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Human Brain Mapping
Article . 2026 . Peer-reviewed
License: CC BY
Data sources: Crossref
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https://doi.org/10.1101/2024.0...
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
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PURE Aarhus University
Article . 2026
License: CC BY
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Effects of Age on Resting‐State Cortical Networks

Authors: Chetan Gohil; Oliver Kohl; Jemma Pitt; Mats W.J. van Es; Andrew J Quinn; Diego Vidaurre; Martin R Turner; +2 Authors

Effects of Age on Resting‐State Cortical Networks

Abstract

ABSTRACT Understanding how ageing affects brain function remains a central challenge in neuroscience. Electrophysiological brain imaging techniques provide a near‐direct measure of neuronal activity, which is useful for characterising neurophysiological health. They offer us the ability to track large‐scale networks of functional activity with high temporal precision. The effects of healthy ageing on these networks remain poorly understood, in part due to small sample sizes and limited control for confounding factors in previous studies. Here, we analysed resting‐state source‐reconstructed magnetoencephalography (MEG) data from a large cross‐sectional cohort of healthy adults ( = 612, 18–88 years old) to characterise the effect of age using not only time‐averaged (static), but also transient (dynamic) network activity. We examined time‐averaged power and coherence across canonical frequency bands (, , , , ), as well as transient network dynamics identified using Hidden Markov Modelling. We included many confounding variables known to be affected by age, such as brain volume, as well as head size and position, which have previously been overlooked. Ageing was associated with frequency‐specific changes in oscillatory power, with decreases in low‐frequency (, ) power and increases in high‐frequency () power. Coherence increased across all frequency bands and was positively associated with cognitive performance. Transient network analyses additionally revealed that frontal network occurrences declined with age, with evidence suggesting a compensatory role in supporting cognition. These findings provide a more comprehensive electrophysiological signature for healthy ageing and establish a baseline for detecting pathological change.

Country
United Kingdom
Keywords

MEG, ageing, networks, oscillations, dynamics, HMM

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green
gold
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