Literature DB >> 18596161

What grid cells convey about rat location.

Ila R Fiete1, Yoram Burak, Ted Brookings.   

Abstract

We characterize the relationship between the simultaneously recorded quantities of rodent grid cell firing and the position of the rat. The formalization reveals various properties of grid cell activity when considered as a neural code for representing and updating estimates of the rat's location. We show that, although the spatially periodic response of grid cells appears wasteful, the code is fully combinatorial in capacity. The resulting range for unambiguous position representation is vastly greater than the approximately 1-10 m periods of individual lattices, allowing for unique high-resolution position specification over the behavioral foraging ranges of rats, with excess capacity that could be used for error correction. Next, we show that the merits of the grid cell code for position representation extend well beyond capacity and include arithmetic properties that facilitate position updating. We conclude by considering the numerous implications, for downstream readouts and experimental tests, of the properties of the grid cell code.

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Mesh:

Year:  2008        PMID: 18596161      PMCID: PMC6670990          DOI: 10.1523/JNEUROSCI.5684-07.2008

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  72 in total

Review 1.  How environment and self-motion combine in neural representations of space.

Authors:  Talfan Evans; Andrej Bicanski; Daniel Bush; Neil Burgess
Journal:  J Physiol       Date:  2016-01-06       Impact factor: 5.182

2.  Grid cell mechanisms and function: contributions of entorhinal persistent spiking and phase resetting.

Authors:  Michael E Hasselmo
Journal:  Hippocampus       Date:  2008       Impact factor: 3.899

3.  Conversion of a phase- to a rate-coded position signal by a three-stage model of theta cells, grid cells, and place cells.

Authors:  Hugh T Blair; Kishan Gupta; Kechen Zhang
Journal:  Hippocampus       Date:  2008       Impact factor: 3.899

Review 4.  Independence of landmark and self-motion-guided navigation: a different role for grid cells.

Authors:  Bruno Poucet; Francesca Sargolini; Eun Y Song; Balázs Hangya; Steven Fox; Robert U Muller
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2013-12-23       Impact factor: 6.237

5.  Grid cells generate an analog error-correcting code for singularly precise neural computation.

Authors:  Sameet Sreenivasan; Ila Fiete
Journal:  Nat Neurosci       Date:  2011-09-11       Impact factor: 24.884

6.  Intermittency coding in the primary olfactory system: a neural substrate for olfactory scene analysis.

Authors:  Il Memming Park; Yuriy V Bobkov; Barry W Ache; José C Príncipe
Journal:  J Neurosci       Date:  2014-01-15       Impact factor: 6.167

Review 7.  Framing the grid: effect of boundaries on grid cells and navigation.

Authors:  Julija Krupic; Marius Bauza; Stephen Burton; John O'Keefe
Journal:  J Physiol       Date:  2016-05-10       Impact factor: 5.182

8.  Megamap: flexible representation of a large space embedded with nonspatial information by a hippocampal attractor network.

Authors:  Kathryn R Hedrick; Kechen Zhang
Journal:  J Neurophysiol       Date:  2016-05-18       Impact factor: 2.714

9.  Driving reservoir models with oscillations: a solution to the extreme structural sensitivity of chaotic networks.

Authors:  Philippe Vincent-Lamarre; Guillaume Lajoie; Jean-Philippe Thivierge
Journal:  J Comput Neurosci       Date:  2016-09-02       Impact factor: 1.621

10.  Accurate path integration in continuous attractor network models of grid cells.

Authors:  Yoram Burak; Ila R Fiete
Journal:  PLoS Comput Biol       Date:  2009-02-20       Impact factor: 4.475

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