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Assessing Variations in Areal Organization for the Intrinsic Brain: From Fingerprints to Reliability

Overview of attention for article published in Cerebral Cortex, September 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
4 X users

Citations

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82 Dimensions

Readers on

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82 Mendeley
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Title
Assessing Variations in Areal Organization for the Intrinsic Brain: From Fingerprints to Reliability
Published in
Cerebral Cortex, September 2016
DOI 10.1093/cercor/bhw241
Pubmed ID
Authors

Ting Xu, Alexander Opitz, R. Cameron Craddock, Margaret J. Wright, Xi-Nian Zuo, Michael P. Milham

Abstract

Resting state fMRI (R-fMRI) is a powerful in-vivo tool for examining the functional architecture of the human brain. Recent studies have demonstrated the ability to characterize transitions between functionally distinct cortical areas through the mapping of gradients in intrinsic functional connectivity (iFC) profiles. To date, this novel approach has primarily been applied to iFC profiles averaged across groups of individuals, or in one case, a single individual scanned multiple times. Here, we used a publically available R-fMRI dataset, in which 30 healthy participants were scanned 10 times (10 min per session), to investigate differences in full-brain transition profiles (i.e., gradient maps, edge maps) across individuals, and their reliability. 10-min R-fMRI scans were sufficient to achieve high accuracies in efforts to "fingerprint" individuals based upon full-brain transition profiles. Regarding test-retest reliability, the image-wise intraclass correlation coefficient (ICC) was moderate, and vertex-level ICC varied depending on region; larger durations of data yielded higher reliability scores universally. Initial application of gradient-based methodologies to a recently published dataset obtained from twins suggested inter-individual variation in areal profiles might have genetic and familial origins. Overall, these results illustrate the utility of gradient-based iFC approaches for studying inter-individual variation in brain function.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Unknown 81 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 26%
Researcher 19 23%
Professor 6 7%
Other 4 5%
Student > Postgraduate 4 5%
Other 10 12%
Unknown 18 22%
Readers by discipline Count As %
Neuroscience 26 32%
Psychology 15 18%
Agricultural and Biological Sciences 5 6%
Engineering 3 4%
Medicine and Dentistry 3 4%
Other 8 10%
Unknown 22 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 14 July 2019.
All research outputs
#1,869,844
of 22,886,568 outputs
Outputs from Cerebral Cortex
#657
of 4,805 outputs
Outputs of similar age
#35,190
of 334,695 outputs
Outputs of similar age from Cerebral Cortex
#17
of 112 outputs
Altmetric has tracked 22,886,568 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,805 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.8. This one has done well, scoring higher than 86% 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 334,695 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 112 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.