Model of rhythmic ball bouncing using a visually controlled neural oscillator - CentraleSupélec Accéder directement au contenu
Article Dans Une Revue Journal of Neurophysiology Année : 2017

Model of rhythmic ball bouncing using a visually controlled neural oscillator

Résumé

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.
Fichier principal
Vignette du fichier
JNP4_avrin_v8.pdf (3.01 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Licence : CC BY NC ND - Paternité - Pas d'utilisation commerciale - Pas de modification

Dates et versions

hal-01591865 , version 1 (01-12-2023)

Identifiants

Citer

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⟩
216 Consultations
2 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More