Alpha-bumps as a potential neuromarker for screening mild cognitive impairment

Neurodegenerative disease like dementia is one of the most health challenges in the 21st century that lead to multiscale problems such as loss of activities of daily living (ADL), caregiver dependency, and economic burden. Early detection and prevention are key strategies in treating patients at the prodromal stage of dementia, also known as mild cognitive impairment (MCI). Growing literature points to the clinical application of electroencephalography (EEG) such as event-related potentials (ERPs) in memory encoding (Micanovic, 2014). While ERP is mainly used for cognitive assessment, it requires many trials of experiment and time-consuming being a gap for clinical application (Beres, 2017). Instead, alpha oscillations (~8-12Hz) in the EEG data can be used to track focused attention and discriminate between healthy versus various neuropsychiatric conditions: Parkinson's disease, stroke, autism spectrum disorder, schizophrenia, etc. (Giovanni, 2017). Alpha oscillation is also known to be stable, and hence, are tentatively more applicable in clinical settings. To test our hypothesis, we compared EEG bandpower during visuospatial attention cueing modified Eriksen Flanker’s task between 19 MCI patients and 19 cognitively intact subjects, controlled age and sex match between 55 and 82 years old. Both groups were screened by a standard neuropsychological test, Montreal Cognitive Assessment (MoCA) before recruitment. MCI with age-matched control showed a decrease in power between alpha-to-beta frequency, especially in alpha peak frequency (alpha bumps) as shown in figure below. Therefore, alpha bumps could be a potential screening neuromarker, which in the near future we aim to study neural oscillation in specific domains of cognitive decline. This approach will promisingly help in designing dementia prevention in the current precision medicine era.