Article

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. 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.
CI - (c) The Author(s) 2016.

Langue : ANGLAIS