Evidence map›Paper›PMID 40090876›Full record

ArticlePsychophysiology2025

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

Thomas M James, Adrian P Burgess

Abstract read
In one paragraph

Article in Psychophysiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Behavioral Phenotype Associations With Resting State EEG Signal Complexity and Power Spectral Density in Fragile X Syndrome.Autism research : official journal of the International Society for Autism Research · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Thomas M JamesAston Research Centre for Health in Ageing (ARCHA) and Aston Institute of Health and Neurodevelopment (IHN), College of Health and Life Sciences (HLS), School of Psychology, Aston University, Birmingham, UK.ORCID 0000-0002-3222-467X
Adrian P BurgessARCHA, HLS, School of Psychology, Aston University, Birmingham, UK.ORCID 0000-0002-0977-8105

Funding

Aston University
6 · The paper itself

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.

Indexed as

AgingBrainElectroencephalographyAdultAgedFemaleHumansMaleMiddle AgedYoung Adultaging brainbrain integritydementiaEEG power Spectrumhuman lifespanpartial least squares regressionpeak alpha frequencyresting state electroencephalography

Identifiers

PMID40090876
PMCPMC11911306

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.