Graph neural networks predict individual cognitive scores from structural connectomes

Abstract

Structural connectomes encode rich information about individual brain organisation. We train graph neural networks on diffusion-MRI-derived connectomes from 9,000 participants and show they outperform kernel baselines in predicting fluid intelligence, with attributions concentrated in fronto-parietal hubs.

Keywords

• connectomics
• graph neural networks
• cognition
• MRI