Hierarchical motor adaptations negotiate failures during force field learning - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Journal Articles PLoS Computational Biology Year : 2021

Hierarchical motor adaptations negotiate failures during force field learning

Abstract

Humans have the amazing ability to learn the dynamics of the body and environment to develop motor skills. Traditional motor studies using arm reaching paradigms have viewed this ability as the process of ‘internal model adaptation’. However, the behaviors have not been fully explored in the case when reaches fail to attain the intended target. Here we examined human reaching under two force fields types; one that induces failures (i.e., target errors), and the other that does not. Our results show the presence of a distinct failure-driven adaptation process that enables quick task success after failures, and before completion of internal model adaptation, but that can result in persistent changes to the undisturbed trajectory. These behaviors can be explained by considering a hierarchical interaction between internal model adaptation and the failure-driven adaptation of reach direction. Our findings suggest that movement failure is negotiated using hierarchical motor adaptations by humans.

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Neuroscience
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lirmm-03477893 , version 1 (13-12-2021)

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Tsuyoshi Ikegami, Gowrishankar Ganesh, Tricia L. Gibo, Toshinori Yoshioka, Rieko Osu, et al.. Hierarchical motor adaptations negotiate failures during force field learning. PLoS Computational Biology, 2021, 17 (4), pp.e1008481. ⟨10.1371/journal.pcbi.1008481⟩. ⟨lirmm-03477893⟩
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