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A test-retest fMRI dataset for motor, language and spatial attention functions

Overview of attention for article published in Giga Science, April 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)

Mentioned by

1 blog
25 tweeters
1 peer review site
1 Facebook page
1 Google+ user


29 Dimensions

Readers on

74 Mendeley
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A test-retest fMRI dataset for motor, language and spatial attention functions
Published in
Giga Science, April 2013
DOI 10.1186/2047-217x-2-6
Pubmed ID

Krzysztof J Gorgolewski, Amos Storkey, Mark E Bastin, Ian R Whittle, Joanna M Wardlaw, Cyril R Pernet


Since its inception over twenty years ago, functional magnetic resonance imaging (fMRI) has been used in numerous studies probing neural underpinnings of human cognition. However, the between session variance of many tasks used in fMRI remains understudied. Such information is especially important in context of clinical applications. A test-retest dataset was acquired to validate fMRI tasks used in pre-surgical planning. In particular, five task-related fMRI time series (finger, foot and lip movement, overt verb generation, covert verb generation, overt word repetition, and landmark tasks) were used to investigate which protocols gave reliable single-subject results. Ten healthy participants in their fifties were scanned twice using an identical protocol 2-3 days apart. In addition to the fMRI sessions, high-angular resolution diffusion tensor MRI (DTI), and high-resolution 3D T1-weighted volume scans were acquired.

Twitter Demographics

The data shown below were collected from the profiles of 25 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Hong Kong 2 3%
Australia 1 1%
Germany 1 1%
United Kingdom 1 1%
Belgium 1 1%
United States 1 1%
Unknown 67 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 27%
Student > Ph. D. Student 17 23%
Professor > Associate Professor 6 8%
Student > Master 5 7%
Other 4 5%
Other 14 19%
Unknown 8 11%
Readers by discipline Count As %
Neuroscience 18 24%
Psychology 10 14%
Agricultural and Biological Sciences 8 11%
Medicine and Dentistry 7 9%
Computer Science 5 7%
Other 13 18%
Unknown 13 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 20 August 2017.
All research outputs
of 16,008,054 outputs
Outputs from Giga Science
of 771 outputs
Outputs of similar age
of 156,243 outputs
Outputs of similar age from Giga Science
of 1 outputs
Altmetric has tracked 16,008,054 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 771 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.1. This one has gotten more attention than average, scoring higher than 71% 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 156,243 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 94% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them