Craig D. Takahashi

Hemiparetic stroke impairs anticipatory control of arm movement

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.

Design of robot assistance for arm movement therapy following stroke

This paper describes the mechanical and control design of a robotic device for providing therapeutic assistance to arm movement following stroke. The device uses a single motor and a passively oriented linear constraint to allow patients to reach across their workspace. Experimental evaluation of two controllers for assisting in reaching is presented.

Modeling reaching impairment after stroke using a population vector model of movement control that incorporates neural firing-rate variability

The directional control of reaching after stroke was simulated by including cell death and firing-rate noise in a population vector model of movement control. In this model, cortical activity was assumed to cause the hand to move in the direction of a population vector, defined by a summation of responses from neurons with cosine directional tuning. Two types of directional error were analyzed: the between-target variability, defined as the standard deviation of the directional error across a wide range of target directions, and the within-target variability, defined as the standard deviation of the directional error for many reaches to a single target. Both between and within-target variability increased with increasing cell death. The increase in between-target variability arose because cell death caused a nonuniform distribution of preferred directions. The increase in within-target variability arose because the magnitude of the population vector decreased more quickly than its standard deviation for increasing cell death, provided appropriate levels of firing-rate noise were present. Comparisons to reaching data from 29 stroke subjects revealed similar increases in between and within-target variability as clinical impairment severity increased. Relationships between simulated cell death and impairment severity were derived using the between and within-target variability results. For both relationships, impairment severity increased similarly with decreasing percentage of surviving cells, consistent with results from previous imaging studies. These results demonstrate that a population vector model of movement control that incorporates cosine tuning, linear summation of unitary responses, firing-rate noise, and random cell death can account for some features of impaired arm movement after stroke.

Impaired motor control in patients with benign focal epilepsy of childhood.

Upper extremity motor function was quantitatively assessed in 6 children (age 7—11 years) treated with antiepileptic drugs for benign focal epilepsies of childhood and compared with that of 30 age-matched normal children. Both motor performance and adaptation to perturbing mechanical constraints imposed by a robotic device were significantly impaired in children with benign focal epilepsies of childhood. Our findings thus question whether certain “benign” epilepsies are truly benign and whether pharmacologic treatment might contribute to motor impairment. (J Child Neurol 2006;21:157—160; DOI 10.2310/7010.2006.00023).

Computational motor adaptation-a kindergarten skill

We investigated computational aspects of motor adaptation in 43 children (age range 6-17) who reached while holding the end effector of a lightweight robot. The robot applied an unpredictable, noisy, viscous force field to the hand of each subject. Children adapted to the force field in ostensibly the same manner as adults, reducing their reaching error with practice and forming a model of the approximate mean field gain. However, the children showed more variability in their movement trajectories. A simple ARX learning algorithm proposed previously for adults, adequately captured the childrens performance. These results suggest that the computational algorithms for motor adaptation are established early in development, but operate in a context of increased neuromuscular variability.