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

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dc.contributor.authorDottori, Martin
dc.contributor.authorSedeño, Lucas
dc.contributor.authorMartorell, Miguel
dc.contributor.authorAlifano, Florencia
dc.contributor.authorHesse, Eugenia
dc.contributor.authorMikulan, Ezequiel
dc.contributor.authorGarcía, Adolfo
dc.contributor.authorRuiz-Tagle, Amparo
dc.contributor.authorLillo, Patricia
dc.contributor.authorSlachevsky, Andrea
dc.contributor.authorSerrano, Cecilia
dc.contributor.authorFraiman, Daniel
dc.contributor.authorIbañez, Agustin
dc.date.accessioned2018-01-24T14:27:36Z
dc.date.available2018-01-24T14:27:36Z
dc.date.issued2017
dc.description.abstractDeveloping 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.
dc.format.extent12
dc.identifier.citationDottori M, Sedeño L, Martorell Caro M, Alifano F, Hesse E, Mikulan E, García AM, Ruiz-Tagle A, Lillo P, Slachevsky A, Serrano C, Fraiman D, Ibanez A. Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing. Sci Rep. 2017 Jun 19;7(1):3822
dc.identifier.urihttp://hdl.handle.net/11447/1965
dc.identifier.urihttp://dx.doi.org/10.1038/s41598-017-04204-8
dc.language.isoen_US
dc.publisherNature Publishing Group
dc.subjectdementia
dc.titleTowards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing
dc.typeArtículo

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