We published a research article in Imaging Neuroscience, demonstrating that the graph neural network accurately predicted unseen individuals’ functional connectivity from structural connectivity, reflecting a strong structure-function coupling. This coupling was primarily driven by network topology and was substantially stronger than that of the correlation approaches. Moreover, we observed that structure-function coupling was dominated by group-common effects, with subtle yet significant individual-specific effects. The regional group and individual effects of coupling were hierarchically organized across the cortex along a sensorimotor-association axis, with lower group and higher individual effects in association cortices. Big congratulations to Peiyu and Hang. Thank you to all our collaborators, especially our colleague Tatsuo and his team at CIBR. Check the paper: https://doi.org/10.1162/imag_a_00378