Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing

Autores
Dottori, Martin; Sedeño, Lucas; Martorell Caro, Miguel Angel; Alifano, Florencia; Hesse Rizzi, Eugenia Fátima; Mikulan, Ezequiel Pablo; García, Adolfo Martín; Ruiz Tagle, Amparo; Lillo, Patricia; Slachevsky, Andrea; Serrano, Cecilia Mariela; Fraiman Borrazás, Daniel Edmundo; Ibáñez Barassi, Agustín Mariano
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Developing effective and affordable biomarkers for dementias is critical given the difficulty to achieve early diagnosis. In this sense, electroencephalographic (EEG) methods offer promising alternatives due to their low cost, portability, and growing robustness. Here, we relied on EEG signals and a novel information-sharing method to study resting-state connectivity in patients with behavioral variant frontotemporal dementia (bvFTD) and controls. To evaluate the specificity of our results, we also tested Alzheimer's disease (AD) patients. The classification power of the ensuing connectivity patterns was evaluated through a supervised classification algorithm (support vector machine). In addition, we compared the classification power yielded by (i) functional connectivity, (ii) relevant neuropsychological tests, and (iii) a combination of both. BvFTD patients exhibited a specific pattern of hypoconnectivity in mid-range frontotemporal links, which showed no alterations in AD patients. These functional connectivity alterations in bvFTD were replicated with a low-density EEG setting (20 electrodes). Moreover, while neuropsychological tests yielded acceptable discrimination between bvFTD and controls, the addition of connectivity results improved classification power. Finally, classification between bvFTD and AD patients was better when based on connectivity than on neuropsychological measures. Taken together, such findings underscore the relevance of EEG measures as potential biomarker signatures for clinical settings.
Fil: Dottori, Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina
Fil: Sedeño, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina
Fil: Martorell Caro, Miguel Angel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina
Fil: Alifano, Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina
Fil: Hesse Rizzi, Eugenia Fátima. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad de Buenos Aires. Facultad de Ingeniería; Argentina
Fil: Mikulan, Ezequiel Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina
Fil: García, Adolfo Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad Nacional de Cuyo. Facultad de Educación Elemental y Especial; Argentina
Fil: Ruiz Tagle, Amparo. Centre for Advanced Research in Education; Chile
Fil: Lillo, Patricia. Universidad de Chile; Chile. Gerosciences Center for Brain Health and Metabolism; Chile
Fil: Slachevsky, Andrea. Universidad de Chile; Chile. Gerosciences Center for Brain Health and Metabolism; Chile. Hospital del Salvador; Chile. Centre for Advanced Research in Education; Chile. Clínica Alemana-Universidad del Desarrollo; Chile
Fil: Serrano, Cecilia Mariela. Clínica de Memoria y Equilibrio; Argentina
Fil: Fraiman Borrazás, Daniel Edmundo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; Argentina
Fil: Ibáñez Barassi, Agustín Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. The University of New South Wales; Australia. Macquarie University; Australia. Universidad Autónoma del Caribe; Colombia. Universidad Adolfo Ibañez; Chile
Materia
Bbiomarkers
Frontotemporal Dementia
Information Sharing
Eeg
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/66737
Acceder
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spelling Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharingDottori, MartinSedeño, LucasMartorell Caro, Miguel AngelAlifano, FlorenciaHesse Rizzi, Eugenia FátimaMikulan, Ezequiel PabloGarcía, Adolfo MartínRuiz Tagle, AmparoLillo, PatriciaSlachevsky, AndreaSerrano, Cecilia MarielaFraiman Borrazás, Daniel EdmundoIbáñez Barassi, Agustín MarianoBbiomarkersFrontotemporal DementiaInformation SharingEeghttps://purl.org/becyt/ford/3.1https://purl.org/becyt/ford/3Developing effective and affordable biomarkers for dementias is critical given the difficulty to achieve early diagnosis. In this sense, electroencephalographic (EEG) methods offer promising alternatives due to their low cost, portability, and growing robustness. Here, we relied on EEG signals and a novel information-sharing method to study resting-state connectivity in patients with behavioral variant frontotemporal dementia (bvFTD) and controls. To evaluate the specificity of our results, we also tested Alzheimer's disease (AD) patients. The classification power of the ensuing connectivity patterns was evaluated through a supervised classification algorithm (support vector machine). In addition, we compared the classification power yielded by (i) functional connectivity, (ii) relevant neuropsychological tests, and (iii) a combination of both. BvFTD patients exhibited a specific pattern of hypoconnectivity in mid-range frontotemporal links, which showed no alterations in AD patients. These functional connectivity alterations in bvFTD were replicated with a low-density EEG setting (20 electrodes). Moreover, while neuropsychological tests yielded acceptable discrimination between bvFTD and controls, the addition of connectivity results improved classification power. Finally, classification between bvFTD and AD patients was better when based on connectivity than on neuropsychological measures. Taken together, such findings underscore the relevance of EEG measures as potential biomarker signatures for clinical settings.Fil: Dottori, Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: Sedeño, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: Martorell Caro, Miguel Angel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: Alifano, Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: Hesse Rizzi, Eugenia Fátima. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad de Buenos Aires. Facultad de Ingeniería; ArgentinaFil: Mikulan, Ezequiel Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: García, Adolfo Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad Nacional de Cuyo. Facultad de Educación Elemental y Especial; ArgentinaFil: Ruiz Tagle, Amparo. Centre for Advanced Research in Education; ChileFil: Lillo, Patricia. Universidad de Chile; Chile. Gerosciences Center for Brain Health and Metabolism; ChileFil: Slachevsky, Andrea. Universidad de Chile; Chile. Gerosciences Center for Brain Health and Metabolism; Chile. Hospital del Salvador; Chile. Centre for Advanced Research in Education; Chile. Clínica Alemana-Universidad del Desarrollo; ChileFil: Serrano, Cecilia Mariela. Clínica de Memoria y Equilibrio; ArgentinaFil: Fraiman Borrazás, Daniel Edmundo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; ArgentinaFil: Ibáñez Barassi, Agustín Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. The University of New South Wales; Australia. Macquarie University; Australia. Universidad Autónoma del Caribe; Colombia. Universidad Adolfo Ibañez; ChileNature Publishing Group2017-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/66737Dottori, Martin; Sedeño, Lucas; Martorell Caro, Miguel Angel; Alifano, Florencia; Hesse Rizzi, Eugenia Fátima; et al.; Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing; Nature Publishing Group; Scientific Reports; 7; 1; 12-2017; 1-122045-2322CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41598-017-04204-8info:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-017-04204-8info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:35:03Zoai:ri.conicet.gov.ar:11336/66737instacron: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 10:35:04.019CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing
title Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing
spellingShingle Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing
Dottori, Martin
Bbiomarkers
Frontotemporal Dementia
Information Sharing
Eeg
title_short Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing
title_full Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing
title_fullStr Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing
title_full_unstemmed Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing
title_sort Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing
dc.creator.none.fl_str_mv Dottori, Martin
Sedeño, Lucas
Martorell Caro, Miguel Angel
Alifano, Florencia
Hesse Rizzi, Eugenia Fátima
Mikulan, Ezequiel Pablo
García, Adolfo Martín
Ruiz Tagle, Amparo
Lillo, Patricia
Slachevsky, Andrea
Serrano, Cecilia Mariela
Fraiman Borrazás, Daniel Edmundo
Ibáñez Barassi, Agustín Mariano
author Dottori, Martin
author_facet Dottori, Martin
Sedeño, Lucas
Martorell Caro, Miguel Angel
Alifano, Florencia
Hesse Rizzi, Eugenia Fátima
Mikulan, Ezequiel Pablo
García, Adolfo Martín
Ruiz Tagle, Amparo
Lillo, Patricia
Slachevsky, Andrea
Serrano, Cecilia Mariela
Fraiman Borrazás, Daniel Edmundo
Ibáñez Barassi, Agustín Mariano
author_role author
author2 Sedeño, Lucas
Martorell Caro, Miguel Angel
Alifano, Florencia
Hesse Rizzi, Eugenia Fátima
Mikulan, Ezequiel Pablo
García, Adolfo Martín
Ruiz Tagle, Amparo
Lillo, Patricia
Slachevsky, Andrea
Serrano, Cecilia Mariela
Fraiman Borrazás, Daniel Edmundo
Ibáñez Barassi, Agustín Mariano
author2_role author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Bbiomarkers
Frontotemporal Dementia
Information Sharing
Eeg
topic Bbiomarkers
Frontotemporal Dementia
Information Sharing
Eeg
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.1
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv Developing effective and affordable biomarkers for dementias is critical given the difficulty to achieve early diagnosis. In this sense, electroencephalographic (EEG) methods offer promising alternatives due to their low cost, portability, and growing robustness. Here, we relied on EEG signals and a novel information-sharing method to study resting-state connectivity in patients with behavioral variant frontotemporal dementia (bvFTD) and controls. To evaluate the specificity of our results, we also tested Alzheimer's disease (AD) patients. The classification power of the ensuing connectivity patterns was evaluated through a supervised classification algorithm (support vector machine). In addition, we compared the classification power yielded by (i) functional connectivity, (ii) relevant neuropsychological tests, and (iii) a combination of both. BvFTD patients exhibited a specific pattern of hypoconnectivity in mid-range frontotemporal links, which showed no alterations in AD patients. These functional connectivity alterations in bvFTD were replicated with a low-density EEG setting (20 electrodes). Moreover, while neuropsychological tests yielded acceptable discrimination between bvFTD and controls, the addition of connectivity results improved classification power. Finally, classification between bvFTD and AD patients was better when based on connectivity than on neuropsychological measures. Taken together, such findings underscore the relevance of EEG measures as potential biomarker signatures for clinical settings.
Fil: Dottori, Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina
Fil: Sedeño, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina
Fil: Martorell Caro, Miguel Angel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina
Fil: Alifano, Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina
Fil: Hesse Rizzi, Eugenia Fátima. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad de Buenos Aires. Facultad de Ingeniería; Argentina
Fil: Mikulan, Ezequiel Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina
Fil: García, Adolfo Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad Nacional de Cuyo. Facultad de Educación Elemental y Especial; Argentina
Fil: Ruiz Tagle, Amparo. Centre for Advanced Research in Education; Chile
Fil: Lillo, Patricia. Universidad de Chile; Chile. Gerosciences Center for Brain Health and Metabolism; Chile
Fil: Slachevsky, Andrea. Universidad de Chile; Chile. Gerosciences Center for Brain Health and Metabolism; Chile. Hospital del Salvador; Chile. Centre for Advanced Research in Education; Chile. Clínica Alemana-Universidad del Desarrollo; Chile
Fil: Serrano, Cecilia Mariela. Clínica de Memoria y Equilibrio; Argentina
Fil: Fraiman Borrazás, Daniel Edmundo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; Argentina
Fil: Ibáñez Barassi, Agustín Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. The University of New South Wales; Australia. Macquarie University; Australia. Universidad Autónoma del Caribe; Colombia. Universidad Adolfo Ibañez; Chile
description Developing effective and affordable biomarkers for dementias is critical given the difficulty to achieve early diagnosis. In this sense, electroencephalographic (EEG) methods offer promising alternatives due to their low cost, portability, and growing robustness. Here, we relied on EEG signals and a novel information-sharing method to study resting-state connectivity in patients with behavioral variant frontotemporal dementia (bvFTD) and controls. To evaluate the specificity of our results, we also tested Alzheimer's disease (AD) patients. The classification power of the ensuing connectivity patterns was evaluated through a supervised classification algorithm (support vector machine). In addition, we compared the classification power yielded by (i) functional connectivity, (ii) relevant neuropsychological tests, and (iii) a combination of both. BvFTD patients exhibited a specific pattern of hypoconnectivity in mid-range frontotemporal links, which showed no alterations in AD patients. These functional connectivity alterations in bvFTD were replicated with a low-density EEG setting (20 electrodes). Moreover, while neuropsychological tests yielded acceptable discrimination between bvFTD and controls, the addition of connectivity results improved classification power. Finally, classification between bvFTD and AD patients was better when based on connectivity than on neuropsychological measures. Taken together, such findings underscore the relevance of EEG measures as potential biomarker signatures for clinical settings.
publishDate 2017
dc.date.none.fl_str_mv 2017-12
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/11336/66737
Dottori, Martin; Sedeño, Lucas; Martorell Caro, Miguel Angel; Alifano, Florencia; Hesse Rizzi, Eugenia Fátima; et al.; Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing; Nature Publishing Group; Scientific Reports; 7; 1; 12-2017; 1-12
2045-2322
CONICET Digital
CONICET
url http://hdl.handle.net/11336/66737
identifier_str_mv Dottori, Martin; Sedeño, Lucas; Martorell Caro, Miguel Angel; Alifano, Florencia; Hesse Rizzi, Eugenia Fátima; et al.; Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing; Nature Publishing Group; Scientific Reports; 7; 1; 12-2017; 1-12
2045-2322
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
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info:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-017-04204-8
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Nature Publishing Group
publisher.none.fl_str_mv Nature Publishing Group
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
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reponame_str CONICET Digital (CONICET)
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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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