Journal
NEUROIMAGE
Volume 244, Issue -, Pages -Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2021.118543
Keywords
Diffusion imaging; Functional MRI; Parcellation; Magnetoencephalography; Connectivity; Behavior; informatics
Funding
- NIH [U54MH091657, U01MH109589, U01AG052564, 5R24MH108315, 1R24MH122820]
- McDonnell Center for Systems Neuroscience at Washington University
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The Human Connectome Project (HCP) aims to accelerate advances in human neuroimaging by studying a large number of healthy young adults and sharing data and tools. The WU-Minn-Ox consortium has achieved its core objectives and emerged as a set of best-practice strategies for optimizing data acquisition and analysis.
The Human Connectome Project (HCP) was launched in 2010 as an ambitious effort to accelerate advances in hu-man neuroimaging, particularly for measures of brain connectivity; apply these advances to study a large number of healthy young adults; and freely share the data and tools with the scientific community. NIH awarded grants to two consortia; this retrospective focuses on the WU-Minn-Ox HCP consortium centered at Washington Uni-versity, the University of Minnesota, and University of Oxford. In just over 6 years, the WU-Minn-Ox consortium succeeded in its core objectives by: 1) improving MR scanner hardware, pulse sequence design, and image recon-struction methods, 2) acquiring and analyzing multimodal MRI and MEG data of unprecedented quality together with behavioral measures from more than 1100 HCP participants, and 3) freely sharing the data (via the Connec-tomeDB database) and associated analysis and visualization tools. To date, more than 27 Petabytes of data have been shared, and 1538 papers acknowledging HCP data use have been published. The HCP-style neuroimaging paradigm has emerged as a set of best-practice strategies for optimizing data acquisition and analysis. This article reviews the history of the HCP, including comments on key events and decisions associated with major project components. We discuss several scientific advances using HCP data, including improved cortical parcellations, analyses of connectivity based on functional and diffusion MRI, and analyses of brain-behavior relationships. We also touch upon our efforts to develop and share a variety of associated data processing and analysis tools along with detailed documentation, tutorials, and an educational course to train the next generation of neuroimagers. We conclude with a look forward at opportunities and challenges facing the human neuroimaging field from the perspective of the HCP consortium.
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