1. Neuroscience

The neural basis for a persistent internal state in Drosophila females

  1. David S Deutsch
  2. Diego A Pacheco
  3. Lucas Encarnacion-Rivera
  4. Talmo D Pereira
  5. Ramie Fathy
  6. Jan Clemens
  7. Cyrille Girardin
  8. Adam J Calhoun
  9. Elise C Ireland
  10. Austin T Burke
  11. Sven Dorkenwald
  12. Claire E McKellar
  13. Thomas Macrina
  14. Ran Lu
  15. Kisuk Lee
  16. Nico Kemnitz
  17. Dodham Ih
  18. Manuel Castro
  19. Akhilesh Halageri
  20. Chris Jordan
  21. William Silversmith
  22. Jingpeng Wu
  23. H Sebastian Seung
  24. Mala Murthy  Is a corresponding author
  1. Princeton University, United States
  2. European Neuroscience Institute, Germany
https://doi.org/10.7554/eLife.59502
Share this article
Cite this article
  1. David S Deutsch
  2. Diego A Pacheco
  3. Lucas Encarnacion-Rivera
  4. Talmo D Pereira
  5. Ramie Fathy
  6. Jan Clemens
  7. Cyrille Girardin
  8. Adam J Calhoun
  9. Elise C Ireland
  10. Austin T Burke
  11. Sven Dorkenwald
  12. Claire E McKellar
  13. Thomas Macrina
  14. Ran Lu
  15. Kisuk Lee
  16. Nico Kemnitz
  17. Dodham Ih
  18. Manuel Castro
  19. Akhilesh Halageri
  20. Chris Jordan
  21. William Silversmith
  22. Jingpeng Wu
  23. H Sebastian Seung
  24. Mala Murthy
(2020)
The neural basis for a persistent internal state in Drosophila females
eLife 9:e59502.
https://doi.org/10.7554/eLife.59502
  2. Download BibTeX
  3. Download .RIS

Abstract

Sustained changes in mood or action require persistent changes in neural activity, but it has been difficult to identify the neural circuit mechanisms that underlie persistent activity and contribute to long-lasting changes in behavior. Here, we show that a subset of Doublesex+ pC1 neurons in the Drosophila female brain, called pC1d/e, can drive minutes-long changes in female behavior in the presence of males. Using automated reconstruction of a volume electron microscopic (EM) image of the female brain, we map all inputs and outputs to both pC1d and pC1e. This reveals strong recurrent connectivity between, in particular, pC1d/e neurons and a specific subset of Fruitless+ neurons called aIPg. We additionally find that pC1d/e activation drives long-lasting persistent neural activity in brain areas and cells overlapping with the pC1d/e neural network, including both Doublesex+ and Fruitless+ neurons. Our work thus links minutes-long persistent changes in behavior with persistent neural activity and recurrent circuit architecture in the female brain.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files.

Article and author information

Author details

  1. David S Deutsch

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8587-2435

  2. Diego A Pacheco

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  3. Lucas Encarnacion-Rivera

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  4. Talmo D Pereira

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9075-8365

  5. Ramie Fathy

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  6. Jan Clemens

    European Neuroscience Institute, Göttingen, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4200-8097

  7. Cyrille Girardin

    Neuroscience, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  8. Adam J Calhoun

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  9. Elise C Ireland

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  10. Austin T Burke

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  11. Sven Dorkenwald

    Princeton Neuroscience Institute and Department of Computer Science, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  12. Claire E McKellar

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3580-7336

  13. Thomas Macrina

    Princeton Neuroscience Institute and Department of Computer Science, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  14. Ran Lu

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  15. Kisuk Lee

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  16. Nico Kemnitz

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  17. Dodham Ih

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  18. Manuel Castro

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  19. Akhilesh Halageri

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  20. Chris Jordan

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  21. William Silversmith

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  22. Jingpeng Wu

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  23. H Sebastian Seung

    Princeton Neuroscience Institute and Department of Computer Science, Princeton University, Princeton, United States
    Competing interests
    The authors declare that no competing interests exist.

  24. Mala Murthy

    Princeton Neuroscience Institute, Princeton University, Princeton, United States
    For correspondence
    mmurthy@princeton.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3063-3389

Funding

National Institutes of Health (RF1 MH117815-01)

  • Mala Murthy

National Institutes of Health (R01 NS104899)

  • Mala Murthy

Howard Hughes Medical Institute (Faculty Scholar)

  • Mala Murthy

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

Copyright

© 2020, Deutsch 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

  • 6,646
    views
  • 662
    downloads
  • 84
    citations

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

Citations by DOI

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. David S Deutsch
  2. Diego A Pacheco
  3. Lucas Encarnacion-Rivera
  4. Talmo D Pereira
  5. Ramie Fathy
  6. Jan Clemens
  7. Cyrille Girardin
  8. Adam J Calhoun
  9. Elise C Ireland
  10. Austin T Burke
  11. Sven Dorkenwald
  12. Claire E McKellar
  13. Thomas Macrina
  14. Ran Lu
  15. Kisuk Lee
  16. Nico Kemnitz
  17. Dodham Ih
  18. Manuel Castro
  19. Akhilesh Halageri
  20. Chris Jordan
  21. William Silversmith
  22. Jingpeng Wu
  23. H Sebastian Seung
  24. Mala Murthy
(2020)
The neural basis for a persistent internal state in Drosophila females
eLife 9:e59502.
https://doi.org/10.7554/eLife.59502

Share this article

https://doi.org/10.7554/eLife.59502

Categories and tags

Research organism

Further reading

    1. Neuroscience

    Cell types and neuronal circuitry underlying female aggression in Drosophila

    Catherine E Schretter, Yoshinori Aso ... Gerald M Rubin
    Research Article Updated

    Aggressive social interactions are used to compete for limited resources and are regulated by complex sensory cues and the organism’s internal state. While both sexes exhibit aggression, its neuronal underpinnings are understudied in females. Here, we identify a population of sexually dimorphic aIPg neurons in the adult Drosophila melanogaster central brain whose optogenetic activation increased, and genetic inactivation reduced, female aggression. Analysis of GAL4 lines identified in an unbiased screen for increased female chasing behavior revealed the involvement of another sexually dimorphic neuron, pC1d, and implicated aIPg and pC1d neurons as core nodes regulating female aggression. Connectomic analysis demonstrated that aIPg neurons and pC1d are interconnected and suggest that aIPg neurons may exert part of their effect by gating the flow of visual information to descending neurons. Our work reveals important regulatory components of the neuronal circuitry that underlies female aggressive social interactions and provides tools for their manipulation.