Journal article
Operation regimes of spinal circuits controlling locomotion and the role of supraspinal drives and sensory feedback
eLife, v 13
14 Oct 2024
Abstract
Locomotion in mammals is directly controlled by the spinal neuronal network, operating under the control of supraspinal signals and somatosensory feedback that interact with each other. However, the functional architecture of the spinal locomotor network, its operation regimes, and the role of supraspinal and sensory feedback in different locomotor behaviors, including at different speeds, remain unclear. We developed a computational model of spinal locomotor circuits receiving supraspinal drives and limb sensory feedback that could reproduce multiple experimental data obtained in intact and spinal-transected cats during tied-belt and split-belt treadmill locomotion. We provide evidence that the spinal locomotor network operates in different regimes depending on locomotor speed. In an intact system, at slow speeds (<0.4 m/s), the spinal network operates in a non-oscillating state-machine regime and requires sensory feedback or external inputs for phase transitions. Removing sensory feedback related to limb extension prevents locomotor oscillations at slow speeds. With increasing speed and supraspinal drives, the spinal network switches to a flexor-driven oscillatory regime and then to a classical half-center regime. Following spinal transection, the model predicts that the spinal network can only operate in the state-machine regime. Our results suggest that the spinal network operates in different regimes for slow exploratory and fast escape locomotor behaviors, making use of different control mechanisms.
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Details
- Title
- Operation regimes of spinal circuits controlling locomotion and the role of supraspinal drives and sensory feedback
- Creators
- Ilya A Rybak - Drexel UniversityNatalia A Shevtsova - Drexel UniversitySergey N Markin - Drexel UniversityBoris I Prilutsky - Georgia Institute of TechnologyAlain Frigon - Université de Sherbrooke
- Publication Details
- eLife, v 13
- Publisher
- eLife
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Neurobiology and Anatomy
- Other Identifier
- 991021929344604721