Model of rhythmic ball bouncing using a visually controlled neural oscillator - CentraleSupélec
Journal Articles Journal of Neurophysiology Year : 2017

Model of rhythmic ball bouncing using a visually controlled neural oscillator

Abstract

The present paper investigates the sensory-driven modulations of central pattern generator dynamics that can be expected to reproduce human behavior during rhythmic hybrid tasks. We propose a theoretical model of human sensorimotor behavior able to account for the observed data from the ball-bouncing task. The novel control architecture is composed of a Matsuoka neural oscillator coupled with the environment through visual sensory feedback. The architecture’s ability to reproduce human-like performance during the ball-bouncing task in the presence of perturbations is quantified by comparison of simulated and recorded trials. The results suggest that human visual control of the task is achieved online. The adaptive behavior is made possible by a parametric and state control of the limit cycle emerging from the interaction of the rhythmic pattern generator, the musculoskeletal system, and the environment.
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hal-01591865 , version 1 (01-12-2023)

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Guillaume Avrin, Isabelle Anne Siegler, Maria Makarov, Pedro Rodriguez-Ayerbe. Model of rhythmic ball bouncing using a visually controlled neural oscillator. Journal of Neurophysiology, 2017, 118 (4), pp.2470-2482. ⟨10.1152/jn.00054.2017⟩. ⟨hal-01591865⟩
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