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.NEW & NOTEWORTHY The study demonstrates that a behavioral model based on a neural oscillator controlled by visual information is able to accurately reproduce human modulations in a motor action with respect to sensory information during the rhythmic ball-bouncing task. The model attractor dynamics emerging from the interaction between the neuromusculoskeletal system and the environment met task requirements, environmental constraints, and human behavioral choices without relying on movement planning and explicit internal models of the environment.

journal_name

J Neurophysiol

authors

Avrin G,Siegler IA,Makarov M,Rodriguez-Ayerbe P

doi

10.1152/jn.00054.2017

subject

Has Abstract

pub_date

2017-10-01 00:00:00

pages

2470-2482

issue

4

eissn

0022-3077

issn

1522-1598

pii

jn.00054.2017

journal_volume

118

pub_type

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