Lifespan Trajectories of Resting State EEG power

Area of Science:

• Neuroscience
• Human Physiology
• Biophysics

Background:

• Resting state electroencephalography (EEG) provides insights into brain function.
• Understanding age-related changes in EEG power and correlations is crucial for characterizing neural development and aging.
• Previous studies have not comprehensively analyzed both EEG power trajectories and inter/intra-frequency correlations across the lifespan.

Purpose of the Study:

• To analyze the developmental trajectories of resting state monopolar EEG power and power value correlations in a large cohort of healthy adults.
• To investigate sex differences in EEG power trajectories and correlations across the lifespan.
• To establish a baseline for future analyses of bipolar EEG power and coherence.

Main Methods:

• Analysis of resting state EEG data from 5238 participants (11906 observations) aged 12-70 from the Collaborative Study on the Genetics of Alcoholism (COGA).
• Inclusion of only participants without a history of alcohol use disorder.
• Calculation of EEG power using standard Fourier transform methods across seven frequency bands and 17 electrodes.
• Examination of means, variances, and correlations of power values, including inter-frequency and intra-frequency correlations.

Main Results:

• EEG power generally decreased from ages 12-20 across all frequency bands and sexes.
• Post-age 20, EEG power trajectories diverged, showing sex-specific patterns and regional variations, particularly in alpha and beta bands.
• Inter-frequency correlations (high alpha with theta and beta bands) showed a pervasive increase with age, primarily in anterior regions, with minimal sex differences.
• Intra-frequency correlations remained high and stable across age.

Conclusions:

• Resting state EEG power exhibits distinct developmental trajectories influenced by age and sex, particularly after adolescence.
• Increasing inter-frequency correlations with age suggest evolving functional connectivity and neural network maturation.
• This study provides a comprehensive analysis of EEG power and correlation dynamics, offering valuable data for understanding normative brain aging and development.