| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
1ATR Computational Neuroscience Laboratories, Kyoto 619-0288, Japan; 2School of Kinesiology, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada; and 3Department of Mechanical Engineering and Division of Bioengineering, National University of Singapore, 119260, Singapore
Submitted 11 December 2002; accepted in final form 16 February 2002
This study compared adaptation in novel force fields where trajectories were initially either stable or unstable to elucidate the processes of learning novel skills and adapting to new environments. Subjects learned to move in a null force field (NF), which was unexpectedly changed either to a velocity-dependent force field (VF), which resulted in perturbed but stable hand trajectories, or a position-dependent divergent force field (DF), which resulted in unstable trajectories. With practice, subjects learned to compensate for the perturbations produced by both force fields. Adaptation was characterized by an initial increase in the activation of all muscles followed by a gradual reduction. The time course of the increase in activation was correlated with a reduction in hand-path error for the DF but not for the VF. Adaptation to the VF could have been achieved solely by formation of an inverse dynamics model and adaptation to the DF solely by impedance control. However, indices of learning, such as hand-path error, joint torque, and electromyographic activation and deactivation suggest that the CNS combined these processes during adaptation to both force fields. Our results suggest that during the early phase of learning there is an increase in endpoint stiffness that serves to reduce hand-path error and provides additional stability, regardless of whether the dynamics are stable or unstable. We suggest that the motor control system utilizes an inverse dynamics model to learn the mean dynamics and an impedance controller to assist in the formation of the inverse dynamics model and to generate needed stability.
This article has been cited by other articles:
|
|
 |
|
  A. G. Richardson, G. Lassi-Tucci, C. Padoa-Schioppa, and E. Bizzi Neuronal Activity in the Cingulate Motor Areas During Adaptation to a New Dynamic Environment J Neurophysiol, March 1, 2008; 99(3): 1253 - 1266. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. R. Hinder and T. E. Milner Rapid Adaptation to Scaled Changes of the Mechanical Environment J Neurophysiol, November 1, 2007; 98(5): 3072 - 3080. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 D. W. Franklin, G. Liaw, T. E. Milner, R. Osu, E. Burdet, and M. Kawato Endpoint Stiffness of the Arm Is Directionally Tuned to Instability in the Environment J. Neurosci., July 18, 2007; 27(29): 7705 - 7716. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
E. Trainin, R. Meir, and A. Karniel Explaining Patterns of Neural Activity in the Primary Motor Cortex Using Spinal Cord and Limb Biomechanics Models J Neurophysiol, May 1, 2007; 97(5): 3736 - 3750. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
E. Guigon, P. Baraduc, and M. Desmurget Computational Motor Control: Redundancy and Invariance J Neurophysiol, January 1, 2007; 97(1): 331 - 347. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. Gupta and J. Ashe Lack of Adaptation to Random Conflicting Force Fields of Variable Magnitude J Neurophysiol, January 1, 2007; 97(1): 738 - 745. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
L. P. J. Selen, J. H. van Dieen, and P. J. Beek Impedance Modulation and Feedback Corrections in Tracking Targets of Variable Size and Frequency J Neurophysiol, November 1, 2006; 96(5): 2750 - 2759. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
T. E. Milner and M. R. Hinder Position Information But Not Force Information Is Used in Adapting to Changes in Environmental Dynamics J Neurophysiol, August 1, 2006; 96(2): 526 - 534. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
D. M. Shiller, G. Houle, and D. J. Ostry Voluntary Control of Human Jaw Stiffness J Neurophysiol, September 1, 2005; 94(3): 2207 - 2217. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 T. E. Milner and D. W. Franklin Impedance control and internal model use during the initial stage of adaptation to novel dynamics in humans J. Physiol., September 1, 2005; 567(2): 651 - 664. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. Trommershauser, S. Gepshtein, L. T. Maloney, M. S. Landy, and M. S. Banks Optimal Compensation for Changes in Task-Relevant Movement Variability J. Neurosci., August 3, 2005; 25(31): 7169 - 7178. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. K. Wainscott, O. Donchin, and R. Shadmehr Internal Models and Contextual Cues: Encoding Serial Order and Direction of Movement J Neurophysiol, February 1, 2005; 93(2): 786 - 800. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
D. W. Franklin, U. So, M. Kawato, and T. E. Milner Impedance Control Balances Stability With Metabolically Costly Muscle Activation J Neurophysiol, November 1, 2004; 92(5): 3097 - 3105. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. Osu, N. Kamimura, H. Iwasaki, E. Nakano, C. M. Harris, Y. Wada, and M. Kawato Optimal Impedance Control for Task Achievement in the Presence of Signal-Dependent Noise J Neurophysiol, August 1, 2004; 92(2): 1199 - 1215. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. Osu, E. Burdet, D. W. Franklin, T. E. Milner, and M. Kawato Different Mechanisms Involved in Adaptation to Stable and Unstable Dynamics J Neurophysiol, November 1, 2003; 90(5): 3255 - 3269. [Abstract] [Full Text] [PDF]
|
|
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Visit Other APS Journals Online |
