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. 2011 Jun 27:5:4.
doi: 10.3389/fninf.2011.00004. eCollection 2011.

Informatics and data mining tools and strategies for the human connectome project

Daniel S Marcus  1 , John Harwell, Timothy Olsen, Michael Hodge, Matthew F Glasser, Fred Prior, Mark Jenkinson, Timothy Laumann, Sandra W Curtiss, David C Van Essen
Affiliations

Informatics and data mining tools and strategies for the human connectome project

Daniel S Marcus et al. Front Neuroinform. .

Abstract

The Human Connectome Project (HCP) is a major endeavor that will acquire and analyze connectivity data plus other neuroimaging, behavioral, and genetic data from 1,200 healthy adults. It will serve as a key resource for the neuroscience research community, enabling discoveries of how the brain is wired and how it functions in different individuals. To fulfill its potential, the HCP consortium is developing an informatics platform that will handle: (1) storage of primary and processed data, (2) systematic processing and analysis of the data, (3) open-access data-sharing, and (4) mining and exploration of the data. This informatics platform will include two primary components. ConnectomeDB will provide database services for storing and distributing the data, as well as data analysis pipelines. Connectome Workbench will provide visualization and exploration capabilities. The platform will be based on standard data formats and provide an open set of application programming interfaces (APIs) that will facilitate broad utilization of the data and integration of HCP services into a variety of external applications. Primary and processed data generated by the HCP will be openly shared with the scientific community, and the informatics platform will be available under an open source license. This paper describes the HCP informatics platform as currently envisioned and places it into the context of the overall HCP vision and agenda.

Keywords: Human Connectome Project; XNAT; brain parcellation; caret; connectomics; diffusion imaging; network analysis; resting state fMRI.

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Figures

Figure 1
Figure 1
HCP subject workflow.
Figure 2
Figure 2
The Connectome UI. (Left) This mockup of the Visualization & Discovery track illustrates key concepts that are being implemented, including a faceted search interface to construct subject groups and an embedded version of Connectome Workbench. Both the search interface and Workbench view are fed by ConnectomeDB's open API. (Right) This mockup of the Download track illustrates the track's emphasis on guiding users quickly to standard download packages and navigation to specific data.
Figure 3
Figure 3
ConnectomeDB architecture, including data transfer components. ConnectomeDB will utilize the Tomcat servlet container as the application server and use the enterprise grade, open source PostgreSQL database for storage of non-imaging data, imaging session meta-data, and system data. Actual images and other binary content are stored on a file system rather than in the database, improving performance and making the data more easily consumable by external software packages.
Figure 4
Figure 4
HCP data distribution tiers.
Figure 5
Figure 5
Connectome Workbench visualization of the inflated atlas surfaces for the left and right cerebral hemispheres plus the cerebellum. Probabilistic architectonic maps are shown of area 18 on the left hemisphere and area 2 on the right hemisphere.
See this image and copyright information in PMC

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