Beyond curve fitting: a dynamical systems account of exponential learning in a discrete timing task.

Full Abstract

The authors examined the function for learning a discrete timing task from a dynamical systems perspective rather than solely the traditional curve-fitting viewpoint. Adult participants (N = 8) practiced a single-limb angular movement task of 125 ms over 20 degrees for 200 trials. There was no significant difference in percentage of variance accounted for in 3 parameter exponential and power-law nonlinear fits to the individual and averaged data. The percentage of variance increased in both exponential and power-law equations when the data were averaged over participants and trials. Drawing on a dynamical systems approach to time scales in motor learning and on analysis of the distinctive features of exponential and power-law functions, however, the authors conclude that the exponential is the learning function for that task and that level of practice.

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Author information

Author/s: Liu, Yeou-Teh (YT); Mayer-Kress, Gottfried (G); Newell, Karl M (KM);

Affiliation: Department of Physical Education, Taiwan Normal University, Taiwan.

Journal and publication information

Publication Type: Journal Article

Journal: Journal of motor behavior (J Mot Behav), published in United States. (Language: eng)

Reference: 2003-Jun; vol 35 (issue 2) : pp 197-207

Dates: Created 2003/04/24; Completed 2003/09/09; Revised 2004/11/17;

PMID: 12711589, status: MEDLINE (last retrieval date: 11/6/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

Comments and Corrections

CommentIn: J Mot Behav. 2004 Jun;36(2):225-32; discussion 233-8. (PMID: 15130872)

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Female
Humans
Learning
Male
Models, Biological

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