Advances in diffusion MRI acquisition and processing in the Human Connectome Project

Stamatios N. Sotiropoulos, Saad Jbabdi, Junqian Xu, Jesper L. Andersson, Steen Moeller, Edward J. Auerbach, Matthew F. Glasser, Moises Hernandez, Guillermo Sapiro, Mark Jenkinson, David A. Feinberg, Essa Yacoub, Christophe Lenglet, David C. Van Essen, Kamil Ugurbil, Timothy E.J. Behrens

Research output: Contribution to journalArticlepeer-review

659 Scopus citations


The Human Connectome Project (HCP) is a collaborative 5-year effort to map human brain connections and their variability in healthy adults. A consortium of HCP investigators will study a population of 1200 healthy adults using multiple imaging modalities, along with extensive behavioral and genetic data. In this overview, we focus on diffusion MRI (dMRI) and the structural connectivity aspect of the project. We present recent advances in acquisition and processing that allow us to obtain very high-quality in-vivo MRI data, whilst enabling scanning of a very large number of subjects. These advances result from 2. years of intensive efforts in optimising many aspects of data acquisition and processing during the piloting phase of the project. The data quality and methods described here are representative of the datasets and processing pipelines that will be made freely available to the community at quarterly intervals, beginning in 2013.

Original languageEnglish (US)
Pages (from-to)125-143
Number of pages19
StatePublished - Oct 15 2013

Bibliographical note

Funding Information:
We acknowledge the support from the Human Connectome Project ( 1U54MH091657-01 ), from the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research, plus grants P41 EB015894 , P30 NS057091 , P30 NS076408 and R01 MH60974 . Computations were performed using the facilities of the Washington University Center for High Performance Computing, which were partially provided through grant NCRR 1S10RR022984-01A1 . Members of the WU-Minn HCP Consortium are listed at and .


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