Informatics and Data Mining Tools and Strategies for the Human Connectome Project

By Daniel S. Marcus, John W. Harwell, Timothy R. Olsen, M. Hodge, Matthew F. Glasser, F. Prior, Mark Jenkinson, Timothy O. Laumann, Sandra W. Curtiss, David C. Van Essen. 2011

690 citations recorded by the source corpus.

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.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

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Citations in the corpus

TRIPLE REPRESENTATION OF LANGUAGE, WORKING MEMORY, SOCIAL AND EMOTION PROCESSING IN THE CEREBELLUM: CONVERGENT EVIDENCE FROM TASK AND SEED-BASED RESTING-STATE FMRI ANALYSES IN A SINGLE LARGE COHORT (2018, methodology): “visualization software and Workbench Command (Marcus et al., 2011).”
Advances in diffusion MRI acquisition and processing in the Human Connectome Project (2013, background): “The Human Connectome Project (HCP) (Marcus et al., 2011; Van Essen et al., 2013) represents an ambitious attempt towards these two aims.”
Data sharing in neuroimaging research (2012, methodology): “Indeed, data aggregation tools to meet the requirements for large, collaborative studies, like the Human Connectome Project 23 , are generally available, but these are tailored to the speciﬁc project and not always easy to adapt (for instance, there is no easy way of including genome data in an XNAT”
The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository (2013, background): “More recently, the Human Connectome Project (HCP) [4, 5] is accumulating vast amounts of image data in order to accelerate our understanding of brain function.”
Brain templates and atlases (2012, methodology): “…based on fiber tract mapping is a rapidly developing area (Knösche and Tittgemeyer, 2011 and references therein) and initiatives such as the Human Connectome Project (Marcus et al., 2011) will provide a wealth of new information on structural and functional connectivity in the human brain.”
neuromaps: structural and functional interpretation of brain maps (2022, methodology): “All mappings used functionality from the Connectome Workbench 92 rather than FreeSurfer to ensure standardization of methodology irrespective of the target coordinate systems.”
Comparing spatial null models for brain maps (2021, neutral): “4.2, https://www.humanconnectome.org/software/connectome-workbench ; Marcus et al. 2011 ).”
Optimal positioning and size of high-density electrocorticography grids for speech brain-computer interfaces (2025, unknown): “To visualize the observed activity in relation to the parcellation from the Human Connectome Project, we utilized the Connectome Workbench software to map the regions of interest (55b and 6v) onto the MNI brain (Marcus et al., 2011, Glasser et al., 2016).”