Box 2: Accessing and using HCP data, software and protocols
Overview of the HCP's data sharing. ConnectomeDB (http://db.humanconnectome.org/) is the primary repository of HCP imaging, behavioral and demographic data. Three-tesla structural, functional and diffusion imaging data for ~1,100 subjects are shared in unprocessed, minimally preprocessed, and more extensively processed forms and staged over four major releases (Q1, Q1–Q3, S500, S900), with the final S1100 release slated for summer 2016. Seven-tesla data acquired on 180 subjects have been released in part, with the rest to follow shortly. Magnetoencephalography data acquired from 95 subjects give a window on fast temporal dynamics of the brain and were released in the fall of 2015 (ref. 115). Notably, the S900 release and the forthcoming S1100 release include the improved intersubject registration provided by MSMAll. The HCP_MMP1.0 parcellation is available in BALSA (https://balsa.wustl.edu/study/show/RVVG), and individual subject parcellations for each HCP subject will be released on ConnectomeDB in the future (anticipated in fall 2016).
HCP data set is much larger than those of past studies. With the high spatial and temporal resolution of HCP data, the data set is at least an order of magnitude larger than widely used open-access neuroimaging data sets such as ADNI (http://adni.loni.usc.edu)116. For a single subject, the compressed NIFTI-formatted unprocessed data are around 10 GB, and the preprocessed data are nearly 30 GB.
HCP data are widely used via multiple modes of data access. To date, >5,200 investigators have agreed to HCP open-access data-use terms (~520 to restricted-access terms for accessing family structure and other sensitive data). Users can (i) access ConnectomeDB directly to download packages for individual subjects, user-selected subject groups or HCP-specified groups; (ii) purchase Connectome-in-a-Box for the cost of the hard drives, which can be shared by investigators at a given institution; and (iii) access data via the Amazon cloud for processing on the cloud (or for download). Data downloaded directly from ConnectomeDB exceed 5,400 terabytes (TB), with an additional 2,000 TB transferred via hard drives (Connectome-in-a-Box) and the Amazon cloud.
Data documentation. The richness and complexity of the HCP data require extensive documentation for users to understand what is available, how the data sets are organized and how they were processed, including quality control measures. Available resources include (i) a Reference Manual associated with each data release (http://humanconnectome.org/documentation/); (ii) HCP course materials (lectures, tutorials and associated data, available at http://humanconnectome.org/courses/); (iii) publications (for example, for database organization)91; and (iv) the HCP public wiki (https://wiki.humanconnectome.org/display/PublicData/Home/), which provides additional documentation, answers to frequently asked questions, and updates (including known issues and planned fixes).
Software sharing. Also important to the replicability of neuroimaging studies is the sharing of the software used for analysis. Scripts for HCP pipelines are available on GitHub (https://github.com/Washington-University/Pipelines/), and their usage is described in the HCP course materials. This includes pipelines for magnetoencephalography as well as MRI data. Connectome Workbench is available as binaries and source code (http://www.humanconnectome.org/software/get-connectome-workbench.html, on GitHub, and at http://neuro.debian.net/) along with tutorials. Many of the labs that make up the HCP consortia also share their software on either their own websites or the HCP website.
MRI protocols. The MRI protocols used for the main HCP 3 T and 7 T scans are available at http://protocols.humanconnectome.org/HCP/; HCP-style pulse sequences have been widely distributed (http://www.cmrr.umn.edu/multiband/index.shtml). The HCP-Short protocols used for the HCP Lifespan project (Supplementary Note 4) are at http://protocols.humanconnectome.org/lifespan/.
User Support. Users of the HCP's data and software are supported on the 'HCP-Users' mailing list (https://www.humanconnectome.org/contact/hcp-users-request.php), where support requests are answered by HCP consortium members and other community members in a public forum so that all users may benefit.
Department of Neuroscience, Washington University Medical School, St. Louis, Missouri, USA.
- Matthew F Glasser,
- Timothy S Coalson &
- David C Van Essen
FMRIB Centre, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK.
- Stephen M Smith,
- Jesper L R Andersson,
- Timothy E J Behrens,
- Mark Jenkinson &
- Stamatios N Sotiropoulos
Department of Radiology, Washington University Medical School, St. Louis, Missouri, USA.
- Daniel S Marcus
Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, Minnesota, USA.
- Edward J Auerbach,
- Steen Moeller,
- Essa Yacoub &
- Kamil Ugurbil
Department of Psychiatry, Washington University Medical School, St. Louis, Missouri, USA.
- Michael P Harms
Department of Computing, Imperial College London, London, UK.
- Emma C Robinson
7Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
- Junqian Xu
M.F.G., S.M.S., D.S.M., K.U. and D.C.V.E. framed the issues and generated the initial draft. M.F.G., S.M.S., D.S.M., J.L.R.A., E.J.A., T.E.J.B., T.S.C., M.P.H., M.J., S.M., E.C.R., S.N.S., J.X., E.Y., K.U. and D.C.V.E. contributed novel methods or analyses. M.F.G., S.M.S., D.S.M., T.E.J.B., T.S.C., M.P.H., E.C.R., S.N.S., J.X., E.Y., K.U. and D.C.V.E. wrote the manuscript.
Competing financial interests
The authors declare no competing financial interests.
Matthew F Glasser
Stephen M Smith
Daniel S Marcus
Jesper L R Andersson
Edward J Auerbach
Timothy E J Behrens
Timothy S Coalson
Michael P Harms
Emma C Robinson
Stamatios N Sotiropoulos
David C Van Essen
Supplementary Figure 1: Average cortical thickness map of 210 HCP subjects at each left hemisphere vertex and the associated colorized histogram.Hover over figure to zoom
Supplementary Figure 2: dMRI data for 3T and 7T scans of the same subject (HCP Subject 158035).Hover over figure to zoom
Supplementary Figure 3: Patterns of cortico-striatal connectivity revealed by tractography.Hover over figure to zoom
Supplementary Figure 4: Multi-band imaging schematic and exemplar results.Hover over figure to zoom
Supplementary Figure 5: Beta map of the mean fMRI timeseries.Hover over figure to zoom
Supplementary Figure 6: Visualization of the mean grey signal.Hover over figure to zoom
Supplementary Figure 7: Effects of the Wishart rolloff on dense functional connectivity maps of both an individual subject and group data (210 HCP subjects; MSMAll surface registration).Hover over figure to zoom
Supplementary Figure 8: The HCP language task (story vs baseline) beta maps and their spatial gradients.Hover over figure to zoom
Supplementary Figure 9: Effects on average brain volume of registering 196 HCP brains to MNI space.Hover over figure to zoom
Supplementary Figure 10: A comparison between the HCP data and published retinotopic parcellation data.Hover over figure to zoom
Supplementary Figure 11: Classification of area 55b in individual subjects by the areal classifier.Hover over figure to zoom
Supplementary Figure 12: Effects of averaging surface coordinates and folding maps after areal feature-based registration (MSMAll).Hover over figure to zoom