GARCIA adolfo Martin
congresos y reuniones científicas
Exploring the use of EEG brain connectivity as a potential biomarkers of frontotemporal dementia
DOTTORI, MARTÍN; SEDEÑO, LUCAS; MARTORELL CARO, MIGUEL; ALIFANO, FLORENCIA; HESSE, EUGENIA; MIKULAN, EZEQUIEL; GARCÍA, ADOLFO M.; RUIZ-TAGLE, AMPARO; LILLO, PATRICIA; SLACHEVSKY, ANDREA; SERRANO, CECILIA; MANES, FACUNDO; FRAIMAN, DANIEL; IBÁÑEZ, AGUSTÍN
Conferencia; 11th International Conference on Frontotemporal Dementias; 2018
The challenges of achieving early diagnosis of dementia calls for new research on affordable, potentially effective biomarkers. Electroencephalographic (EEG) methods constitute highly relevant tools to such ends, given their low cost, portability, and growing robustness. Using this approach, we studied brain connectivity differences between 13 patients with behavioral variant frontotemporal dementia (bvFTD) and 25 controls, targeting resting-state signals through a novel information-sharing method. Thirteen Alzheimer?s disease (AD) patients were included as a contrastive pathological group, to test the specificity of our results. We analyzed the classification power of (i) functional connectivity, (ii) relevant neuropsychological tests for bvFTD, 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. Such results were replicated with a low-density EEG setting (20 electrodes). Classification between bvFTD patients and controls improved when connectivity results were combined with neuropsychological outcomes, yielding an acceptable discrimination rate (87.4%). Moreover, connectivity metrics (72.2%) were better than neuropsychological ones (66.7%) to classify between bvFTD and AD patients. These findings highlight the relevance of EEG measures as potential biomarker signatures for early diagnosis, assessment of therapy response, and disease progression. Its potential implementation is also boosted by its affordable and massive application compared to other neuroimaging techniques (e.g., PET or MRI). Partially supported by grants from CONICET, CONICYT/FONDECYT Regular (1170010), FONDAP 15150012, INECO Foundation, and the Inter-American Development Bank.