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Inferring Nonlinear Neuronal Computation Based on Physiologically Plausible Inputs

Overview of attention for article published in PLoS Computational Biology, July 2013
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

Mentioned by

patent
1 patent
googleplus
1 Google+ user

Citations

dimensions_citation
156 Dimensions

Readers on

mendeley
209 Mendeley
citeulike
3 CiteULike
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Title
Inferring Nonlinear Neuronal Computation Based on Physiologically Plausible Inputs
Published in
PLoS Computational Biology, July 2013
DOI 10.1371/journal.pcbi.1003143
Pubmed ID
Authors

James M. McFarland, Yuwei Cui, Daniel A. Butts

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 209 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 4%
United Kingdom 3 1%
France 2 <1%
Germany 2 <1%
Netherlands 1 <1%
Ireland 1 <1%
Austria 1 <1%
Belarus 1 <1%
Canada 1 <1%
Other 0 0%
Unknown 189 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 64 31%
Researcher 48 23%
Student > Master 22 11%
Student > Bachelor 15 7%
Student > Doctoral Student 13 6%
Other 23 11%
Unknown 24 11%
Readers by discipline Count As %
Neuroscience 61 29%
Agricultural and Biological Sciences 50 24%
Engineering 23 11%
Computer Science 12 6%
Physics and Astronomy 10 5%
Other 21 10%
Unknown 32 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 16 January 2024.
All research outputs
#7,427,456
of 25,576,801 outputs
Outputs from PLoS Computational Biology
#5,026
of 9,003 outputs
Outputs of similar age
#59,137
of 208,339 outputs
Outputs of similar age from PLoS Computational Biology
#49
of 106 outputs
Altmetric has tracked 25,576,801 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 9,003 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 42nd percentile – i.e., 42% 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 208,339 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 106 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 53% of its contemporaries.