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° 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.
| Original language | English |
|---|---|
| Pages (from-to) | 197-207 |
| Number of pages | 11 |
| Journal | Journal of Motor Behavior |
| Volume | 35 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2003 Jan 1 |
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Keywords
- Dynamical systems theory
- Learning curve
- Motor learning
ASJC Scopus subject areas
- Biophysics
- Orthopedics and Sports Medicine
- Experimental and Cognitive Psychology
- Cognitive Neuroscience
Cite this
Beyond curve fitting : A dynamical systems account of exponential learning in a discrete timing task. / Liu, Yeou Teh; Mayer-Kress, Gottfried; Newell, Karl M.
In: Journal of Motor Behavior, Vol. 35, No. 2, 01.01.2003, p. 197-207.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Beyond curve fitting
T2 - A dynamical systems account of exponential learning in a discrete timing task
AU - Liu, Yeou Teh
AU - Mayer-Kress, Gottfried
AU - Newell, Karl M.
PY - 2003/1/1
Y1 - 2003/1/1
N2 - 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° 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.
AB - 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° 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.
KW - Dynamical systems theory
KW - Learning curve
KW - Motor learning
UR - http://www.scopus.com/inward/record.url?scp=0038301394&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0038301394&partnerID=8YFLogxK
U2 - 10.1080/00222890309602133
DO - 10.1080/00222890309602133
M3 - Article
C2 - 12711589
AN - SCOPUS:0038301394
VL - 35
SP - 197
EP - 207
JO - Journal of Motor Behavior
JF - Journal of Motor Behavior
SN - 0022-2895
IS - 2
ER -