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Accurate Path Integration in Continuous Attractor Network Models of Grid Cells

Overview of attention for article published in PLoS Computational Biology, February 2009
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

twitter
6 X users
patent
1 patent
wikipedia
10 Wikipedia pages

Citations

dimensions_citation
601 Dimensions

Readers on

mendeley
677 Mendeley
citeulike
7 CiteULike
connotea
1 Connotea
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Title
Accurate Path Integration in Continuous Attractor Network Models of Grid Cells
Published in
PLoS Computational Biology, February 2009
DOI 10.1371/journal.pcbi.1000291
Pubmed ID
Authors

Yoram Burak, Ila R. Fiete

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 677 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 18 3%
United Kingdom 6 <1%
Germany 4 <1%
Norway 4 <1%
Netherlands 3 <1%
France 2 <1%
Italy 2 <1%
Switzerland 2 <1%
Kenya 1 <1%
Other 3 <1%
Unknown 632 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 197 29%
Researcher 117 17%
Student > Master 78 12%
Student > Bachelor 69 10%
Professor 28 4%
Other 88 13%
Unknown 100 15%
Readers by discipline Count As %
Neuroscience 178 26%
Agricultural and Biological Sciences 151 22%
Computer Science 62 9%
Physics and Astronomy 39 6%
Engineering 38 6%
Other 102 15%
Unknown 107 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 18 November 2023.
All research outputs
#3,846,447
of 25,622,179 outputs
Outputs from PLoS Computational Biology
#3,309
of 9,017 outputs
Outputs of similar age
#13,064
of 109,944 outputs
Outputs of similar age from PLoS Computational Biology
#11
of 42 outputs
Altmetric has tracked 25,622,179 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,017 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has gotten more attention than average, scoring higher than 63% 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 109,944 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 85% of its contemporaries.
We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.