Learning the dynamics of reaching movements results in the modification of arm impedance and long-latency perturbation responses |
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Authors: | Tie Wang Goran S Dordevic Reza Shadmehr |
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Institution: | (1) Department of Biomedical Engineering, Johns Hopkins University School of Medicine, 419 Traylor Building, 720 Rutland Ave, Baltimore, MD 21205, USA, US |
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Abstract: | Some characteristics of arm movements that humans exhibit during learning the dynamics of reaching are consistent with a
theoretical framework where training results in motor commands that are gradually modified to predict and compensate for novel
forces that may act on the hand. As a first approximation, the motor control system behaves as an adapting controller that
learns an internal model of the dynamics of the task. It approximates inverse dynamics and predicts motor commands that are
appropriate for a desired limb trajectory. However, we had previously noted that subtle motion characteristics observed during
changes in task dynamics challenged this simple model and raised the possibility that adaptation also involved sensory–motor
feedback pathways. These pathways reacted to sensory feedback during the course of the movement. Here we hypothesize that
adaptation to dynamics might also involve a modification of how the CNS responds to sensory feedback. We tested this through
experiments that quantified how the motor system's response to errors during voluntary movements changed as it adapted to
dynamics of a force field. We describe a nonlinear approach that approximates the impedance of the arm, i.e., force response
as a function of arm displacement trajectory. We observe that after adaptation, the impedance function changes in a way that
closely matches and counters the effect of the force field. This is particularly prominent in the long-latency (>100 ms) component
of response to perturbations. Therefore, it appears that practice not only modifies the internal model with which the brain
generates motor commands that initiate a movement, but also the internal model with which sensory feedback is integrated with
the ongoing descending commands in order to respond to error during the movement.
Received: 10 January 2001 / Accepted in revised form: 30 May 2001 |
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