Harmonizing network-based statistics across different atlases in brain connectome analysis
Incorporating summary statistics across neuroimaging studies is important for enhancing translatability but poses challenges to connectomic analyses due to diverse methodological pipelines and brain atlases. We present TACOS (Transform brAin COnnectomes across atlaSes), a novel tool that translates network-based statistics across different atlases without requiring individual raw data. TACOS employs linear models based on anatomical information from brain parcellations and white matter fibers. Testing across 17 atlases, we show TACOS-transformed t-statistics to correlate well to the ground truth for both structural (r = 0.32-0.95) and functional networks (r = 0.57-0.95) using HCP surrogate statistics. These correlations remain consistent when tested with independent data from populations of different ancestries. Furthermore, TACOS effectively harmonizes connectomic results across multi-site schizophrenia data cohorts (r = 0.57-0.94 and 0.75-0.95 for structural and functional networks, respectively). This tool enables cross-atlas transformations of network-based statistics, showing great potential for downstream applications that share and combine multi-site connectomic data.
Authors
- Ting Qi (ORCID: https://orcid.org/0000-0002-4327-4365)
- Martijn P. van den Heuvel (ORCID: https://orcid.org/0000-0003-1570-1195)
- Yongbin Wei (ORCID: https://orcid.org/0000-0002-8044-7667)
- Long‐Biao Cui (ORCID: https://orcid.org/0000-0002-0784-181X)
- Dongxu Liu (ORCID: https://orcid.org/0000-0001-7393-7337)
- Yong Liu (ORCID: https://orcid.org/0000-0002-1862-3121)
- Qingyuan Liu (ORCID: https://orcid.org/0000-0001-9647-1381)
- Yahong Zhang (ORCID: https://orcid.org/0000-0002-1653-7027)
- Kun Zhao (ORCID: https://orcid.org/0000-0001-5260-4170)
Institutions
- Beijing University of Posts and Telecommunications (CN)
- Beijing Academy of Artificial Intelligence (CN)
- Amsterdam Neuroscience (NL)
- Second Affiliated Hospital of Xi'an Jiaotong University (CN)
- Xijing Hospital (CN)
- Xi'an Chest Hospital (CN)
- Vrije Universiteit Amsterdam (NL)
- Air Force Medical University (CN)
Publication Details
- Journal
- Communications Biology
- Published
- 2025-06-19
- DOI
- https://doi.org/10.1038/s42003-025-08341-z
- Citations
- 1
- Primary Topic
- Functional Brain Connectivity Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.43
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Beijing Municipality
- National Institutes of Health
- McDonnell Center for Systems Neuroscience
- Key Research and Development Projects of Shaanxi Province
- Natural Science Basic Research Program of Shaanxi Province