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

Jungmi Choi,Soyoung Ryu,Gahye Kim,Young Gooun You,Youyoung Choi,Jaeuk U Kim,Boncho Ku,Segyeong Jung,Minji Kwon,Hoyeon Go,Eunjeong Park,Wonseok Cha,Miok Jo

doi:10.1038/s41598-019-46789-2

Abstract

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.

Highlights

At the clinical manifestation stage of dementia, irreversible brain damage is already present
The present study focused on the following EEG biomarkers (EEG variables) to explain the slowing of brain rhythms in a resting eyes-closed state: median frequency (MDF), peak frequency (PF) and the alpha-to-theta ratio (ATR), which have been reported to be suitable classification biomarkers for Alzheimer’s disease and mild cognitive impairment[17,18]
In examining the association between the EEG biomarkers and each Mini-Mental State Examination (MMSE) cognitive domain, namely, orientation to time and place, memory registration and recall, attention and calculation, language, visual construction, and decision making, we found the strongest association between EEG variables and the orientation to time and place, and the level of association was affected by sex, age or education level (Fig. 3 and Table 6)

Summary

Introduction

At the clinical manifestation stage of dementia, irreversible brain damage is already present. The objective of this study was to investigate whether the severity of cognitive decline could be explained by resting, eyes-closed prefrontal EEG biomarkers, with the aim of identifying low-cost, accessible, portable, and noninvasive biomarkers that could aid in the early detection of cognitive decline and in the prevention of dementia. To this end, in this study, we tested the hypothesis that three promising biomarkers of resting EEG rhythms are correlated with global cognitive status, as estimated by the MMSE

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Discussion

Conclusion