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Resting-state prefrontal EEG biomarkers in correlation with MMSE scores in elderly individuals

机译:静息状态前额叶脑电生物标志物与老年人个体的MMSE评分相关

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摘要

We investigated whether cognitive decline could be explained by resting-state electroencephalography (EEG) biomarkers measured in prefrontal regions that reflect the slowing of intrinsic EEG oscillations. In an aged population dwelling in a rural community (total = 496, males = 165, females = 331), we estimated the global cognitive decline using the Mini-Mental State Examination (MMSE) and measured resting-state EEG parameters at the prefrontal regions of Fp1 and Fp2 in an eyes-closed state. Using a tertile split method, the subjects were classified as T3 (MMSE 28–30, N = 162), T2 (MMSE 25–27, N = 179), or T1 (MMSE ≤ 24, N = 155). The EEG slowing biomarkers of the median frequency, peak frequency and alpha-to-theta ratio decreased as the MMSE scores decreased from T2 to T1 for both sexes (−5.19 ≤ t-value ≤ −3.41 for males and −7.24 ≤ t-value ≤ −4.43 for females) after adjusting for age and education level. Using a double cross-validation procedure, we developed a prediction model for the MMSE scores using the EEG slowing biomarkers and demographic covariates of sex, age and education level. The maximum intraclass correlation coefficient between the MMSE scores and model-predicted values was 0.757 with RMSE = 2.685. The resting-state EEG biomarkers showed significant changes in people with early cognitive decline and correlated well with the MMSE scores. Resting-state EEG slowing measured in the prefrontal regions may be useful for the screening and follow-up of global cognitive decline in elderly individuals.
机译:我们调查了认知下降是否可以用前额叶区域测量的静息状态脑电图(EEG)生物标志物来解释,该标志物反映了内在EEG振荡的减慢。在一个农村社区的老年人口中(总数= 496,男性= 165,女性= 331),我们使用最小精神状态考试(MMSE)估算了全球认知能力下降,并测量了额叶前额区的静息状态脑电参数Fp1和Fp2处于闭眼状态。使用三分位数拆分法,将受试者分为T3(MMSE 28–30,N = 162),T2(MMSE 25-27,N = 179)或T1(MMSE≤24,N = 155)。男女的MMSE分数从T2降低到T1,中位数频率,峰值频率和α-θ比的EEG减慢生物标志物降低(男性为−5.19≤t值≤-3.41,男性为−7.24≤t值调整年龄和教育水平后,女性≤≤−4.43)。使用双重交叉验证程序,我们使用EEG慢速生物标志物以及性别,年龄和教育水平的人口统计学变量,开发了MMSE分数的预测模型。 MMSE评分与模型预测值之间的类内最大相关系数为0.757,RMSE = 2.685。静息状态的脑电生物标志物在早期认知能力下降的人中表现出显着变化,并且与MMSE得分密切相关。在前额叶区域测得的静息状态脑电图减慢可能有助于筛查和随访老年个体的整体认知能力下降。

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