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Motor learning by field approximation.
Open accessAbstract
We investigated how human subjects adapt to forces perturbing the motion of their ams. We found that this kind of learning is based on the capacity of the central nervous system (CNS) to predict and therefore to cancel externally applied perturbing forces. Our experimental results indicate: (i) that the ability of the CNS to compensate for the perturbing forces is restricted to those spatial locations where the perturbations have been experienced by the moving arm. The subjects also are able to compensate for forces experienced at neighboring workspace locations. However, adaptation decays smoothly and quickly with distance from the locations where disturbances had been sensed by the moving limb. (ii) Our experiments also how that the CNS builds an internal model of the external perturbing forces in intrinsic (muscles and / or joints) coordinates.
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Citations
Cited by
Internal models for motor control and trajectory planning.
Kawato, M. (1999) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(99)00028-8 · Cited by 2,685
Internal models in the cerebellum
Wolpert, D. M., Miall, R. C., & Kawato, M. (1998) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(98)01221-2 · Cited by 2,469
Computational principles of movement neuroscience
Wolpert, D. M., & Ghahramani, Z. (2000) · Nature Neuroscience · doi:10.1038/81497 · Cited by 2,122
Error Correction, Sensory Prediction, and Adaptation in Motor Control
Shadmehr, R., Smith, M. A., & Krakauer, J. W. (2010) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-060909-153135 · Cited by 1,869
Learning of action through adaptive combination of motor primitives
Thoroughman, K. A., & Shadmehr, R. (2000) · Nature · doi:10.1038/35037588 · Cited by 945
Metadata
- Authors
- Gandolfo, F., Mussa-Ivaldi, F. A., & Bizzi, E.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 1996-04-30
- Volume
- 93
- Issue
- 9
- Pages
- 3843-3846
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2084402145
- Cited by
- 481
- References
- 0
- FWCI
- 4.57
- Type
- journal article
- Language
- en
- Open access
- green
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- Gandolfo, F., Mussa-Ivaldi, F. A., & Bizzi, E. (1996). Motor learning by field approximation. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.93.9.3843
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
