TY - JOUR
T1 - Mapping the coupling between tract reachability and cortical geometry of the human brain
AU - IMAGEN Consortium
AU - Li, Deying
AU - Zalesky, Andrew
AU - Wang, Yufan
AU - Wang, Haiyan
AU - Ma, Liang
AU - Cheng, Luqi
AU - Banaschewski, Tobias
AU - Barker, Gareth J
AU - Bokde, Arun L W
AU - Brühl, Rüdiger
AU - Desrivières, Sylvane
AU - Flor, Herta
AU - Garavan, Hugh
AU - Gowland, Penny
AU - Grigis, Antoine
AU - Heinz, Andreas
AU - Lemaitre, Herve
AU - Martinot, Jean-Luc
AU - Martinot, Marie-Laure Paillère
AU - Artiges, Eric
AU - Nees, Frauke
AU - Orfanos, Dimitri Papadopoulos
AU - Poustka, Luise
AU - Smolka, Michael N
AU - Vaidya, Nilakshi
AU - Walter, Henrik
AU - Whelan, Robert
AU - Schumann, Gunter
AU - Jia, Tianye
AU - Chu, Congying
AU - Fan, Lingzhong
PY - 2025/4/3
Y1 - 2025/4/3
N2 - 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.
AB - 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.
U2 - 10.1101/2025.03.31.646498
DO - 10.1101/2025.03.31.646498
M3 - Article
C2 - 40236130
SN - 2692-8205
JO - bioRxiv : the preprint server for biology
JF - bioRxiv : the preprint server for biology
ER -