Connectomes for 40,000 UK Biobank participants: A multi-modal, multi-scale brain network resource

• Published in: NeuroImage (Orlando, Fla.) Vol. 283; p. 120407
• Main Authors: Mansour L., Sina, Di Biase, Maria A., Smith, Robert E., Zalesky, Andrew, Seguin, Caio
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 01.12.2023; Elsevier Limited; Elsevier
• Subjects: Biobanks; Brain Networks; Data resource; Functional Connectivity; Functional magnetic resonance imaging; Neural networks; Quality control; Structural Connectivity; Structure-function relationships; UK Biobank; United Kingdom > UK; Structural Connectivity; Brain Networks; Functional Connectivity; UK Biobank; Data resource
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2023.120407

We mapped functional and structural brain networks for more than 40,000 UK Biobank participants. Structural connectivity was estimated with tractography and diffusion MRI. Resting-state functional MRI was used to infer regional functional connectivity. We provide high-quality structural and functional connectomes for multiple parcellation granularities, several alternative measures of interregional connectivity, and a variety of common data pre-processing techniques, yielding more than one million connectomes in total and requiring more than 200,000 h of compute time. For a single subject, we provide 28 out-of-the-box versions of structural and functional brain networks, allowing users to select, e.g., the parcellation and connectivity measure that best suit their research goals. Furthermore, we provide code and intermediate data for the time-efficient reconstruction of more than 1000 different versions of a subject’s connectome based on an array of methodological choices. All connectomes are available via the UK Biobank data-sharing platform and our connectome mapping pipelines are openly available. In this report, we describe our connectome resource in detail for users, outline key considerations in developing an efficient pipeline to map an unprecedented number of connectomes, and report on the quality control procedures that were completed to ensure connectome reliability and accuracy. We demonstrate that our structural and functional connectivity matrices meet a number of quality control checks and replicate previously established findings in network neuroscience. We envisage that our resource will enable new studies of the human connectome in health, disease, and aging at an unprecedented scale. •We provide a brain network resource for more than 40,000 UK Biobank participants.•Diffusion MRI data was used to compute structural connectivity and resting-state functional MRI was used to infer regional functional connectivity.•For every individual, we provide 28 ready-to-use precomputed structural and functional brain networks for a range of alternative parcellations and connection metrics.•We provide supporting code and data enabling time-efficient reconstruction of more than 1000 different versions of an individual’s connectome.•A battery of quality control procedures was conducted to ensure connectome reliability and accuracy.