Adaptation and learning: Characteristic time scales of performance dynamics

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


研究成果: 雜誌貢獻期刊論文同行評審

48 引文 斯高帕斯(Scopus)


A multiple time scales landscape model is presented that reveals structures of performance dynamics that were not resolved in the traditional power law analysis of motor learning. It shows the co-existence of separate processes during and between practice sessions that evolve in two independent dimensions characterized by time scales that differ by about an order of magnitude. Performance along the slow persistent dimension of learning improves often as much and sometimes more during rest (memory consolidation and/or insight generation processes) than during a practice session itself. In contrast, the process characterized by the fast, transient dimension of adaptation reverses direction between practice sessions, thereby significantly degrading performance at the beginning of the next practice session (warm-up decrement). The theoretical model fits qualitatively and quantitatively the data from Snoddy's [Snoddy, G. S. (1926). Learning and stability. Journal of Applied Psychology, 10, 1-36] classic learning study of mirror tracing and other averaged and individual data sets, and provides a new account of the processes of change in adaptation and learning.

頁(從 - 到)655-687
期刊Human Movement Science
出版狀態已發佈 - 2009 12月

ASJC Scopus subject areas

  • 生物物理學
  • 骨科和運動醫學
  • 實驗與認知心理學


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