publication . Article . Preprint . Other literature type . 2019

The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services

Paolo Avesani; Brent McPherson; Soichi Hayashi; Cesar F. Caiafa; Robert Henschel; Eleftherios Garyfallidis; Lindsey Kitchell; Daniel Bullock; Andrew Patterson; Emanuele Olivetti; ...
Open Access English
  • Published: 01 May 2019 Journal: Scientific Data (issn: 2052-4463, Copyright policy)
  • Publisher: Nature Publishing Group
  • Country: Argentina
Abstract
We describe the Open Diffusion Data Derivatives (O3D) repository: an integrated collection of preserved brain data derivatives and processing pipelines, published together using a single digital-object-identifier. The data derivatives were generated using modern diffusion-weighted magnetic resonance imaging data (dMRI) with diverse properties of resolution and signal-to-noise ratio. In addition to the data, we publish all processing pipelines (also referred to as open cloud services). The pipelines utilize modern methods for neuroimaging data processing (diffusion-signal modelling, fiber tracking, tractography evaluation, white matter segmentation, and structura...
Subjects
free text keywords: Diffusion Imaging, Tractography, Human connector, Otras Biotecnologías de la Salud, Biotecnología de la Salud, CIENCIAS MÉDICAS Y DE LA SALUD, Science, Q, Data Descriptor, Network models, Brain imaging, Computational science, Cognitive neuroscience, Magnetic resonance imaging, bepress|Life Sciences, bepress|Life Sciences|Neuroscience and Neurobiology, bepress|Life Sciences|Neuroscience and Neurobiology|Cognitive Neuroscience, bepress|Life Sciences|Neuroscience and Neurobiology|Computational Neuroscience, PsyArXiv|Life Sciences, PsyArXiv|Neuroscience, PsyArXiv|Neuroscience|Cognitive Neuroscience, PsyArXiv|Neuroscience|Computational Neuroscience, Statistics, Probability and Uncertainty, Statistics and Probability, Education, Library and Information Sciences, Information Systems, Computer Science Applications, Data science, Data processing, Cloud computing, business.industry, business, Upcycling, Segmentation, Reuse, Bioinformatics, Biology, Source code, media_common.quotation_subject, media_common, Connectome
Funded by
NIH| Administrative Core
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5P30DK089503-04
  • Funding stream: NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES
,
NSF| NCS-FO: Connectome mapping algorithms with application to community services for big data neuroscience
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1734853
  • Funding stream: Directorate for Social, Behavioral & Economic Sciences | Division of Behavioral and Cognitive Sciences
,
NIH| Training in Clinical Translational Science: Maximizing the Public Health Impact
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5T32MH103213-04
  • Funding stream: NATIONAL INSTITUTE OF MENTAL HEALTH
,
NIH| Older Breast Cancer Patients: Risk For Cognitive Decline
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01CA129769-09
  • Funding stream: NATIONAL CANCER INSTITUTE
,
NIH| Bioinformatics Strategies for Multidimensional Brain Imaging Genetics
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01LM011360-03
  • Funding stream: NATIONAL LIBRARY OF MEDICINE
Communities
Neuroinformatics
139 references, page 1 of 10

Glasser, MF. The Human Connectome Project’s neuroimaging approach. Nat. Neurosci.. 2016; 19: 1175-1187 [OpenAIRE] [PubMed] [DOI]

Van Essen, DC. The WU-Minn Human Connectome Project: an overview. Neuroimage. 2013; 80: 62-79 [OpenAIRE] [PubMed] [DOI]

Marcus, DS. Informatics and data mining tools and strategies for the human connectome project. Front. Neuroinform.. 2011; 5: 4 [OpenAIRE] [PubMed] [DOI]

Miller, KL. Multimodal population brain imaging in the UK Biobank prospective epidemiological study. Nat. Neurosci.. 2016; 19: 1523-1536 [OpenAIRE] [PubMed] [DOI]

Allen, NE, Sudlow, C, Peakman, T, Collins, R. UK Biobank Data: Come and Get It. Sci. Transl. Med.. 2014; 6: 224ed4-224ed4 [OpenAIRE] [PubMed] [DOI]

Weiner, MW. The Alzheimer’s disease neuroimaging initiative: progress report and future plans. Alzheimers. Dement.. 2010; 6: 202-11.e7 [OpenAIRE] [PubMed] [DOI]

Biswal, BB. Toward discovery science of human brain function. Proc. Natl. Acad. Sci. USA. 2010; 107: 4734-4739 [OpenAIRE] [PubMed] [DOI]

Jernigan, TL, Brown, SA, Dowling, GJ. The Adolescent Brain Cognitive Development Study. J. Res. Adolesc.. 2018; 28: 154-156 [OpenAIRE] [PubMed] [DOI]

Taylor, JR. The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository: Structural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample. Neuroimage. 2017; 144: 262-269 [OpenAIRE] [PubMed] [DOI]

Poldrack, RA. Toward open sharing of task-based fMRI data: the Open fMRI project. Front. Neuroinform.. 2013; 7: 12 [OpenAIRE] [PubMed] [DOI]

Nichols, TE. Best practices in data analysis and sharing in neuroimaging using MRI. Nat. Neurosci.. 2017; 20: 299-303 [OpenAIRE] [PubMed] [DOI]

Eglen, SJ. Toward standard practices for sharing computer code and programs in neuroscience. Nat. Neurosci.. 2017; 20: 770-773 [OpenAIRE] [PubMed] [DOI]

Nosek, BA. Promoting an open research culture. Science. 2015; 348: 1422-1425 [OpenAIRE] [PubMed] [DOI]

Pernet, C, Poline, J-B. Improving functional magnetic resonance imaging reproducibility. Gigascience. 2015; 4: 15 [OpenAIRE] [PubMed] [DOI]

Halchenko, YO, Hanke, M. Open is Not Enough. Let’s Take the Next Step: An Integrated, Community-Driven Computing Platform for Neuroscience. Front. Neuroinform.. 2012; 6: 22 [OpenAIRE] [PubMed] [DOI]

139 references, page 1 of 10
Abstract
We describe the Open Diffusion Data Derivatives (O3D) repository: an integrated collection of preserved brain data derivatives and processing pipelines, published together using a single digital-object-identifier. The data derivatives were generated using modern diffusion-weighted magnetic resonance imaging data (dMRI) with diverse properties of resolution and signal-to-noise ratio. In addition to the data, we publish all processing pipelines (also referred to as open cloud services). The pipelines utilize modern methods for neuroimaging data processing (diffusion-signal modelling, fiber tracking, tractography evaluation, white matter segmentation, and structura...
Subjects
free text keywords: Diffusion Imaging, Tractography, Human connector, Otras Biotecnologías de la Salud, Biotecnología de la Salud, CIENCIAS MÉDICAS Y DE LA SALUD, Science, Q, Data Descriptor, Network models, Brain imaging, Computational science, Cognitive neuroscience, Magnetic resonance imaging, bepress|Life Sciences, bepress|Life Sciences|Neuroscience and Neurobiology, bepress|Life Sciences|Neuroscience and Neurobiology|Cognitive Neuroscience, bepress|Life Sciences|Neuroscience and Neurobiology|Computational Neuroscience, PsyArXiv|Life Sciences, PsyArXiv|Neuroscience, PsyArXiv|Neuroscience|Cognitive Neuroscience, PsyArXiv|Neuroscience|Computational Neuroscience, Statistics, Probability and Uncertainty, Statistics and Probability, Education, Library and Information Sciences, Information Systems, Computer Science Applications, Data science, Data processing, Cloud computing, business.industry, business, Upcycling, Segmentation, Reuse, Bioinformatics, Biology, Source code, media_common.quotation_subject, media_common, Connectome
Funded by
NIH| Administrative Core
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5P30DK089503-04
  • Funding stream: NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES
,
NSF| NCS-FO: Connectome mapping algorithms with application to community services for big data neuroscience
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1734853
  • Funding stream: Directorate for Social, Behavioral & Economic Sciences | Division of Behavioral and Cognitive Sciences
,
NIH| Training in Clinical Translational Science: Maximizing the Public Health Impact
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5T32MH103213-04
  • Funding stream: NATIONAL INSTITUTE OF MENTAL HEALTH
,
NIH| Older Breast Cancer Patients: Risk For Cognitive Decline
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01CA129769-09
  • Funding stream: NATIONAL CANCER INSTITUTE
,
NIH| Bioinformatics Strategies for Multidimensional Brain Imaging Genetics
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01LM011360-03
  • Funding stream: NATIONAL LIBRARY OF MEDICINE
Communities
Neuroinformatics
139 references, page 1 of 10

Glasser, MF. The Human Connectome Project’s neuroimaging approach. Nat. Neurosci.. 2016; 19: 1175-1187 [OpenAIRE] [PubMed] [DOI]

Van Essen, DC. The WU-Minn Human Connectome Project: an overview. Neuroimage. 2013; 80: 62-79 [OpenAIRE] [PubMed] [DOI]

Marcus, DS. Informatics and data mining tools and strategies for the human connectome project. Front. Neuroinform.. 2011; 5: 4 [OpenAIRE] [PubMed] [DOI]

Miller, KL. Multimodal population brain imaging in the UK Biobank prospective epidemiological study. Nat. Neurosci.. 2016; 19: 1523-1536 [OpenAIRE] [PubMed] [DOI]

Allen, NE, Sudlow, C, Peakman, T, Collins, R. UK Biobank Data: Come and Get It. Sci. Transl. Med.. 2014; 6: 224ed4-224ed4 [OpenAIRE] [PubMed] [DOI]

Weiner, MW. The Alzheimer’s disease neuroimaging initiative: progress report and future plans. Alzheimers. Dement.. 2010; 6: 202-11.e7 [OpenAIRE] [PubMed] [DOI]

Biswal, BB. Toward discovery science of human brain function. Proc. Natl. Acad. Sci. USA. 2010; 107: 4734-4739 [OpenAIRE] [PubMed] [DOI]

Jernigan, TL, Brown, SA, Dowling, GJ. The Adolescent Brain Cognitive Development Study. J. Res. Adolesc.. 2018; 28: 154-156 [OpenAIRE] [PubMed] [DOI]

Taylor, JR. The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository: Structural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample. Neuroimage. 2017; 144: 262-269 [OpenAIRE] [PubMed] [DOI]

Poldrack, RA. Toward open sharing of task-based fMRI data: the Open fMRI project. Front. Neuroinform.. 2013; 7: 12 [OpenAIRE] [PubMed] [DOI]

Nichols, TE. Best practices in data analysis and sharing in neuroimaging using MRI. Nat. Neurosci.. 2017; 20: 299-303 [OpenAIRE] [PubMed] [DOI]

Eglen, SJ. Toward standard practices for sharing computer code and programs in neuroscience. Nat. Neurosci.. 2017; 20: 770-773 [OpenAIRE] [PubMed] [DOI]

Nosek, BA. Promoting an open research culture. Science. 2015; 348: 1422-1425 [OpenAIRE] [PubMed] [DOI]

Pernet, C, Poline, J-B. Improving functional magnetic resonance imaging reproducibility. Gigascience. 2015; 4: 15 [OpenAIRE] [PubMed] [DOI]

Halchenko, YO, Hanke, M. Open is Not Enough. Let’s Take the Next Step: An Integrated, Community-Driven Computing Platform for Neuroscience. Front. Neuroinform.. 2012; 6: 22 [OpenAIRE] [PubMed] [DOI]

139 references, page 1 of 10
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