Time scales of performance levels during training of complex motor tasks

Gottfried Mayer-Kress*, Yeou Teh Liu, Karl M. Newell

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)


Complex motor tasks - such as skydiving or landing an airplane - require extensive training and practice of coordinated movement sequences. But even once the task is learned, experience shows that the proper execution of the task is not guaranteed if the task is to be performed years, months, or even days after its most recent execution. That is why, for example, pilots need to demonstrate a minimum number of flight hours per year. We have developed a dynamical systems model that describes these phenomena in the context of different time scales of adaptation and learning processes. We could show that the performance decrement after interruption of skill practice is exclusively due to the dynamics of adaptive processes, whereas learning continued even without practice. The proper understanding of the separation between these two types of processes can help to predict the type and intensity of warm-up that is necessary to safely and reliably execute a task after a given rest time. Such a situation seems to be especially relevant for complex military missions, which include long pauses between task execution together with short preparation and high stress levels during the relatively infrequent task executions.

Original languageEnglish
Title of host publicationApplications of Nonlinear Dynamics
Subtitle of host publicationModel and Design of Complex Systems
Number of pages4
Publication statusPublished - 2009
Externally publishedYes

Publication series

NameUnderstanding Complex Systems
ISSN (Print)1860-0832
ISSN (Electronic)1860-0840

ASJC Scopus subject areas

  • Software
  • Computational Mechanics
  • Artificial Intelligence


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