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ENIGMA and the individual: Predicting factors that affect the brain in 35 countries worldwide

Overview of attention for article published in NeuroImage, January 2017
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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 (96th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

75 tweeters
1 Facebook page
1 Google+ user


124 Dimensions

Readers on

302 Mendeley
1 CiteULike
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ENIGMA and the individual: Predicting factors that affect the brain in 35 countries worldwide
Published in
NeuroImage, January 2017
DOI 10.1016/j.neuroimage.2015.11.057
Pubmed ID

Paul M. Thompson, Ole A. Andreassen, Alejandro Arias-Vasquez, Carrie E. Bearden, Premika S. Boedhoe, Rachel M. Brouwer, Randy L. Buckner, Jan K. Buitelaar, Kazima B. Bulayeva, Dara M. Cannon, Ronald A. Cohen, Patricia J. Conrod, Anders M. Dale, Ian J. Deary, Emily L. Dennis, Marcel A. de Reus, Sylvane Desrivieres, Danai Dima, Gary Donohoe, Simon E. Fisher, Jean-Paul Fouche, Clyde Francks, Sophia Frangou, Barbara Franke, Habib Ganjgahi, Hugh Garavan, David C. Glahn, Hans J. Grabe, Tulio Guadalupe, Boris A. Gutman, Ryota Hashimoto, Derrek P. Hibar, Dominic Holland, Martine Hoogman, Hilleke E. Hulshoff Pol, Norbert Hosten, Neda Jahanshad, Sinead Kelly, Peter Kochunov, William S. Kremen, Phil H. Lee, Scott Mackey, Nicholas G. Martin, Bernard Mazoyer, Colm McDonald, Sarah E. Medland, Rajendra A. Morey, Thomas E. Nichols, Tomas Paus, Zdenka Pausova, Lianne Schmaal, Gunter Schumann, Li Shen, Sanjay M. Sisodiya, Dirk J.A. Smit, Jordan W. Smoller, Dan J. Stein, Jason L. Stein, Roberto Toro, Jessica A. Turner, Martijn P. van den Heuvel, Odile L. van den Heuvel, Theo G.M. van Erp, Daan van Rooij, Dick J. Veltman, Henrik Walter, Yalin Wang, Joanna M. Wardlaw, Christopher D. Whelan, Margaret J. Wright, Jieping Ye


In this review, we discuss recent work by the ENIGMA Consortium (http://enigma.ini.usc.edu) - a global alliance of over 500 scientists spread across 200 institutions in 35 countries collectively analyzing brain imaging, clinical, and genetic data. Initially formed to detect genetic influences on brain measures, ENIGMA has grown to over 30 working groups studying 12 major brain diseases by pooling and comparing brain data. In some of the largest neuroimaging studies to date - of schizophrenia and major depression - ENIGMA has found replicable disease effects on the brain that are consistent worldwide, as well as factors that modulate disease effects. In partnership with other consortia including ADNI, CHARGE, IMAGEN and others, ENIGMA's genomic screens - now numbering over 30,000 MRI scans - have revealed at least 8 genetic loci that affect brain volumes. Downstream of gene findings, ENIGMA has revealed how these individual variants - and genetic variants in general - may affect both the brain and risk for a range of diseases. The ENIGMA consortium is discovering factors that consistently affect brain structure and function that will serve as future predictors linking individual brain scans and genomic data. It is generating vast pools of normative data on brain measures - from tens of thousands of people - that may help detect deviations from normal development or aging in specific groups of subjects. We discuss challenges and opportunities in applying these predictors to individual subjects and new cohorts, as well as lessons we have learned in ENIGMA's efforts so far.

Twitter Demographics

The data shown below were collected from the profiles of 75 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 302 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
New Zealand 1 <1%
Hungary 1 <1%
France 1 <1%
Australia 1 <1%
Unknown 298 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 65 22%
Researcher 58 19%
Student > Master 34 11%
Student > Bachelor 25 8%
Professor 22 7%
Other 57 19%
Unknown 41 14%
Readers by discipline Count As %
Neuroscience 60 20%
Psychology 44 15%
Medicine and Dentistry 41 14%
Agricultural and Biological Sciences 19 6%
Biochemistry, Genetics and Molecular Biology 15 5%
Other 57 19%
Unknown 66 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 44. 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 24 March 2019.
All research outputs
of 16,370,396 outputs
Outputs from NeuroImage
of 9,677 outputs
Outputs of similar age
of 369,610 outputs
Outputs of similar age from NeuroImage
of 298 outputs
Altmetric has tracked 16,370,396 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 9,677 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.1. This one has done particularly well, scoring higher than 96% 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 369,610 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 96% of its contemporaries.
We're also able to compare this research output to 298 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 94% of its contemporaries.