From grid cells to place cells with realistic field sizes

  • While grid cells in the medial entorhinal cortex (MEC) of rodents have multiple, regularly arranged firing fields, place cells in the cornu ammonis (CA) regions of the hippocampus mostly have single spatial firing fields. Since there are extensive projections from MEC to the CA regions, many models have suggested that a feedforward network can transform grid cell firing into robust place cell firing. However, these models generate place fields that are consistently too small compared to those recorded in experiments. Here, we argue that it is implausible that grid cell activity alone can be transformed into place cells with robust place fields of realistic size in a feedforward network. We propose two solutions to this problem. Firstly, weakly spatially modulated cells, which are abundant throughout EC, provide input to downstream place cells along with grid cells. This simple model reproduces many place cell characteristics as well as results from lesion studies. Secondly, the recurrent connections between place cells in the CA3 network generate robust and realistic place fields. Both mechanisms could work in parallel in the hippocampal formation and this redundancy might account for the robustness of place cell responses to a range of disruptions of the hippocampal circuitry.

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Metadaten
Author:Torsten NeherGND, Amir Hossein AziziGND, Sen ChengORCiDGND
URN:urn:nbn:de:hbz:294-73598
DOI:https://doi.org/10.1371/journal.pone.0181618
Parent Title (English):PLoS ONE
Publisher:Public Library of Science
Place of publication:San Francisco
Document Type:Article
Language:English
Date of Publication (online):2020/07/22
Date of first Publication:2017/07/27
Publishing Institution:Ruhr-Universität Bochum, Universitätsbibliothek
Volume:12
Issue:7, Artikel e0181618
First Page:e0181618-1
Last Page:e0181618-27
Institutes/Facilities:Mercator Forschergruppe "Strukturen des Gedächtnisses"
Research Department of Neuroscience
Institut für Neuroinformatik, Research Group Computational Neuroscience
Sonderforschungsbereich 1280, A14 - Modellierung der Kontext-Abhängigkeit des Akquisitions- und Extinktionslernens
open_access (DINI-Set):open_access
Licence (English):License LogoCreative Commons - CC BY 4.0 - Attribution 4.0 International