AUTHOR=Doan Dieu Ni Thi , Ku Boncho , Choi Jungmi , Oh Miae , Kim Kahye , Cha Wonseok , Kim Jaeuk U. 

TITLE=Predicting Dementia With Prefrontal Electroencephalography and Event-Related Potential

JOURNAL=Frontiers in Aging Neuroscience

VOLUME=13

YEAR=2021

URL=https://www.frontiersin.org/journals/aging-neuroscience/articles/10.3389/fnagi.2021.659817

DOI=10.3389/fnagi.2021.659817

ISSN=1663-4365

ABSTRACT=<p><bold>Objective</bold>: To examine whether prefrontal electroencephalography (EEG) can be used for screening dementia.</p><p><bold>Methods</bold>: We estimated the global cognitive decline using the results of Mini-Mental Status Examination (MMSE), measurements of brain activity from resting-state EEG, responses elicited by auditory stimulation [sensory event-related potential (ERP)], and selective attention tasks (selective-attention ERP) from 122 elderly participants (dementia, 35; control, 87). We investigated that the association between MMSE and each EEG/ERP variable by using Pearson’s correlation coefficient and performing univariate linear regression analysis. Kernel density estimation was used to examine the distribution of each EEG/ERP variable in the dementia and non-dementia groups. Both Univariate and multiple logistic regression analyses with the estimated odds ratios were conducted to assess the associations between the EEG/ERP variables and dementia prevalence. To develop the predictive models, five-fold cross-validation was applied to multiple classification algorithms.</p><p><bold>Results</bold>: Most prefrontal EEG/ERP variables, previously known to be associated with cognitive decline, show correlations with the MMSE score (strongest correlation has <italic>|r|</italic> = 0.68). Although variables such as the frontal asymmetry of the resting-state EEG are not well correlated with the MMSE score, they indicate risk factors for dementia. The selective-attention ERP and resting-state EEG variables outperform the MMSE scores in dementia prediction (areas under the receiver operating characteristic curve of 0.891, 0.824, and 0.803, respectively). In addition, combining EEG/ERP variables and MMSE scores improves the model predictive performance, whereas adding demographic risk factors do not improve the prediction accuracy.</p><p><bold>Conclusion</bold>: Prefrontal EEG markers outperform MMSE scores in predicting dementia, and additional prediction accuracy is expected when combining them with MMSE scores.</p><p><bold>Significance</bold>: Prefrontal EEG is effective for screening dementia when used independently or in combination with MMSE.</p>