Brain age prediction accuracy of individual nodes.
REGRESSION
We reiterated the model training procedure for each of the nodes separately. We extracted the row of each node in the resting-state functional connectivity (RSFC) matrix, which represents all the nodes’ connections with the rest of the brain, or its ‘connectivity fingerprint’. As in the original model, we used a linear support vector regression fitted on the Nathan Kline Institute (NKI) dataset, then tested it on the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) dataset. Prediction accuracy was quantified as the correlation between chronological age and predicted age. (