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Related Experiment Videos

Forward Models for Physiological Motor Control.

D M. Wolpert1, R C. Miall

  • 1University Laboratory of Physiology, Oxford; and Sobell Department, Institute of Neurology, London, UK

Neural Networks : the Official Journal of the International Neural Network Society
|November 1, 1996
PubMed
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The central nervous system (CNS) may use internal forward models to simulate motor system behavior for planning, control, and learning. These models predict future states based on current states and motor commands.

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Motor Control

Background:

  • Theoretical and computational studies suggest the central nervous system (CNS) internally simulates motor system behavior.
  • An internal forward model predicts the next state using the current state and motor command.

Purpose of the Study:

  • Outline the uses of internal models for motor control.
  • Review evidence for the CNS's use of internal models.
  • Speculate on identifying the location of internal models within the CNS.

Main Methods:

  • Theoretical analysis
  • Computational modeling
  • Review of existing evidence

Main Results:

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  • Internal forward models offer solutions to fundamental computational problems in motor control.
  • Evidence supports the existence and utilization of internal models by the CNS.
  • Methods for locating internal models within the CNS are discussed.

    • Conclusions:

    • Internal forward models are crucial for motor planning, control, and learning.
    • The CNS actively employs these predictive representations.
    • Further research can pinpoint the neural substrates of these internal models.