The sleep and wake electroencephalogram over the lifespan

Area of Science:

• Neuroscience
• Sleep Science
• Biomedical Engineering

Background:

• Electroencephalogram (EEG) patterns change throughout life, but comprehensive lifespan data, especially on microstructural changes, are limited.
• Previous research often focused on specific age groups or broader sleep/wake patterns, not detailed EEG microarchitecture across development and aging.

Purpose of the Study:

• To establish sex-stratified, age-specific reference norms for key sleep and wake electroencephalogram (EEG) parameters.
• To provide a benchmark for identifying deviations from healthy brain aging using EEG.
• To demonstrate the utility of these norms in detecting EEG alterations in clinical populations.

Main Methods:

• Collected sex-stratified EEG data from 3372 healthy participants aged 11 days to 80 years.
• Estimated age norms for absolute and relative power in delta, theta, alpha, and sigma bands.
• Quantified sleep spindle characteristics including density, amplitude, duration, and frequency.

Main Results:

• Developed comprehensive age-based normative values for sleep and wake EEG parameters.
• Demonstrated that these norms can highlight differences in EEG patterns in individuals with Alzheimer's disease, sleep apnea, depression, osteoarthritis, and osteoporosis compared to healthy controls.
• Sex-stratified analysis revealed specific age-related EEG trajectories.

Conclusions:

• Age-based EEG reference values provide an objective tool for screening deviations from healthy brain aging.
• These norms are valuable for assessing brain health across the lifespan and in individuals with various disorders.
• The findings underscore the importance of considering age and sex in EEG analysis for clinical applications.