Li Deying, Zalesky Andrew, Wang Yufan, Wang Haiyan, Ma Liang, Cheng Luqi, Banaschewski Tobias, Barker Gareth J, Bokde Arun L W, Brühl Rüdiger, Desrivières Sylvane, Flor Herta, Garavan Hugh, Gowland Penny, Grigis Antoine, Heinz Andreas, Lemaître Hervé, Martinot Jean-Luc, Martinot Marie-Laure Paillère, Artiges Eric, Nees Frauke, Orfanos Dimitri Papadopoulos, Poustka Luise, Smolka Michael N, Vaidya Nilakshi, Walter Henrik, Whelan Robert, Schumann Gunter, Jia Tianye, Chu Congying, Fan Lingzhong
Beijing Key Laboratory of Brainnetome and Brain-Computer Interface, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Nat Commun. 2025 Aug 12;16(1):7489. doi: 10.1038/s41467-025-62812-9.
The study of cortical geometry and connectivity is prevalent in human brain research. However, these two aspects of brain structure are usually examined separately, leaving the essential connections between the brain's folding patterns and white matter connectivity unexplored. In this study, we aim to elucidate the fundamental links between cortical geometry and white matter tract connectivity. We develop the concept of tract-geometry coupling (TGC) by optimizing the alignment between tract connectivity to the cortex and multiscale cortical geometry. We confirm in two independent datasets that cortical geometry reliably characterizes tract reachability, and that TGC demonstrates high test-retest reliability and individual-specificity. Interestingly, low-frequency TGC is more heritable and behaviorally informative. Finally, we find that TGC can reproduce task-evoked cortical activation patterns and exhibits non-uniform maturation during youth. Collectively, our study provides an approach to mapping cortical geometry-connectivity coupling, highlighting how these two aspects jointly shape the connected brain.
皮质几何结构与连通性的研究在人类大脑研究中很普遍。然而,大脑结构的这两个方面通常是分开研究的,从而使大脑折叠模式与白质连通性之间的基本联系未得到探索。在本研究中,我们旨在阐明皮质几何结构与白质束连通性之间的基本联系。我们通过优化束连通性与皮质以及多尺度皮质几何结构之间的对齐,提出了束几何耦合(TGC)的概念。我们在两个独立的数据集中证实,皮质几何结构能够可靠地表征束可达性,并且TGC具有较高的重测信度和个体特异性。有趣的是,低频TGC具有更高的遗传性和行为信息性。最后,我们发现TGC能够重现任务诱发的皮质激活模式,并且在青少年时期表现出不均匀的成熟过程。总体而言,我们的研究提供了一种绘制皮质几何结构-连通性耦合的方法,突出了这两个方面如何共同塑造相互连接的大脑。