Skip to main content
Log in

The effects of error augmentation on learning to walk on a narrow balance beam

  • Research Article
  • Published:
Experimental Brain Research Aims and scope Submit manuscript

Abstract

Error augmentation during training has been proposed as a means to facilitate motor learning due to the human nervous system’s reliance on performance errors to shape motor commands. We studied the effects of error augmentation on short-term learning of walking on a balance beam to determine whether it had beneficial effects on motor performance. Four groups of able-bodied subjects walked on a treadmill-mounted balance beam (2.5-cm wide) before and after 30 min of training. During training, two groups walked on the beam with a destabilization device that augmented error (Medium and High Destabilization groups). A third group walked on a narrower beam (1.27-cm) to augment error (Narrow). The fourth group practiced walking on the 2.5-cm balance beam (Wide). Subjects in the Wide group had significantly greater improvements after training than the error augmentation groups. The High Destabilization group had significantly less performance gains than the Narrow group in spite of similar failures per minute during training. In a follow-up experiment, a fifth group of subjects (Assisted) practiced with a device that greatly reduced catastrophic errors (i.e., stepping off the beam) but maintained similar pelvic movement variability. Performance gains were significantly greater in the Wide group than the Assisted group, indicating that catastrophic errors were important for short-term learning. We conclude that increasing errors during practice via destabilization and a narrower balance beam did not improve short-term learning of beam walking. In addition, the presence of qualitatively catastrophic errors seems to improve short-term learning of walking balance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Ahmed AA, Ashton-Miller JA (2004) Is a “loss of balance” a control error signal anomaly? Evidence for three-sigma failure detection in young adults. Gait Posture 19:252–262

    Article  PubMed  Google Scholar 

  • Ahmed AA, Ashton-Miller JA (2007) On use of a nominal internal model to detect a loss of balance in a maximal forward reach. J Neurophysiol 97:2439–2447

    Article  PubMed  Google Scholar 

  • Armstrong TR (1970) Training for the production of memorized movement patterns. Dissertation, University of Michigan

  • Cai LL, Fong AJ, Otoshi CK, Liang Y, Burdick JW, Roy RR, Edgerton VR (2006) Implications of assist-as-needed robotic step training after a complete spinal cord injury on intrinsic strategies of motor learning. J Neurosci 26:10564–10568

    Article  CAS  PubMed  Google Scholar 

  • Criscimagna-Hemminger SE, Bastian AJ, Shadmehr R (2010) Size of error affects cerebellar contributions to motor learning. J Neurophysiol 103:2275–2284

    Google Scholar 

  • Dancause N, Ptito A, Levin MF (2002) Error correction strategies for motor behavior after unilateral brain damage: short-term motor learning processes. Neuropsychologia 40:1313–1323

    Article  PubMed  Google Scholar 

  • Domingo A, Ferris DP (2009) Effects of physical guidance on short-term learning of walking on a narrow beam. Gait Posture 30:464–468

    Article  PubMed  Google Scholar 

  • Donelan JM, Shipman DW, Kram R, Kuo AD (2004) Mechanical and metabolic requirements for active lateral stabilization in human walking. J Biomech 37:827–835

    Article  PubMed  Google Scholar 

  • Emken JL, Reinkensmeyer DJ (2005) Robot-enhanced motor learning: accelerating internal model formation during locomotion by transient dynamic amplification. IEEE Trans Neural Syst Rehabil Eng 13:33–39

    Article  PubMed  Google Scholar 

  • Guadagnoli MA, Lee TD (2004) Challenge point: a framework for conceptualizing the effects of various practice conditions in motor learning. J Mot Behav 36:212–224

    Article  PubMed  Google Scholar 

  • Hidler J, Nichols D, Pelliccio M, Brady K, Campbell DD, Kahn JH, Hornby TG (2009) Multicenter randomized clinical trial evaluating the effectiveness of the Lokomat in subacute stroke. Neurorehabil Neural Repair 23:5–13

    PubMed  Google Scholar 

  • Holden M, Ventura J, Lackner JR (1994) Stabilization of posture by precision contact of the index finger. J Vestib Res 4:285–301

    CAS  PubMed  Google Scholar 

  • Huang VS, Krakauer JW (2009) Robotic neurorehabilitation: a computational motor learning perspective. J Neuroeng Rehabil 6:5

    Article  PubMed  Google Scholar 

  • Jeka JJ, Lackner JR (1994) Fingertip contact influences human postural control. Exp Brain Res 100:495–502

    Article  CAS  PubMed  Google Scholar 

  • Kawato M (1999) Internal models for motor control and trajectory planning. Curr Opin Neurobiol 9:718–727

    Article  CAS  PubMed  Google Scholar 

  • Kouzaki M, Masani K (2008) Reduced postural sway during quiet standing by light touch is due to finger tactile feedback but not mechanical support. Exp Brain Res 188:153–158

    Article  PubMed  Google Scholar 

  • Lam T, Anderschitz M, Dietz V (2006) Contribution of feedback and feedforward strategies to locomotor adaptations. J Neurophysiol 95:766–773

    Article  PubMed  Google Scholar 

  • Lisberger SG (1988) The neural basis for learning of simple motor skills. Science 242:728–735

    Article  CAS  PubMed  Google Scholar 

  • Liu J, Wrisberg CA (1997) The effect of knowledge of results delay and the subjective estimation of movement form on the acquisition and retention of a motor skill. Res Q Exerc Sport 68:145–151

    CAS  PubMed  Google Scholar 

  • Maki BE, McIlroy WE (2007) Cognitive demands and cortical control of human balance-recovery reactions. J Neural Transm 114:1279–1296

    Article  CAS  PubMed  Google Scholar 

  • Marchal-Crespo L, Reinkensmeyer DJ (2009) Review of control strategies for robotic movement training after neurologic injury. J Neuroeng Rehabil 6:20

    Article  PubMed  Google Scholar 

  • Patton JL, Mussa-Ivaldi FA (2004) Robot-assisted adaptive training: custom force fields for teaching movement patterns. IEEE Trans Biomed Eng 51:636–646

    Article  PubMed  Google Scholar 

  • Patton JL, Stoykov ME, Kovic M, Mussa-Ivaldi FA (2006) Evaluation of robotic training forces that either enhance or reduce error in chronic hemiparetic stroke survivors. Exp Brain Res 168:368–383

    Article  PubMed  Google Scholar 

  • Reinkensmeyer DJ, Patton JL (2009) Can robots help the learning of skilled actions? Exerc Sport Sci Rev 37:43–51

    Article  PubMed  Google Scholar 

  • Reinkensmeyer DJ, Emken JL, Cramer SC (2004) Robotics, motor learning, and neurologic recovery. Annu Rev Biomed Eng 6:497–525

    Article  CAS  PubMed  Google Scholar 

  • Rumelhart DE, Hinton GE, Williams RJ (1986) Learning representations by back-propagating errors. Nature 323:533–536

    Article  Google Scholar 

  • Sanger TD (2004) Failure of motor learning for large initial errors. Neural Comput 16:1873–1886

    Article  PubMed  Google Scholar 

  • Scheidt RA, Reinkensmeyer DJ, Conditt MA, Rymer WZ, Mussa-Ivaldi FA (2000) Persistence of motor adaptation during constrained, multi-joint, arm movements. J Neurophysiol 84:853–862

    CAS  PubMed  Google Scholar 

  • Scheidt RA, Dingwell JB, Mussa-Ivaldi FA (2001) Learning to move amid uncertainty. J Neurophysiol 86:971–985

    CAS  PubMed  Google Scholar 

  • Schrager MA, Kelly VE, Price R, Ferrucci L, Shumway-Cook A (2008) The effects of age on medio-lateral stability during normal and narrow base walking. Gait Posture 28:466–471

    Article  PubMed  Google Scholar 

  • Seidler RD (2004) Multiple motor learning experiences enhance motor adaptability. J Cogn Neurosci 16:65–73

    Article  PubMed  Google Scholar 

  • Thoroughman KA, Shadmehr R (2000) Learning of action through adaptive combination of motor primitives. Nature 407:742–747

    Article  CAS  PubMed  Google Scholar 

  • Wagner MJ, Smith MA (2008) Shared internal models for feedforward and feedback control. J Neurosci 28:10663–10673

    Article  CAS  PubMed  Google Scholar 

  • Wei K, Kording K (2009) Relevance of error: what drives motor adaptation? J Neurophysiol 101:655–664

    Article  PubMed  Google Scholar 

  • Wei Y, Bajaj P, Scheidt R, Patton JL (2005) Visual error augmentation for enhancing motor learning and rehabilitative relearning. In: International conference on rehabilitation robotics. IEEE, Chicago, IL, pp 505–510

  • Winstein CJ, Pohl PS, Lewthwaite R (1994) Effects of physical guidance and knowledge of results on motor learning: support for the guidance hypothesis. Res Q Exerc Sport 65:316–323

    CAS  PubMed  Google Scholar 

  • Wolpert DM, Ghahramani Z (2000) Computational principles of movement neuroscience. Nat Neurosci 3:1212–1217

    Article  CAS  PubMed  Google Scholar 

  • Wolpert DM, Ghahramani Z, Flanagan JR (2001) Perspectives and problems in motor learning. Trends Cogn Sci 5:487–494

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

The authors would like to thank Daniela Weiss, Sarah Weiss, Evelyn Anaka and other members of the Human Neuromechanics Lab for help with data collection and processing. We would also like to thank Shawn O'Connor and Peter Adamczyk for help with data analysis and Steve Collins for help with the negative-stiffness spring design. This work was supported by the Rackham Graduate Student Research Grant, the Foundation for Physical Therapy PODS II Scholarship, and National Institutes of Health F31 HD056588-01.

Conflict of interest

The authors declare that they have no conflict of interest.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Antoinette Domingo.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Domingo, A., Ferris, D.P. The effects of error augmentation on learning to walk on a narrow balance beam. Exp Brain Res 206, 359–370 (2010). https://doi.org/10.1007/s00221-010-2409-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00221-010-2409-x

Keywords

Navigation