Journal
NEUROIMAGE
Volume 80, Issue -, Pages 105-124Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2013.04.127
Keywords
Human Connectome Project; Image analysis pipeline; Surface-based analysis; CIFTI; Grayordinates; Multi-modal data integration
Funding
- NIH [F30 MH097312]
- Human Connectome Project from the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research and NIH [1U54MH091657-01, ROI MH-60974]
- National Center for Research Resources [P41-RR14075]
- NOT BIRN Morphometric Project [BIRN002, U24 RR021382]
- National Institute for Biomedical Imaging and Bioengineering [R01EB006758]
- National Institute on Aging [AG022381, 5R01AG008122-22]
- National Center for Alternative Medicine [RC1 AT005728-01]
- National Institute for Neurological Disorders and Stroke [R01 NS052585-01, 1R21NS072652-01, 1R01NS070963]
- Shared Instrumentation Grant [1S10RR023401, 1S10RR019307, 1S10RR023043]
- Autism & Dyslexia Project
- Ellison Medical Foundation
- NIH Blueprint for Neuroscience Research, part of the multi-institutional Human Connectome Project [5U01-MH093765]
- MRC [G0800578] Funding Source: UKRI
- Biotechnology and Biological Sciences Research Council [BB/C519938/1] Funding Source: researchfish
- Medical Research Council [G0800578] Funding Source: researchfish
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The Human Connectome Project (HCP) faces the challenging task of bringing multiple magnetic resonance imaging (MRI) modalities together in a common automated preprocessing framework across a large cohort of subjects. The MRI data acquired by the HCP differ in many ways from data acquired on conventional 3 Tesla scanners and often require newly developed preprocessing methods. We describe the minimal preprocessing pipelines for structural, functional, and diffusion MRI that were developed by the HCP to accomplish many low level tasks, including spatial artifact/distortion removal, surface generation, cross-modal registration, and alignment to standard space. These pipelines are specially designed to capitalize on the high quality data offered by the HCP. The final standard space makes use of a recently introduced CIFTI file format and the associated grayordinate spatial coordinate system. This allows for combined cortical surface and subcortical volume analyses while reducing the storage and processing requirements for high spatial and temporal resolution data. Here, we provide the minimum image acquisition requirements for the HCP minimal preprocessing pipelines and additional advice for investigators interested in replicating the HCP's acquisition protocols or using these pipelines. Finally, we discuss some potential future improvements to the pipelines. (C) 2013 Elsevier Inc. All rights reserved.
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