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Effects of Age on Resting‐State Cortical Networks

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 ( N $$ N $$ = 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 ( δ $$ \delta $$ , θ $$ \theta $$ , α $$ \alpha $$ , β $$ \beta $$ , γ $$ \gamma $$ ), 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 ( δ $$ \delta $$ , θ $$ \theta $$ ) power and increases in high‐frequency ( β $$ \beta $$ ) 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.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1002/hbm.70516

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Institution:
University of Oxford
Role:
Author
ORCID:
0000-0002-0888-1207
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Institution:
University of Oxford
Role:
Author
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Institution:
University of Oxford
Role:
Author
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Institution:
University of Oxford
Role:
Author


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Funder identifier:
https://ror.org/03dy4aq19
Grant:
220020448
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Funder identifier:
https://ror.org/029chgv08
Grant:
203139/Z/16/Z
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Funder identifier:
https://ror.org/02gq0fg61
More from this funder
Funder identifier:
10.13039/501100000265


Publisher:
Wiley
Journal:
Human Brain Mapping More from this journal
Volume:
47
Issue:
5
Article number:
e70516
Publication date:
2026-03-26
Acceptance date:
2026-03-14
DOI:
EISSN:
1097-0193
ISSN:
1065-9471


Language:
English
Keywords:
Pubs id:
2398159
Local pid:
pubs:2398159
Source identifiers:
3892174
Deposit date:
2026-03-27
ARK identifier:
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