Role of the cerebellum in reaching movements in humans. I. Distributed inverse dynamics control

Authors

  • Nicolas Schweighofer,

    1. Centre for Neural Engineering, University of Southern California, Los Angeles, CA 90089-2520, USA, ATR Human Information Processing Research Laboratories, 2–2, Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-02 Japan
    Search for more papers by this author
  • Michael A. Arbib,

    1. Centre for Neural Engineering, University of Southern California, Los Angeles, CA 90089-2520, USA, ATR Human Information Processing Research Laboratories, 2–2, Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-02 Japan
    Search for more papers by this author
  • Mitsuo Kawato

    1. Centre for Neural Engineering, University of Southern California, Los Angeles, CA 90089-2520, USA, ATR Human Information Processing Research Laboratories, 2–2, Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-02 Japan
    Search for more papers by this author

Abstract

This study focuses on the role of the motor cortex, the spinal cord and the cerebellum in the dynamics stage of the control of arm movement. Currently, two classes of models have been proposed for the neural control of movements, namely the virtual trajectory control hypothesis and the acquisition of internal models of the motor apparatus hypothesis. In the present study, we expand the virtual trajectory model to whole arm reaching movements. This expanded model accurately reproduced slow movements, but faster reaching movements deviated significantly from the planned trajectories, indicating that for fast movements, this model was not sufficient. These results led us to propose a new distributed functional model consistent with behavioural, anatomical and neurophysiological data, which takes into account arm muscles, spinal cord, motor cortex and cerebellum and is consistent with the view that the central nervous system acquires a distributed inverse dynamics model of the arm. Previous studies indicated that the cerebellum compensates for the interaction forces that arise during reaching movements. We show here how the cerebellum may increase the accuracy of reaching movements by compensating for the interaction torques by learning a portion of an inverse dynamics model that refines a basic inverse model in the motor cortex and spinal cord.

Ancillary