Bipolar EEG Power Spectral Density Analysis of Resting-State for Multi-Level Cognitive Impairment Evaluation

Area of Science:

• Neuroscience
• Biomedical Engineering
• Clinical Neurology

Background:

• Dementia prevention is a major concern, with mild cognitive impairment (MCI) recognized as a precursor.
• Identifying reliable indicators of cognitive decline is crucial for timely intervention.
• Existing methods for cognitive assessment can be invasive or costly.

Purpose of the Study:

• To investigate the utility of bipolar electroencephalography (EEG) and power spectral density (PSD) features for differentiating cognitive impairment levels.
• To compare EEG-PSD features among healthy controls, MCI patients, and dementia patients.
• To develop predictive models for MCI and dementia using EEG data.

Main Methods:

• Utilized bipolar EEG to analyze regional brain waves and PSD.
• Compared absolute power, average power, and individualized alpha peak frequency across different brain areas.
• Included 50 healthy controls, 70 MCI patients, and 70 dementia patients.

Main Results:

• Dementia group exhibited significantly higher delta and theta band power and lower peak frequencies compared to controls and MCI.
• Significant differences between healthy controls and MCI were localized to low-frequency power in frontal, temporal, and parietal areas.
• Preliminary models for dementia and MCI achieved high performance (ROC AUC >81.7% and >63.79%, respectively).

Conclusions:

• Bipolar EEG-derived PSD features effectively differentiate cognitive impairment stages.
• These findings suggest a non-invasive, cost-effective approach for cognitive impairment evaluation.
• EEG-based PSD analysis holds potential for early detection and monitoring of cognitive decline progression.