1. Neuroscience

Dorsal Periaqueductal gray ensembles represent approach and avoidance states

  1. Fernando MCV Reis  Is a corresponding author
  2. Johannes Y Lee
  3. Sandra Maesta-Pereira
  4. Peter J Schuette
  5. Meghmik Chakerian
  6. Jinhan Liu
  7. Mimi Q La-Vu
  8. Brooke C Tobias
  9. Juliane M Ikebara
  10. Alexandre Hiroaki Kihara
  11. Newton S Canteras
  12. Jonathan C Kao  Is a corresponding author
  13. Avishek Adhikari  Is a corresponding author
  1. University of California, Los Angeles, United States
  2. Universidade Federal do ABC, Brazil
  3. University of São Paulo, Brazil
https://doi.org/10.7554/eLife.64934
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Cite this article
  1. Fernando MCV Reis
  2. Johannes Y Lee
  3. Sandra Maesta-Pereira
  4. Peter J Schuette
  5. Meghmik Chakerian
  6. Jinhan Liu
  7. Mimi Q La-Vu
  8. Brooke C Tobias
  9. Juliane M Ikebara
  10. Alexandre Hiroaki Kihara
  11. Newton S Canteras
  12. Jonathan C Kao
  13. Avishek Adhikari
(2021)
Dorsal Periaqueductal gray ensembles represent approach and avoidance states
eLife 10:e64934.
https://doi.org/10.7554/eLife.64934
  2. Download BibTeX
  3. Download .RIS

Abstract

Animals must balance needs to approach threats for risk-assessment and to avoid danger. The dorsal periaqueductal gray (dPAG) controls defensive behaviors, but it is unknown how it represents states associated with threat approach and avoidance. We identified a dPAG threat-avoidance ensemble in mice that showed higher activity far from threats such as the open arms of the elevated plus maze and a live predator. These cells were also more active during threat-avoidance behaviors such as escape and freezing, even though these behaviors have antagonistic motor output. Conversely, the threat-approach ensemble was more active during risk-assessment behaviors and near threats. Furthermore, unsupervised methods showed that avoidance/approach states were encoded with shared activity patterns across threats. Lastly, the relative number of cells in each ensemble predicted threat-avoidance across mice. Thus, dPAG ensembles dynamically encode threat approach and avoidance states, providing a flexible mechanism to balance risk-assessment and danger avoidance.

Data availability

All data was uploaded to dryad and all code was uploaded to github.https://datadryad.org/stash/share/4GezSjw4dvDJClAWa_zRoNWioH9qzGtDCJjLQ89HVoAhttps://doi.org/10.5068/D1TM2Ghttps://github.com/schuettepeter/eLife_dPAG-ensembles-represent-approach-and-avoidance-states

The following data sets were generated

Article and author information

Author details

  1. Fernando MCV Reis

    Psychology, University of California, Los Angeles, Los Angeles, United States
    For correspondence
    freis@ucla.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0121-2887

  2. Johannes Y Lee

    Electrical Engineering, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2420-4916

  3. Sandra Maesta-Pereira

    Electrical Engineering, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6522-8311

  4. Peter J Schuette

    Psychology, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.

  5. Meghmik Chakerian

    Psychology, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.

  6. Jinhan Liu

    Electrical Engineering, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.

  7. Mimi Q La-Vu

    Psychology, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.

  8. Brooke C Tobias

    Psychology, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2043-9523

  9. Juliane M Ikebara

    Centro de Matemática, Computação e Cognição, Universidade Federal do ABC, São Bernardo do Campo, Brazil
    Competing interests
    The authors declare that no competing interests exist.

  10. Alexandre Hiroaki Kihara

    Center of Mathematics, Computing and Cognition, Universidade Federal do ABC, Santo André, Brazil
    Competing interests
    The authors declare that no competing interests exist.

  11. Newton S Canteras

    Department of Anatomy, University of São Paulo, Sao Paulo, Brazil
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7205-5372

  12. Jonathan C Kao

    Electrical and Computer Engineering, University of California, Los Angeles, Los Angeles, United States
    For correspondence
    kao@seas.ucla.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9298-0143

  13. Avishek Adhikari

    Psychology, University of California, Los Angeles, Los Angeles, United States
    For correspondence
    avi@psych.ucla.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9187-9211

Funding

National Institutes of Health (R00 MH106649)

  • Avishek Adhikari

National Institutes of Health (F31 MH121050-01A1)

  • Mimi Q La-Vu

Achievement Rewards for College Scientists Foundation

  • Mimi Q La-Vu

National Institutes of Health (R01 MH119089)

  • Avishek Adhikari

Brain and Behavior Research Foundation (22663)

  • Avishek Adhikari

Brain and Behavior Research Foundation (27654)

  • Fernando MCV Reis

National Science Foundation (DGE-1650604)

  • Peter J Schuette

Fundação de Amparo à Pesquisa do Estado de São Paulo (2015/23092-3)

  • Fernando MCV Reis

Fundação de Amparo à Pesquisa do Estado de São Paulo (2017/08668-1)

  • Fernando MCV Reis

Fundação de Amparo à Pesquisa do Estado de São Paulo (2014/05432-9)

  • Newton S Canteras

Hellman Foundation

  • Avishek Adhikari

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

Ethics

Animal experimentation: All procedures have been approved by the University of California, Los Angeles Institutional Animal Care and Use Committee, protocols 2017-011 and 2017-075.

Copyright

© 2021, Reis 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. Fernando MCV Reis
  2. Johannes Y Lee
  3. Sandra Maesta-Pereira
  4. Peter J Schuette
  5. Meghmik Chakerian
  6. Jinhan Liu
  7. Mimi Q La-Vu
  8. Brooke C Tobias
  9. Juliane M Ikebara
  10. Alexandre Hiroaki Kihara
  11. Newton S Canteras
  12. Jonathan C Kao
  13. Avishek Adhikari
(2021)
Dorsal Periaqueductal gray ensembles represent approach and avoidance states
eLife 10:e64934.
https://doi.org/10.7554/eLife.64934

Share this article

https://doi.org/10.7554/eLife.64934

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