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. 2018 Oct 24;10:317. doi: 10.3389/fnagi.2018.00317

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Copyright © 2018 Le, Kuplicki, McKinney, Yeh, Thompson, and Paulus.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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BrainAGE simulation and analysis framework (Equations 2–4). (A) Linear and non-linear age basis functions (ABFs) f_i (orange, black, and blue lines). For a particular individual i, the ABFs are combined to create volume k's gray matter proportion v_ik (orange, black, and blue arrows) and age-dependent covariates of interest, Z_ij(A) with a different set of coefficients α_j. (B) Some of the Z_ij are then fed back into the w_ik when generating volume v_ik, which leads to two levels of age association between covariate and BrainAGE. (C) Proportional gray matter volume (volumetric data) generated from non-linear combinations of ABFs. (D) Predicted-age and BrainAGE computed from simulated volumetric data and simulated chronological age with Support Vector-based regression; (E) Test for association between BrainAGE and covariates of interest.