Models of grid cell spatial firing published 2005-2011

Since the discovery of grid cells in rat entorhinal cortex, many models of their hexagonally-arrayed spatial firing fields have been suggested. We review the models and organize them according to the mechanisms they use to encode position, update the positional code, read it out in the spatial grid...

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Main Author: Eric A Zilli
Format: Article
Language:English
Published: Frontiers Media S.A. 2012-04-01
Series:Frontiers in Neural Circuits
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fncir.2012.00016/full
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author Eric A Zilli
author_facet Eric A Zilli
author_sort Eric A Zilli
collection DOAJ
description Since the discovery of grid cells in rat entorhinal cortex, many models of their hexagonally-arrayed spatial firing fields have been suggested. We review the models and organize them according to the mechanisms they use to encode position, update the positional code, read it out in the spatial grid pattern, and learn any patterned synaptic connections needed. We mention biological implementations of the models, but focus on on the models on Marr's algorithmic level, where they are not things to individually prove or disprove, but rather are a valuable collection of metaphors of the grid cell system for guiding research that are all likely true to some degree, with each simply emphasizing different aspects of the system. For the convenience of interested researchers, MATLAB implementations of the discussed grid cell models are provided at ModelDB accession 144006 or http://people.bu.edu/zilli/gridmodels.html.
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spelling doaj.art-bc237b970d7b4633bbc1b292682512042022-12-22T02:32:06ZengFrontiers Media S.A.Frontiers in Neural Circuits1662-51102012-04-01610.3389/fncir.2012.0001620608Models of grid cell spatial firing published 2005-2011Eric A Zilli0Boston UniversitySince the discovery of grid cells in rat entorhinal cortex, many models of their hexagonally-arrayed spatial firing fields have been suggested. We review the models and organize them according to the mechanisms they use to encode position, update the positional code, read it out in the spatial grid pattern, and learn any patterned synaptic connections needed. We mention biological implementations of the models, but focus on on the models on Marr's algorithmic level, where they are not things to individually prove or disprove, but rather are a valuable collection of metaphors of the grid cell system for guiding research that are all likely true to some degree, with each simply emphasizing different aspects of the system. For the convenience of interested researchers, MATLAB implementations of the discussed grid cell models are provided at ModelDB accession 144006 or http://people.bu.edu/zilli/gridmodels.html.http://journal.frontiersin.org/Journal/10.3389/fncir.2012.00016/fullpath integrationself-organizationPlace cellmedial temporal lobering attractor
spellingShingle Eric A Zilli
Models of grid cell spatial firing published 2005-2011
Frontiers in Neural Circuits
path integration
self-organization
Place cell
medial temporal lobe
ring attractor
title Models of grid cell spatial firing published 2005-2011
title_full Models of grid cell spatial firing published 2005-2011
title_fullStr Models of grid cell spatial firing published 2005-2011
title_full_unstemmed Models of grid cell spatial firing published 2005-2011
title_short Models of grid cell spatial firing published 2005-2011
title_sort models of grid cell spatial firing published 2005 2011
topic path integration
self-organization
Place cell
medial temporal lobe
ring attractor
url http://journal.frontiersin.org/Journal/10.3389/fncir.2012.00016/full
work_keys_str_mv AT ericazilli modelsofgridcellspatialfiringpublished20052011