ConnectomeDB-Sharing human brain connectivity data

Michael R. Hodge, William Horton, Timothy Brown, Rick Herrick, Timothy Olsen, Michael E. Hileman, Michael McKay, Kevin A. Archie, Eileen Cler, Michael P. Harms, Gregory C. Burgess, Matthew F. Glasser, Jennifer S. Elam, Sandra W. Curtiss, Deanna M. Barch, Robert Oostenveld, Linda J. Larson-Prior, Kamil Ugurbil, David C. Van Essen, Daniel S. Marcus

Research output: Contribution to journalArticlepeer-review

61 Scopus citations


ConnectomeDB is a database for housing and disseminating data about human brain structure, function, and connectivity, along with associated behavioral and demographic data. It is the main archive and dissemination platform for data collected under the WU-Minn consortium Human Connectome Project. Additional connectome-style study data is and will be made available in the database under current and future projects, including the Connectome Coordination Facility. The database currently includes multiple modalities of magnetic resonance imaging (MRI) and magnetoencephalograpy (MEG) data along with associated behavioral data. MRI modalities include structural, task, resting state and diffusion. MEG modalities include resting state and task. Imaging data includes unprocessed, minimally preprocessed and analysis data. Imaging data and much of the behavioral data are publicly available, subject to acceptance of data use terms, while access to some sensitive behavioral data is restricted to qualified investigators under a more stringent set of terms. ConnectomeDB is the public side of the WU-Minn HCP database platform. As such, it is geared towards public distribution, with a web-based user interface designed to guide users to the optimal set of data for their needs and a robust backend mechanism based on the commercial Aspera fasp service to enable high speed downloads. HCP data is also available via direct shipment of hard drives and Amazon S3.

Original languageEnglish (US)
Pages (from-to)1102-1107
Number of pages6
StatePublished - Jan 1 2016

Bibliographical note

Funding Information:
ConnectomeDB will become the foundation for the NIH-supported Connectome Coordination Facility (CCF) and the primary dissemination platform for NIH-funded HCP-style data acquisition and analysis supported by the Connectomes of Human Diseases ( ) and Lifespan-HCP ( ) funding mechanisms. An important function of the CCF will be to facilitate comparison and aggregation across datasets. Consequently, ConnectomeDB is being developed to provide an improved unified-yet-customized interface to support data from many sites and studies and to handle the corresponding increase in traffic these studies are expected to generate.

Funding Information:
Author note: Funded in part by the Human Connectome Project, WU-Minn consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 5U54MH091657 ) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University . Additional funding was provided by 5R01EB009352 for XNAT support and 5P30NS048056 for the NIAC.

Publisher Copyright:
© 2015 Elsevier Inc.


  • Connectome coordination facility
  • Connectomics
  • Data sharing
  • Human connectome project
  • Neuroinformatics databases
  • Open access
  • XNAT


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