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Pycortex: an interactive surface visualizer for fMRI

Overview of attention for article published in Frontiers in Neuroinformatics, September 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#5 of 847)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
257 X users
facebook
1 Facebook page

Citations

dimensions_citation
148 Dimensions

Readers on

mendeley
172 Mendeley
citeulike
1 CiteULike
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Title
Pycortex: an interactive surface visualizer for fMRI
Published in
Frontiers in Neuroinformatics, September 2015
DOI 10.3389/fninf.2015.00023
Pubmed ID
Authors

James S. Gao, Alexander G. Huth, Mark D. Lescroart, Jack L. Gallant

Abstract

Surface visualizations of fMRI provide a comprehensive view of cortical activity. However, surface visualizations are difficult to generate and most common visualization techniques rely on unnecessary interpolation which limits the fidelity of the resulting maps. Furthermore, it is difficult to understand the relationship between flattened cortical surfaces and the underlying 3D anatomy using tools available currently. To address these problems we have developed pycortex, a Python toolbox for interactive surface mapping and visualization. Pycortex exploits the power of modern graphics cards to sample volumetric data on a per-pixel basis, allowing dense and accurate mapping of the voxel grid across the surface. Anatomical and functional information can be projected onto the cortical surface. The surface can be inflated and flattened interactively, aiding interpretation of the correspondence between the anatomical surface and the flattened cortical sheet. The output of pycortex can be viewed using WebGL, a technology compatible with modern web browsers. This allows complex fMRI surface maps to be distributed broadly online without requiring installation of complex software.

X Demographics

X Demographics

The data shown below were collected from the profiles of 257 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 172 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 2%
Italy 2 1%
Chile 1 <1%
Japan 1 <1%
Unknown 164 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 40 23%
Student > Ph. D. Student 36 21%
Student > Master 26 15%
Student > Bachelor 14 8%
Professor 12 7%
Other 30 17%
Unknown 14 8%
Readers by discipline Count As %
Neuroscience 50 29%
Psychology 28 16%
Computer Science 23 13%
Engineering 17 10%
Agricultural and Biological Sciences 10 6%
Other 16 9%
Unknown 28 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 155. 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 15 July 2022.
All research outputs
#270,401
of 25,784,004 outputs
Outputs from Frontiers in Neuroinformatics
#5
of 847 outputs
Outputs of similar age
#3,522
of 287,182 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#1
of 5 outputs
Altmetric has tracked 25,784,004 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% 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 7.9. This one has done particularly well, scoring higher than 99% 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 287,182 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 98% of its contemporaries.
We're also able to compare this research output to 5 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