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

Abstract 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 sign...

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Autores principales:	Martin Dottori, Lucas Sedeño, Miguel Martorell Caro, Florencia Alifano, Eugenia Hesse, Ezequiel Mikulan, Adolfo M. García, Amparo Ruiz-Tagle, Patricia Lillo, Andrea Slachevsky, Cecilia Serrano, Daniel Fraiman, Agustin Ibanez
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/21a47f120e114993882a3c0b9d9ce90b
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spelling	oai:doaj.org-article:21a47f120e114993882a3c0b9d9ce90b2021-12-02T12:30:44ZTowards affordable biomarkers of frontotemporal dementia: A classification study via network’s information sharing10.1038/s41598-017-04204-82045-2322https://doaj.org/article/21a47f120e114993882a3c0b9d9ce90b2017-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-04204-8https://doaj.org/toc/2045-2322Abstract 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.Martin DottoriLucas SedeñoMiguel Martorell CaroFlorencia AlifanoEugenia HesseEzequiel MikulanAdolfo M. GarcíaAmparo Ruiz-TaglePatricia LilloAndrea SlachevskyCecilia SerranoDaniel FraimanAgustin IbanezNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-12 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Martin Dottori Lucas Sedeño Miguel Martorell Caro Florencia Alifano Eugenia Hesse Ezequiel Mikulan Adolfo M. García Amparo Ruiz-Tagle Patricia Lillo Andrea Slachevsky Cecilia Serrano Daniel Fraiman Agustin Ibanez Towards affordable biomarkers of frontotemporal dementia: A classification study via network’s information sharing
description	Abstract 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.
format	article
author	Martin Dottori Lucas Sedeño Miguel Martorell Caro Florencia Alifano Eugenia Hesse Ezequiel Mikulan Adolfo M. García Amparo Ruiz-Tagle Patricia Lillo Andrea Slachevsky Cecilia Serrano Daniel Fraiman Agustin Ibanez
author_facet	Martin Dottori Lucas Sedeño Miguel Martorell Caro Florencia Alifano Eugenia Hesse Ezequiel Mikulan Adolfo M. García Amparo Ruiz-Tagle Patricia Lillo Andrea Slachevsky Cecilia Serrano Daniel Fraiman Agustin Ibanez
author_sort	Martin Dottori
title	Towards affordable biomarkers of frontotemporal dementia: A classification study via network’s information sharing
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
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/21a47f120e114993882a3c0b9d9ce90b
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Towards affordable biomarkers of frontotemporal dementia: A classification study via network’s information sharing

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