Automated item‐level measures of verbal fluency in semantic and logopenic primary progressive aphasia

Autores
Vonk, Jet M. J.; Ferrante, Franco; Morin, Brittany T.; Rodriguez, Diana Alejandra; Lin, Mia; Bogley, Rian; de Leon, Jessica; Tee, Boon Lead; Santos Santos, Miguel Ángel; Miller, Zachary A.; Mandelli, Maria Luisa; Gorno Tempini, Maria Luisa; García, Adolfo Martín
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Introduction: Verbal fluency tasks are widely used in primary progressive aphasia (PPA), but most studies rely only on total correct responses, overlooking qualitative features of the words produced. We applied a scalable computational framework to extract item-level features from fluency responses in semantic (svPPA) and logopenic PPA (lvPPA) to test their value for differential diagnosis.Methods: We analyzed animal fluency responses from 113 participants (40 svPPA, 40 lvPPA, 33 controls) using an automated pipeline extracting nine psycholinguistic features. Group differences were examined with (co)variance models, classification with logistic regression, and brain-behavior associations via structural MRI.Results: All features except semantic variability distinguished svPPA from lvPPA. Models including features outperformed (AUC=.86) those using only total correct or clinical variables (AUC=.60-.68). Features related mainly to temporal lobe atrophy, whereas total correct also related to the angular gyrus.Discussion: Automated item-level analysis offers a sensitive, scalable method for supporting PPA diagnosis and monitoring.
Fil: Vonk, Jet M. J.. University of California; Estados Unidos
Fil: Ferrante, Franco. University of California; Estados Unidos. Universidad de San Andrés. Rectorado. Centro de Neurociencias Cognitivas;
Fil: Morin, Brittany T.. University of California; Estados Unidos
Fil: Rodriguez, Diana Alejandra. University of California; Estados Unidos
Fil: Lin, Mia. University of California; Estados Unidos
Fil: Bogley, Rian. University of California; Estados Unidos
Fil: de Leon, Jessica. University of California; Estados Unidos
Fil: Tee, Boon Lead. University of California; Estados Unidos
Fil: Santos Santos, Miguel Ángel. Instituto de Salud Carlos III; España. Sant Pau Biomedical Research Institute; España
Fil: Miller, Zachary A.. University of California; Estados Unidos
Fil: Mandelli, Maria Luisa. University of California; Estados Unidos
Fil: Gorno Tempini, Maria Luisa. University of California; Estados Unidos
Fil: García, Adolfo Martín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés. Rectorado. Centro de Neurociencias Cognitivas; . University of California; Estados Unidos. Universidad de Santiago de Chile; Chile
Materia
Aphasia
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:11336/280704
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/280704
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Automated item‐level measures of verbal fluency in semantic and logopenic primary progressive aphasiaVonk, Jet M. J.Ferrante, FrancoMorin, Brittany T.Rodriguez, Diana AlejandraLin, MiaBogley, Riande Leon, JessicaTee, Boon LeadSantos Santos, Miguel ÁngelMiller, Zachary A.Mandelli, Maria LuisaGorno Tempini, Maria LuisaGarcía, Adolfo MartínAphasiahttps://purl.org/becyt/ford/3.2https://purl.org/becyt/ford/3Introduction: Verbal fluency tasks are widely used in primary progressive aphasia (PPA), but most studies rely only on total correct responses, overlooking qualitative features of the words produced. We applied a scalable computational framework to extract item-level features from fluency responses in semantic (svPPA) and logopenic PPA (lvPPA) to test their value for differential diagnosis.Methods: We analyzed animal fluency responses from 113 participants (40 svPPA, 40 lvPPA, 33 controls) using an automated pipeline extracting nine psycholinguistic features. Group differences were examined with (co)variance models, classification with logistic regression, and brain-behavior associations via structural MRI.Results: All features except semantic variability distinguished svPPA from lvPPA. Models including features outperformed (AUC=.86) those using only total correct or clinical variables (AUC=.60-.68). Features related mainly to temporal lobe atrophy, whereas total correct also related to the angular gyrus.Discussion: Automated item-level analysis offers a sensitive, scalable method for supporting PPA diagnosis and monitoring.Fil: Vonk, Jet M. J.. University of California; Estados UnidosFil: Ferrante, Franco. University of California; Estados Unidos. Universidad de San Andrés. Rectorado. Centro de Neurociencias Cognitivas;Fil: Morin, Brittany T.. University of California; Estados UnidosFil: Rodriguez, Diana Alejandra. University of California; Estados UnidosFil: Lin, Mia. University of California; Estados UnidosFil: Bogley, Rian. University of California; Estados UnidosFil: de Leon, Jessica. University of California; Estados UnidosFil: Tee, Boon Lead. University of California; Estados UnidosFil: Santos Santos, Miguel Ángel. Instituto de Salud Carlos III; España. Sant Pau Biomedical Research Institute; EspañaFil: Miller, Zachary A.. University of California; Estados UnidosFil: Mandelli, Maria Luisa. University of California; Estados UnidosFil: Gorno Tempini, Maria Luisa. University of California; Estados UnidosFil: García, Adolfo Martín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés. Rectorado. Centro de Neurociencias Cognitivas; . University of California; Estados Unidos. Universidad de Santiago de Chile; ChileElsevier Science Inc.2025-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/280704Vonk, Jet M. J.; Ferrante, Franco; Morin, Brittany T.; Rodriguez, Diana Alejandra; Lin, Mia; et al.; Automated item‐level measures of verbal fluency in semantic and logopenic primary progressive aphasia; Elsevier Science Inc.; Alzheimers & Dementia; 22; 1; 8-2025; 1-141552-5260CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://alz-journals.onlinelibrary.wiley.com/doi/10.1002/alz.71124info:eu-repo/semantics/altIdentifier/doi/10.1002/alz.71124info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2026-02-26T10:24:24Zoai:ri.conicet.gov.ar:11336/280704instacron: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:34982026-02-26 10:24:24.349CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Automated item‐level measures of verbal fluency in semantic and logopenic primary progressive aphasia
title Automated item‐level measures of verbal fluency in semantic and logopenic primary progressive aphasia
spellingShingle Automated item‐level measures of verbal fluency in semantic and logopenic primary progressive aphasia
Vonk, Jet M. J.
Aphasia
title_short Automated item‐level measures of verbal fluency in semantic and logopenic primary progressive aphasia
title_full Automated item‐level measures of verbal fluency in semantic and logopenic primary progressive aphasia
title_fullStr Automated item‐level measures of verbal fluency in semantic and logopenic primary progressive aphasia
title_full_unstemmed Automated item‐level measures of verbal fluency in semantic and logopenic primary progressive aphasia
title_sort Automated item‐level measures of verbal fluency in semantic and logopenic primary progressive aphasia
dc.creator.none.fl_str_mv Vonk, Jet M. J.
Ferrante, Franco
Morin, Brittany T.
Rodriguez, Diana Alejandra
Lin, Mia
Bogley, Rian
de Leon, Jessica
Tee, Boon Lead
Santos Santos, Miguel Ángel
Miller, Zachary A.
Mandelli, Maria Luisa
Gorno Tempini, Maria Luisa
García, Adolfo Martín
author Vonk, Jet M. J.
author_facet Vonk, Jet M. J.
Ferrante, Franco
Morin, Brittany T.
Rodriguez, Diana Alejandra
Lin, Mia
Bogley, Rian
de Leon, Jessica
Tee, Boon Lead
Santos Santos, Miguel Ángel
Miller, Zachary A.
Mandelli, Maria Luisa
Gorno Tempini, Maria Luisa
García, Adolfo Martín
author_role author
author2 Ferrante, Franco
Morin, Brittany T.
Rodriguez, Diana Alejandra
Lin, Mia
Bogley, Rian
de Leon, Jessica
Tee, Boon Lead
Santos Santos, Miguel Ángel
Miller, Zachary A.
Mandelli, Maria Luisa
Gorno Tempini, Maria Luisa
García, Adolfo Martín
author2_role author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Aphasia
topic Aphasia
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.2
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv Introduction: Verbal fluency tasks are widely used in primary progressive aphasia (PPA), but most studies rely only on total correct responses, overlooking qualitative features of the words produced. We applied a scalable computational framework to extract item-level features from fluency responses in semantic (svPPA) and logopenic PPA (lvPPA) to test their value for differential diagnosis.Methods: We analyzed animal fluency responses from 113 participants (40 svPPA, 40 lvPPA, 33 controls) using an automated pipeline extracting nine psycholinguistic features. Group differences were examined with (co)variance models, classification with logistic regression, and brain-behavior associations via structural MRI.Results: All features except semantic variability distinguished svPPA from lvPPA. Models including features outperformed (AUC=.86) those using only total correct or clinical variables (AUC=.60-.68). Features related mainly to temporal lobe atrophy, whereas total correct also related to the angular gyrus.Discussion: Automated item-level analysis offers a sensitive, scalable method for supporting PPA diagnosis and monitoring.
Fil: Vonk, Jet M. J.. University of California; Estados Unidos
Fil: Ferrante, Franco. University of California; Estados Unidos. Universidad de San Andrés. Rectorado. Centro de Neurociencias Cognitivas;
Fil: Morin, Brittany T.. University of California; Estados Unidos
Fil: Rodriguez, Diana Alejandra. University of California; Estados Unidos
Fil: Lin, Mia. University of California; Estados Unidos
Fil: Bogley, Rian. University of California; Estados Unidos
Fil: de Leon, Jessica. University of California; Estados Unidos
Fil: Tee, Boon Lead. University of California; Estados Unidos
Fil: Santos Santos, Miguel Ángel. Instituto de Salud Carlos III; España. Sant Pau Biomedical Research Institute; España
Fil: Miller, Zachary A.. University of California; Estados Unidos
Fil: Mandelli, Maria Luisa. University of California; Estados Unidos
Fil: Gorno Tempini, Maria Luisa. University of California; Estados Unidos
Fil: García, Adolfo Martín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés. Rectorado. Centro de Neurociencias Cognitivas; . University of California; Estados Unidos. Universidad de Santiago de Chile; Chile
description Introduction: Verbal fluency tasks are widely used in primary progressive aphasia (PPA), but most studies rely only on total correct responses, overlooking qualitative features of the words produced. We applied a scalable computational framework to extract item-level features from fluency responses in semantic (svPPA) and logopenic PPA (lvPPA) to test their value for differential diagnosis.Methods: We analyzed animal fluency responses from 113 participants (40 svPPA, 40 lvPPA, 33 controls) using an automated pipeline extracting nine psycholinguistic features. Group differences were examined with (co)variance models, classification with logistic regression, and brain-behavior associations via structural MRI.Results: All features except semantic variability distinguished svPPA from lvPPA. Models including features outperformed (AUC=.86) those using only total correct or clinical variables (AUC=.60-.68). Features related mainly to temporal lobe atrophy, whereas total correct also related to the angular gyrus.Discussion: Automated item-level analysis offers a sensitive, scalable method for supporting PPA diagnosis and monitoring.
publishDate 2025
dc.date.none.fl_str_mv 2025-08
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/11336/280704
Vonk, Jet M. J.; Ferrante, Franco; Morin, Brittany T.; Rodriguez, Diana Alejandra; Lin, Mia; et al.; Automated item‐level measures of verbal fluency in semantic and logopenic primary progressive aphasia; Elsevier Science Inc.; Alzheimers & Dementia; 22; 1; 8-2025; 1-14
1552-5260
CONICET Digital
CONICET
url http://hdl.handle.net/11336/280704
identifier_str_mv Vonk, Jet M. J.; Ferrante, Franco; Morin, Brittany T.; Rodriguez, Diana Alejandra; Lin, Mia; et al.; Automated item‐level measures of verbal fluency in semantic and logopenic primary progressive aphasia; Elsevier Science Inc.; Alzheimers & Dementia; 22; 1; 8-2025; 1-14
1552-5260
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/10.1002/alz.71124
info:eu-repo/semantics/altIdentifier/doi/10.1002/alz.71124
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
dc.publisher.none.fl_str_mv Elsevier Science Inc.
publisher.none.fl_str_mv Elsevier Science Inc.
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
_version_ 1858305754266599424
score 13.176822

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