The Impact of Atlas Parcellation on Functional Connectivity Analysis Across Six Psychiatric Disorders
Neuropsychiatric disorders are associated with altered functional connectivity (FC); however, the reported regional patterns of functional alterations suffered from low replicability and high variability. This is partly because of differences in the atlas and delineation techniques used to measure FC-related deficits within/across disorders. We systematically investigated the impact of the brain parcellation approach on the FC-based brain network analysis. We focused on identifying the replicable FCs using three structural brain atlases, including Automated Anatomical Labeling (AAL), Brainnetome atlas (BNA) and HCP_MMP_1.0, and four functional brain parcellation approaches: Yeo-Networks (Yeo), Gordon parcel (Gordon) and two Schaefer parcelletions, among correlation, group difference, and classification tasks in six neuropsychiatric disorders: attention deficit and hyperactivity disorder (ADHD, n = 340), autism spectrum disorder (ASD, n = 513), schizophrenia (SZ, n = 200), schizoaffective disorder (SAD, n = 142), bipolar disorder (BP, n = 172), and major depression disorder (MDD, n = 282). Our cross-atlas/disorder analyses demonstrated that frontal-related FC deficits were reproducible in all disorders, independent of the atlasing approach; however, replicable FC extraction in other areas and the classification accuracy were affected by the parcellation schema. Overall, functional atlases with finer granularity performed better in classification tasks. Specifically, the Schaefer atlases generated the most repeatable FC deficit patterns across six illnesses. These results indicate that frontal-related FCs may serve as potential common and robust neuro-abnormalities across 6 psychiatric disorders. Furthermore, in order to improve the replicability of rsfMRI-based FC analyses, this study suggests the use of functional templates at larger granularity.
Authors
- Rongtao Jiang (ORCID: https://orcid.org/0000-0003-4657-0079)
- Zening Fu (ORCID: https://orcid.org/0000-0002-1591-4900)
- Peter Kochunov (ORCID: https://orcid.org/0000-0003-3656-4281)
- Juan Bustillo (ORCID: https://orcid.org/0000-0001-8730-8152)
- Xuyun Wen (ORCID: https://orcid.org/0000-0003-2230-8658)
- Jing Sui (Beijing Normal University), my correct affiliation is beijing normal university, not Qingdao University of Science and Technology, please correct the current affiliation. Thank you (ORCID: https://orcid.org/0000-0001-6837-5966)
- Xiaoya Wu (ORCID: https://orcid.org/0009-0005-4601-6846)
- Xiao Yang (ORCID: https://orcid.org/0000-0001-5527-1762)
- Chuang Liang (ORCID: https://orcid.org/0009-0003-7308-7944)
- Shile Qi
- Daoqiang Zhang
- Vince D. Calhoun (ORCID: https://orcid.org/0000-0002-8471-9287)
Institutions
- Georgia Institute of Technology (US)
- Emory University (US)
- University of New Mexico (US)
- Georgia State University (US)
- Sichuan University (CN)
- Beijing Normal University (CN)
- Yale University (US)
- West China Hospital of Sichuan University (CN)
- Center for Translational Research in Neuroimaging and Data Science (US)
- The University of Texas Health Science Center at Houston (US)
- Nanjing University of Aeronautics and Astronautics (CN)
Publication Details
- Journal
- Human Brain Mapping
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1002/hbm.70206
- Citations
- 7
- Primary Topic
- Functional Brain Connectivity Studies
- Type
- article
- Field-Weighted Citation Impact
- 10.02
Funders
- National Natural Science Foundation of China
- Government of Jiangsu Province
- Natural Science Foundation of Jiangsu Province
- Jiangsu Provincial Key Research and Development Program