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On Shapley Ratings in Brain Networks

Overview of attention for article published in Frontiers in Neuroinformatics, November 2016
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Title
On Shapley Ratings in Brain Networks
Published in
Frontiers in Neuroinformatics, November 2016
DOI 10.3389/fninf.2016.00051
Pubmed ID
Authors

Marieke Musegaas, Bas J. Dietzenbacher, Peter E. M. Borm

Abstract

We consider the problem of computing the influence of a neuronal structure in a brain network. Abraham et al. (2006) computed this influence by using the Shapley value of a coalitional game corresponding to a directed network as a rating. Kötter et al. (2007) applied this rating to large-scale brain networks, in particular to the macaque visual cortex and the macaque prefrontal cortex. Our aim is to improve upon the above technique by measuring the importance of subgroups of neuronal structures in a different way. This new modeling technique not only leads to a more intuitive coalitional game, but also allows for specifying the relative influence of neuronal structures and a direct extension to a setting with missing information on the existence of certain connections.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 1%
Portugal 1 1%
France 1 1%
Norway 1 1%
Unknown 66 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 9%
Student > Master 5 7%
Professor 4 6%
Other 1 1%
Student > Ph. D. Student 1 1%
Other 2 3%
Unknown 51 73%
Readers by discipline Count As %
Engineering 5 7%
Psychology 4 6%
Agricultural and Biological Sciences 3 4%
Neuroscience 3 4%
Computer Science 1 1%
Other 1 1%
Unknown 53 76%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 19 December 2016.
All research outputs
#13,495,562
of 22,912,409 outputs
Outputs from Frontiers in Neuroinformatics
#438
of 751 outputs
Outputs of similar age
#208,046
of 416,545 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#8
of 11 outputs
Altmetric has tracked 22,912,409 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 751 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.3. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
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 416,545 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.