Neuromotor Dynamics of Human Locomotion in Challenging Settings.

Behavioral Neuroscience Biological Sciences Neuroscience

Journal

iScience
ISSN: 2589-0042
Titre abrégé: iScience
Pays: United States
ID NLM: 101724038

Informations de publication

Date de publication:
24 Jan 2020
Historique:
received: 02 06 2019
revised: 15 09 2019
accepted: 19 12 2019
pubmed: 22 1 2020
medline: 22 1 2020
entrez: 22 1 2020
Statut: ppublish

Résumé

Is the control of movement less stable when we walk or run in challenging settings? Intuitively, one might answer that it is, given that challenging locomotion externally (e.g., rough terrain) or internally (e.g., age-related impairments) makes our movements more unstable. Here, we investigated how young and old humans synergistically activate muscles during locomotion when different perturbation levels are introduced. Of these control signals, called muscle synergies, we analyzed the local stability and the complexity (or irregularity) over time. Surprisingly, we found that perturbations force the central nervous system to produce muscle activation patterns that are less unstable and less complex. These outcomes show that robust locomotion control in challenging settings is achieved by producing less complex control signals that are more stable over time, whereas easier tasks allow for more unstable and irregular control.

Identifiants

pubmed: 31962235
pii: S2589-0042(19)30542-5
doi: 10.1016/j.isci.2019.100796
pmc: PMC6971393
pii:
doi:

Types de publication

Journal Article

Langues

eng

Pagination

100796

Informations de copyright

Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Interests The authors declare no competing interests.

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Auteurs

Alessandro Santuz (A)

Department of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Berlin School of Movement Science, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Atlantic Mobility Action Project, Brain Repair Centre, Department of Medical Neuroscience, Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada. Electronic address: alessandro.santuz@hu-berlin.de.

Leon Brüll (L)

Department of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Berlin School of Movement Science, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Network Aging Research, Heidelberg University, 69117 Heidelberg, Germany.

Antonis Ekizos (A)

Department of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Berlin School of Movement Science, Humboldt-Universität zu Berlin, 10115 Berlin, Germany.

Arno Schroll (A)

Department of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Berlin School of Movement Science, Humboldt-Universität zu Berlin, 10115 Berlin, Germany.

Nils Eckardt (N)

Department of Training and Movement Science, Institute for Sport and Sports Science, University of Kassel, 34125 Kassel, Germany; Department of Sport and Movement Science, Institute of Sport Science, Carl von Ossietzky University of Oldenburg, 26129 Oldenburg, Germany.

Armin Kibele (A)

Department of Training and Movement Science, Institute for Sport and Sports Science, University of Kassel, 34125 Kassel, Germany.

Michael Schwenk (M)

Network Aging Research, Heidelberg University, 69117 Heidelberg, Germany; Institute of Sports and Sports Sciences, Heidelberg University, 69117 Heidelberg, Germany.

Adamantios Arampatzis (A)

Department of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Berlin School of Movement Science, Humboldt-Universität zu Berlin, 10115 Berlin, Germany.

Classifications MeSH