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

Abstract

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
    fiete@mit.edu
    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
    ttaillef@austin.utexas.edu
    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

Funding

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.

Copyright

© 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.

Metrics

  • 1,364
    views
  • 297
    downloads
  • 9
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Man Yi Yim
  2. Lorenzo A Sadun
  3. Ila R Fiete
  4. Thibaud Taillefumier
(2021)
Place-cell capacity and volatility with grid-like inputs
eLife 10:e62702.
https://doi.org/10.7554/eLife.62702

Share this article

https://doi.org/10.7554/eLife.62702

Further reading

    1. Computational and Systems Biology
    2. Neuroscience
    Anna Cattani, Don B Arnold ... Nancy Kopell
    Research Article

    The basolateral amygdala (BLA) is a key site where fear learning takes place through synaptic plasticity. Rodent research shows prominent low theta (~3–6 Hz), high theta (~6–12 Hz), and gamma (>30 Hz) rhythms in the BLA local field potential recordings. However, it is not understood what role these rhythms play in supporting the plasticity. Here, we create a biophysically detailed model of the BLA circuit to show that several classes of interneurons (PV, SOM, and VIP) in the BLA can be critically involved in producing the rhythms; these rhythms promote the formation of a dedicated fear circuit shaped through spike-timing-dependent plasticity. Each class of interneurons is necessary for the plasticity. We find that the low theta rhythm is a biomarker of successful fear conditioning. The model makes use of interneurons commonly found in the cortex and, hence, may apply to a wide variety of associative learning situations.

    1. Cancer Biology
    2. Computational and Systems Biology
    Rosalyn W Sayaman, Masaru Miyano ... Mark LaBarge
    Research Article

    Effects from aging in single cells are heterogenous, whereas at the organ- and tissue-levels aging phenotypes tend to appear as stereotypical changes. The mammary epithelium is a bilayer of two major phenotypically and functionally distinct cell lineages: luminal epithelial and myoepithelial cells. Mammary luminal epithelia exhibit substantial stereotypical changes with age that merit attention because these cells are the putative cells-of-origin for breast cancers. We hypothesize that effects from aging that impinge upon maintenance of lineage fidelity increase susceptibility to cancer initiation. We generated and analyzed transcriptomes from primary luminal epithelial and myoepithelial cells from younger <30 (y)ears old and older >55y women. In addition to age-dependent directional changes in gene expression, we observed increased transcriptional variance with age that contributed to genome-wide loss of lineage fidelity. Age-dependent variant responses were common to both lineages, whereas directional changes were almost exclusively detected in luminal epithelia and involved altered regulation of chromatin and genome organizers such as SATB1. Epithelial expression of gap junction protein GJB6 increased with age, and modulation of GJB6 expression in heterochronous co-cultures revealed that it provided a communication conduit from myoepithelial cells that drove directional change in luminal cells. Age-dependent luminal transcriptomes comprised a prominent signal that could be detected in bulk tissue during aging and transition into cancers. A machine learning classifier based on luminal-specific aging distinguished normal from cancer tissue and was highly predictive of breast cancer subtype. We speculate that luminal epithelia are the ultimate site of integration of the variant responses to aging in their surrounding tissue, and that their emergent phenotype both endows cells with the ability to become cancer-cells-of-origin and represents a biosensor that presages cancer susceptibility.