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Between-subject variability of muscle synergies during a complex motor skill

Overview of attention for article published in Frontiers in Computational Neuroscience, January 2012
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Title
Between-subject variability of muscle synergies during a complex motor skill
Published in
Frontiers in Computational Neuroscience, January 2012
DOI 10.3389/fncom.2012.00099
Pubmed ID
Authors

Julien Frère, François Hug

Abstract

The purpose of the present study was to determine whether subjects who have learned a complex motor skill exhibit similar neuromuscular control strategies. We studied a population of experienced gymnasts during backward giant swings on the high bar. This cyclic movement is interesting because it requires learning, as untrained subjects are unable to perform this task. Nine gymnasts were tested. Both kinematics and electromyographic (EMG) patterns of 12 upper-limb and trunk muscles were recorded. Muscle synergies were extracted by non-negative matrix factorization (NMF), providing two components: muscle synergy vectors and synergy activation coefficients. First, the coefficient of correlation (r) and circular cross-correlation (r(max)) were calculated to assess similarities in the mechanical patterns, EMG patterns, and muscle synergies between gymnasts. We performed a further analysis to verify that the muscle synergies (in terms of muscle synergy vectors or synergy activation coefficients) extracted for one gymnast accounted for the EMG patterns of the other gymnasts. Three muscle synergies explained 89.9 ± 2.0% of the variance accounted for (VAF). The coefficients of correlation of the muscle synergy vectors among the participants were 0.83 ± 0.08, 0.86 ± 0.09, and 0.66 ± 0.28 for synergy #1, #2, and #3, respectively. By keeping the muscle synergy vectors constant, we obtained an averaged VAF across all pairwise comparisons of 79 ± 4%. For the synergy activation coefficients, r(max)-values were 0.96 ± 0.03, 0.92 ± 0.03, and 0.95 ± 0.03, for synergy #1, #2, and #3, respectively. By keeping the synergy activation coefficients constant, we obtained an averaged VAF across all pairwise comparisons of 72 ± 5%. Although variability was found (especially for synergy #3), the gymnasts exhibited gross similar neuromuscular strategies when performing backward giant swings. This confirms that the muscle synergies are consistent across participants, even during a skilled motor task that requires learning.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 235 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 2%
France 3 1%
Japan 3 1%
Australia 1 <1%
Portugal 1 <1%
Switzerland 1 <1%
Spain 1 <1%
Unknown 221 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 49 21%
Student > Master 37 16%
Researcher 33 14%
Student > Bachelor 16 7%
Student > Doctoral Student 14 6%
Other 38 16%
Unknown 48 20%
Readers by discipline Count As %
Engineering 61 26%
Sports and Recreations 36 15%
Neuroscience 30 13%
Agricultural and Biological Sciences 16 7%
Medicine and Dentistry 14 6%
Other 21 9%
Unknown 57 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 November 2020.
All research outputs
#17,675,320
of 22,691,736 outputs
Outputs from Frontiers in Computational Neuroscience
#958
of 1,336 outputs
Outputs of similar age
#191,358
of 244,134 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#46
of 69 outputs
Altmetric has tracked 22,691,736 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
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