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Related Experiment Videos

Modelling the control of interceptive actions.

P J Beek1, J C Dessing, C E Peper

  • 1Institute for Fundamental and Clinical Human Movement Sciences and Faculty of Human Movement Sciences, Vrije Universiteit, Van der Boechorststraat 9, 1081 BT, Amsterdam, The Netherlands. p_j_beek@fbw.vu.nl

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
|October 17, 2003
PubMed
Summary

This study introduces a long-route modeling approach for motor control, integrating sensory and musculoskeletal dynamics to better understand perception-action patterns in interceptive actions.

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Area of Science:

  • Motor control
  • Human action system dynamics
  • Computational neuroscience

Background:

  • Current "short-route" models of motor control do not fully account for the dynamical constraints of sensory, neural, and musculoskeletal systems.
  • Perceptual variables are incorporated into motor control, but the underlying system dynamics remain underexplored.

Purpose of the Study:

  • To advocate for and exemplify a "long-route" modeling approach that integrates subsystem dynamics for motor control.
  • To present a novel neural network model for generating motor commands in interceptive actions.
  • To explore the modulation of motor commands considering musculoskeletal dynamics.

Main Methods:

  • Formulation of phenomenological dynamical models for perception-action control.
  • Development of a long-route modeling approach integrating subsystem dynamics.

Related Experiment Videos

  • Implementation of a neural network architecture for online motor command generation based on time-to-contact and relative hand-ball dynamics.

    • Main Results:

    • The proposed long-route model offers a more comprehensive framework for understanding perception-action patterns.
    • The neural network model is consistent with existing behavioral and neurophysiological data.
    • The study highlights challenges in modulating motor commands based on musculoskeletal dynamics.

    Conclusions:

    • A long-route modeling approach is crucial for a complete understanding of motor control, especially in interceptive actions.
    • The developed neural network model provides a viable framework for simulating human motor behavior.
    • Further research is needed to fully integrate musculoskeletal dynamics into motor command generation models.