NIH Blueprint: The Human Connectome Project

News and Updates

Press Releases,Project News | March 1, 2017

Announcing the 1200 Subjects Data Release!

The Human Connectome Project (HCP) WU-Minn consortium is pleased to announce the 1200 Subjects Release of HCP image and behavioral data, its final release of new HCP Subjects.

The 1200 Subjects release includes behavioral/demographic and 3T MR imaging data from 1206 healthy young adult participants collected August 2012‒October 2015, including:

  • 3T MR structural scans available for 1113 subjects.
  • 889 subjects have fully complete data for all of the four 3T MRI modalities in the HCP protocol: structural images (T1w and T2w), resting-state fMRI (rfMRI), task fMRI (tfMRI), and high angular resolution diffusion imaging (dMRI).
  • 46 subjects (all monozygotic twins) have 3T HCP protocol Retest data available.
  • 84 subjects also have 7T multimodal MR scan data available (in addition to 3T MR scans). 175 of the 7T subjects have fully complete data for all of the 7T MRI modalities in the HCP protocol: rfMRI, retinotopy fMRI, movie-watching fMRI, and dMRI.
  • 95 subjects also have at least some resting-state MEG (rMEG) and/or task MEG (tMEG) data available (in addition to 3T MR scans).

What’s new in the S1200 release?

  • All released 3T Diffusion data on all HCP subjects re-preprocessed with updated diffusion preprocessing pipeline and with the BEDPOSTX diffusion analysis pipeline. All 3T diffusion data was re-preprocessed using an updated diffusion pipeline that supports an updated version of FSL’s EDDY that significantly improves slice outlier detection to remove noise caused by subject movement. Additionally, 3T diffusion MRI data for all subjects is further processed with FSL’s BEDPOSTX to model white matter fiber orientations and crossing fibers for probabilistic tractography.
  • Addition of 3T Retest data. Subjects (all monozygotic twins, 21 twin pairs + 4 MZ twins without retest of co-twin) were recruited to undergo the full 3T HCP imaging and behavioral protocol for a second time. Retest datasets are available in the separate WU-Minn HCP Retest Data project on the ConnectomeDB splashpage.
  • Addition of preprocessed 7T Diffusion data. Only unprocessed Diffusion data was released as part of the Initial 7T Release (June 2016). For all 7T subjects with dMRI scans, 7T dMRI data preprocessed with the updated diffusion pipeline is now available.
  • Resting State Stats added to 7T rfMRI ICA-FIX cleaned datasets. Resting state stats were not available as part of the 7T rfMRI ICA-FIX Extended packages of the Initial 7T Release (June 2016). These files provide information about different types of ’noise’ and ’signal’ in HCP resting state data, gleaned by partitioning the variance according to different processing stages in the FIX denoising pipeline.
  • Genetically verified family structure measures. We have updated restricted data measures for Mother_ID, Father_ID and ZygosityGT based on genotyping data available from blood and saliva samples from HCP subjects. For some subjects, these genetically verified values for these measures have changed from what they were in previous releases.  Notably, 36 HCP twin pairs who self reported (now the ZygositySR measure) as dizygotic twins were found to be genetically monozygotic.
  • QC_Issue measure added. A subject data measure has been added to ConnectomeDB to flag subjects with notable brain anatomical, processing, or data noise issues found in the HCP Quality Control process.  The issues are notable, but were not considered severe enough to exclude the subject’s imaging data from release. Codes for each issue included are detailed in the S1200 Reference Manual and more specific information on these subjects is available on the HCP QC Issues wiki page.

Soon to be available:

  • Genetic data on all HCP subjects. Genome-wide Association Study (GWAS) analyzed data for all HCP subjects with useable blood or saliva-based genetic material will be deposited and available on NIH’s dbGaP in March/April 2017.
  • Updated group-average rfMRI dense connectivity data and tfMRI data. MSM-All-registered group-average rfMRI dense connectivity data for a 1000+ group of S1200 subjects with complete rfMRI data and MSM-Sulc and MSM-All-registered group-average tfMRI data for all S1200 subjects with complete tfMRI data are planned to be available in late spring 2017. These data will be released as Connectome Workbench-compatible datasets.
  • Updated parcellation, timecourse, and netmap (PTN) data for all S1200 subjects with complete rfMRI data. Updated PTN data for a 1000+ group of S1200 subjects is planned to be available in late spring 2017.

All S1200 imaging data soon to be available on the cloud through Amazon S3. HCP has continued our partnership with the Amazon Web Services Amazon Web Services (AWS) Public Data Sets program ( to offer storage and access to all HCP S1200 imaging data on Amazon S3 within several weeks of the 1200 Subjects Release. (Currently, S900 data is still available via S3)

Access 1200 Subjects data on the HCP website. Explore, download, or order the HCP 1200 Subjects dataset (~76TB of data!) via the ConnectomeDB database. Most HCP image and behavioral data is openly accessible to investigators worldwide who register and accept a limited set of Open Access Data Use Terms. Note: Please clear your browser cache before logging in to ConnectomeDB.

Want more information?  Check out the HCP 1200 Subjects Release Reference Manual for a comprehensive guide that includes details on imaging protocols, behavioral measures, and information that will help users obtain and analyze the 1200 Subjects data.

If you are actively using HCP data and tools, we encourage you to join and be active in the hcp-users discussion group (, so that you can tune in to technical discussions on issues that may be of interest.

Thanks again for your interest in the HCP and enjoy the data!


The WU-Minn HCP Consortium

Project News,Recommended Reading,The Science of Connectome | August 26, 2016

Nature Neuroscience: “The Human Connectome Project’s neuroimaging approach”

Screen shot 2016-08-26 at 11.53.08 AMPublished today in Nature Neuroscience is a primer on the Human Connectome Project’s style of data collection, processing, analysis, and open-access distribution.

“The Human Connectome Project’s neuroimaging approach”

Nature Neuroscience 19, 1175–1187 doi:10.1038/nn.4361

The data for this study has been uploaded to the BALSA database as Connectome Workbench-compatible scene files for interactive viewing and comparison to other imaging data/analyses.

Authors: 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, Mark Jenkinson, Steen Moeller, Emma C Robinson, Stamatios N Sotiropoulos, Junqian Xu, Essa Yacoub, Kamil Ugurbil & David C Van Essen

Abstract: Noninvasive human neuroimaging has yielded many discoveries about the brain. Numerous methodological advances have also occurred, though inertia has slowed their adoption. This paper presents an integrated approach to data acquisition, analysis and sharing that builds upon recent advances, particularly from the Human Connectome Project (HCP). The ‘HCP-style’ paradigm has seven core tenets: (i) collect multimodal imaging data from many subjects; (ii) acquire data at high spatial and temporal resolution; (iii) preprocess data to minimize distortions, blurring and temporal artifacts; (iv) represent data using the natural geometry of cortical and subcortical structures; (v) accurately align corresponding brain areas across subjects and studies; (vi) analyze data using neurobiologically accurate brain parcellations; and (vii) share published data via user-friendly databases. We illustrate the HCP-style paradigm using existing HCP data sets and provide guidance for future research. Widespread adoption of this paradigm should accelerate progress in understanding the brain in health and disease.

Posted by Jenn Elam @ 9:34 am

Project News |

Connectome Workbench v1.2.3 Released

Screen shot 2016-08-26 at 11.38.35 AMWe are pleased to announce version 1.2.3 of Connectome Workbench (WB) brain visualization and analysis software is now available for 64-bit Mac OSX, Windows, and Linux at:

The Workbench distribution includes wb_view, a GUI-based visualization platform, and wb_command, a command-line program for performing a variety of algorithmic tasks using volume, surface, and grayordinate data.

New features in WB v1.2.3 include:

  • Zip scene file wb_command function is now available from within the wb_view GUI
  • wb_shortcuts script implemented to more easily do common tasks for interactive shells
  • New Preferences option for hiding dynamic connectivity *.dynconn layers by default

Changes to existing behavior:

  • warnings produced when creating files with an extension not matching what wb_view expects
  • interpolation of volume with a length-1 spatial dimension always uses enclosing voxel
  • wb_command accepts (but warns) about unicode non-ascii dashes, but also replaces them in filenames
  • nifti headers default pixdim[] to all 1s even when unused (cifti)


  •  -cifti-label-import -drop-unused-labels option fixed
  • files loaded by scene properly restore the “in spec” status
  • chart timecourse status properly restored from scenes

WB v1.2.3 is compatible with the WB v1.0 tutorial and the processed 900 Subjects Group Average Data available to download at and on the ConnectomeDB HCP project page. Access to both datasets require ConnectomeDB login and signature of the HCP Open Access Data Use Terms.

To download the WB v1.2.3 source code from GitHub: follow the link, click releases (near the top of the page), then under v1.2.0, click the “Source code (zip)” or “Source code (tar.gz)” button.

We encourage you to check out Connectome Workbench v1.2.3 for visualizing and performing analysis on imaging data from the HCP and elsewhere and for making scenes and figures. Discussion of Connectome Workbench usage, bugs, and features can be posted to the hcp-users discussion list. Sign up for hcp-users at


Posted by Jenn Elam @ 8:49 am
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