http://nnr.sagepub.com/content/31/1/95?etoc
- Katie P. Wadden, MSc1
- Kristopher De Asis1
- Cameron S. Mang, MSc1
- Jason L. Neva, PhD1
- Sue Peters, MPT1
- Bimal Lakhani, PhD1
- Lara A. Boyd, PhD1⇑
- Lara A. Boyd, Department of Physical Therapy, University of British Columbia, 212-2177 Wesbrook Mall, Vancouver, British Columbia, V6T 1Z3, Canada. Email: lara.boyd@ubc.ca
Abstract
Background. Conventionally,
change in motor performance is quantified with discrete measures of
behavior taken pre- and postpractice.
As a high degree of movement variability exists in
motor performance after stroke, pre- and posttesting of motor skill may
lack sensitivity to predict potential for motor
recovery.
Objective. Evaluate the use of predictive models of motor learning based on individual performance curves and clinical characteristics
of motor function in individuals with stroke.
Methods. Ten healthy and fourteen individuals with chronic stroke performed a continuous joystick-based tracking task over 6 days, and at a 24-hour delayed retention test, to assess implicit motor sequence learning.
Results. Individuals with chronic stroke demonstrated significantly slower rates of improvements in implicit sequence-specific motor performance compared with a healthy control (HC) group when root mean squared error performance data were fit to an exponential function. The HC group showed a positive relationship between a faster rate of change in implicit sequence-specific motor performance during practice and superior performance at the delayed retention test. The same relationship was shown for individuals with stroke only after accounting for overall motor function by including Wolf Motor Function Test rate in our model.
Methods. Ten healthy and fourteen individuals with chronic stroke performed a continuous joystick-based tracking task over 6 days, and at a 24-hour delayed retention test, to assess implicit motor sequence learning.
Results. Individuals with chronic stroke demonstrated significantly slower rates of improvements in implicit sequence-specific motor performance compared with a healthy control (HC) group when root mean squared error performance data were fit to an exponential function. The HC group showed a positive relationship between a faster rate of change in implicit sequence-specific motor performance during practice and superior performance at the delayed retention test. The same relationship was shown for individuals with stroke only after accounting for overall motor function by including Wolf Motor Function Test rate in our model.
Conclusion.
Nonlinear information extracted from multiple time points across
practice, specifically the rate of motor skill acquisition
during practice, relates strongly with changes in
motor behavior at the retention test following practice and could be
used
to predict optimal doses of practice on an
individual basis.
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