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Grid coding, spatial representation, and navigation: Should we assume an isomorphism?
Author(s) -
Ekstrom Arne D.,
Harootonian Sevan K.,
Huffman Derek J.
Publication year - 2020
Publication title -
hippocampus
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.767
H-Index - 155
eISSN - 1098-1063
pISSN - 1050-9631
DOI - 10.1002/hipo.23175
Subject(s) - grid , coding (social sciences) , spatial memory , computer science , isomorphism (crystallography) , spatial cognition , neural coding , cognitive science , perspective (graphical) , cognitive map , mental representation , representation (politics) , spatial relation , artificial intelligence , metric (unit) , grid cell , theoretical computer science , space (punctuation) , cognition , psychology , mathematics , neuroscience , working memory , engineering , operations management , law , chemistry , crystal structure , geometry , political science , statistics , politics , crystallography , operating system
Abstract Grid cells provide a compelling example of a link between cellular activity and an abstract and difficult to define concept like space. Accordingly, a representational perspective on grid coding argues that neural grid coding underlies a fundamentally spatial metric. Recently, some theoretical proposals have suggested extending such a framework to nonspatial cognition as well, such as category learning. Here, we provide a critique of the frequently employed assumption of an isomorphism between patterns of neural activity (e.g., grid cells), mental representation, and behavior (e.g., navigation). Specifically, we question the strict isomorphism between these three levels and suggest that human spatial navigation is perhaps best characterized by a wide variety of both metric and nonmetric strategies. We offer an alternative perspective on how grid coding might relate to human spatial navigation, arguing that grid coding is part of a much larger conglomeration of neural activity patterns that dynamically tune to accomplish specific behavioral outputs.