1. Computational and Systems Biology
  2. Neuroscience
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Place-cell capacity and volatility with grid-like inputs

  1. Man Yi Yim
  2. Lorenzo A Sadun
  3. Ila R Fiete  Is a corresponding author
  4. Thibaud Taillefumier  Is a corresponding author
  1. The University of Texas, Austin, United States
  2. Brain & Cognitive Sciences Department and the McGovern Institute at MIT, United States
Research Article
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Cite this article as: eLife 2021;10:e62702 doi: 10.7554/eLife.62702


What factors constrain the arrangement of the multiple fields of a place cell? By modeling place cells as perceptrons that act on multiscale periodic grid-cell inputs, we analytically enumerate a place cell's repertoire - how many field arrangements it can realize without external cues while its grid inputs are unique; and derive its capacity - the spatial range over which it can achieve any field arrangement. We show that the repertoire is very large and relatively noise-robust. However, the repertoire is a vanishing fraction of all arrangements, while capacity scales only as the sum of the grid periods so field arrangements are constrained over larger distances. Thus, grid-driven place field arrangements define a large response scaffold that is strongly constrained by its structured inputs. Finally, we show that altering grid-place weights to generate an arbitrary new place field strongly affects existing arrangements, which could explain the volatility of the place code.

Data availability

The authors confirm that the data supporting the findings of this study are available within the article. Implementation details and code are available at: https://github.com/myyim/placecellperceptron.

Article and author information

Author details

  1. Man Yi Yim

    Department of Neuroscience, The University of Texas, Austin, Austin, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Lorenzo A Sadun

    Department of Mathematics, The University of Texas, Austin, Austin, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2518-573X
  3. Ila R Fiete

    Brain & Cognitive Sciences Department and the McGovern Institute at MIT, Cambridge, United States
    For correspondence
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4738-2539
  4. Thibaud Taillefumier

    Department of Mathematics and Neuroscience, The University of Texas, Austin, Austin, United States
    For correspondence
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3538-6882


Simons Foundation (Simons Collaboration on the Global Brain)

  • Man Yi Yim
  • Ila R Fiete

Howard Hughes Medical Institute (Faculty Scholars Program)

  • Ila R Fiete

Alfred P. Sloan Foundation (Alfred P. Sloan Research Fellowship FG-2017-9554)

  • Thibaud Taillefumier

Office of Naval Research (S&T BAA Award N00014-19-1-2584)

  • Ila R Fiete

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

Reviewing Editor

  1. Gordon J Berman, Emory University, United States

Publication history

  1. Received: September 2, 2020
  2. Accepted: April 28, 2021
  3. Accepted Manuscript published: May 24, 2021 (version 1)
  4. Accepted Manuscript updated: May 26, 2021 (version 2)
  5. Version of Record published: July 21, 2021 (version 3)


© 2021, Yim 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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