Human Connectome Project informatics: Quality control, database services, and data visualization
Open accessAbstract
The Human Connectome Project (HCP) has developed protocols, standard operating and quality control procedures, and a suite of informatics tools to enable high throughput data collection, data sharing, automated data processing and analysis, and data mining and visualization. Quality control procedures include methods to maintain data collection consistency over time, to measure head motion, and to establish quantitative modality-specific overall quality assessments. Database services developed as customizations of the XNAT imaging informatics platform support both internal daily operations and open access data sharing. The Connectome Workbench visualization environment enables user interaction with HCP data and is increasingly integrated with the HCP's database services. Here we describe the current state of these procedures and tools and their application in the ongoing HCP study.
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Neurobiologically relevant fluctuations represent only about 4% of total temporal variance in the minimally preprocessed datasets.
“Neurobiologically relevant fluctuations, which ideally should be the only signals used to drive functional connectivity analyses, represent only a small fraction (~4%) of the total temporal variance in the minimally preprocessed datasets (Glasser et al., 2013b; Marcus et al., 2013).”
From The WU-Minn Human Connectome Project: An overview (2013) · cites this paper as Marcus et al., 2013
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- Authors
- Marcus, D. S., Harms, M. P., Snyder, A. Z., Jenkinson, M., Wilson, J. A., Glasser, M. F., Barch, D. M., Archie, K. A., Burgess, G. C., Ramaratnam, M., Hodge, M., Horton, W., Herrick, R., Olsen, T., McKay, M., House, M., Hileman, M., Reid, E., Harwell, J., Coalson, T., Schindler, J., Elam, J. S., Curtiss, S. W., & Van Essen, D. C.
- Affiliations
- Washington University in St. Louis (US)
- John Radcliffe Hospital (GB)
- Corresponding author
- Marcus, Daniel S.
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2013-10
- Volume
- 80
- Pages
- 202-219
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3845379
- OpenAlex
- W2148519294
- Cited by
- 465
- References
- 30
- Citations by year
- 2026: 40 · 2025: 40 · 2024: 61 · 2023: 46 · 2022: 41 · 2021: 37 · 2020: 54 · 2019: 41 · 2018: 36 · 2017: 23 · 2016: 9 · 2015: 15 · 2014: 12 · 2013: 10
- FWCI
- 8.38
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- UniTERAMO Research Catalog (University of Teramo) (submittedVersion)
- Funders
- NIH (1U54MH091657, U54 MH091657, U24 GM104203, R01 EB009352)
- McDonnell Center for Systems Neuroscience at Washington University
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Keywords
- Human Connectome Project, quality control, data sharing, XNAT, data visualization, neuroimaging informatics, automated data processing, data mining, database services
- MeSH terms
- Brain, Database Management Systems, Humans, Models, Anatomic, Models, Neurological, Nerve Net, Quality Control, User-Computer Interface, Databases, Factual, Information Storage and Retrieval, Computational Biology, Data Mining, Connectome
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