) Neurology Department Hospital del Salvador and Faculty of Medicine University of Chile Providencia Santiago Chile

17. Servicio de Neurología Departamento de Medicina Clínica Alemana‐Universidad del Desarrollo Las Condes Región Metropolitana Chile

18. Instituto de Envejecimiento Department of Psychiatry School of Medicine Pontifical Xaverian University Bogotá Colombia

19. Department of Mental Health Hospital Universitario Santa Fe de Bogotá Bogotá Colombia

20. Centro de Memoria y Cognición Intellectus‐Hospital Universitario San Ignacio Bogotá Colombia

21. Pontificia Universidad Javeriana Departments of Physiology Psychiatry and Aging Institute Bogotá Colombia

22. Global Brain Health Institute, University of California San Francisco, San Francisco, California, USA Trinity College Dublin Dublin Ireland

23. Departamento de Lingüística y Literatura Facultad de Humanidades Universidad de Santiago de Chile Estación Central Santiago Chile

Abstract

AbstractINTRODUCTIONVerbal fluency tasks are common in Alzheimer's disease (AD) assessments. Yet, standard valid response counts fail to reveal disease‐specific semantic memory patterns. Here, we leveraged automated word‐property analysis to capture neurocognitive markers of AD vis‐à‐vis behavioral variant frontotemporal dementia (bvFTD).METHODSPatients and healthy controls completed two fluency tasks. We counted valid responses and computed each word's frequency, granularity, neighborhood, length, familiarity, and imageability. These features were used for group‐level discrimination, patient‐level identification, and correlations with executive and neural (magnetic resonanance imaging [MRI], functional MRI [fMRI], electroencephalography [EEG]) patterns.RESULTSValid responses revealed deficits in both disorders. Conversely, frequency, granularity, and neighborhood yielded robust group‐ and subject‐level discrimination only in AD, also predicting executive outcomes. Disease‐specific cortical thickness patterns were predicted by frequency in both disorders. Default‐mode and salience network hypoconnectivity, and EEG beta hypoconnectivity, were predicted by frequency and granularity only in AD.DISCUSSIONWord‐property analysis of fluency can boost AD characterization and diagnosis.Highlights We report novel word‐property analyses of verbal fluency in AD and bvFTD. Standard valid response counts captured deficits and brain patterns in both groups. Specific word properties (e.g., frequency, granularity) were altered only in AD. Such properties predicted cognitive and neural (MRI, fMRI, EEG) patterns in AD. Word‐property analysis of fluency can boost AD characterization and diagnosis.

Funder

Fondo de Fomento al Desarrollo Científico y Tecnológico

Alzheimer's Association

Rainwater Charitable Foundation

Tau Consortium

Publisher

Wiley

Subject

Psychiatry and Mental health,Cellular and Molecular Neuroscience,Geriatrics and Gerontology,Neurology (clinical),Developmental Neuroscience,Health Policy,Epidemiology

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