白质
神经科学
可达性
几何学
皮质(解剖学)
联轴节(管道)
集合(抽象数据类型)
物理
计算机科学
生物
数学
磁共振成像
算法
材料科学
医学
放射科
冶金
程序设计语言
作者
Deying Li,Andrew Zalesky,Yufan Wang,Haiyan Wang,Liang Ma,Luqi Cheng,Tobias Banaschewski,Gareth J. Barker,Arun L.W. Bokde,Rüdiger Brühl,Sylvane Desrivières,Herta Flor,Hugh Garavan,Penny Gowland,Antoine Grigis,Andreas Heinz,Hervé Lemaître,Jean‐Luc Martinot,Marie‐Laure Paillère Martinot,Éric Artiges
出处
期刊:
[Cold Spring Harbor Laboratory]
日期:2025-04-03
标识
DOI:10.1101/2025.03.31.646498
摘要
Abstract The study of cortical geometry and connectivity is prevalent in research on the human brain. 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 aimed to elucidate fundamental links between cortical geometry and white matter tract connectivity. We developed the concept of tract-geometry coupling (TGC) by optimizing the alignment between tract connectivity to the cortex and multiscale cortical geometry. Specifically, spectral analyses of the cortical surface yielded a set of geometrical eigenmodes, which were then used to explain the locations on the cortical surface reached by specific white matter tracts, referred to as tract reachability. In two independent datasets, we confirmed that tract reachability was well characterized by cortical geometry. We further observed that TGC had high test-retest ability and was specific to each individual. Interestingly, low-frequency TGC was found to be heritable and more informative than the high-frequency components in behavior prediction. Finally, we found that TGC could reproduce task-evoked cortical activation patterns. Collectively, our study provides a new approach to mapping coupling between cortical geometry and connectivity, highlighting how these two aspects jointly shape the connected brain.
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