Journal article
Individual variation underlying brain age estimates in typical development
G Ball, CE Kelly, R Beare, ML Seal
Neuroimage | ACADEMIC PRESS INC ELSEVIER SCIENCE | Published : 2021
Abstract
Typical brain development follows a protracted trajectory throughout childhood and adolescence. Deviations from typical growth trajectories have been implicated in neurodevelopmental and psychiatric disorders. Recently, the use of machine learning algorithms to model age as a function of structural or functional brain properties has been used to examine advanced or delayed brain maturation in healthy and clinical populations. Termed ‘brain age’, this approach often relies on complex, nonlinear models that can be difficult to interpret. In this study, we use model explanation methods to examine the cortical features that contribute to brain age modelling on an individual basis. In a large coh..
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Awarded by National Institute of Mental Health
Funding Acknowledgements
This research was conducted within the Developmental Imaging research group, Murdoch Childrens Research Institute and the Children's MRI Centre, Royal Children's Hospital, Melbourne, Victoria. It was supported by the Murdoch Childrens Research Institute, the Royal Children's Hospital, Department of Paediatrics, The University of Melbourne and the Victorian Government's Operational Infrastructure Support Program. The project was generously supported by RCH1000, a unique arm of The Royal Children's Hospital Foundation devoted to raising funds for research at The Royal Children's Hospital.r Data and/or research tools used in the preparation of this manuscript can be obtained from the controlled access datasets distributed from the NIMH-supported Research Domain Criteria Database (RDoCdb) . RDoCdb is a collaborative informatics system created by the National Institute of Mental Health to store and share data resulting from grants funded through the Research Domain Criteria (RDoC) project.