A multilayer circuit architecture for the generation of distinct locomotor behaviors in Drosophila
- Howard Hughes Medical Institute, University of Oregon, United States
- Janelia Research Campus, Howard Hughes Medical Institute, United States
- Columbia University, United States
- Cited 3
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Abstract
Animals generate diverse motor behaviors, yet how the same motor neurons (MNs) generate two distinct or antagonistic behaviors remains an open question. Here we characterize Drosophila larval muscle activity patterns and premotor/motor circuits to understand how they generate forward and backward locomotion. We show that all body wall MNs are activated during both behaviors, but a subset of MNs change recruitment timing for each behavior. We used TEM to reconstruct a full segment of all 60 MNs and 236 premotor neurons (PMNs), including differentially-recruited MNs. Analysis of this comprehensive connectome identified PMN-MN ‘labeled line’ connectivity; PMN-MN combinatorial connectivity; asymmetric neuronal morphology; and PMN-MN circuit motifs that could all contribute to generating distinct behaviors. We generated a recurrent network model that reproduced the observed behaviors, and used functional optogenetics to validate selected model predictions. This PMN-MN connectome will provide a foundation for analyzing the full suite of larval behaviors.
Article and author information
Author details
Ashok Litwin-Kumar
Funding
Howard Hughes Medical Institute
- Aref Arzan Zarin
- Albert Cardona
- Chris Q Doe
National Institutes of Health (HD27056)
- Brandon Mark
- Chris Q Doe
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Kristin Scott, University of California, Berkeley, United States
Publication history
- Received: September 11, 2019
- Accepted: December 22, 2019
- Accepted Manuscript published: December 23, 2019 (version 1)
- Version of Record published: January 31, 2020 (version 2)
Copyright
© 2019, Zarin 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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