Estimating chronological age from the electrical activity of the brain: how EEG-age can be used as a marker of neural integrity

As the number of older adults around the globe increases, the need to understand age-related changes in the brain, and their effects on cognition, has become increasingly pressing as we seek to make progress in the early detection and treatment of conditions such as dementia. There is extensive literature on the effects of ageing on the EEG, such as a decline in Peak Alpha Frequency (PAF), but here, in a reversal of convention, we used the EEG power-frequency spectrum to estimate chronological age. The motivation for this approach was that an individual’s brain age might act as a marker of their neural integrity, whereby a discrepancy between chronological age and EEG-age could prove clinically informative by implicating deleterious conditions. With a sample of sixty healthy adults, whose ages ranged from 20 to 78 years, and using multivariate methods to analyse the broad EEG spectrum (0.1 to 45 Hz), strong positive correlations between chronological age and EEG-age emerged. Furthermore, EEG-age was a more accurate estimate and accounted for nearly twice as much variance in chronological age as the best PAF-based estimate of age, indicating that EEG-age is a more comprehensive measure of integrity. We conclude that EEG-age could become a biomarker for neural and cognitive integrity.