Multi-muscle synergies in a dual postural task: Evidence for the principle of superposition

Miriam Klous, Alessander Danna-Dos-Santos, Mark L. Latash

Research output: Contribution to journalArticle

31 Scopus citations

Abstract

We used the framework of the uncontrolled manifold hypothesis to quantify multi-muscle synergies stabilizing the moment of force about the frontal axis (M Y) and the shear force in the anterior-posterior direction (F X) during voluntary body sway performed by standing subjects. We tested a hypothesis whether the controller could stabilize both M Y and F X at the same time when the task and the visual feedback was provided only on one of the variables (M Y). Healthy young subjects performed voluntary body sway in the anterior-posterior direction while different loads were attached at the ankle level producing horizontal forces acting forward or backwards. Principal component analysis was used to identify three M-modes within the space of integrated indices of muscle activation. Variance in the M-mode space across sway cycles was partitioned into two components, one that did not affect a selected performance variable (M Y or F X) and the other that did. Under all loading conditions and for each performance variable, a higher value for the former variance component was found. We interpret these results as reflections of two multi-M-mode synergies stabilizing both F X and M Y. The indices of synergies were modulated within the sway cycle; both performance variables were better stabilized when the body moved forward than when it moved backward. The results show that the controller can use a set of three elemental variables (M-modes) to stabilize two performance variables at the same time. No negative interference was seen between the synergy indices computed for the two performance variables supporting the principle of superposition with respect to multi-muscle postural control.

Original languageEnglish (US)
Pages (from-to)457-471
Number of pages15
JournalExperimental Brain Research
Volume202
Issue number2
DOIs
StatePublished - Apr 2010

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)

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