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.

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.

Metrics

  • 2,877
    views
  • 474
    downloads
  • 10
    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. 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

Share this article

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

Further reading

    1. Cell Biology
    2. Neuroscience
    Jun Sun, Francisca Rojo-Cortes ... Alicia Hidalgo
    Research Article

    Experience shapes the brain as neural circuits can be modified by neural stimulation or the lack of it. The molecular mechanisms underlying structural circuit plasticity and how plasticity modifies behaviour are poorly understood. Subjective experience requires dopamine, a neuromodulator that assigns a value to stimuli, and it also controls behaviour, including locomotion, learning, and memory. In Drosophila, Toll receptors are ideally placed to translate experience into structural brain change. Toll-6 is expressed in dopaminergic neurons (DANs), raising the intriguing possibility that Toll-6 could regulate structural plasticity in dopaminergic circuits. Drosophila neurotrophin-2 (DNT-2) is the ligand for Toll-6 and Kek-6, but whether it is required for circuit structural plasticity was unknown. Here, we show that DNT-2-expressing neurons connect with DANs, and they modulate each other. Loss of function for DNT-2 or its receptors Toll-6 and kinase-less Trk-like kek-6 caused DAN and synapse loss, impaired dendrite growth and connectivity, decreased synaptic sites, and caused locomotion deficits. In contrast, over-expressed DNT-2 increased DAN cell number, dendrite complexity, and promoted synaptogenesis. Neuronal activity modified DNT-2, increased synaptogenesis in DNT-2-positive neurons and DANs, and over-expression of DNT-2 did too. Altering the levels of DNT-2 or Toll-6 also modified dopamine-dependent behaviours, including locomotion and long-term memory. To conclude, a feedback loop involving dopamine and DNT-2 highlighted the circuits engaged, and DNT-2 with Toll-6 and Kek-6 induced structural plasticity in this circuit modifying brain function and behaviour.

    1. Cell Biology
    2. Neuroscience
    Josse Poppinga, Nolan J Barrett ... Jan RT van Weering
    Research Article

    Sorting nexin 4 (SNX4) is an evolutionary conserved organizer of membrane recycling. In neurons, SNX4 accumulates in synapses, but how SNX4 affects synapse function remains unknown. We generated a conditional SNX4 knock-out mouse model and report that SNX4 cKO synapses show enhanced neurotransmission during train stimulation, while the first evoked EPSC was normal. SNX4 depletion did not affect vesicle recycling, basic autophagic flux, or the levels and localization of SNARE-protein VAMP2/synaptobrevin-2. However, SNX4 depletion affected synapse ultrastructure: an increase in docked synaptic vesicles at the active zone, while the overall vesicle number was normal, and a decreased active zone length. These effects together lead to a substantially increased density of docked vesicles per release site. In conclusion, SNX4 is a negative regulator of synaptic vesicle docking and release. These findings suggest a role for SNX4 in synaptic vesicle recruitment at the active zone.