Journal
HIPPOCAMPUS
Volume 22, Issue 2, Pages 320-334Publisher
WILEY-BLACKWELL
DOI: 10.1002/hipo.20901
Keywords
grid cells; entorhinal cortex; self-organized learning; path integration; spatial navigation
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Funding
- CELEST, an NSF Science of Learning Center [SBE-0354378]
- DARPA [HR0011-09-C-0001]
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Grid cells in the dorsal segment of the medial entorhinal cortex (dMEC) show remarkable hexagonal activity patterns, at multiple spatial scales, during spatial navigation. It has previously been shown how a self-organizing map can convert firing patterns across entorhinal grid cells into hippocampal place cells that are capable of representing much larger spatial scales. Can grid cell firing fields also arise during navigation through learning within a self-organizing map This article describes a simple and general mathematical property of the trigonometry of spatial navigation which favors hexagonal patterns. The article also develops a neural model that can learn to exploit this trigonometric relationship. This GRIDSmap self-organizing map model converts path integration signals into hexagonal grid cell patterns of multiple scales. GRIDSmap creates only grid cell firing patterns with the observed hexagonal structure, predicts how these hexagonal patterns can be learned from experience, and can process biologically plausible neural input and output signals during navigation. These results support an emerging unified computational framework based on a hierarchy of self-organizing maps for explaining how entorhinal-hippocampal interactions support spatial navigation. (C) 2010 Wiley Periodicals, Inc.
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