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Test–retest reliability of brain morphology estimates

Overview of attention for article published in Brain Informatics, January 2017
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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 (94th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

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62 tweeters

Citations

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20 Dimensions

Readers on

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40 Mendeley
Title
Test–retest reliability of brain morphology estimates
Published in
Brain Informatics, January 2017
DOI 10.1007/s40708-016-0060-4
Pubmed ID
Authors

Christopher R. Madan, Elizabeth A. Kensinger

Abstract

Metrics of brain morphology are increasingly being used to examine inter-individual differences, making it important to evaluate the reliability of these structural measures. Here we used two open-access datasets to assess the intersession reliability of three cortical measures (thickness, gyrification, and fractal dimensionality) and two subcortical measures (volume and fractal dimensionality). Reliability was generally good, particularly with the gyrification and fractal dimensionality measures. One dataset used a sequence previously optimized for brain morphology analyses and had particularly high reliability. Examining the reliability of morphological measures is critical before the measures can be validly used to investigate inter-individual differences.

Twitter Demographics

The data shown below were collected from the profiles of 62 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 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Austria 1 3%
Unknown 38 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 23%
Student > Ph. D. Student 8 20%
Student > Master 6 15%
Unspecified 5 13%
Other 3 8%
Other 9 23%
Readers by discipline Count As %
Unspecified 12 30%
Psychology 10 25%
Neuroscience 7 18%
Engineering 4 10%
Medicine and Dentistry 3 8%
Other 4 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 34. 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 23 May 2019.
All research outputs
#486,730
of 13,378,837 outputs
Outputs from Brain Informatics
#1
of 50 outputs
Outputs of similar age
#21,103
of 371,107 outputs
Outputs of similar age from Brain Informatics
#1
of 6 outputs
Altmetric has tracked 13,378,837 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 50 research outputs from this source. They receive a mean Attention Score of 3.1. This one scored the same or higher as 49 of them.
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 371,107 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 94% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them