Pitfalls in brain age analyses

Hum Brain Mapp. 2021 Sep;42(13):4092-4101. doi: 10.1002/hbm.25533. Epub 2021 Jun 30.

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.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Age Factors
  • Brain / diagnostic imaging*
  • Brain / physiology*
  • Humans
  • Models, Theoretical*
  • Neuroimaging / methods*