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A Computational Model for Spatial Navigation Based on Reference Frames in the Hippocampus, Retrosplenial Cortex, and Posterior Parietal Cortex

Overview of attention for article published in Frontiers in Neurorobotics, February 2017
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  • 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 (62nd percentile)

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Title
A Computational Model for Spatial Navigation Based on Reference Frames in the Hippocampus, Retrosplenial Cortex, and Posterior Parietal Cortex
Published in
Frontiers in Neurorobotics, February 2017
DOI 10.3389/fnbot.2017.00004
Pubmed ID
Authors

Timo Oess, Jeffrey L. Krichmar, Florian Röhrbein

Abstract

Behavioral studies for humans, monkeys, and rats have shown that, while traversing an environment, these mammals tend to use different frames of reference and frequently switch between them. These frames represent allocentric, egocentric, or route-centric views of the environment. However, combinations of either of them are often deployed. Neurophysiological studies on rats have indicated that the hippocampus, the retrosplenial cortex, and the posterior parietal cortex contribute to the formation of these frames and mediate the transformation between those. In this paper, we construct a computational model of the posterior parietal cortex and the retrosplenial cortex for spatial navigation. We demonstrate how the transformation of reference frames could be realized in the brain and suggest how different brain areas might use these reference frames to form navigational strategies and predict under what conditions an animal might use a specific type of reference frame. Our simulated navigation experiments demonstrate that the model's results closely resemble behavioral findings in humans and rats. These results suggest that navigation strategies may depend on the animal's reliance in a particular reference frame and shows how low confidence in a reference frame can lead to fluid adaptation and deployment of alternative navigation strategies. Because of its flexibility, our biologically inspired navigation system may be applied to autonomous robots.

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X Demographics

The data shown below were collected from the profiles of 8 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 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 99 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 28%
Researcher 18 18%
Student > Master 11 11%
Student > Bachelor 7 7%
Professor 4 4%
Other 12 12%
Unknown 19 19%
Readers by discipline Count As %
Neuroscience 26 26%
Agricultural and Biological Sciences 10 10%
Psychology 10 10%
Computer Science 8 8%
Engineering 6 6%
Other 11 11%
Unknown 28 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 02 January 2018.
All research outputs
#6,383,400
of 22,952,268 outputs
Outputs from Frontiers in Neurorobotics
#158
of 871 outputs
Outputs of similar age
#122,739
of 420,202 outputs
Outputs of similar age from Frontiers in Neurorobotics
#6
of 16 outputs
Altmetric has tracked 22,952,268 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 871 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done well, scoring higher than 81% 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 420,202 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 16 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 62% of its contemporaries.