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

Autores
Ferrante, Franco Javier; Migeot, Joaquín; Birba, Agustina; Amoruso, Lucía; Pérez, Gonzalo Nicolas; Hesse Rizzi, Eugenia Fátima; Tagliazucchi, Enzo Rodolfo; Estienne, Claudio; Serrano, Cecilia Mariela; Slachevsky, Andrea; Matallana, Diana; Reyes, Pablo; Ibañez, Agustin Mariano; Fittipaldi, Sol; Gonzalez Campo, Cecilia; García, Adolfo Martín
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
NTRODUCTION: Verbal 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). METHODS: Patients 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. RESULTS: Valid 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. DISCUSSION: Word-property analysis of fluency can boost AD characterization and diagnosis.
Fil: Ferrante, Franco Javier. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ingeniería; Argentina
Fil: Migeot, Joaquín. Universidad Adolfo Ibañez; Chile
Fil: Birba, Agustina. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de La Laguna; España
Fil: Amoruso, Lucía. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Pérez, Gonzalo Nicolas. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ingeniería; Argentina
Fil: Hesse Rizzi, Eugenia Fátima. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; Argentina
Fil: Tagliazucchi, Enzo Rodolfo. Universidad Adolfo Ibañez; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Estienne, Claudio. Universidad de Buenos Aires; Argentina
Fil: Serrano, Cecilia Mariela. Unidad Asistencial "Dr. César Milstein"; Argentina
Fil: Slachevsky, Andrea. Universidad de Chile.; Chile
Fil: Matallana, Diana. Pontificia Universidad Javeriana; Colombia
Fil: Reyes, Pablo. Pontificia Universidad Javeriana; Colombia
Fil: Ibañez, Agustin Mariano. Universidad de San Andrés; Argentina. Universidad Adolfo Ibañez; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of California; Estados Unidos
Fil: Fittipaldi, Sol. Universidad de San Andrés; Argentina. Universidad Adolfo Ibañez; Chile. University of California; Estados Unidos
Fil: Gonzalez Campo, Cecilia. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: García, Adolfo Martín. Universidad Adolfo Ibañez; Chile. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of California; Estados Unidos
Materia
ELECTROENCEPHALOGRAPHY
MACHINE LEARNING
NEURODEGENERATION
NEUROIMAGING
SEMANTIC MEMORY
WORD PROPERTIES
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/237036
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/237036
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementiaFerrante, Franco JavierMigeot, JoaquínBirba, AgustinaAmoruso, LucíaPérez, Gonzalo NicolasHesse Rizzi, Eugenia FátimaTagliazucchi, Enzo RodolfoEstienne, ClaudioSerrano, Cecilia MarielaSlachevsky, AndreaMatallana, DianaReyes, PabloIbañez, Agustin MarianoFittipaldi, SolGonzalez Campo, CeciliaGarcía, Adolfo MartínELECTROENCEPHALOGRAPHYMACHINE LEARNINGNEURODEGENERATIONNEUROIMAGINGSEMANTIC MEMORYWORD PROPERTIEShttps://purl.org/becyt/ford/6.2https://purl.org/becyt/ford/6https://purl.org/becyt/ford/5.1https://purl.org/becyt/ford/5NTRODUCTION: Verbal 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). METHODS: Patients 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. RESULTS: Valid 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. DISCUSSION: Word-property analysis of fluency can boost AD characterization and diagnosis.Fil: Ferrante, Franco Javier. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ingeniería; ArgentinaFil: Migeot, Joaquín. Universidad Adolfo Ibañez; ChileFil: Birba, Agustina. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de La Laguna; EspañaFil: Amoruso, Lucía. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Pérez, Gonzalo Nicolas. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ingeniería; ArgentinaFil: Hesse Rizzi, Eugenia Fátima. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; ArgentinaFil: Tagliazucchi, Enzo Rodolfo. Universidad Adolfo Ibañez; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Estienne, Claudio. Universidad de Buenos Aires; ArgentinaFil: Serrano, Cecilia Mariela. Unidad Asistencial "Dr. César Milstein"; ArgentinaFil: Slachevsky, Andrea. Universidad de Chile.; ChileFil: Matallana, Diana. Pontificia Universidad Javeriana; ColombiaFil: Reyes, Pablo. Pontificia Universidad Javeriana; ColombiaFil: Ibañez, Agustin Mariano. Universidad de San Andrés; Argentina. Universidad Adolfo Ibañez; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of California; Estados UnidosFil: Fittipaldi, Sol. Universidad de San Andrés; Argentina. Universidad Adolfo Ibañez; Chile. University of California; Estados UnidosFil: Gonzalez Campo, Cecilia. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: García, Adolfo Martín. Universidad Adolfo Ibañez; Chile. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of California; Estados UnidosJohn Wiley & Sons2024-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/237036Ferrante, Franco Javier; Migeot, Joaquín; Birba, Agustina; Amoruso, Lucía; Pérez, Gonzalo Nicolas; et al.; Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia; John Wiley & Sons; Alzheimer's and Dementia; 20; 2; 2-2024; 925-9401552-5279CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://alz-journals.onlinelibrary.wiley.com/doi/full/10.1002/alz.13472info:eu-repo/semantics/altIdentifier/doi/10.1002/alz.13472info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:41:21Zoai:ri.conicet.gov.ar:11336/237036instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:41:21.874CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia
title Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia
spellingShingle Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia
Ferrante, Franco Javier
ELECTROENCEPHALOGRAPHY
MACHINE LEARNING
NEURODEGENERATION
NEUROIMAGING
SEMANTIC MEMORY
WORD PROPERTIES
title_short Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia
title_full Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia
title_fullStr Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia
title_full_unstemmed Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia
title_sort Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia
dc.creator.none.fl_str_mv Ferrante, Franco Javier
Migeot, Joaquín
Birba, Agustina
Amoruso, Lucía
Pérez, Gonzalo Nicolas
Hesse Rizzi, Eugenia Fátima
Tagliazucchi, Enzo Rodolfo
Estienne, Claudio
Serrano, Cecilia Mariela
Slachevsky, Andrea
Matallana, Diana
Reyes, Pablo
Ibañez, Agustin Mariano
Fittipaldi, Sol
Gonzalez Campo, Cecilia
García, Adolfo Martín
author Ferrante, Franco Javier
author_facet Ferrante, Franco Javier
Migeot, Joaquín
Birba, Agustina
Amoruso, Lucía
Pérez, Gonzalo Nicolas
Hesse Rizzi, Eugenia Fátima
Tagliazucchi, Enzo Rodolfo
Estienne, Claudio
Serrano, Cecilia Mariela
Slachevsky, Andrea
Matallana, Diana
Reyes, Pablo
Ibañez, Agustin Mariano
Fittipaldi, Sol
Gonzalez Campo, Cecilia
García, Adolfo Martín
author_role author
author2 Migeot, Joaquín
Birba, Agustina
Amoruso, Lucía
Pérez, Gonzalo Nicolas
Hesse Rizzi, Eugenia Fátima
Tagliazucchi, Enzo Rodolfo
Estienne, Claudio
Serrano, Cecilia Mariela
Slachevsky, Andrea
Matallana, Diana
Reyes, Pablo
Ibañez, Agustin Mariano
Fittipaldi, Sol
Gonzalez Campo, Cecilia
García, Adolfo Martín
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv ELECTROENCEPHALOGRAPHY
MACHINE LEARNING
NEURODEGENERATION
NEUROIMAGING
SEMANTIC MEMORY
WORD PROPERTIES
topic ELECTROENCEPHALOGRAPHY
MACHINE LEARNING
NEURODEGENERATION
NEUROIMAGING
SEMANTIC MEMORY
WORD PROPERTIES
purl_subject.fl_str_mv https://purl.org/becyt/ford/6.2
https://purl.org/becyt/ford/6
https://purl.org/becyt/ford/5.1
https://purl.org/becyt/ford/5
dc.description.none.fl_txt_mv NTRODUCTION: Verbal 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). METHODS: Patients 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. RESULTS: Valid 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. DISCUSSION: Word-property analysis of fluency can boost AD characterization and diagnosis.
Fil: Ferrante, Franco Javier. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ingeniería; Argentina
Fil: Migeot, Joaquín. Universidad Adolfo Ibañez; Chile
Fil: Birba, Agustina. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de La Laguna; España
Fil: Amoruso, Lucía. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Pérez, Gonzalo Nicolas. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ingeniería; Argentina
Fil: Hesse Rizzi, Eugenia Fátima. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; Argentina
Fil: Tagliazucchi, Enzo Rodolfo. Universidad Adolfo Ibañez; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Estienne, Claudio. Universidad de Buenos Aires; Argentina
Fil: Serrano, Cecilia Mariela. Unidad Asistencial "Dr. César Milstein"; Argentina
Fil: Slachevsky, Andrea. Universidad de Chile.; Chile
Fil: Matallana, Diana. Pontificia Universidad Javeriana; Colombia
Fil: Reyes, Pablo. Pontificia Universidad Javeriana; Colombia
Fil: Ibañez, Agustin Mariano. Universidad de San Andrés; Argentina. Universidad Adolfo Ibañez; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of California; Estados Unidos
Fil: Fittipaldi, Sol. Universidad de San Andrés; Argentina. Universidad Adolfo Ibañez; Chile. University of California; Estados Unidos
Fil: Gonzalez Campo, Cecilia. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: García, Adolfo Martín. Universidad Adolfo Ibañez; Chile. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of California; Estados Unidos
description NTRODUCTION: Verbal 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). METHODS: Patients 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. RESULTS: Valid 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. DISCUSSION: Word-property analysis of fluency can boost AD characterization and diagnosis.
publishDate 2024
dc.date.none.fl_str_mv 2024-02
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/237036
Ferrante, Franco Javier; Migeot, Joaquín; Birba, Agustina; Amoruso, Lucía; Pérez, Gonzalo Nicolas; et al.; Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia; John Wiley & Sons; Alzheimer's and Dementia; 20; 2; 2-2024; 925-940
1552-5279
CONICET Digital
CONICET
url http://hdl.handle.net/11336/237036
identifier_str_mv Ferrante, Franco Javier; Migeot, Joaquín; Birba, Agustina; Amoruso, Lucía; Pérez, Gonzalo Nicolas; et al.; Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia; John Wiley & Sons; Alzheimer's and Dementia; 20; 2; 2-2024; 925-940
1552-5279
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://alz-journals.onlinelibrary.wiley.com/doi/full/10.1002/alz.13472
info:eu-repo/semantics/altIdentifier/doi/10.1002/alz.13472
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv John Wiley & Sons
publisher.none.fl_str_mv John Wiley & Sons
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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