  Background: Mild cognitive impairment (MCI) is often considered a precursor
to Alzheimer's disease (AD) due to the high rate of progression from MCI to AD.
Sensitive neural biomarkers may provide a tool for an accurate MCI diagnosis,
enabling earlier and perhaps more effective treatment. Despite the availability
of numerous neuroscience techniques, electroencephalography (EEG) is the most
popular and frequently used tool among researchers due to its low cost and
superior temporal resolution. Objective: We conducted a scoping review of EEG
and MCI between 2012 and 2022 to track the progression of research in this
field. Methods: In contrast to previous scoping reviews, the data charting was
aided by co-occurrence analysis using VOSviewer, while data reporting adopted a
Patterns, Advances, Gaps, Evidence of Practice, and Research Recommendations
(PAGER) framework to increase the quality of the results. Results:
Event-related potentials (ERPs) and EEG, epilepsy, quantitative EEG (QEEG), and
EEG-based machine learning were the research themes addressed by 2310
peer-reviewed articles on EEG and MCI. Conclusion: Our review identified the
main research themes in EEG and MCI with high-accuracy detection of seizure and
MCI performed using ERP/EEG, QEEG and EEG-based machine learning frameworks.
