Experimental Brain Research

, Volume 149, Issue 2, pp 131–140 | Cite as

Hemiparetic stroke impairs anticipatory control of arm movement

Research Article

Abstract

Internal models are sensory motor mappings used by the nervous system to anticipate the force requirements of movement tasks. The ability to use internal models likely underlies the development of skillful control of the arm throughout life. It is currently unknown to what extent individuals with hemiparetic stroke can form and implement such internal models. To examine this issue, we measured whether such individuals could learn to anticipate forces applied to their arms by a lightweight robotic device as they practiced reaching to a target. Thirteen subjects with post-stroke hemiparesis were tested. Forces were applied to the arm, which curved the hand path in either the medial or lateral direction, as the subjects reached repeatedly towards a target located in front of them at their workspace boundary. The subjects exhibited a decreased ability to adapt to the perturbing forces with their hemiparetic arms. That is, they did not straighten their reaching path as well, compared to their ipsilesional arms, and they exhibited smaller aftereffects when the perturbing force was unexpectedly removed. The ability to adapt to the force improved significantly with decreasing impairment severity, as quantified using both clinical scales and quantitative strength measurements. Some subjects with strength reductions as severe as 60% were able to adapt to the fields, generating significant aftereffects. We conclude that hemiparetic stroke impairs the ability to implement internal models used for anticipatory control of arm movement, although even some severely weakened subjects retain at least a partial ability to form and use internal models. Finding ways to fully restore this adaptive ability, or to make use of what adaptive ability remains during rehabilitation, is an important goal for improving functional motor recovery.

Keywords

Hemiparesis Motor skills Biomechanics Neurological model 

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Copyright information

© Springer-Verlag 2003

Authors and Affiliations

  1. 1.Department of Mechanical and Aerospace EngineeringUniversity of CaliforniaIrvineUSA
  2. 2.Center for Biomedical EngineeringUniversity of CaliforniaIrvineUSA

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