Pitfalls in brain age analyses
- PMID: 34190372
- PMCID: PMC8357007
- DOI: 10.1002/hbm.25533
Pitfalls in brain age analyses
Abstract
Over the past decade, there has been an abundance of research on the difference between age and age predicted using brain features, which is commonly referred to as the "brain age gap." Researchers have identified that the brain age gap, as a linear transformation of an out-of-sample residual, is dependent on age. As such, any group differences on the brain age gap could simply be due to group differences on age. To mitigate the brain age gap's dependence on age, it has been proposed that age be regressed out of the brain age gap. If this modified brain age gap is treated as a corrected deviation from age, model accuracy statistics such as R2 will be artificially inflated to the extent that it is highly improbable that an R2 value below .85 will be obtained no matter the true model accuracy. Given the limitations of proposed brain age analyses, further theoretical work is warranted to determine the best way to quantify deviation from normality.
Keywords: age; brain; development; deviation; prediction; residual.
© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.
Conflict of interest statement
The authors declare no conflict of interest.
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References
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- Alam, S. B., Nakano, R., & Kobashi, S. (2016). Brain age estimation using multiple regression analysis in brain MR images. IJICIC, 12(4), 1385–1396.
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