Beta to Theta Power Ratio in Electroencephalogram Periodic Components to Discriminate Mild Cognitive Impairment and Alzheimer’s Dementia

Background Alzheimer’s disease dementia (AD) and mild cognitive impairment (MCI) are often associated with abnormalities in full power spectrum of electroencephalogram (EEG), including the ratio of beta/theta. Full spectrum EEG consists of aperiodic and periodic components with the latter being better associated with cognition. We investigated whether the aperiodic and periodic power components of EEGs are disrupted differently in individuals with MCI vs. AD vs. healthy controls (HC), and whether a periodic based beta/theta ratio better differentiates the three groups than a ratio based on the full spectrum. Method Data were collected in 199 participants ‐ 44 with HC (mean (SD) age: 69.1 (5.3) years), 114 with MCI (72.3 (7.5)), and 41 with AD (75.6 (6.5)). We cleaned the data using a band‐pass filter with cut‐off frequencies 1 and 45 Hz and then independent component analysis. We then used the “fooof” toolbox to decompose the EEGs into their aperiodic and periodic components. We used the area under the receiver operating characteristic curve (AUCROC) of a logistic regression classifier to distinguish HC from MCI and AD participants, and MCI from AD participants, using beta/theta ratios based on the periodic power spectrum vs. full power spectrum. Result There was an increase in full spectrum powers for delta, theta, and gamma, and a decrease of relative power for beta in AD participants compared to HC and MCI participants. In contrast, there were no differences in aperiodic background EEG components among HC, MCI, and AD participants. Overall, the periodic and full spectrum comparisons among the three groups were comparable except for the periodic based analysis that showed a difference between MCI and HC in the occipital beta/theta ratio (Bonferroni corrected p = 0.036). Classifiers based on beta/theta power ratio in EEG periodic components distinguished AD from HC and MCI with high AUCROC values (0.94 and 0.83, respectively), and outperformed classifiers based on beta/theta power ratio in EEG all oscillations (0.078 and 0.67, respectively). Conclusion This study supports an advantage of a periodic based analysis over a full EEG spectrum analysis and the use of occipital beta/theta power ratio based on periodic components as a screening tool for AD.