The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Role of Cocontraction in Arm Movement Accuracy
Abstract
Cocontraction (the simultaneous activation of antagonist muscles around a joint) provides the nervous system with a way to adapt the mechanical properties of the limb to changing task requirements—both in statics and during movement. However, relatively little is known about the conditions under which the motor system modulates limb impedance through cocontraction. The goal of this study was to test for a possible relationship between cocontraction and movement accuracy in multi-joint limb movements. The electromyographic activity of seven single- and double-joint shoulder and elbow muscles was recorded using surface electrodes while subjects performed a pointing task in a horizontal plane to targets that varied randomly in size. Movement speed was controlled by providing subjects with feedback on a trial-to-trial basis. Measures of cocontraction were estimated both during movement and during a 200-ms window immediately following movement end. We observed an inverse relationship between target size and cocontraction: as target size was reduced, cocontraction activity increased. In addition, trajectory variability decreased and endpoint accuracy improved. This suggests that, although energetically expensive, cocontraction may be a strategy used by the motor system to facilitate multi-joint arm movement accuracy. We also observed a general trend for cocontraction levels to decrease over time, supporting the idea that cocontraction and associated limb stiffness are reduced over the course of practice.
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Cites
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The central nervous system stabilizes unstable dynamics by learning optimal impedance
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Electromyographic correlates of learning an internal model of reaching movements
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Cited by
Faisal, A. A., Selen, L. P. J., & Wolpert, D. M. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2258 · Cited by 2,883
The Role of Execution Noise in Movement Variability
van Beers, R. J., Haggard, P., & Wolpert, D. M. (2004) · Journal of Neurophysiology · doi:10.1152/jn.00652.2003 · Cited by 494
Evidence for the Flexible Sensorimotor Strategies Predicted by Optimal Feedback Control
Liu, D., & Todorov, E. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.1110-06.2007 · Cited by 447
Restoring sensorimotor function through intracortical interfaces: progress and looming challenges
Bensmaia, S. J., & Miller, L. E. (2014) · Nature Reviews Neuroscience · doi:10.1038/nrn3724 · Cited by 368
Tele-impedance: Teleoperation with impedance regulation using a body–machine interface
Ajoudani, A., Tsagarakis, N., & Bicchi, A. (2012) · The International Journal of Robotics Research · doi:10.1177/0278364912464668 · Cited by 276
Metadata
- Authors
- Gribble, P. L., Mullin, L. I., Cothros, N., & Mattar, A.
- Venue
- Journal of Neurophysiology
- Publisher
- American Physiological Society
- Published
- 2003-05-01
- Volume
- 89
- Issue
- 5
- Pages
- 2396-2405
- ISSN
- 0022-3077 (ISSN-L)
- 1522-1598
- OpenAlex
- W2111705205
- Cited by
- 660
- References
- 6
- FWCI
- 8.57
- Type
- journal article
- Language
- en
- Open access
- closed
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