Estimating Chronological Age From the Electrical Activity of the Brain: How EEG ‐Age Can Be Used as a Marker of General Brain Functioning

With an aging global population, the number of older adults with age‐related changes in the brain, including dementia, will continue to increase unless we can make progress in the early detection and treatment of such conditions. There is extensive literature on the effects of aging on the EEG, particularly a decline in the 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 proxy for their general brain functioning, 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 analyze the broad EEG spectrum (0.1–45 Hz), strong positive correlations between chronological age and EEG age emerged. Furthermore, EEG age was a more accurate estimate and accounted for more variance in chronological age than well‐established PAF‐based estimates of age, indicating that EEG age could be a more comprehensive measure of general brain functioning. We conclude that EEG age could become a biomarker for neural and cognitive integrity.

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Aston Publications Explorer (Aston University)
Published
2025-03-01
Primary Topic
Prenatal Screening and Diagnostics
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article

Estimating Chronological Age From the Electrical Activity of the Brain: How EEG ‐Age Can Be Used as a Marker of General Brain Functioning

Aston Publications Explorer (Aston University)
Prenatal Screening and Diagnostics
article

Estimating Chronological Age From the Electrical Activity of the Brain: How EEG ‐Age Can Be Used as a Marker of General Brain Functioning

article en

Abstract

With an aging global population, the number of older adults with age‐related changes in the brain, including dementia, will continue to increase unless we can make progress in the early detection and treatment of such conditions. There is extensive literature on the effects of aging on the EEG, particularly a decline in the 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 proxy for their general brain functioning, 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 analyze the broad EEG spectrum (0.1–45 Hz), strong positive correlations between chronological age and EEG age emerged. Furthermore, EEG age was a more accurate estimate and accounted for more variance in chronological age than well‐established PAF‐based estimates of age, indicating that EEG age could be a more comprehensive measure of general brain functioning. We conclude that EEG age could become a biomarker for neural and cognitive integrity.

Aston Publications Explorer (Aston University)
Aston University
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Prenatal Screening and Diagnostics
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Estimating Chronological Age From the Electrical Activity of the Brain: How EEG ‐Age Can Be Used as a Marker of General Brain Functioning · Aston Publications Explorer (Aston University) (2025) | TGRS Research Map | TGRS