The minimal preprocessing pipelines for the Human Connectome Project

• Published in: NeuroImage (Orlando, Fla.) Vol. 80; pp. 105 - 124
• Main Authors: Glasser, Matthew F., Sotiropoulos, Stamatios N., Wilson, J. Anthony, Coalson, Timothy S., Fischl, Bruce, Andersson, Jesper L., Xu, Junqian, Jbabdi, Saad, Webster, Matthew, Polimeni, Jonathan R., Van Essen, David C., Jenkinson, Mark
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.10.2013; Elsevier Limited
• Subjects: Acquisitions & mergers; Algorithms; Brain; Brain - anatomy & histology; Brain - physiology; CIFTI; Connectome - methods; Cross-modal; Diffusion Tensor Imaging - methods; Grayordinates; Human Connectome Project; Humans; Image analysis pipeline; Image Interpretation, Computer-Assisted - methods; Medical imaging; Models, Anatomic; Models, Neurological; Multi-modal data integration; Nerve Net - anatomy & histology; Nerve Net - physiology; Neurosciences; Surface-based analysis; Human Connectome Project; Surface-based analysis; Image analysis pipeline; Multi-modal data integration; Grayordinates; CIFTI
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2013.04.127

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 3Tesla 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. •Multi-modal preprocessing pipelines for the Human Connectome Project•Description of CIFTI file format and grayordinate coordinate system•Combined surface and volume neuroimaging analysis