Accurate Path Integration in Continuous Attractor Network Models of Grid Cells

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Accurate Path Integration in Continuous Attractor Network Models of Grid Cells

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Title: Accurate Path Integration in Continuous Attractor Network Models of Grid Cells
Author: Fiete, Ila R.; Burak, Yoram

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Citation: Burak, Yoram, and Ila R. Fiete. 2009. Accurate Path Integration in Continuous Attractor Network Models of Grid Cells. PLoS Computational Biology 5(2): e1000291.
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Abstract: Grid cells in the rat entorhinal cortex display strikingly regular firing
responses to the animal's position in 2-D space and have been
hypothesized to form the neural substrate for dead-reckoning. However, errors
accumulate rapidly when velocity inputs are integrated in existing models of
grid cell activity. To produce grid-cell-like responses, these models would
require frequent resets triggered by external sensory cues. Such inadequacies,
shared by various models, cast doubt on the dead-reckoning potential of the grid
cell system. Here we focus on the question of accurate path integration,
specifically in continuous attractor models of grid cell activity. We show, in
contrast to previous models, that continuous attractor models can generate
regular triangular grid responses, based on inputs that encode only the
rat's velocity and heading direction. We consider the role of the
network boundary in the integration performance of the network and show that
both periodic and aperiodic networks are capable of accurate path integration,
despite important differences in their attractor manifolds. We quantify the rate
at which errors in the velocity integration accumulate as a function of network
size and intrinsic noise within the network. With a plausible range of
parameters and the inclusion of spike variability, our model networks can
accurately integrate velocity inputs over a maximum of ∼10–100
meters and ∼1–10 minutes. These findings form a
proof-of-concept that continuous attractor dynamics may underlie velocity
integration in the dorsolateral medial entorhinal cortex. The simulations also
generate pertinent upper bounds on the accuracy of integration that may be
achieved by continuous attractor dynamics in the grid cell network. We suggest
experiments to test the continuous attractor model and differentiate it from
models in which single cells establish their responses independently of each
other.
Published Version: doi:10.1371/journal.pcbi.1000291
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2632741/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:11213318
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