NIH Blueprint: The Human Connectome Project

News and Updates

Press Releases,Project News | May 19, 2016

Check out Connectome Workbench v1.2.0!

WBv1.2.0releaseThe WU-Minn HCP Consortium is pleased to announce that version 1.2.0 of Connectome Workbench (WB) brain visualization and analysis software is now available at http://humanconnectome.org/connectome/get-connectome-workbench.html  for 64-bit Mac OSX, Windows, and Linux. 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 v1.2.0 include:

wb_view:

  • Annotations are a powerful new feature for placing text and symbols within wb_view tabs and windows. They enable generation of publication-ready figures without the need for further annotation in a separate application (e.g., Photoshop).  Annotation features are extensively documented in “Guide to WB Annotations”.
  • New options for locking the aspect ratio for tabs and windows when converting between Tile Tabs and single tile views and when adjusting the wb_view viewport (aka viewing area).
  • Improved control over gaps and margins between tabs.
  • More flexible control over color bars and associated labels.
  • Refinements to scene files, including the option to override the user’s default background/foreground color settings.
  • Separate panning and zooming enabled between left and right hemisphere flatmaps.

Refinements to wb_command:

    -surface-average now takes per-surface weights, uses much less memory

    -spec-file-relocate changes the location of a spec file relative to its data files

    -scene-file-relocate changes the location of a scene file relative to its data files

    -label-to-volume-mapping – new command, uses ribbon mapping method

…plus many refinements to existing commands and also various bug fixes.

You will also notice in the Scenes window, some reference to BALSA Scene and Study IDs. These are WB features that will become useful in the soon to be released Brain Analysis Library of Spatial Maps and Atlases (BALSA) database (stay tuned!).

WB v1.2.0 is compatible with the WB v1.0 tutorial and the processed 900 Subjects Group Average Data available to download at http://humanconnectome.org/connectome/get-connectome-workbench.html 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 v1.2.0 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 v1.2.0 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 http://humanconnectome.org/contact/#subscribe

Press Releases,Project News,Upcoming events | May 11, 2016

Attend the HCP Course 2016 in Boston Aug 28-Sept 1!

course-banner-HCP2016-crop

We are pleased to announce the 2016 HCP Course: “Exploring the Human Connectome”, to be held August 28-September 1 (Sunday-Thursday) at the Joseph B. Martin Conference Center at Harvard Medical School, in Boston, Massachusetts, USA.

This 5-day intensive course will provide training in the acquisition, analysis and visualization of whole-brain imaging and behavioral data from the Human Connectome Project (HCP) using methods and informatics tools developed by the WU-Minn HCP consortium plus data made freely available to the neuroscience community.

The course is designed for investigators who are interested in:

  • using data being collected and distributed by HCP
  • acquiring and analyzing HCP-style imaging and behavioral data at your own institution
  • processing your own non-HCP imaging data using HCP pipelines and methods
  • learning to use Connectome Workbench tools and the CIFTI connectivity data format
  • learning HCP multi-modal neuroimaging analysis methods, including those that combine MEG and MRI data
  • positioning yourself to capitalize on HCP-style data from forthcoming large-scale projects (e.g., Lifespan HCP and Connectomes Related to Human Disease)

Participants will learn how to acquire, analyze, visualize, and interpret data from four major MR modalities (structural MR, resting-state fMRI, diffusion imaging, task-evoked fMRI) plus magnetoencephalography (MEG) and extensive behavioral data.  Lectures and labs will provide grounding in neurobiological as well as methodological issues involved in interpreting multimodal data, and will span the range from single-voxel/vertex to brain network analysis approaches.

The course is open to graduate students, postdocs, faculty, and industry participants.  The course is aimed at both new and existing users of HCP data, methods, and tools, and will cover both basic and advanced topics. Prior experience in human neuroimaging or in computational analysis of brain networks is desirable, preferably including familiarity with FSL and Freesurfer software.

For more info and to register visit the HCP Course website.

We hope to see you in Bah-ston!

Press Releases,Project News | January 12, 2016

Announcing release of S900 “PTN” and other Group Average Data

Screen Shot 2016-01-12 at 3.04.07 PMWe are pleased to announce the release of extensively processed data associated with the HCP S900 Data Release, which is first HCP data release to capitalize on cortical areal feature-based surface registration (“MSMAlll”, using folding, myelin maps, and resting-state networks).

The release includes (i) the “PTN” dataset (Parcellation + Timeseries + Netmats); (ii) group average dense functional connectomes; and (iii) other group average data (plus composite of individual-subject maps).

Download the data here (requires ConnectomeDB login).

PTN (Parcellation + Timeseries + Netmats) dataset. This analysis is based on data from all 820 subjects in the S900 data release having four complete rfMRI runs (with 100% of collected timepoints), yielding the following outputs:

  1. Group-average “parcellations”, obtained by means of group-ICA.
  2. Subject-specific sets of “node timeseries” – for each subject, a representative time series per ICA component (“parcel”).
  3. A subject-specific “parcellated connectome” – for each subject, a nodes x nodes matrix – the functional connectivity between node timeseries.

Additional information is provided in the pdf (HCP900_GroupICA+NodeTS+Netmats_Sumary_15dec2015.pdf) included in the download.

HCP_S900_GroupAvg_v1 dataset. This dataset (1.4 GB zip file) includes group-average structural and functional MRI data for the HCP S900 data release (December, 2015). Also included are composite files containing MSMAll-registered maps of folding, ‘sulc’, myelin, and thickness that enable efficient navigation of individual subject data. An associated tutorial document aids in viewing the data using Connectome Workbench ‘wb_view’ visualization software.

HCP_S900 group average functional connectivity. Two group average dense functional connectomes have been generated from 820 subjects in the S900 release, one based on MSMAll (recommended for most analyses) and the other based on MSMSulc (less well aligned, available for comparison purposes). Because these are large (33 GB) files, we recommend accessing them remotely, as explained in the tutorial document noted above. However, they can also be downloaded directly from ConnectomeDB via:

https://db.humanconnectome.org/app/action/ChooseDownloadResources?project=HCP_Resources&resource=GroupAvg&filePath= HCP_S900_820_rfMRI_MSMAll_groupPCA_d4500ROW_zcorr.zip

and https://db.humanconnectome.org/app/action/ChooseDownloadResources?project=HCP_Resources&resource=GroupAvg&filePath= HCP_S900_820_rfMRI_MSMSulc_groupPCA_d4500ROW_zcorr.zip

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