Towards affordable biomarkers of frontotemporal dementia: a classification study via network's information sharing
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Dottori, Martín
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Towards affordable biomarkers of frontotemporal dementia: a classification study via network's information sharing
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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.
Patrocinador
CONICYT/FONDECYT
1170010
1140114
11404223
1160940 /
Conicyt/Associative Research Program/Basal Funds Grant for Centers of Excellence (AS ART)
FB 0003 /
INECO Foundation /
PICT
2012-0412
2012-1309 /
CONICET /
CONICYT/FONDAP
15150012
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Artículo de publicación ISI
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Scientific Reports 7: 3822 (2017)
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