Fig. 5: Prediction of subjects’ clinical measures using task contrast maps and resting-state connectome on UK Biobank.

We predicted subjects’ clinical measures in the UK Biobank dataset using three modalities: synthetic task contrast maps, actual task contrast maps, and resting-state connectome data. resting-state connectome, actual contrast map from the EMOTION task, and seven synthetic task contrast maps. All predictions were made using L2 regularized regression (i.e., ridge regression) within a 5-fold cross-validation framework. Permutation testing \((P=1000)\) was used to assess the significance of out-of-sample performance against a null distribution. Actual and synthetic brain measures are depicted in blue and red colors, respectively. Note that only the EMOTION task has both actual and predicted contrast maps on UKB, indicated in blue and red, while the remaining six tasks are indicated in red as UKB does not provide them. Significant predictions based on permutation testing are highlighted. Colored horizontal lines indicate mean prediction performance. Balanced accuracy was used to measure hypertension classification performance, while Pearson’s correlation was employed to assess other variables. Sample sizes for all analyses are indicated in each figure. Test statistics were only performed between predictions surviving permutation testing. The detailed test statistics are given in Supplementary Tables 16, 17, and 22–24. The results for the additional clinical measures are depicted in Supplementary Fig. 19.