A size principle for recruitment of Drosophila leg motor neurons

  1. Anthony W Azevedo
  2. Evyn S Dickinson
  3. Pralaksha Gurung
  4. Lalanti Venkatasubramanian
  5. Richard S Mann
  6. John C Tuthill  Is a corresponding author
  1. University of Washington, United States
  2. Columbia University, United States

Abstract

To move the body, the brain must precisely coordinate patterns of activity among diverse populations of motor neurons. Here, we use in vivo calcium imaging, electrophysiology, and behavior to understand how genetically-identified motor neurons control flexion of the fruit fly tibia. We find that leg motor neurons exhibit a coordinated gradient of anatomical, physiological, and functional properties. Large, fast motor neurons control high force, ballistic movements while small, slow motor neurons control low force, postural movements. Intermediate neurons fall between these two extremes. This hierarchical organization resembles the size principle, first proposed as a mechanism for establishing recruitment order among vertebrate motor neurons. Recordings in behaving flies confirmed that motor neurons are typically recruited in order from slow to fast. However, we also find that fast, intermediate, and slow motor neurons receive distinct proprioceptive feedback signals, suggesting that the size principle is not the only mechanism that dictates motor neuron recruitment. Overall, this work reveals the functional organization of the fly leg motor system and establishes Drosophila as a tractable system for investigating neural mechanisms of limb motor control.

Data availability

All data is publicly available on Dryad doi:10.5061/dryad.76hdr7stb

The following data sets were generated

Article and author information

Author details

  1. Anthony W Azevedo

    Department of Physiology and Biophysics, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Evyn S Dickinson

    Dept of Physiology and Biophysics, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Pralaksha Gurung

    Dept of Physiology and Biophysics, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Lalanti Venkatasubramanian

    Department of Biochemistry and Molecular Biophysics, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9280-8335
  5. Richard S Mann

    Department of Biochemistry and Molecular Biophysics, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4749-2765
  6. John C Tuthill

    Dept of Physiology and Biophysics, University of Washington, Seattle, United States
    For correspondence
    johnctuthill@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5689-5806

Funding

NIH (U19NS104655)

  • Anthony W Azevedo
  • Evyn S Dickinson
  • Pralaksha Gurung
  • Lalanti Venkatasubramanian
  • Richard S Mann
  • John C Tuthill

Searle Foundation (Scholar Award)

  • Anthony W Azevedo
  • Evyn S Dickinson
  • Pralaksha Gurung
  • John C Tuthill

McKnight Foundation (Scholar Award)

  • Anthony W Azevedo
  • Evyn S Dickinson
  • Pralaksha Gurung
  • John C Tuthill

Pew Biomedical Trust (Scholar Award)

  • Anthony W Azevedo
  • Evyn S Dickinson
  • Pralaksha Gurung
  • John C Tuthill

Sloan Foundation (Research Fellowship)

  • Anthony W Azevedo
  • Evyn S Dickinson
  • Pralaksha Gurung
  • John C Tuthill

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

Reviewing Editor

  1. Ronald L Calabrese, Emory University, United States

Version history

  1. Received: March 9, 2020
  2. Accepted: June 1, 2020
  3. Accepted Manuscript published: June 3, 2020 (version 1)
  4. Version of Record published: July 9, 2020 (version 2)

Copyright

© 2020, Azevedo 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

  • 4,711
    views
  • 535
    downloads
  • 40
    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. Anthony W Azevedo
  2. Evyn S Dickinson
  3. Pralaksha Gurung
  4. Lalanti Venkatasubramanian
  5. Richard S Mann
  6. John C Tuthill
(2020)
A size principle for recruitment of Drosophila leg motor neurons
eLife 9:e56754.
https://doi.org/10.7554/eLife.56754

Share this article

https://doi.org/10.7554/eLife.56754

Further reading

    1. Neuroscience
    Kenta Abe, Yuki Kambe ... Tatsuo Sato
    Research Article

    Midbrain dopamine neurons impact neural processing in the prefrontal cortex (PFC) through mesocortical projections. However, the signals conveyed by dopamine projections to the PFC remain unclear, particularly at the single-axon level. Here, we investigated dopaminergic axonal activity in the medial PFC (mPFC) during reward and aversive processing. By optimizing microprism-mediated two-photon calcium imaging of dopamine axon terminals, we found diverse activity in dopamine axons responsive to both reward and aversive stimuli. Some axons exhibited a preference for reward, while others favored aversive stimuli, and there was a strong bias for the latter at the population level. Long-term longitudinal imaging revealed that the preference was maintained in reward- and aversive-preferring axons throughout classical conditioning in which rewarding and aversive stimuli were paired with preceding auditory cues. However, as mice learned to discriminate reward or aversive cues, a cue activity preference gradually developed only in aversive-preferring axons. We inferred the trial-by-trial cue discrimination based on machine learning using anticipatory licking or facial expressions, and found that successful discrimination was accompanied by sharper selectivity for the aversive cue in aversive-preferring axons. Our findings indicate that a group of mesocortical dopamine axons encodes aversive-related signals, which are modulated by both classical conditioning across days and trial-by-trial discrimination within a day.

    1. Neuroscience
    Baiwei Liu, Zampeta-Sofia Alexopoulou, Freek van Ede
    Research Article

    Working memory enables us to bridge past sensory information to upcoming future behaviour. Accordingly, by its very nature, working memory is concerned with two components: the past and the future. Yet, in conventional laboratory tasks, these two components are often conflated, such as when sensory information in working memory is encoded and tested at the same location. We developed a task in which we dissociated the past (encoded location) and future (to-be-tested location) attributes of visual contents in working memory. This enabled us to independently track the utilisation of past and future memory attributes through gaze, as observed during mnemonic selection. Our results reveal the joint consideration of past and future locations. This was prevalent even at the single-trial level of individual saccades that were jointly biased to the past and future. This uncovers the rich nature of working memory representations, whereby both past and future memory attributes are retained and can be accessed together when memory contents become relevant for behaviour.