Learning accurate path integration in ring attractor models of the head direction system

  1. Pantelis Vafidis  Is a corresponding author
  2. David Owald
  3. Tiziano D'Albis
  4. Richard Kempter  Is a corresponding author
  1. California Institute of Technology, United States
  2. Charité - Universitätsmedizin Berlin, Germany
  3. Humboldt-Universität zu Berlin, Germany

Abstract

Ring attractor models for angular path integration have received strong experimental support. To function as integrators, head direction circuits require precisely tuned connectivity, but it is currently unknown how such tuning could be achieved. Here, we propose a network model in which a local, biologically plausible learning rule adjusts synaptic efficacies during development, guided by supervisory allothetic cues. Applied to the Drosophila head direction system, the model learns to path-integrate accurately and develops a connectivity strikingly similar to the one reported in experiments. The mature network is a quasi-continuous attractor and reproduces key experiments in which optogenetic stimulation controls the internal representation of heading, and where the network remaps to integrate with different gains in rodents. Our model predicts that path integration requires self-supervised learning during a developmental phase, and proposes a general framework to learn to path-integrate with gain-1 even in architectures that lack the physical topography of a ring.

Data availability

All code used in this work is available at https://github.com/panvaf/LearnPI. The files required to reproduce the figures can be found at https://gin.g-node.org/pavaf/LearnPI.

The following previously published data sets were used

Article and author information

Author details

  1. Pantelis Vafidis

    Computation and Neural Systems, California Institute of Technology, Pasadena, United States
    For correspondence
    pvafeidi@caltech.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9768-0609
  2. David Owald

    NeuroCure, Charité - Universitätsmedizin Berlin, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7747-7884
  3. Tiziano D'Albis

    Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1585-1433
  4. Richard Kempter

    Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany
    For correspondence
    r.kempter@biologie.hu-berlin.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5344-2983

Funding

German Research Foundation (SFB 1315 - project-ID 327654276)

  • David Owald
  • Richard Kempter

Emmy Noether Programme (282979116)

  • David Owald

German Federal Ministry for Education and Research (01GQ1705)

  • Richard Kempter

Onassis Foundation Scholarship

  • Pantelis Vafidis

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

Reviewing Editor

  1. Srdjan Ostojic, Ecole Normale Superieure Paris, France

Version history

  1. Preprint posted: March 12, 2021 (view preprint)
  2. Received: April 28, 2021
  3. Accepted: June 17, 2022
  4. Accepted Manuscript published: June 20, 2022 (version 1)
  5. Version of Record published: July 15, 2022 (version 2)

Copyright

© 2022, Vafidis 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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  1. Pantelis Vafidis
  2. David Owald
  3. Tiziano D'Albis
  4. Richard Kempter
(2022)
Learning accurate path integration in ring attractor models of the head direction system
eLife 11:e69841.
https://doi.org/10.7554/eLife.69841

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https://doi.org/10.7554/eLife.69841

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