An atlas of trait associations with resting-state and task-evoked human brain functional organizations in the UK Biobank

Author:

Zhao Bingxin12,Li Tengfei34,Li Yujue2,Fan Zirui12,Xiong Di5,Wang Xifeng5,Gao Mufeng5,Smith Stephen M.6,Zhu Hongtu45789

Affiliation:

1. Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA

2. Department of Statistics, Purdue University, West Lafayette, Indiana, USA

3. Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA

4. Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA

5. Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA

6. Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

7. Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA

8. Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA

9. Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA

Abstract

Abstract Functional magnetic resonance imaging (fMRI) has been widely used to identify brain regions linked to critical functions, such as language and vision, and to detect tumors, strokes, brain injuries, and diseases. It is now known that large sample sizes are necessary for fMRI studies to detect small effect sizes and produce reproducible results. Here, we report a systematic association analysis of 647 traits with imaging features extracted from resting-state and task-evoked fMRI data of more than 40,000 UK Biobank participants. We used a parcellation-based approach to generate 64,620 functional connectivity measures to reveal fine-grained details about cerebral cortex functional organizations. The difference between functional organizations at rest and during task was examined, and we have prioritized important brain regions and networks associated with a variety of human traits and clinical outcomes. For example, depression was most strongly associated with decreased connectivity in the somatomotor network. We have made our results publicly available and developed a browser framework to facilitate the exploration of brain function-trait association results (http://fmriatlas.org/).

Publisher

MIT Press

Reference85 articles.

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