Connectome-based spatial statistics enabling large-scale population analyses of human connectome across cohorts
UK Biobank participants together with five independent lifespan cohorts, we evaluated the streamline-, voxel- and network-level measures in the aspects of reliability, heritability, structure-function coupling, cognitive and behavioral prediction, brain aging patterns and lifespan trajectories across cohorts. The systematic evaluation workflow compares population-level white-matter representations across methods, spatial scales, tasks and datasets. The results support CBSS as a common connectome reference for large-scale, cross-cohort diffusion MRI studies.
Authors
- X. Qian
- Jason L. Stein (ORCID: https://orcid.org/0000-0003-4829-0513)
- Thomas E. Nichols (ORCID: https://orcid.org/0000-0002-4516-5103)
- H. Zhu
- Martín G. Cole (ORCID: https://orcid.org/0000-0002-4645-8856)
- Tengfei Li (ORCID: https://orcid.org/0000-0001-6142-3865)
- Xiaohai Wang (ORCID: https://orcid.org/0000-0002-1931-7708)
- Zhiwen Jiang (ORCID: https://orcid.org/0000-0001-8841-618X)
- Zehui Sun
- Zhengwu Zhang
- Tianyou Luo
- Maxime Descoteaux
- Shan Gao
Institutions
- University of North Carolina at Chapel Hill (US)
- Université de Sherbrooke (CA)
- Purdue University West Lafayette (US)
- Yale University (US)
- University of Oxford (GB)
- University of Rochester (US)
Publication Details
- Journal
- bioRxiv (Cold Spring Harbor Laboratory)
- Published
- 2026-04-10
- DOI
- https://doi.org/10.64898/2026.04.09.717492
- Primary Topic
- Functional Brain Connectivity Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institute on Aging