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Heritability of the network architecture of intrinsic brain functional connectivity

Overview of attention for article published in NeuroImage, November 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

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11 tweeters

Citations

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28 Dimensions

Readers on

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66 Mendeley
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Title
Heritability of the network architecture of intrinsic brain functional connectivity
Published in
NeuroImage, November 2015
DOI 10.1016/j.neuroimage.2015.07.048
Pubmed ID
Authors

Benjamin Sinclair, Narelle K. Hansell, Gabriëlla A.M. Blokland, Nicholas G. Martin, Paul M. Thompson, Michael Breakspear, Greig I. de Zubicaray, Margaret J. Wright, Katie L. McMahon

Abstract

The brain's functional network exhibits many features facilitating functional specialization, integration and robustness to attack. Using graph theory to characterize brain networks, studies demonstrate their small-world, modular, and "rich-club" properties, with deviations reported in many common neuropathological conditions. Here we estimate the heritability of five widely used graph theoretical metrics (Mean Clustering Coefficient (γ), Modularity (Q), Rich Club Coefficient (ϕnorm), Global Efficiency (λ), Small Worldness (σ)) over a range of connection densities (k=5-25%) in a large cohort of twins (N=592, 84 MZ and 89 DZ twin pairs, 246 single twins, age 23±2.5). We also considered the effects of global signal regression (GSR). We found the graph metrics were moderately influenced by genetic factors h(2)(γ=47-59%, Q=38-59%, ϕnorm=0-29%, λ =52-64%, σ=51-59%) at lower connection densities (≤15%), and when global signal regression was implemented heritability estimates decreased substantially h(2)(γ=0-26%, Q=0-28%, ϕnorm=0%, λ =23-30%, σ=0-27%). Distinct network features were phenotypically correlated (|r|=0.15-0.81) and γ, Q and λ were found to be influenced by overlapping genetic factors. Our findings suggest that these metrics may be potential endophenotypes for psychiatric disease and suitable for genetic association studies, but that genetic effects must be interpreted with respect to methodological choices.

Twitter Demographics

The data shown below were collected from the profiles of 11 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 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 6%
United Kingdom 3 5%
Hong Kong 1 2%
Netherlands 1 2%
Unknown 57 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 32%
Researcher 14 21%
Student > Master 10 15%
Professor 5 8%
Student > Doctoral Student 5 8%
Other 11 17%
Readers by discipline Count As %
Unspecified 15 23%
Neuroscience 14 21%
Psychology 13 20%
Medicine and Dentistry 8 12%
Agricultural and Biological Sciences 6 9%
Other 10 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 21 July 2016.
All research outputs
#2,092,718
of 12,212,281 outputs
Outputs from NeuroImage
#2,279
of 7,453 outputs
Outputs of similar age
#49,721
of 237,889 outputs
Outputs of similar age from NeuroImage
#74
of 252 outputs
Altmetric has tracked 12,212,281 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,453 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.0. This one has gotten more attention than average, scoring higher than 66% 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 237,889 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 78% of its contemporaries.
We're also able to compare this research output to 252 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.