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A multi-modal parcellation of human cerebral cortex

Overview of attention for article published in Nature, July 2016
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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)

Citations

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565 Dimensions

Readers on

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2048 Mendeley
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5 CiteULike
Title
A multi-modal parcellation of human cerebral cortex
Published in
Nature, July 2016
DOI 10.1038/nature18933
Pubmed ID
Authors

Matthew F. Glasser, Timothy S. Coalson, Emma C. Robinson, Carl D. Hacker, John Harwell, Essa Yacoub, Kamil Ugurbil, Jesper Andersson, Christian F. Beckmann, Mark Jenkinson, Stephen M. Smith, David C. Van Essen

Abstract

Understanding the amazingly complex human cerebral cortex requires a map (or parcellation) of its major subdivisions, known as cortical areas. Making an accurate areal map has been a century-old objective in neuroscience. Using multi-modal magnetic resonance images from the Human Connectome Project (HCP) and an objective semi-automated neuroanatomical approach, we delineated 180 areas per hemisphere bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults. We characterized 97 new areas and 83 areas previously reported using post-mortem microscopy or other specialized study-specific approaches. To enable automated delineation and identification of these areas in new HCP subjects and in future studies, we trained a machine-learning classifier to recognize the multi-modal 'fingerprint' of each cortical area. This classifier detected the presence of 96.6% of the cortical areas in new subjects, replicated the group parcellation, and could correctly locate areas in individuals with atypical parcellations. The freely available parcellation and classifier will enable substantially improved neuroanatomical precision for studies of the structural and functional organization of human cerebral cortex and its variation across individuals and in development, aging, and disease.

Twitter Demographics

The data shown below were collected from the profiles of 852 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 2,048 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 53 3%
United Kingdom 21 1%
Germany 20 <1%
Italy 10 <1%
Spain 9 <1%
Japan 8 <1%
France 7 <1%
Canada 7 <1%
China 5 <1%
Other 45 2%
Unknown 1863 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 555 27%
Researcher 490 24%
Student > Master 245 12%
Student > Bachelor 138 7%
Professor > Associate Professor 106 5%
Other 514 25%
Readers by discipline Count As %
Neuroscience 507 25%
Psychology 354 17%
Unspecified 265 13%
Agricultural and Biological Sciences 250 12%
Medicine and Dentistry 249 12%
Other 423 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 2252. 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 29 September 2018.
All research outputs
#440
of 12,300,035 outputs
Outputs from Nature
#81
of 62,532 outputs
Outputs of similar age
#22
of 267,161 outputs
Outputs of similar age from Nature
#5
of 1,008 outputs
Altmetric has tracked 12,300,035 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 62,532 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 73.7. 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 267,161 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 1,008 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.