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

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dc.contributor.author Dottori, Martin
dc.contributor.author Sedeño, Lucas
dc.contributor.author Martorell, Miguel
dc.contributor.author Alifano, Florencia
dc.contributor.author Hesse, Eugenia
dc.contributor.author Mikulan, Ezequiel
dc.contributor.author García, Adolfo
dc.contributor.author Ruiz-Tagle, Amparo
dc.contributor.author Lillo, Patricia
dc.contributor.author Slachevsky, Andrea
dc.contributor.author Serrano, Cecilia
dc.contributor.author Fraiman, Daniel
dc.contributor.author Ibañez, Agustin
dc.date.accessioned 2018-01-24T14:27:36Z
dc.date.available 2018-01-24T14:27:36Z
dc.date.issued 2017
dc.identifier.citation Scientific Reports 7, Article number: 3822 (2017) es_CL
dc.identifier.uri http://dx.doi.org/10.1038/s41598-017-04204-8 es_CL
dc.identifier.uri http://hdl.handle.net/11447/1965
dc.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. es_CL
dc.format.extent 12 es_CL
dc.language.iso en_US es_CL
dc.publisher Nature Publishing Group es_CL
dc.subject dementia es_CL
dc.title Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing es_CL
dc.type Artículo es_CL


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