1. Neuroscience
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Theta-modulation drives the emergence of connectivity patterns underlying replay in a network model of place cells

  1. Panagiota Theodoni
  2. Bernat Rovira
  3. Yingxue Wang
  4. Alex Roxin  Is a corresponding author
  1. Centre de Recerca Matemàtica, Spain
  2. Max Planck Florida Institute for Neuroscience, United States
Research Article
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Cite this article as: eLife 2018;7:e37388 doi: 10.7554/eLife.37388

Abstract

Place cells of the rodent hippocampus fire action potentials when the animal traverses a particular spatial location in any environment. Therefore for any given trajectory one observes a repeatable sequence of place cell activations. When the animal is quiescent or sleeping, one can observe similar sequences of activation known as replay, which underlie the process of memory consolidation. However, it remains unclear how replay is generated. Here we show how a temporally asymmetric plasticity rule during spatial exploration gives rise to spontaneous replay in a model network by shaping the recurrent connectivity to reflect the topology of the learned environment. Crucially, the rate of this encoding is strongly modulated by ongoing rhythms. Oscillations in the theta range optimize learning by generating repeated pre-post pairings on a time-scale commensurate with the window for plasticity, while lower and higher frequencies generate learning rates which are lower by orders of magnitude.

Article and author information

Author details

  1. Panagiota Theodoni

    Computational Neuroscience, Centre de Recerca Matemàtica, Bellaterra, Spain
    Competing interests
    The authors declare that no competing interests exist.
  2. Bernat Rovira

    Computational Neuroscience, Centre de Recerca Matemàtica, Bellaterra, Spain
    Competing interests
    The authors declare that no competing interests exist.
  3. Yingxue Wang

    Max Planck Florida Institute for Neuroscience, Jupiter, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Alex Roxin

    Computational Neuroscience, Centre de Recerca Matemàtica, Bellaterra, Spain
    For correspondence
    aroxin@crm.cat
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1015-8138

Funding

Ministerio de Economía y Competitividad (BFU-2012-33413)

  • Alex Roxin

Ministerio de Economía y Competitividad (MTM-2015-71509)

  • Alex Roxin

Generalitat de Catalunya (CERCA program)

  • Alex Roxin

Howard Hughes Medical Institute

  • Yingxue Wang

Max-Planck-Gesellschaft

  • Yingxue Wang

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Mark CW van Rossum, University of Nottingham, United Kingdom

Publication history

  1. Received: April 9, 2018
  2. Accepted: October 24, 2018
  3. Accepted Manuscript published: October 25, 2018 (version 1)
  4. Version of Record published: November 8, 2018 (version 2)

Copyright

© 2018, Theodoni et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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