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BigBrain: An Ultrahigh-Resolution 3D Human Brain Model

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

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
54 news outlets
blogs
18 blogs
twitter
228 X users
facebook
27 Facebook pages
wikipedia
3 Wikipedia pages
googleplus
39 Google+ users
reddit
1 Redditor
video
2 YouTube creators

Citations

dimensions_citation
675 Dimensions

Readers on

mendeley
975 Mendeley
citeulike
15 CiteULike
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Title
BigBrain: An Ultrahigh-Resolution 3D Human Brain Model
Published in
Science, June 2013
DOI 10.1126/science.1235381
Pubmed ID
Authors

Katrin Amunts, Claude Lepage, Louis Borgeat, Hartmut Mohlberg, Timo Dickscheid, Marc-Étienne Rousseau, Sebastian Bludau, Pierre-Louis Bazin, Lindsay B. Lewis, Ana-Maria Oros-Peusquens, Nadim J. Shah, Thomas Lippert, Karl Zilles, Alan C. Evans

Abstract

Reference brains are indispensable tools in human brain mapping, enabling integration of multimodal data into an anatomically realistic standard space. Available reference brains, however, are restricted to the macroscopic scale and do not provide information on the functionally important microscopic dimension. We created an ultrahigh-resolution three-dimensional (3D) model of a human brain at nearly cellular resolution of 20 micrometers, based on the reconstruction of 7404 histological sections. "BigBrain" is a free, publicly available tool that provides considerable neuroanatomical insight into the human brain, thereby allowing the extraction of microscopic data for modeling and simulation. BigBrain enables testing of hypotheses on optimal path lengths between interconnected cortical regions or on spatial organization of genetic patterning, redefining the traditional neuroanatomy maps such as those of Brodmann and von Economo.

X Demographics

X Demographics

The data shown below were collected from the profiles of 228 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 975 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 32 3%
Germany 16 2%
United Kingdom 11 1%
France 8 <1%
China 8 <1%
Switzerland 5 <1%
Spain 5 <1%
Japan 5 <1%
Netherlands 4 <1%
Other 21 2%
Unknown 860 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 239 25%
Student > Ph. D. Student 222 23%
Student > Master 87 9%
Professor 73 7%
Student > Bachelor 53 5%
Other 191 20%
Unknown 110 11%
Readers by discipline Count As %
Neuroscience 175 18%
Agricultural and Biological Sciences 173 18%
Medicine and Dentistry 107 11%
Psychology 86 9%
Engineering 85 9%
Other 187 19%
Unknown 162 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 776. 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 11 January 2024.
All research outputs
#25,212
of 26,017,215 outputs
Outputs from Science
#1,152
of 83,593 outputs
Outputs of similar age
#99
of 213,616 outputs
Outputs of similar age from Science
#4
of 854 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 83,593 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 65.8. This one has done particularly well, scoring higher than 98% 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 213,616 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 99% of its contemporaries.
We're also able to compare this research output to 854 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.