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Toward open sharing of task-based fMRI data: the OpenfMRI project
The large-scale sharing of task-based functional neuroimaging data has the potential to allow novel insights into the organization of mental function in the brain, but the field of neuroimaging has lagged behind other areas of bioscience in the development of data sharing resources. This paper descr...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3703526/ https://www.ncbi.nlm.nih.gov/pubmed/23847528 http://dx.doi.org/10.3389/fninf.2013.00012 |
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author | Poldrack, Russell A. Barch, Deanna M. Mitchell, Jason P. Wager, Tor D. Wagner, Anthony D. Devlin, Joseph T. Cumba, Chad Koyejo, Oluwasanmi Milham, Michael P. |
author_facet | Poldrack, Russell A. Barch, Deanna M. Mitchell, Jason P. Wager, Tor D. Wagner, Anthony D. Devlin, Joseph T. Cumba, Chad Koyejo, Oluwasanmi Milham, Michael P. |
author_sort | Poldrack, Russell A. |
collection | PubMed |
description | The large-scale sharing of task-based functional neuroimaging data has the potential to allow novel insights into the organization of mental function in the brain, but the field of neuroimaging has lagged behind other areas of bioscience in the development of data sharing resources. This paper describes the OpenFMRI project (accessible online at http://www.openfmri.org), which aims to provide the neuroimaging community with a resource to support open sharing of task-based fMRI studies. We describe the motivation behind the project, focusing particularly on how this project addresses some of the well-known challenges to sharing of task-based fMRI data. Results from a preliminary analysis of the current database are presented, which demonstrate the ability to classify between task contrasts with high generalization accuracy across subjects, and the ability to identify individual subjects from their activation maps with moderately high accuracy. Clustering analyses show that the similarity relations between statistical maps have a somewhat orderly relation to the mental functions engaged by the relevant tasks. These results highlight the potential of the project to support large-scale multivariate analyses of the relation between mental processes and brain function. |
format | Online Article Text |
id | pubmed-3703526 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-37035262013-07-11 Toward open sharing of task-based fMRI data: the OpenfMRI project Poldrack, Russell A. Barch, Deanna M. Mitchell, Jason P. Wager, Tor D. Wagner, Anthony D. Devlin, Joseph T. Cumba, Chad Koyejo, Oluwasanmi Milham, Michael P. Front Neuroinform Neuroscience The large-scale sharing of task-based functional neuroimaging data has the potential to allow novel insights into the organization of mental function in the brain, but the field of neuroimaging has lagged behind other areas of bioscience in the development of data sharing resources. This paper describes the OpenFMRI project (accessible online at http://www.openfmri.org), which aims to provide the neuroimaging community with a resource to support open sharing of task-based fMRI studies. We describe the motivation behind the project, focusing particularly on how this project addresses some of the well-known challenges to sharing of task-based fMRI data. Results from a preliminary analysis of the current database are presented, which demonstrate the ability to classify between task contrasts with high generalization accuracy across subjects, and the ability to identify individual subjects from their activation maps with moderately high accuracy. Clustering analyses show that the similarity relations between statistical maps have a somewhat orderly relation to the mental functions engaged by the relevant tasks. These results highlight the potential of the project to support large-scale multivariate analyses of the relation between mental processes and brain function. Frontiers Media S.A. 2013-07-08 /pmc/articles/PMC3703526/ /pubmed/23847528 http://dx.doi.org/10.3389/fninf.2013.00012 Text en Copyright © 2013 Poldrack, Barch, Mitchell, Wager, Wagner, Devlin, Cumba, Koyejo and Milham. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc. |
spellingShingle | Neuroscience Poldrack, Russell A. Barch, Deanna M. Mitchell, Jason P. Wager, Tor D. Wagner, Anthony D. Devlin, Joseph T. Cumba, Chad Koyejo, Oluwasanmi Milham, Michael P. Toward open sharing of task-based fMRI data: the OpenfMRI project |
title | Toward open sharing of task-based fMRI data: the OpenfMRI project |
title_full | Toward open sharing of task-based fMRI data: the OpenfMRI project |
title_fullStr | Toward open sharing of task-based fMRI data: the OpenfMRI project |
title_full_unstemmed | Toward open sharing of task-based fMRI data: the OpenfMRI project |
title_short | Toward open sharing of task-based fMRI data: the OpenfMRI project |
title_sort | toward open sharing of task-based fmri data: the openfmri project |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3703526/ https://www.ncbi.nlm.nih.gov/pubmed/23847528 http://dx.doi.org/10.3389/fninf.2013.00012 |
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