Deans' stroke musings

Changing stroke rehab and research worldwide now.Time is Brain!Just think of all the trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 493 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It's quite disgusting that this information is not available from every stroke association and doctors group.
My back ground story is here:

Tuesday, December 13, 2016

Predicting Motor Sequence Learning in Individuals With Chronic Stroke

  1. Katie P. Wadden, MSc1
  2. Kristopher De Asis1
  3. Cameron S. Mang, MSc1
  4. Jason L. Neva, PhD1
  5. Sue Peters, MPT1
  6. Bimal Lakhani, PhD1
  7. Lara A. Boyd, PhD1
  1. 1University of British Columbia, Vancouver, British Columbia, Canada
  1. Lara A. Boyd, Department of Physical Therapy, University of British Columbia, 212-2177 Wesbrook Mall, Vancouver, British Columbia, V6T 1Z3, Canada. Email:


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.  
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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