Evidence map›Paper›PMID 41812241›Full record

ArticleCerebral cortex (New York, N.Y. : 1991)2026

The role of age in the relationship between brain structure and cognition: moderator or confound?

Ben Griffin, Chetan Gohil, Mark W Woolrich, Stephen M Smith, Diego Vidaurre

Abstract read
In one paragraph

Article in Cerebral cortex (New York, N.Y. : 1991), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Ben GriffinOxford Centre for Functional MRI of the Brain (FMRIB), Oxford Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Headley Way, Headington, Oxford, Oxfordshire OX3 9DU, United Kingdom.ORCID 0009-0000-7310-6074
Chetan GohilOxford Centre for Human Brain Activity (OHBA), Oxford Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Warneford Hospital, Warneford Lane, Headington, Oxford, Oxfordshire OX3 7JX, United Kingdom.ORCID 0000-0002-0888-1207
Mark W WoolrichOxford Centre for Human Brain Activity (OHBA), Oxford Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Warneford Hospital, Warneford Lane, Headington, Oxford, Oxfordshire OX3 7JX, United Kingdom.
Stephen M SmithOxford Centre for Functional MRI of the Brain (FMRIB), Oxford Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Headley Way, Headington, Oxford, Oxfordshire OX3 9DU, United Kingdom.
Diego VidaurreCenter of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Building 1710, Universitetsbyen 3, 8000 Aarhus, Denmark.ORCID 0000-0002-9650-2229

Funding

Dementia Platform UK RG94383/RG89702European Research Council ERC-StG-2019-850404Independent Research Fund Denmark 2034-00054BMedical Research CouncilNational Institute for Health and Care Research NIHR203316Novo Nordisk Foundation NNF19OC-0054895Wellcome Trust 106183/Z/14/ZWellcome Trust 215573/Z/19/Z
6 · The paper itself

Abstract

Understanding how differences in brain structure relate to differences in cognition across the lifespan is essential for addressing age-related cognitive decline. Since age is strongly associated with both brain structure and cognition, predictive models often risk simply capturing age effects. To mitigate this risk, deconfounding is typically applied to remove the effects of age. Here, beyond treating age as a confound, we treat it as a moderator by estimating brain-cognition associations separately across age groups. This captures age-stratified changes in how brain structure and cognitive performance are statistically connected. For this view to hold, variations in brain structure linked to differences in cognitive performance in older subjects (eg related to disease) would differ from those in younger subjects. Using structural brain imaging data from the UK Biobank we found an asymmetry in generalisability: models trained on younger subjects successfully predicted cognition in older subjects, but models trained on older subjects failed to generalize to younger individuals. These findings reveal a trade-off between model specificity and generalisability, suggesting the optimal approach-whether age-specific or pooled-depends on the research or clinical goal for the target population.

Indexed as

AgingBrainCognitionAdultAgedAged, 80 and overAge FactorsFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedUK Biobankelastic net regressionindividual differenceslifespan neurosciencemoderation analysisstructural MRI

Identifiers

PMID41812241
PMCPMC13017657

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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.