Flexible muscle modes and synergies in challenging whole-body tasks

Abstract

We used the idea of hierarchical control to study multi-muscle synergies during a whole-body sway task performed by a standing person. Within this view, at the lower level of the hierarchy, muscles are united into groups (M-modes). At the higher level, gains at the M-modes are co-varied by the controller in a task-specific way to ensure low variability of important physical variables. In particular, we hypothesized that (1) the composition of M-modes could adjust and (2) an index of M-mode co-variation would become weaker in more challenging conditions. Subjects were required to perform a whole-body sway at 0.5 Hz paced by a metronome. They performed the task with eyes open and closed, while standing on both feet or on one foot only, with and without vibration applied to the Achilles tendons. Integrated indices of muscle activation were subjected to principal component analysis to identify M-modes. An increase in the task complexity led to an increase in the number of principal components that contained significantly loaded indices of muscle activation from 3 to 5. Hence, in more challenging tasks, the controller manipulated a larger number of variables. Multiple regression analysis was used to define the Jacobian of the system mapping small changes in M-mode gains onto shifts of the center of pressure (COP) in the anterior-posterior direction. Further, the variance in the M-mode space across sway cycles was partitioned into two components, one that did not affect an average across cycles COP coordinate and the other that did (good and bad variance, respectively). Under all conditions, the subjects showed substantially more good variance than bad variance interpreted as a multi-M-mode synergy stabilizing the COP trajectory. An index of the strength of the synergy was comparable across all conditions, and there was no modulation of this index over the sway cycle. Hence, our first hypothesis that the composition of M-modes could adjust under challenging conditions has been confirmed while the second hypothesis stating that the index of M-mode co-variation would become weaker in more challenging conditions has been falsified. We interpret the observations as suggesting that adjustments at the lower level of the hierarchy-in the M-mode composition-allowed the subjects to maintain a comparable level of stabilization of the COP trajectory in more challenging tasks. The findings support the (at least) two-level hierarchical control scheme of whole-body movements.

The influence of visual information on multi-muscle control during quiet stance: a spectral analysis approach

“…These investigations also provided evidence that the activation of such muscle modes co-vary to allow a stable trajectory of the body COP. Other investigations provided evidence that this synergistic organization changes according to the challenges imposed by the task (Danna-dos-Santos et al 2008), and suggest that the CNS optimizes its controlling mechanisms according to the imposed task requirements. These studies, however, were not designed to identify the neural mechanisms involved in the generation of such synergies.…”

Task-specific stability in muscle activation space during unintentional movements

“…While many M-modes corresponded to activation patterns without co-contraction of agonist-antagonist muscle pairs, M-modes with co-contractions were also common (see also earlier studies documenting such M-modes, Krishnamoorthy et al 2004; Danna-dos-Santos et al 2008). Within the equilibrium-point hypothesis, muscle co-contraction can be produced by the so-called c -command (Feldman 1980, 1986; Latash 1992).…”

“…As in similar earlier studies of synergies in the muscle mode space (Krishnamoorthy et al 2003; Danna-dos-Santos et al 2007, 2008; Klous et al 2010), we were looking for large effect sizes, on the order of 1–1.5. While the number of subjects was low, it was expected to be sufficient to reach statistical significance for the expected large effect sizes.…”

“…However, the data set was of sufficient power to reach statistical significance in the main comparisons, and none of the other main comparisons were close to the significance level. As in earlier studies of multi-muscle synergies (Krishnamoorthy et al 2003; Danna-dos-Santos et al 2007, 2008; Klous et al 2010), we looked for large effect sizes on the order of 1 – 1.5, and 7 subjects are sufficient to detect such effects. We have to admit, however, that the unbalanced number of male and female subjects is a drawback of the study.…”

“…A change in the robot force led to motion to a new equilibrium state where the arm stayed until the robot force returned back to the bias value. We assumed that elemental variables corresponded to parallel changes in activation within a few muscle groups (muscle modes, M-modes, Krishnamoorthy et al 2003; Danna-dos-Santos et al 2008). Two predictions were tested.…”