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Learning, motor skill, and long-range correlations.

Déborah Nourrit-Lucas1, Adaté Olivier Tossa, Grégory Zélic

  • 1a UMR 7349; MAPMO, UFR Sciences , Orléans University , France.

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|December 16, 2014
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Summary

Long-range correlations in human performance may stem from the learning process. Experts exhibit more structured and correlated fluctuations than novices, suggesting learning installs system complexity.

Keywords:
1/f noisedegeneracylong-range correlationsmotor learningmotor skills

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Area of Science:

  • Motor control
  • Cognitive science
  • Dynamical systems theory

Background:

  • Long-range correlations (LRCs) are observed in human performance, often in overlearned tasks.
  • It is hypothesized that LRCs might be a byproduct of the learning process itself.

Purpose of the Study:

  • To investigate if long-range correlations are a consequence of learning.
  • To compare the temporal dynamics of experts and novices in a motor task.

Main Methods:

  • Participants: expert and novice groups.
  • Task: prolonged trials on a ski simulator.
  • Analysis: fractal analysis of time series data (period series).

Main Results:

  • Expert performance showed significantly lower variability compared to novices.
  • Fractal analyses revealed more structured and correlated fluctuations in expert performance.
  • Novice performance exhibited less structured and less correlated fluctuations.

Conclusions:

  • Learning appears to progressively install complexity within a system.
  • Long-range correlations may be an indicator of the learning process in motor tasks.
  • Expertise is associated with enhanced temporal structure and correlation in performance dynamics.