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Original Research Articles

System level analysis of motor-related neural activities in larval Drosophila

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Pages 179-189 | Received 31 Mar 2018, Accepted 05 Apr 2019, Published online: 07 Jun 2019
 

Abstract

The way in which the central nervous system (CNS) governs animal movement is complex and difficult to solve solely by the analyses of muscle movement patterns. We tackle this problem by observing the activity of a large population of neurons in the CNS of larval Drosophila. We focused on two major behaviors of the larvae – forward and backward locomotion – and analyzed the neuronal activity related to these behaviors during the fictive locomotion that occurs spontaneously in the isolated CNS. We expressed a genetically-encoded calcium indicator, GCaMP and a nuclear marker in all neurons and then used digitally scanned light-sheet microscopy to record (at a fast frame rate) neural activities in the entire ventral nerve cord (VNC). We developed image processing tools that automatically detected the cell position based on the nuclear staining and allocate the activity signals to each detected cell. We also applied a machine learning-based method that we recently developed to assign motor status in each time frame. Our experimental procedures and computational pipeline enabled systematic identification of neurons that showed characteristic motor activities in larval Drosophila. We found cells whose activity was biased toward forward locomotion and others biased toward backward locomotion. In particular, we identified neurons near the boundary of the subesophageal zone (SEZ) and thoracic neuromeres, which were strongly active during an early phase of backward but not forward fictive locomotion.

Acknowledgments

We are grateful to the Bloomington Drosophila stock center and Kyoto stock center. We are also grateful to Suguru Takagi for giving us advice on the morphology of neurons and interpretation of their activities.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by MEXT/Japan Society for the Promotion of Science (JSPS) KAKENHI grants (26430004, 17K07042, 22115002, 15H04255 and 16H06280).

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