Group-common and individual-specific effects of structure-function coupling in human brain networks with graph neural networks

bioRxiv [Preprint]. 2024 Mar 15:2023.11.22.568257. doi: 10.1101/2023.11.22.568257.

Abstract

The human cerebral cortex is organized into functionally segregated but synchronized regions bridged by the structural connectivity of white matter pathways. While structure-function coupling has been implicated in cognitive development and neuropsychiatric disorders, studies yield inconsistent findings. The extent to which the structure-function coupling reflects reliable individual differences or primarily group-common characteristics remains unclear, at both the global and regional brain levels. By leveraging two independent, high-quality datasets, we found 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 linear models. 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. These findings emphasize the importance of considering both group and individual effects in understanding cortical structure-function coupling, suggesting insights into interpreting individual differences of the coupling and informing connectivity-guided therapeutics.

Publication types

  • Preprint