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Is dynamics the content of a generalized motor program for rhythmic interlimb coordination?

Polemnia G Amazeen1

  • 1Center for the Ecological Study of Perception and Action, University of Connecticut, USA. nia@asu.edu

Journal of Motor Behavior
|March 6, 2009
PubMed
Summary

This study suggests that coordination dynamics, not a generalized motor program (GMP), underlies rhythmic interlimb coordination. Learning appears to shape an intrinsic attractor landscape rather than altering a GMP.

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Area of Science:

  • Motor Control
  • Biophysics
  • Cognitive Science

Background:

  • The generalized motor program (GMP) theory posits that a single program controls various movements.
  • Rhythmic interlimb coordination involves complex timing and sequencing of limb movements.
  • Understanding the underlying mechanisms of motor learning is crucial for rehabilitation and performance enhancement.

Purpose of the Study:

  • To test the hypothesis that coordination dynamics, rather than a generalized motor program (GMP), constitutes the basis for rhythmic interlimb coordination.
  • To investigate how learning influences the dynamics of interlimb coordination.
  • To explore the concept of an attractor landscape in motor learning.

Main Methods:

  • Three experiments involving human participants (N=14, 13, 8) practicing rhythmic interlimb coordination tasks.
  • Manipulation of limb timing during practice (identical vs. different timing).
  • Assessment of learning through acquisition and transfer of novel movement patterns and phase relations.
  • Attractor reconstruction to analyze changes in movement predictability and dimensionality.

Main Results:

  • Learning conditions did not affect the acquisition or transfer of coordination patterns, suggesting intrinsic dynamics govern in-phase and antiphase movements.
  • Learning of different phase relations (-90 and -45 degrees) was qualitatively similar, with increased trajectory predictability and decreased attractor dimensionality.
  • Learning altered the performance of established in-phase and antiphase relations, supporting a continuous attractor landscape.

Conclusions:

  • Coordination dynamics, specifically an attractor landscape, appears to be the content of motor programs for rhythmic interlimb coordination.
  • Motor learning modifies the attractor landscape, influencing movement variability and predictability.
  • Results challenge the traditional GMP theory by emphasizing the role of intrinsic dynamics in motor control and learning.