Predicting brain-age from multimodal imaging data captures cognitive impairment.

Abstract:

The disparity between the chronological age of an individual and their brain-age measured based on biological information has the potential to offer clinically relevant biomarkers of neurological syndromes that emerge late in the lifespan. While prior brain-age prediction studies have relied exclusively on either structural or functional brain data, here we investigate how multimodal brain-imaging data improves age prediction. Using cortical anatomy and whole-brain functional connectivity on a large adult lifespan sample (N=2354, age 19-82), we found that multimodal data improves brain-based age prediction, resulting in a mean absolute prediction error of 4.29 years. Furthermore, we found that the discrepancy between predicted age and chronological age captures cognitive impairment. Importantly, the brain-age measure was robust to confounding effects: head motion did not drive brain-based age prediction and our models generalized reasonably to an independent dataset acquired at a different site (N=475). Generalization performance was increased by training models on a larger and more heterogeneous dataset. The robustness of multimodal brain-age prediction to confounds, generalizability across sites, and sensitivity to clinically-relevant impairments, suggests promising future application to the early prediction of neurocognitive disorders.

LHA-ID: 7Q6RC7XWU8-2

PubMed ID: 27890805

Projects: LIFE Adult

Journal: Neuroimage

Human Diseases: No Human Disease specified

Citation: Neuroimage. 2017 Mar 1;148:179-188. doi: 10.1016/j.neuroimage.2016.11.005. Epub 2016 Nov 23.

Date Published: 1st Mar 2017

Authors: F. Liem, G. Varoquaux, J. Kynast, Frauke Beyer, S. Kharabian Masouleh, J. M. Huntenburg, L. Lampe, M. Rahim, A. Abraham, R. C. Craddock, Steffi Gerlinde Riedel-Heller, Tobias Luck, Markus Löffler, M. L. Schroeter, A. V. Witte, A. Villringer, D. S. Margulies

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Created: 13th May 2019 at 08:15

Last updated: 13th May 2019 at 08:16

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