| Literature DB >> 25948611 |
Eugenio Urdapilleta1, Francesca Troiani1, Federico Stella1, Alessandro Treves2.
Abstract
The grid cells discovered in the rodent medial entorhinal cortex have been proposed to provide a metric for Euclidean space, possibly even hardwired in the embryo. Yet, one class of models describing the formation of grid unit selectivity is entirely based on developmental self-organization, and as such it predicts that the metric it expresses should reflect the environment to which the animal has adapted. We show that, according to self-organizing models, if raised in a non-Euclidean hyperbolic cage rats should be able to form hyperbolic grids. For a given range of grid spacing relative to the radius of negative curvature of the hyperbolic surface, such grids are predicted to appear as multi-peaked firing maps, in which each peak has seven neighbours instead of the Euclidean six, a prediction that can be tested in experiments. We thus demonstrate that a useful universal neuronal metric, in the sense of a multi-scale ruler and compass that remain unaltered when changing environments, can be extended to other than the standard Euclidean plane.Entities:
Keywords: grid cells; hyperbolic geometry; self-organizing process; space representation
Mesh:
Year: 2015 PMID: 25948611 PMCID: PMC4590491 DOI: 10.1098/rsif.2014.1214
Source DB: PubMed Journal: J R Soc Interface ISSN: 1742-5662 Impact factor: 4.118