Neurovale EEG Laboratory, Taubaté, SP, Brazil.
CECS - Engineering, Modelling and Applied Social Sciences Center, UFABC - Universidade Federal do ABC, Santo André, SP, Brazil.
Comput Methods Programs Biomed. 2017 Jan;138:13-22. doi: 10.1016/j.cmpb.2016.09.023. Epub 2016 Oct 18.
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.
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 O1, O2 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).
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.
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.
闭眼清醒脑电图(EEG)是阿尔茨海默病诊断的有用工具。然而,存在主导或罕见阿尔法节律的闭眼清醒 EEG。在本文中,我们表明,不考虑阿尔法节律随机选择 EEG 时段会导致基于 EEG 的阿尔茨海默病诊断出现偏差。
我们比较了轻度阿尔茨海默病患者和健康老年人中阿尔法节律超过 30%和低于 30%的 EEG 时段。我们根据 O1、O2 和 Oz 通道中阿尔法节律(8-13 Hz)的百分比,将时段分类为主导阿尔法情景和罕见阿尔法情景。相应地,我们将研究对象分为四组:17 名主导阿尔法情景对照组、15 名主导阿尔法情景轻度阿尔茨海默病患者、12 名罕见阿尔法情景健康老年人和 15 名罕见阿尔法情景轻度阿尔茨海默病患者。我们使用单向方差分析(ANOVA)测试寻找组间差异,然后使用事后多重比较(p<0.05),比较两种不同电极配置(顶枕部和中央)下其他四个已知频段(δ、θ、β和γ)的归一化能量值(%)。
进行事后多重比较后,对于两种电极配置,我们发现仅在罕见阿尔法情景下,轻度阿尔茨海默病患者和健康老年人在β和θ频段的能量(%)上存在显著差异。在任何一个频段中,主导阿尔法情景都没有发现差异。
这是第一项关于阿尔茨海默病清醒 EEG 的研究,报告了阿尔法节律对时段选择的影响,我们的结果表明,与最有可能的预期相反,较少同步的 EEG 时段(罕见阿尔法情景)比那些呈现丰富阿尔法(主导阿尔法情景)更好地区分轻度阿尔茨海默病。此外,我们发现时段选择在 qEEG 研究中是一个非常敏感的问题。因此,对于涉及静息状态 EEG 的阿尔茨海默病研究,我们建议时段选择策略应始终谨慎设计并进行详细解释。