Abstract
INTRODUCTION: Electroencephalographic (EEG) abnormalities, such as increased theta power, have been proposed as biomarkers for neurocognitive disorders. Advancements in amyloid positron emission tomography (PET) imaging have enhanced our understanding of the pathology of neurocognitive disorders, such as amyloid deposition. However, much remains unknown regarding the relationship between regional amyloid deposition and EEG abnormalities. This study aimed to explore the relationship between regional EEG abnormalities and amyloid deposition in patients with mild cognitive impairment (MCI). METHODS: We recruited 24 older adults with MCI from a community center for dementia prevention, and 21 participants were included in the final analysis. EEG was recorded using a 64-channel system, and amyloid deposition was measured using amyloid PET imaging. Magnetic resonance imaging (MRI) data were used to create individualized brain models for EEG source localization. Correlations between relative theta power and standardized uptake value ratios (SUVRs) in 12 brain regions were analyzed using Spearman's correlation coefficient. RESULTS: Significant positive correlations between relative theta power and SUVR values were found in several brain regions in the individualized brain model during the resting eyes-closed condition, including right temporal lobe (r = 0.581, p = 0.006), left hippocampus (r = 0.438, p = 0.047), left parietal lobe (r = 0.471, p = 0.031), right parietal lobe (r = 0.509, p = 0.018), left occipital lobe (r = 0.597, p = 0.004), and right occipital lobe (r = 0.590, p = 0.005). During the visual working memory condition, significant correlations were found in both cingulate lobes (left: r = 0.483, p = 0.027; right: r = 0.449, p = 0.041), left parietal lobe (r = 0.530, p = 0.010), right parietal lobe (r = 0.606, p = 0.004), left occipital lobe (r = 0.648, p = 0.001), and right occipital lobe (r = 0.657, p = 0.001). CONCLUSION: The result suggests that regional increases in relative theta power are associated with regional amyloid deposition in patients with MCI. These findings highlight the potential of EEG in detecting amyloid deposition. Future large-scale studies are needed to validate these preliminary findings and explore their clinical applications.