Logo image
Afferent control of locomotor CPG: insights from a simple neuromechanical model
Journal article   Open access

Afferent control of locomotor CPG: insights from a simple neuromechanical model

Sergey N Markin, Alexander N Klishko, Natalia A Shevtsova, Michel A Lemay, Boris I Prilutsky and Ilya A Rybak
Annals of the New York Academy of Sciences, v 1198(1), pp 21-34
Jun 2010
PMID: 20536917
url
https://doi.org/10.1111/j.1749-6632.2010.05435.xView
Published, Version of Record (VoR) Open

Abstract

spinal cord injury modeling recovery of locomotor function central pattern generator locomotion afferent control
A simple neuromechanical model has been developed that describes a spinal central pattern generator (CPG) controlling the locomotor movement of a single-joint limb via activation of two antagonist (flexor and extensor) muscles. The limb performs rhythmic movements under control of the muscular, gravitational and ground reaction forces. Muscle afferents provide length-dependent (types Ia and II) and force-dependent (type Ib from the extensor) feedback to the CPG. We show that afferent feedback adjusts CPG operation to the kinematics and dynamics of the limb providing stable “locomotion.” Increasing the supraspinal drive to the CPG increases locomotion speed by reducing the duration of stance phase. We show that such asymmetric, extensor-dominated control of locomotor speed (with relatively constant swing duration) is provided by afferent feedback independent of the asymmetric rhythmic pattern generated by the CPG alone (in “fictive locomotion” conditions). Finally, we demonstrate the possibility of reestablishing stable locomotion after removal of the supraspinal drive (associated with spinal cord injury) by increasing the weights of afferent inputs to the CPG, which is thought to occur following locomotor training.

Metrics

14 Record Views
80 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Web of Science research areas
Neurosciences
Logo image