PofoliaShared via Pofolia

eLife· 2026Q1

Robust and replicable effects of ageing on resting-state brain electrophysiology measured with MEG

Andrew J. Quinn, Jemma Pitt, Oliver Kohl, Chetan Gohil et al.

Short summary

Ageing robustly affects resting-state brain activity across frequencies and locations, replicable across datasets and largely independent of covariates like grey matter volume.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Ageing significantly impacts neuronal oscillations across a wide range of frequencies and spatial locations.
  • The observed age effect on brain activity is replicable across multiple open-access MEG datasets.
  • The effect remains robust to common sources of inter-subject variability and partially robust to grey matter volume.
  • Effect sizes vary across space and frequency, necessitating careful sample-size planning for future studies.

AI-generated from the title and abstract; the full text is not read.

Abstract

Abstract Non-invasive recordings using brain electrophysiology provide credible insights into decline in neuronal functioning with age. New approaches are required to translate these results into compelling clinical metrics and meet the global challenge of preserving brain health in ageing. Changes in neuronal dynamics with ageing are observable in the power spectra of EEG and MEG recordings. Highly promising candidates for electrophysiological markers have been identified, but progress is hindered by substantial methodological variability across studies. This makes it challenging to establish a clear consensus on the frequency, location, and direction of any single reported effect within the larger body of research. We estimate a full-frequency whole-head profile of the ageing effect on eyes-closed resting-state MEG using the GLM-Spectrum. This data representation is easily sharable, facilitates meta-analyses and provides a framework for estimating statistical power of age effects for future study planning. We use this to show that the effect of age replicates across open-access MEG datasets and is robust to modelling of common covariates. Distinct components within the full frequency profile have different effect sizes, indicating that sample-size planning for ageing effects must consider the specific features of interest. The frequency profile of ageing is strongly robust to a range of common covariates and partially robust to modelling of grey matter volume. We establish that what seems a well-powered study may become underpowered when analyses target an age effect that is linearly separable from an age-relevant covariate such as grey matter volume. These results provide a pathway towards formal comparison and assessment of candidate markers for brain health in ageing. Graphical Abstract Highlights There is a strong effect of ageing across the adult lifespan on neuronal oscillations across a range of frequencies and spatial locations. The effect is replicable across multiple open-access datasets. The effect is robust to a range of sources of inter-subject variability. The age effect has heterogeneous effect size across space and frequency with implications for future study planning.

The authors' abstract, as published at the source. eLife, 2026 · DOI ↗

TakeawaysPremium
Ask the paperFree account

Continue with a free account

Ask the paper: 3 free questions a day about this paper; save it, get its citation, new summaries every day for your field. Takeaways are Premium.

Continue free on the web

Sign in with Google or Apple; no card needed. You come back to this paper.

On your phone:

Field: Cognitive Neuroscience

Cognitive NeuroscienceNeuroscience