Unveiling the neuromechanical mechanisms underlying the synergistic interactions in human sensorimotor system.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
08 01 2021
Historique:
received: 09 07 2020
accepted: 21 12 2020
entrez: 9 1 2021
pubmed: 10 1 2021
medline: 10 8 2021
Statut: epublish

Résumé

Motor synergies are neural organizations of a set of redundant motor effectors that interact with one another to compensate for each other's error and ensure the stabilization of a performance variable. Recent studies have demonstrated that central nervous system synergistically coordinates its numerous motor effectors through Bayesian multi-sensory integration. Deficiency in sensory synergy weakens the synergistic interaction between the motor effectors. Here, we scrutinize the neuromechanical mechanism underlying this phenomenon through spectral analysis and modeling. We validate our model-generated results using experimental data reported in the literature collected from participants performing a finger force production task with and without tactile feedback (manipulated through injection of anesthetic in fingers). Spectral analysis reveals that the error compensation feature of synergies occurs only at low frequencies. Modeling suggests that the neurophysiological structures involving short-latency back-coupling loops similar to the well-known Renshaw cells explain the deterioration of synergy due to sensory deprivation.

Identifiants

pubmed: 33420251
doi: 10.1038/s41598-020-80420-z
pii: 10.1038/s41598-020-80420-z
pmc: PMC7794444
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

203

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Auteurs

S Honarvar (S)

Department of Mechanical Engineering, University of Maryland, College Park, MD, 20742, USA.

C Kim (C)

School of Mechanical Engineering, Chonnam National University, Gwangju, 61186, South Korea.

Y Diaz-Mercado (Y)

Department of Mechanical Engineering, University of Maryland, College Park, MD, 20742, USA. yancy@umd.edu.

K Koh (K)

School of Medicine, University of Maryland, Baltimore, MD, 21201, USA.

H J Kwon (HJ)

Department of Kinesiology, University of Maryland, College Park, MD, 20742, USA.

T Kiemel (T)

Department of Kinesiology, University of Maryland, College Park, MD, 20742, USA.
Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, 20742, USA.

M Caminita (M)

Department of Kinesiology, University of Maryland, College Park, MD, 20742, USA.

J O Hahn (JO)

Department of Mechanical Engineering, University of Maryland, College Park, MD, 20742, USA.

J K Shim (JK)

Department of Kinesiology, University of Maryland, College Park, MD, 20742, USA. jkshim@umd.edu.
Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, 20742, USA. jkshim@umd.edu.
Department of Mechanical Engineering, Kyung Hee University, Yongin-Si, Gyeonggi-do, South Korea. jkshim@umd.edu.

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