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Toward open sharing of task-based fMRI data: the OpenfMRI project

Overview of attention for article published in Frontiers in Neuroinformatics, January 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#29 of 847)
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

blogs
1 blog
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30 X users
wikipedia
3 Wikipedia pages
googleplus
3 Google+ users
reddit
1 Redditor

Readers on

mendeley
252 Mendeley
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2 CiteULike
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Title
Toward open sharing of task-based fMRI data: the OpenfMRI project
Published in
Frontiers in Neuroinformatics, January 2013
DOI 10.3389/fninf.2013.00012
Pubmed ID
Authors

Russell A. Poldrack, Deanna M. Barch, Jason P. Mitchell, Tor D. Wager, Anthony D. Wagner, Joseph T. Devlin, Chad Cumba, Oluwasanmi Koyejo, Michael P. Milham

Abstract

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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 30 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 252 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 3%
France 3 1%
Germany 2 <1%
Spain 2 <1%
Netherlands 1 <1%
Canada 1 <1%
Malaysia 1 <1%
United Kingdom 1 <1%
Luxembourg 1 <1%
Other 0 0%
Unknown 232 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 63 25%
Researcher 52 21%
Student > Master 27 11%
Student > Bachelor 22 9%
Professor > Associate Professor 12 5%
Other 52 21%
Unknown 24 10%
Readers by discipline Count As %
Psychology 73 29%
Neuroscience 44 17%
Agricultural and Biological Sciences 22 9%
Engineering 21 8%
Computer Science 18 7%
Other 36 14%
Unknown 38 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 31. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 January 2020.
All research outputs
#1,293,670
of 25,805,386 outputs
Outputs from Frontiers in Neuroinformatics
#29
of 847 outputs
Outputs of similar age
#10,745
of 291,279 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#4
of 36 outputs
Altmetric has tracked 25,805,386 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 847 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.5. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 291,279 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.