Multi-muscle synergies in an unusual postural task: quick shear force production
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We considered a hypothetical two-level hierarchy participating in the control of vertical posture. The framework of the uncontrolled manifold (UCM) hypothesis was used to explore the muscle groupings (M-modes) and multi-M-mode synergies involved in the stabilization of a time profile of the shear force in the anterior–posterior direction. Standing subjects were asked to produce pulses of shear force into a target using visual feedback while trying to minimize the shift of the center of pressure (COP). Principal component analysis applied to integrated muscle activation indices identified three M-modes. The composition of the M-modes was similar across subjects and the two directions of the shear force pulse. It differed from the composition of M-modes described in earlier studies of more natural actions associated with large COP shifts. Further, the trial-to-trial M-mode variance was partitioned into two components: one component that does not affect a particular performance variable (V UCM), and its orthogonal component (V ORT). We argued that there is a multi-M-mode synergy stabilizing this particular performance variable if V UCM is higher than V ORT. Overall, we found a multi-M-mode synergy stabilizing both shear force and COP coordinate. For the shear force, this synergy was strong for the backward force pulses and nonsignificant for the forward pulses. An opposite result was found for the COP coordinate: the synergy was stronger for the forward force pulses. The study shows that M-mode composition can change in a task-specific way and that two different performance variables can be stabilized using the same set of elemental variables (M-modes). The different dependences of the ΔV indices for the shear force and COP coordinate on the force pulse direction supports applicability of the principle of superposition (separate controllers for different performance variables) to the control of different mechanical variables in postural tasks. The M-mode composition allows a natural mechanical interpretation.
KeywordsSynergy Posture Muscle mode Uncontrolled manifold hypothesis Electromyogram Reference configuration hypothesis
The study was partly supported by NIH grants AG-018751, NS-035032, and AR-048563. We are grateful to Alessander Danna-Dos-Santos for his help.
- Bernstein NA (1967) The co-ordination and regulation of movements. Pergamon Press, OxfordGoogle Scholar
- Feldman AG (1966) Functional tuning of the nervous system with control of movement or maintenance of a steady posture. II. Controllable parameters of the muscle. Biophysics 11:565–578Google Scholar
- Feldman AG, Levin MF (1995) Positional frames of reference in motor control: their origin and use. Behav Brain Sci 18:723–806Google Scholar
- Gelfand IM, Tsetlin ML (1966) On mathematical modeling of the mechanisms of the central nervous system. In: Gelfand IM, Gurfinkel VS, Fomin SV, Tsetlin ML (eds) Models of the structural-functional organization of certain biological systems. Nauka, Moscow, pp 9–26 (in Russian, a translation is available in 1971 edition by MIT Press, Cambridge)Google Scholar
- Latash ML, Zatsiorsky VM (2006) Principle of superposition in human prehension. In: Kawamura S, Swinin M (eds) Advances in robot control: from everyday physics to human-like movements, Springer, New York, pp 249–261Google Scholar
- Latash ML, Scholz JF, Danion F, Schöner G (2002a) Finger coordination during discrete and oscillatory force production tasks. Exp Brain Res 146:412–432Google Scholar
- Latash ML, Scholz JP, Schöner G (2007) Toward a new theory of motor synergies. Motor Control 11:275–307Google Scholar
- Saltiel P, Wyler-Duda K, d’Avella A, Tresch MC, Bizzi E (2001) Muscle synergies encoded within the spinal cord: evidence from focal intraspinal NMDA iontophoresis in the frog. J Neurophysiol 5:605–619Google Scholar
- Zhang W, Zatsiorsky VM, Latash ML (2008) What do synergies do? Effects of secondary constraints on multi-digit synergies in accurate force-production tasks. J Neurophysiol. PMID: 18046000Google Scholar