JN AJP: Renal Physiology
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

J Neurophysiol 81: 2140-2155, 1999;
0022-3077/99 $5.00
This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Nakano, E.
Right arrow Articles by Kawato, M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Nakano, E.
Right arrow Articles by Kawato, M.

The Journal of Neurophysiology Vol. 81 No. 5 May 1999, pp. 2140-2155
Copyright ©1999 by the American Physiological Society

Quantitative Examinations of Internal Representations for Arm Trajectory Planning: Minimum Commanded Torque Change Model

Eri Nakano,1,2 Hiroshi Imamizu,3 Rieko Osu,3 Yoji Uno,4 Hiroaki Gomi,5 Toshinori Yoshioka,3 and Mitsuo Kawato1,3

 1ATR Human Information Processing Research Laboratories, Kyoto 619-0288;  2Graduate School of Science and Technology, Kobe University, Hyogo 657-0013;  3Kawato Dynamic Brain Project, ERATO, Japan Science and Technology Corporation, Kyoto 619-0288;  4Department of Information and Computer Sciences, Toyohashi University of Technology, Aichi 441-8540; and  5NTT Communication Science Laboratories, Nippon Telegraph and Telephone Corporation, Kanagawa 243-0198, Japan

Nakano, Eri, Hiroshi Imamizu, Rieko Osu, Yoji Uno, Hiroaki Gomi, Toshinori Yoshioka, and Mitsuo Kawato. Quantitative Examinations of Internal Representations for Arm Trajectory Planning: Minimum Commanded Torque Change Model. J. Neurophysiol. 81: 2140-2155, 1999.Quantitative examinations of internal representations for arm trajectory planning: minimum commanded torque change model. A number of invariant features of multijoint planar reaching movements have been observed in measured hand trajectories. These features include roughly straight hand paths and bell-shaped speed profiles where the trajectory curvatures between transverse and radial movements have been found to be different. For quantitative and statistical investigations, we obtained a large amount of trajectory data within a wide range of the workspace in the horizontal and sagittal planes (400 trajectories for each subject). A pair of movements within the horizontal and sagittal planes was set to be equivalent in the elbow and shoulder flexion/extension. The trajectory curvatures of the corresponding pair in these planes were almost the same. Moreover, these curvatures can be accurately reproduced with a linear regression from the summation of rotations in the elbow and shoulder joints. This means that trajectory curvatures systematically depend on the movement location and direction represented in the intrinsic body coordinates. We then examined the following four candidates as planning spaces and the four corresponding computational models for trajectory planning. The candidates were as follows: the minimum hand jerk model in an extrinsic-kinematic space, the minimum angle jerk model in an intrinsic-kinematic space, the minimum torque change model in an intrinsic-dynamic-mechanical space, and the minimum commanded torque change model in an intrinsic-dynamic-neural space. The minimum commanded torque change model, which is proposed here as a computable version of the minimum motor command change model, reproduced actual trajectories best for curvature, position, velocity, acceleration, and torque. The model's prediction that the longer the duration of the movement the larger the trajectory curvature was also confirmed. Movements passing through via-points in the horizontal plane were also measured, and they converged to those predicted by the minimum commanded torque change model with training. Our results indicated that the brain may plan, and learn to plan, the optimal trajectory in the intrinsic coordinates considering arm and muscle dynamics and using representations for motor commands controlling muscle tensions.




This article has been cited by other articles:


Home page
 J. Neurophysiol.Home page
U. Maoz, A. Berthoz, and T. Flash
Complex Unconstrained Three-Dimensional Hand Movement and Constant Equi-Affine Speed
J Neurophysiol, February 1, 2009; 101(2): 1002 - 1015.
[Abstract] [Full Text] [PDF]

Home page
 J. Neurosci.Home page
A. Biess, D. G. Liebermann, and T. Flash
A Computational Model for Redundant Human Three-Dimensional Pointing Movements: Integration of Independent Spatial and Temporal Motor Plans Simplifies Movement Dynamics
J. Neurosci., November 28, 2007; 27(48): 13045 - 13064.
[Abstract] [Full Text] [PDF]

Home page
 J. Neurophysiol.Home page
T. E. Hudson, L. T. Maloney, and M. S. Landy
Movement Planning With Probabilistic Target Information
J Neurophysiol, November 1, 2007; 98(5): 3034 - 3046.
[Abstract] [Full Text] [PDF]

Home page
 J. Neurophysiol.Home page
J. L. Emken, R. Benitez, A. Sideris, J. E. Bobrow, and D. J. Reinkensmeyer
Motor Adaptation as a Greedy Optimization of Error and Effort
J Neurophysiol, June 1, 2007; 97(6): 3997 - 4006.
[Abstract] [Full Text] [PDF]

Home page
 J. Neurophysiol.Home page
D. A. Kistemaker, A. J. Van Soest, and M. F. Bobbert
Is Equilibrium Point Control Feasible for Fast Goal-Directed Single-Joint Movements?
J Neurophysiol, May 1, 2006; 95(5): 2898 - 2912.
[Abstract] [Full Text] [PDF]

Home page
 J. Neurophysiol.Home page
L. E. Sergio, C. Hamel-Paquet, and J. F. Kalaska
Motor Cortex Neural Correlates of Output Kinematics and Kinetics During Isometric-Force and Arm-Reaching Tasks
J Neurophysiol, October 1, 2005; 94(4): 2353 - 2378.
[Abstract] [Full Text] [PDF]

Home page
 J. Neurophysiol.Home page
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]

Home page
 J. Neurophysiol.Home page
J. B. Dingwell, C. D. Mah, and F. A. Mussa-Ivaldi
Experimentally Confirmed Mathematical Model for Human Control of a Non-Rigid Object
J Neurophysiol, March 1, 2004; 91(3): 1158 - 1170.
[Abstract] [Full Text] [PDF]

Home page
 J. Neurophysiol.Home page
R. J. van Beers, P. Haggard, and D. M. Wolpert
The Role of Execution Noise in Movement Variability
J Neurophysiol, February 1, 2004; 91(2): 1050 - 1063.
[Abstract] [Full Text] [PDF]

Home page
 J. Neurosci.Home page
O. Donchin, J. T. Francis, and R. Shadmehr
Quantifying Generalization from Trial-by-Trial Behavior of Adaptive Systems that Learn with Basis Functions: Theory and Experiments in Human Motor Control
J. Neurosci., October 8, 2003; 23(27): 9032 - 9045.
[Abstract] [Full Text] [PDF]

Home page
 J. Neurophysiol.Home page
A. Fagergren, O. Ekeberg, and H. Forssberg
Control Strategies Correcting Inaccurately Programmed Fingertip Forces: Model Predictions Derived From Human Behavior
J Neurophysiol, June 1, 2003; 89(6): 2904 - 2916.
[Abstract] [Full Text] [PDF]

Home page
 J. Neurophysiol.Home page
P. L. Gribble, L. I. Mullin, N. Cothros, and A. Mattar
Role of Cocontraction in Arm Movement Accuracy
J Neurophysiol, May 1, 2003; 89(5): 2396 - 2405.
[Abstract] [Full Text] [PDF]

Home page
 J. Neurophysiol.Home page
M. Flanders, J. M. Hondzinski, J. F. Soechting, and J. C. Jackson
Using Arm Configuration to Learn the Effects of Gyroscopes and Other Devices
J Neurophysiol, January 1, 2003; 89(1): 450 - 459.
[Abstract] [Full Text] [PDF]

Home page
 Human Factors: The Journal of the Human Factors and Ergonomics SocietyHome page
S. A. Jax, D. A. Rosenbaum, J. Vaughan, and R. G. J. Meulenbroek
Computational Motor Control and Human Factors: Modeling Movements in Real and Possible Environments
Human Factors: The Journal of the Human Factors and Ergonomics Society, January 1, 2003; 45(1): 5 - 27.
[Abstract] [PDF]

Home page
 J. Neurosci.Home page
M. J. E. Richardson and T. Flash
Comparing Smooth Arm Movements with the Two-Thirds Power Law and the Related Segmented-Control Hypothesis
J. Neurosci., September 15, 2002; 22(18): 8201 - 8211.
[Abstract] [Full Text] [PDF]

Home page
 J. Neurophysiol.Home page
R. Osu, D. W. Franklin, H. Kato, H. Gomi, K. Domen, T. Yoshioka, and M. Kawato
Short- and Long-Term Changes in Joint Co-Contraction Associated With Motor Learning as Revealed From Surface EMG
J Neurophysiol, August 1, 2002; 88(2): 991 - 1004.
[Abstract] [Full Text] [PDF]


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Visit Other APS Journals Online