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Modeling Boundary Vector Cell Firing Given Optic Flow as a Cue

Overview of attention for article published in PLoS Computational Biology, June 2012
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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 (82nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

blogs
1 blog
twitter
1 X user

Citations

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38 Dimensions

Readers on

mendeley
90 Mendeley
citeulike
3 CiteULike
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Title
Modeling Boundary Vector Cell Firing Given Optic Flow as a Cue
Published in
PLoS Computational Biology, June 2012
DOI 10.1371/journal.pcbi.1002553
Pubmed ID
Authors

Florian Raudies, Michael E. Hasselmo

Abstract

Boundary vector cells in entorhinal cortex fire when a rat is in locations at a specific distance from walls of an environment. This firing may originate from memory of the barrier location combined with path integration, or the firing may depend upon the apparent visual input image stream. The modeling work presented here investigates the role of optic flow, the apparent change of patterns of light on the retina, as input for boundary vector cell firing. Analytical spherical flow is used by a template model to segment walls from the ground, to estimate self-motion and the distance and allocentric direction of walls, and to detect drop-offs. Distance estimates of walls in an empty circular or rectangular box have a mean error of less than or equal to two centimeters. Integrating these estimates into a visually driven boundary vector cell model leads to the firing patterns characteristic for boundary vector cells. This suggests that optic flow can influence the firing of boundary vector cells.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 7%
Germany 2 2%
Hungary 1 1%
Netherlands 1 1%
Portugal 1 1%
United Kingdom 1 1%
France 1 1%
Unknown 77 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 34%
Researcher 22 24%
Student > Master 11 12%
Student > Bachelor 5 6%
Student > Doctoral Student 4 4%
Other 9 10%
Unknown 8 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 30%
Neuroscience 21 23%
Psychology 8 9%
Computer Science 8 9%
Medicine and Dentistry 4 4%
Other 12 13%
Unknown 10 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 07 July 2012.
All research outputs
#4,776,426
of 25,838,141 outputs
Outputs from PLoS Computational Biology
#3,764
of 9,050 outputs
Outputs of similar age
#30,895
of 178,433 outputs
Outputs of similar age from PLoS Computational Biology
#42
of 108 outputs
Altmetric has tracked 25,838,141 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,050 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 58% 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 178,433 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 82% of its contemporaries.
We're also able to compare this research output to 108 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 61% of its contemporaries.