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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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  • 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)

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1393 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

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

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Mendeley readers

The data shown below were compiled from readership statistics for 1,393 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 63 5%
Germany 30 2%
United Kingdom 26 2%
Italy 11 <1%
Spain 11 <1%
Canada 10 <1%
Japan 9 <1%
France 9 <1%
Netherlands 7 <1%
Other 53 4%
Unknown 1164 84%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 390 28%
Researcher 355 25%
Student > Master 168 12%
Student > Bachelor 90 6%
Professor > Associate Professor 83 6%
Other 307 22%
Readers by discipline Count As %
Neuroscience 300 22%
Psychology 270 19%
Agricultural and Biological Sciences 220 16%
Medicine and Dentistry 184 13%
Unspecified 112 8%
Other 307 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 2274. 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 09 August 2017.
All research outputs
#223
of 8,219,190 outputs
Outputs from Nature
#60
of 47,663 outputs
Outputs of similar age
#16
of 258,829 outputs
Outputs of similar age from Nature
#4
of 943 outputs
Altmetric has tracked 8,219,190 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 47,663 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 74.2. 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 258,829 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 943 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.