Experimental Brain Research

, Volume 217, Issue 1, pp 1–5 | Cite as

The bliss (not the problem) of motor abundance (not redundancy)

  • Mark L. LatashEmail author


Motor control is an area of natural science exploring how the nervous system interacts with other body parts and the environment to produce purposeful, coordinated actions. A central problem of motor control—the problem of motor redundancy—was formulated by Nikolai Bernstein as the problem of elimination of redundant degrees-of-freedom. Traditionally, this problem has been addressed using optimization methods based on a variety of cost functions. This review draws attention to a body of recent findings suggesting that the problem has been formulated incorrectly. An alternative view has been suggested as the principle of abundance, which considers the apparently redundant degrees-of-freedom as useful and even vital for many aspects of motor behavior. Over the past 10 years, dozens of publications have provided support for this view based on the ideas of synergic control, computational apparatus of the uncontrolled manifold hypothesis, and the equilibrium-point (referent configuration) hypothesis. In particular, large amounts of “good variance”—variance in the space of elements that has no effect on the overall performance—have been documented across a variety of natural actions. “Good variance” helps an abundant system to deal with secondary tasks and unexpected perturbations; its amount shows adaptive modulation across a variety of conditions. These data support the view that there is no problem of motor redundancy; there is bliss of motor abundance.


Motor redundancy Principle of abundance Synergy Referent configuration 



Preparation of this paper was in part supported by NIH grant NS-035032.


  1. Bernstein NA (1930) A new method of mirror cyclographie and its application towards the study of labor movements during work on a workbench. Hyg, Saf Pathol Labor 5:3–9, and 6:3–11 (in Russian)Google Scholar
  2. Bernstein NA (1967) The co-ordination and regulation of movements. Pergamon Press, OxfordGoogle Scholar
  3. Bottasso CL, Prilutsky BI, Croce A, Imberti E, Sartirana S (2006) A numerical procedure for inferring from experimental data the optimization cost functions using a multibody model of the neuro-musculoskeletal system. Multibody Syst Dyn 16:123–154CrossRefGoogle Scholar
  4. Cruse H, Bruwer M (1987) The human arm as a redundant manipulator: the control of path and joint angles. Biol Cybern 57:137–144PubMedCrossRefGoogle Scholar
  5. de Freitas SM, Scholz JP, Stehman AJ (2007) Effect of motor planning on use of motor abundance. Neurosci Lett 417:66–71PubMedCrossRefGoogle Scholar
  6. Diedrichsen J, Shadmehr R, Ivry RB (2010) The coordination of movement: optimal feedback control and beyond. Trends Cogn Sci 14:31–39PubMedCrossRefGoogle Scholar
  7. Feldman AG (1966) Functional tuning of nervous system with control of movement or maintenance of a steady posture. II. Controllable parameters of the muscles. Biophysics 11:565–578Google Scholar
  8. Feldman AG (1986) Once more on the equilibrium-point hypothesis (λ-model) for motor control. J Mot Behav 18:17–54PubMedGoogle Scholar
  9. Feldman AG (2009) Origin and advances of the equilibrium-point hypothesis. Adv Exp Med Biol 629:637–643PubMedCrossRefGoogle Scholar
  10. Feldman AG (2011) Space and time in the context of equilibrium-point theory. Wiley Interdiscip Rev: Cogn Sci 2:287–304CrossRefGoogle Scholar
  11. Gelfand IM, Latash ML (1998) On the problem of adequate language in movement science. Mot Control 2:306–313Google Scholar
  12. Gorniak SL, Feldman AG, Latash ML (2009) Joint coordination during bimanual transport of real and imaginary objects. Neurosci Lett 456:80–84PubMedCrossRefGoogle Scholar
  13. Henneman E, Somjen G, Carpenter DO (1965) Excitability and inhibitibility of motoneurones of different sizes. J Neurophysiol 28:599–620PubMedGoogle Scholar
  14. Hinder MR, Milner TE (2003) The case for an internal dynamics model versus equilibrium point control in human movement. J Physiol 549:953–963PubMedCrossRefGoogle Scholar
  15. Hommel B, Müsseler J, Aschersleben G, Prinz W (2001) The theory of event coding (TEC): a framework for perception and action planning. Behav Brain Sci 24:849–878PubMedCrossRefGoogle Scholar
  16. Hu X, Newell KM (2011) Modeling constraints to redundancy in bimanual force coordination. J Neurophysiol 105:2169–2180PubMedCrossRefGoogle Scholar
  17. Jaric S, Latash ML (1999) Learning a pointing task with a kinematically redundant limb: emerging synergies and patterns of final position variability. Hum Move Sci 18:819–838CrossRefGoogle Scholar
  18. Kawato M (1999) Internal models for motor control and trajectory planning. Curr Opinions Neurobiol 9:718–727CrossRefGoogle Scholar
  19. Kugler PN, Turvey MT (1987) Information, natural law, and the self-assembly of rhythmic movement. Erlbaum, Hillsdale, NJGoogle Scholar
  20. Latash ML (2000) There is no motor redundancy in human movements. There is motor abundance. Mot Control 4:257–259Google Scholar
  21. Latash ML (2008) Synergy. Oxford University Press, NYCrossRefGoogle Scholar
  22. Latash ML (2010) Motor synergies and the equilibrium-point hypothesis. Mot Control 14:294–322Google Scholar
  23. Latash ML, Kang N, Patterson D (2002) Finger coordination in persons with Down syndrome: atypical patterns of coordination and the effects of practice. Exp Brain Res 146:345–355PubMedCrossRefGoogle Scholar
  24. Latash ML, Scholz JP, Schöner G (2007) Toward a new theory of motor synergies. Mot Control 11:276–308Google Scholar
  25. Latash ML, Sun Y, Latash EM, Mikaelian IL (2011) Speed-difficulty trade-off in speech: Chinese vs. English. Exp Brain Res 211:193–205PubMedCrossRefGoogle Scholar
  26. Martin V, Scholz JP, Schöner G (2009) Redundancy, self-motion, and motor control. Neural Comput 21:1371–1414PubMedCrossRefGoogle Scholar
  27. Mattos D, Latash ML, Park E, Kuhl J, Scholz JP (2011) Unpredictable elbow joint perturbation during reaching results in multijoint motor equivalence. J Neurophysiol 106:1424–1436PubMedCrossRefGoogle Scholar
  28. Maurer C, Mergner T, Peterka RJ (2006) Multisensory control of human upright stance. Exp Brain Res 171:231–250PubMedCrossRefGoogle Scholar
  29. Nelson W (1983) Physical principles for economies of skilled movements. Biol Cybern 46:135–147PubMedCrossRefGoogle Scholar
  30. Park J, Zatsiorsky VM, Latash ML (2011a) Finger coordination under artificial changes in finger strength feedback: a study using analytical inverse optimization. J Mot Behav 43:229–235PubMedCrossRefGoogle Scholar
  31. Park J, Sun Y, Zatsiorsky VM, Latash ML (2011b) Age-related changes in optimality and motor variability: an example of multi-finger redundant tasks. Exp Brain Res 212:1–18PubMedCrossRefGoogle Scholar
  32. Prilutsky BI, Zatsiorsky VM (2002) Optimization-based models of muscle coordination. Exerc Sport Sci Rev 30:32–38PubMedCrossRefGoogle Scholar
  33. Rosenbaum DA, Meulenbroek RJ, Vaughan J, Jansen C (2001) Posture-based motion planning: applications to grasping. Psychol Rev 108:709–734PubMedCrossRefGoogle Scholar
  34. Scholz JP, Schöner G (1999) The uncontrolled manifold concept: identifying control variables for a functional task. Exp Brain Res 126:289–306PubMedCrossRefGoogle Scholar
  35. Shadmehr R, Wise SP (2005) The computational neurobiology of reaching and pointing. MIT Press, Cambridge, MAGoogle Scholar
  36. Singh T, SKM V, Zatsiorsky VM, Latash ML (2010) Fatigue and motor redundancy: adaptive increase in force variance in multi-finger tasks. J Neurophysiol 103:2990–3000PubMedCrossRefGoogle Scholar
  37. Stepp N, Turvey MT (2010) On strong anticipation. Cogn Syst Res 11:148–164PubMedCrossRefGoogle Scholar
  38. Terekhov AV, Pesin YB, Niu X, Latash ML, Zatsiorsky VM (2010) An analytical approach to the problem of inverse optimization: an application to human prehension. J Math Biol 61:423–453PubMedCrossRefGoogle Scholar
  39. Todorov E, Jordan MI (2002) Optimal feedback control as a theory of motor coordination. Nat Neurosci 5:1226–1235PubMedCrossRefGoogle Scholar
  40. Uno Y, Kawato M, Suzuki R (1989) Formation and control of optimal trajectory in human multijoint arm movement. Biol Cybern 61:89–101PubMedCrossRefGoogle Scholar
  41. Yang JF, Scholz JP (2005) Learning a throwing task is associated with differential changes in the use of motor abundance. Exp Brain Res 163:137–158PubMedCrossRefGoogle Scholar
  42. Yang JF, Scholz JP, Latash ML (2007) The role of kinematic redundancy in adaptation of reaching. Exp Brain Res 176:54–69PubMedCrossRefGoogle Scholar
  43. Zhang W, Scholz JP, Zatsiorsky VM, Latash ML (2008) What do synergies do? Effects of secondary constraints on multi-digit synergies in accurate force-production tasks. J Neurophysiol 99:500–513PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  1. 1.Department of KinesiologyThe Pennsylvania State UniversityUniversity ParkUSA

Personalised recommendations