↓ Skip to main content

A multi-modal parcellation of human cerebral cortex

Overview of attention for article published in Nature, July 2016
Altmetric Badge

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)

Readers on

mendeley
1484 Mendeley
citeulike
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, Glasser, Matthew F, Coalson, Timothy S, Robinson, Emma C, Hacker, Carl D, Harwell, John, Yacoub, Essa, Ugurbil, Kamil, Andersson, Jesper, Beckmann, Christian F, Jenkinson, Mark, Smith, Stephen M, Van Essen, David C, Matthew F Glasser, Timothy S Coalson, Emma C Robinson, Carl D Hacker, Christian F Beckmann, 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 862 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 1,484 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 59 4%
Germany 27 2%
United Kingdom 25 2%
Italy 11 <1%
Spain 11 <1%
Canada 10 <1%
Japan 9 <1%
France 9 <1%
Netherlands 7 <1%
Other 51 3%
Unknown 1265 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 412 28%
Researcher 371 25%
Student > Master 183 12%
Student > Bachelor 98 7%
Professor > Associate Professor 91 6%
Other 329 22%
Readers by discipline Count As %
Neuroscience 328 22%
Psychology 290 20%
Agricultural and Biological Sciences 228 15%
Medicine and Dentistry 197 13%
Unspecified 122 8%
Other 319 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 2267. 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 12 October 2017.
All research outputs
#242
of 8,518,608 outputs
Outputs from Nature
#60
of 48,410 outputs
Outputs of similar age
#18
of 261,740 outputs
Outputs of similar age from Nature
#5
of 945 outputs
Altmetric has tracked 8,518,608 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 48,410 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 75.3. 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 261,740 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 945 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.