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The central nervous system stabilizes unstable dynamics by learning optimal impedance

Nature volume 414, pages 446449 (22 November 2001) | Download Citation

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Abstract

To manipulate objects or to use tools we must compensate for any forces arising from interaction with the physical environment. Recent studies indicate that this compensation is achieved by learning an internal model of the dynamics1,2,3,4,5,6, that is, a neural representation of the relation between motor command and movement5,7. In these studies interaction with the physical environment was stable, but many common tasks are intrinsically unstable8,9. For example, keeping a screwdriver in the slot of a screw is unstable because excessive force parallel to the slot can cause the screwdriver to slip and because misdirected force can cause loss of contact between the screwdriver and the screw. Stability may be dependent on the control of mechanical impedance in the human arm because mechanical impedance can generate forces which resist destabilizing motion. Here we examined arm movements in an unstable dynamic environment created by a robotic interface. Our results show that humans learn to stabilize unstable dynamics using the skilful and energy-efficient strategy of selective control of impedance geometry.

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Acknowledgements

The experiments were performed at ATR. We thank A. Illiesch and T. Flash for discussions. We thank A. Smith, S. Scott, D. Wolpert, Z. Ghahramani, and S. Schaal for giving valuable comments on an earlier version of the manuscript. This research was supported by the Special Coordination Fund for promoting Science and Technology of the Science and Technology agency of the Japanese Government; the Swiss National Science Foundation; the Natural Sciences and Engineering Research Council of Canada; and the Human Frontier Science Program.

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Author notes

    • Etienne Burdet
    •  & Rieko Osu

    These authors contributed equally to the work

Affiliations

  1. *Department of Mechanical Engineering, National University of Singapore, 119260, Singapore

    • Etienne Burdet
  2. †Kawato Dynamic Brain Project, ERATO, JST, Hikaridai, Seika-cho, Soraku-gun, Kyoto, 619 0288, Japan

    • Etienne Burdet
    • , Rieko Osu
    •  & Mitsuo Kawato
  3. §ATR Human Information Science Laboratories, Hikaridai, Seika-cho, Soraku-gun, Kyoto, 619 0288, Japan

    • Etienne Burdet
    • , David W. Franklin
    •  & Mitsuo Kawato
  4. ¶School of Kinesiology, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada

    • David W. Franklin
    •  & Theodore E. Milner

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Correspondence to Mitsuo Kawato.

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https://doi.org/10.1038/35106566

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