Adaptive control for hindlimb locomotion in a simulated mouse through temporal cerebellar learning

Thomas Passer Jensen, S. Tata, A. J. Ijspeert, Silvia Tolu

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    Human beings and other vertebrates show remarkable performance and efficiency in locomotion, but the functioning of their biological control systems for locomotion is still only partially understood. The basic patterns and timing for locomotion are provided by a central pattern generator (CPG) in the spinal cord. The cerebellum is known to play an important role in adaptive locomotion. Recent studies have given insights into the error signals responsible for driving the cerebellar adaptation in locomotion. However, the question of how the cerebellar output influences the gait remains unanswered. We hypothesize that the cerebellar correction is applied to the pattern formation part of the CPG. Here, a bio-inspired control system for adaptive locomotion of the musculoskeletal system of the mouse is presented, where a cerebellar-like module adapts the step time by using the double support interlimb asymmetry as a temporal teaching signal. The control system is tested on a simulated mouse in a split-belt treadmill setup similar to those used in experiments with real mice. The results show adaptive locomotion behavior in the interlimb parameters similar to that seen in humans and mice. The control system adaptively decreases the double support asymmetry that occurs due to environmental perturbations in the split-belt protocol.
    Original languageEnglish
    Title of host publicationProceedings of the 8th Annual Neuro-inspired Computational Elements Workshop
    Number of pages8
    PublisherAssociation for Computing Machinery
    Publication date2020
    Article number5
    ISBN (Print)978-1-4503-7718-8
    Publication statusPublished - 2020
    Event8th Annual Neuro-Inspired Computational Elements - Online
    Duration: 16 Mar 202119 Mar 2021
    Conference number: 8


    Conference8th Annual Neuro-Inspired Computational Elements
    OtherNICE 2020 became NICE 2021 due to the COVID-19 Situation.
    Internet address


    • Bio control
    • Learning algorithms
    • Adaptive locomotion
    • Brain models
    • Motor control


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