Functionally annotated electrophysiological neuromarkers of healthy ageing and memory function

Area of Science:

• Neuroscience
• Gerontology
• Biomedical Engineering

Background:

• Increasing life expectancy necessitates understanding ageing, both healthy and pathological.
• Electroencephalography (EEG) is valuable for identifying cognitive ageing neuromarkers due to cost-effectiveness and data richness.
• Contradictory findings and reproducibility issues hinder clinical translation of EEG in ageing research.

Purpose of the Study:

• To introduce a comprehensive, reproducible workflow for investigating static and dynamic EEG neuromarkers of cognitive ageing.
• To assess the sensitivity, robustness, and interpretability of EEG neuromarkers.
• To clarify the role of alpha power in cognitive performance versus ageing.

Main Methods:

• Utilized a large dataset to investigate static and dynamic power and connectivity estimates.
• Assessed marker robustness against variations in frequency band specifications.
• Employed functionally annotated brain networks for improved interpretability and multi-modal integration.

Main Results:

• Dynamic EEG neuromarkers demonstrated greater sensitivity and robustness compared to static markers.
• Replicated established EEG findings in cognitive ageing, including alpha slowing and altered connectivity.
• Individual alpha power was linked to memory performance, not ageing itself.

Conclusions:

• Dynamic neuromarkers are strong candidates for reliable cognitive ageing assessment.
• The developed workflow enhances interpretability and multi-modal integration of EEG findings.
• Functional annotation of brain networks provides insights into electrophysiological mechanisms of memory and ageing.