Computational modeling of brainstem circuits controlling locomotor frequency and gait
- Drexel University College of Medicine, United States
- IBM, United States
Abstract
A series of recent studies identified key structures in the mesencephalic locomotor region and the caudal brainstem of mice involved in the initiation and control of slow (exploratory) and fast (escape-type) locomotion and gait. Yet, how these brainstem centers interact with each other and with the spinal locomotor circuits is poorly understood. In a previous model (Danner et al., 2017), we suggested that commissural and long propriospinal interneurons are the main targets for brainstem inputs adjusting gait. Here, by extending our previous model, we propose a connectome of the brainstem-spinal circuitry and suggest a mechanistic explanation of the operation of brainstem structures and their roles in controlling speed and gait. We suggest that brainstem control of locomotion is mediated by two pathways, one controlling locomotor speed via connections to rhythm generating circuits in the spinal cord and the other providing gait control by targeting commissural and long propriospinal interneurons.
Data availability
Source code and python scripts to create all simulations presented here are available on GitHub at https://github.com/SimonDanner/CPGNetworkSimulator
Article and author information
Author details
Funding
National Institutes of Health (R01NS095366)
- Natalia A Shevtsova
National Institutes of Health (R01NS090919)
- Ilya A Rybak
Edward Jekkal Muscular Dystrophy Association Fellowship
- Jessica Ausborn
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Ausborn 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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Computational modeling of brainstem circuits controlling locomotor frequency and gait
eLife 8:e43587.
https://doi.org/10.7554/eLife.43587
