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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
medicine
Pitfalls in brain age analyses
Human Brain Mapping, Volume 42, No. 13, Year 2021
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Description
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. © 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.
Authors & Co-Authors
Ramadan, Rabie A.
United States, Philadelphia
Temple University
Ruparel, Kosha
United States, Philadelphia
University of Pennsylvania
Moore, Tyler M.
United States, Philadelphia
University of Pennsylvania
Satterthwaite, Theodore Daniel
United States, Philadelphia
University of Pennsylvania
Shou, Haochang
United States, Philadelphia
University of Pennsylvania
United States, Philadelphia
University of Pennsylvania Perelman School of Medicine
Gur, Ruben C.
United States, Philadelphia
University of Pennsylvania
Nichols, Thomas E.
United Kingdom, Oxford
University of Oxford
United Kingdom, Oxford
University of Oxford Medical Sciences Division
Shinohara, Russell Takeshi
United States, Philadelphia
University of Pennsylvania
United States, Philadelphia
University of Pennsylvania Perelman School of Medicine
Statistics
Citations: 34
Authors: 8
Affiliations: 6
Identifiers
Doi:
10.1002/hbm.25533
ISSN:
10659471