AFFORDABLE EEG MARKERS FOR THE SCREENING OF COGNITIVE IMPAIRMENT OF OLD ADULTS

Abstract

Detecting cognitive impairment in its early stage is important for timely care for dementia. Clinically useful markers for the purpose of screening of dementia should be easy to use, low cost and simple to implement to clinical setting. Numerous studies showed that electroencephalography (EEG) was one of such candidates to be used to detect early signs of brain dysfunction. The objective of this study is to investigate whether cognitive impairment can be explained by resting-state electroencephalography (EEG) markers reflecting the slowing of the intrinsic EEG oscillations in the eyes-closed resting-state. As a part of Brain Aging Map Project in Uiryeong County, Korea, we conducted the Korean version of Mini-Mental State Examination (MMSE) and measured resting-state EEG among other investigations in aged community dwellers over 50 years old or older from September 2017 to January 2018. As a result, a total of 500 were recruited. Excluding 4 participants under age 50 years old, a total of 496 (males=163, females=331) were included in the analysis. According to the MMSE score, we categorized the participants in one of the four cognitive stages, namely, M4 (MMSE 26-30), M3 (MMSE 21-25), M2 (MMSE 16-20), and M1 (MMSE 0-15). The resting-state EEG markers of median frequency, peak frequency, and alpha-to-theta ratio decreased monotonically as the MMSE scores decreased from M4 to M1 (p<0.001), and the decreases were more significant between M4 and M3 for males and between M3 and M2 stages for females. Finally, we developed a prediction model for the MMSE scores using the resting-state EEG markers with demographic covariates of sex, age and education level. As a result, we obtained the intra-class correlation coefficient between the MMSE scores and model-predicted values up to 0.748.