Literature DB >> 24577877

A feedforward model for the formation of a grid field where spatial information is provided solely from place cells.

Luísa Castro1, Paulo Aguiar.   

Abstract

Grid cells (GCs) in the medial entorhinal cortex (mEC) have the property of having their firing activity spatially tuned to a regular triangular lattice. Several theoretical models for grid field formation have been proposed, but most assume that place cells (PCs) are a product of the grid cell system. There is, however, an alternative possibility that is supported by various strands of experimental data. Here we present a novel model for the emergence of gridlike firing patterns that stands on two key hypotheses: (1) spatial information in GCs is provided from PC activity and (2) grid fields result from a combined synaptic plasticity mechanism involving inhibitory and excitatory neurons mediating the connections between PCs and GCs. Depending on the spatial location, each PC can contribute with excitatory or inhibitory inputs to GC activity. The nature and magnitude of the PC input is a function of the distance to the place field center, which is inferred from rate decoding. A biologically plausible learning rule drives the evolution of the connection strengths from PCs to a GC. In this model, PCs compete for GC activation, and the plasticity rule favors efficient packing of the space representation. This leads to gridlike firing patterns. In a new environment, GCs continuously recruit new PCs to cover the entire space. The model described here makes important predictions and can represent the feedforward connections from hippocampus CA1 to deeper mEC layers.

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Year:  2014        PMID: 24577877     DOI: 10.1007/s00422-013-0581-3

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


  9 in total

1.  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 2.  The grid code for ordered experience.

Authors:  Jon W Rueckemann; Marielena Sosa; Lisa M Giocomo; Elizabeth A Buffalo
Journal:  Nat Rev Neurosci       Date:  2021-08-27       Impact factor: 38.755

3.  Spatiotemporally random and diverse grid cell spike patterns contribute to the transformation of grid cell to place cell in a neural network model.

Authors:  Sahn Woo Park; Hyun Jae Jang; Mincheol Kim; Jeehyun Kwag
Journal:  PLoS One       Date:  2019-11-14       Impact factor: 3.240

4.  A Model of Spatial Cell Development in Rat Hippocampus Based on Artificial Neural Network.

Authors:  Naigong Yu; Hejie Yu; Yishen Liao; Zongxia Wang; Ouattara Sie
Journal:  J Healthc Eng       Date:  2021-10-26       Impact factor: 2.682

5.  Extracting grid cell characteristics from place cell inputs using non-negative principal component analysis.

Authors:  Yedidyah Dordek; Daniel Soudry; Ron Meir; Dori Derdikman
Journal:  Elife       Date:  2016-03-08       Impact factor: 8.140

6.  Contribution of Embodiment to Solving the Riddle of Infantile Amnesia.

Authors:  Arthur M Glenberg; Justin Hayes
Journal:  Front Psychol       Date:  2016-01-25

7.  A single-cell spiking model for the origin of grid-cell patterns.

Authors:  Tiziano D'Albis; Richard Kempter
Journal:  PLoS Comput Biol       Date:  2017-10-02       Impact factor: 4.475

8.  A Brain-Inspired Adaptive Space Representation Model Based on Grid Cells and Place Cells.

Authors:  Kun Han; Dewei Wu; Lei Lai
Journal:  Comput Intell Neurosci       Date:  2020-08-11

Review 9.  Microcircuits for spatial coding in the medial entorhinal cortex.

Authors:  John J Tukker; Prateep Beed; Michael Brecht; Richard Kempter; Edvard I Moser; Dietmar Schmitz
Journal:  Physiol Rev       Date:  2021-07-13       Impact factor: 37.312

  9 in total

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