Journal
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
Volume 138, Issue -, Pages 13-22Publisher
ELSEVIER IRELAND LTD
DOI: 10.1016/j.cmpb.2016.09.023
Keywords
Alzheimer's disease; Alpha rhythm; Cognitive state; Quantitative EEG; Resting-state EEG
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Funding
- Sao Paulo Research Foundation (FAPESP) [2015/09510-7]
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Background and objective: Eyes-closed-awake electroencephalogram (EEG) is a useful tool in the diagnosis of Alzheimer's. However, there is eyes-closed-awake EEG with dominant or rare alpha rhythm. In this paper, we show that random selection of EEG epochs disregarding the alpha rhythm will lead to bias concerning EEG-based Alzheimer's Disease diagnosis. Methods: We compared EEG epochs with more than 30% and with less than 30% alpha rhythm of mild Alzheimer's Disease patients and healthy elderly. We classified epochs as dominant alpha scenario and rare alpha scenario according to alpha rhythm (8-13 Hz) percentage in 01, 02 and Oz channels. Accordingly, we divided the probands into four groups: 17 dominant alpha scenario controls, 15 mild Alzheimer's patients with dominant alpha scenario epochs, 12 rare alpha scenario healthy elderly and 15 mild Alzheimer's Disease patients with rare alpha scenario epochs. We looked for group differences using one-way ANOVA tests followed by post-hoc multiple comparisons (p < 0.05) over normalized energy values (%) on the other four well-known frequency bands (delta, theta, beta and gamma) using two different electrode configurations (parieto-occipital and central). Results: After carrying out post-hoc multiple comparisons, for both electrode configurations we found significant differences between mild Alzheimer's patients and healthy elderly on beta- and theta-energy (%) only for the rare alpha scenario. No differences were found for the dominant alpha scenario in any of the five frequency bands. Conclusions: This is the first study of Alzheimer's awake-EEG reporting the influence of alpha rhythm on epoch selection, where our results revealed that, contrarily to what was most likely expected, less synchronized EEG epochs (rare alpha scenario) better discriminated mild Alzheimer's than those presenting abundant alpha (dominant alpha scenario). In addition, we find out that epoch selection is a very sensitive issue in qEEG research. Consequently, for Alzheimer's studies dealing with resting state EEG, we propose that epoch selection strategies should always be cautiously designed and thoroughly explained. (C) 2016 Elsevier Ireland Ltd. All rights reserved.
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