Literature DB >> 22892761

Grid alignment in entorhinal cortex.

Bailu Si1, Emilio Kropff, Alessandro Treves.   

Abstract

The spatial responses of many of the cells recorded in all layers of rodent medial entorhinal cortex (mEC) show mutually aligned grid patterns. Recent experimental findings have shown that grids can often be better described as elliptical rather than purely circular and that, beyond the mutual alignment of their grid axes, ellipses tend to also orient their long axis along preferred directions. Are grid alignment and ellipse orientation aspects of the same phenomenon? Does the grid alignment result from single-unit mechanisms or does it require network interactions? We address these issues by refining a single-unit adaptation model of grid formation, to describe specifically the spontaneous emergence of conjunctive grid-by-head-direction cells in layers III, V, and VI of mEC. We find that tight alignment can be produced by recurrent collateral interactions, but this requires head-direction (HD) modulation. Through a competitive learning process driven by spatial inputs, grid fields then form already aligned, and with randomly distributed spatial phases. In addition, we find that the self-organization process is influenced by any anisotropy in the behavior of the simulated rat. The common grid alignment often orients along preferred running directions (RDs), as induced in a square environment. When speed anisotropy is present in exploration behavior, the shape of individual grids is distorted toward an ellipsoid arrangement. Speed anisotropy orients the long ellipse axis along the fast direction. Speed anisotropy on its own also tends to align grids, even without collaterals, but the alignment is seen to be loose. Finally, the alignment of spatial grid fields in multiple environments shows that the network expresses the same set of grid fields across environments, modulo a coherent rotation and translation. Thus, an efficient metric encoding of space may emerge through spontaneous pattern formation at the single-unit level, but it is coherent, hence context-invariant, if aided by collateral interactions.

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Mesh:

Year:  2012        PMID: 22892761     DOI: 10.1007/s00422-012-0513-7

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  25 in total

1.  Framing of grid cells within and beyond navigation boundaries.

Authors:  Francesco Savelli; J D Luck; James J Knierim
Journal:  Elife       Date:  2017-01-13       Impact factor: 8.140

2.  Neuronal rebound spiking, resonance frequency and theta cycle skipping may contribute to grid cell firing in medial entorhinal cortex.

Authors:  Michael E Hasselmo
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2013-12-23       Impact factor: 6.237

3.  Can rodents conceive hyperbolic spaces?

Authors:  Eugenio Urdapilleta; Francesca Troiani; Federico Stella; Alessandro Treves
Journal:  J R Soc Interface       Date:  2015-06-06       Impact factor: 4.118

4.  Modeling grid fields instead of modeling grid cells : An effective model at the macroscopic level and its relationship with the underlying microscopic neural system.

Authors:  Sophie Rosay; Simon Weber; Marcello Mulas
Journal:  J Comput Neurosci       Date:  2019-07-08       Impact factor: 1.621

Review 5.  Modelling effects on grid cells of sensory input during self-motion.

Authors:  Florian Raudies; James R Hinman; Michael E Hasselmo
Journal:  J Physiol       Date:  2016-07-10       Impact factor: 5.182

Review 6.  Current questions on space and time encoding.

Authors:  Michael E Hasselmo; Chantal E Stern
Journal:  Hippocampus       Date:  2015-04-15       Impact factor: 3.899

Review 7.  Spatial representation in the hippocampal formation: a history.

Authors:  Edvard I Moser; May-Britt Moser; Bruce L McNaughton
Journal:  Nat Neurosci       Date:  2017-10-26       Impact factor: 24.884

Review 8.  Neural mechanisms of navigation involving interactions of cortical and subcortical structures.

Authors:  James R Hinman; Holger Dannenberg; Andrew S Alexander; Michael E Hasselmo
Journal:  J Neurophysiol       Date:  2018-02-14       Impact factor: 2.714

9.  Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity.

Authors:  Simon Nikolaus Weber; Henning Sprekeler
Journal:  Elife       Date:  2018-02-21       Impact factor: 8.140

Review 10.  Theta rhythm and the encoding and retrieval of space and time.

Authors:  Michael E Hasselmo; Chantal E Stern
Journal:  Neuroimage       Date:  2013-06-14       Impact factor: 6.556

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