Adaptation and learning: Characteristic time scales of performance dynamics

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

Research output: Contribution to journalArticle

35 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)655-687
Number of pages33
JournalHuman Movement Science
Volume28
Issue number6
DOIs
Publication statusPublished - 2009 Dec 1

Keywords

  • Adaptation
  • Learning
  • Time scales
  • Warm-up

ASJC Scopus subject areas

  • Biophysics
  • Orthopedics and Sports Medicine
  • Experimental and Cognitive Psychology

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