Conversion from mild cognitive impairment to Alzheimer’s disease is predicted by sources and coherence of brain electroencephalography rhythms

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• 作者：P.M. Rossini ; C. Del Percio ; P. Pasqualetti ; E. Cassetta ; G. Binetti ; G. Dal Forno ; F. Ferreri ; G. Frisoni ; P. Chiovenda ; C. Miniussi ; et al.
• 刊名：Neuroscience
• 出版年：2006
• 期刊代码：50_03064522
• 类别：neu
• 出版时间：13 December 2006
• 卷：143
• 期：3
• 页码：793-803
• 文件大小：2675 K

摘要

Objective. Can quantitative electroencephalography (EEG) predict the conversion from mild cognitive impairment (MCI) to Alzheimer’s disease (AD)?

Methods. Sixty-nine subjects fulfilling criteria for MCI were enrolled; cortical connectivity (spectral coherence) and (low resolution brain electromagnetic tomography) sources of EEG rhythms (δ=2–4 Hz; θ=4–8 Hz; α 1=8–10.5 Hz; α 2=10.5–13 Hz: β 1=13–20 Hz; β 2=20–30 Hz; and γ=30–40) were evaluated at baseline (time of MCI diagnosis) and follow up (about 14 months later). At follow-up, 45 subjects were still MCI (MCI Stable) and 24 subjects were converted to AD (MCI Converted).

Results. At baseline, fronto-parietal midline coherence as well as δ (temporal), θ (parietal, occipital and temporal), and α 1 (central, parietal, occipital, temporal, limbic) sources were stronger in MCI Converted than stable subjects (P<0.05). Cox regression modeling showed low midline coherence and weak temporal source associated with 10%annual rate AD conversion, while this rate increased up to 40%and 60%when strong temporal δ source and high midline γ coherence were observed respectively.

Interpretation. Low-cost and diffuse computerized EEG techniques are able to statistically predict MCI to AD conversion.