Fig. 4. Prediction accuracy of functional topography varies systematically along the S-A axis.

The sensorimotor-association (S-A) axis represents a hierarchy of cortical organization. The prediction accuracies of models trained on each PFN independently are significantly associated with the rank of each PFN along the S-A axis as shown by statistically significant Spearman correlations (two-sided) for the 17 networks across all three cognitive domains: general cognition (left), executive function (middle), and learning/memory (right). Shaded gray error bands represent 95% confidence intervals. Note: average S-A axis ranks for each PFN are z-scored for visualization purposes. Inset histograms depict the distribution of Spearman correlations between rank and prediction accuracy for 1000 spin-based permutations of the S-A axis, with the vertical line showing the true Spearman correlation value.