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Coactivation of antagonist muscles is readily observed early in motor learning, in interactions with unstable mechanical environments and in motor system pathologies. Here we present evidence that the nervous system uses coactivation control far more extensively and that patterns of cocontraction during movement are closely tied to the specific requirements of the task. We have examined the changes in cocontraction that follow dynamics learning in tasks that are thought to involve finely sculpted feedforward adjustments to motor commands. We find that, even following substantial training, cocontraction varies in a systematic way that depends on both movement direction and the strength of the external load. The proportion of total activity that is due to cocontraction nevertheless remains remarkably constant. Moreover, long after indices of motor learning and electromyographic measures have reached asymptotic levels, cocontraction still accounts for a significant proportion of total muscle activity in all phases of movement and in all load conditions. These results show that even following dynamics learning in predictable and stable environments, cocontraction forms a central part of the means by which the nervous system regulates movement.

Previous studies have shown that the nervous system can produce anticipatory adjustments that alter the mechanical behavior of the arm in order to resist environmental disturbances. In the present paper, we focus on the ability of subjects to transfer acquired stiffness patterns to other parts of the workspace and on the durability of stiffness adaptations. To explore the transfer of stiffness control, subjects were trained at the left of the workspace to resist the effects of a single-axis disturbance that was applied by a robotic device. Following training, they were tested for transfer at the right. One group of subjects experienced similar torques at the left and right of the workspace, whereas the other group of subjects experienced similar forces at the hand. Following the initial training at the left, the observed orientation of the hand-stiffness ellipse rotated in the direction of the disturbance. In tests at the right, transfer was observed only when the direction of disturbance resulted in torques that were similar to those experienced during training. The results thus suggest that under the conditions of this experiment stiffness control is acquired and transfers in a joint- or muscle-based system of coordinates. A second experiment assessed the durability of an acquired stiffness pattern. Subjects were trained on 2 consecutive days to resist a single-axis disturbance. On a third day, the direction of the disturbance was switched by 90 degrees . Substantial interference with the new adaptation was observed. This suggests that stiffness training results in durable changes to the neural signals that underlie stiffness control.

We used a robotic device to test the idea that impedance control involves a process of learning or adaptation that is acquired over time and permits the voluntary control of the pattern of stiffness at the hand. The tests were conducted in statics. Subjects were trained over the course of 3 successive days to resist the effects of one of three different kinds of mechanical loads: single axis loads acting in the lateral direction, single axis loads acting in the forward/backward direction, and isotropic loads that perturbed the limb in eight directions about a circle. We found that subjects in contact with single axis loads voluntarily modified their hand stiffness orientation such that changes to the direction of maximum stiffness mirrored the direction of applied load. In the case of isotropic loads, a uniform increase in endpoint stiffness was observed. Using a physiologically realistic model of two-joint arm movement, the experimentally determined pattern of impedance change could be replicated by assuming that coactivation of elbow and double joint muscles was independent of coactivation of muscles at the shoulder. Moreover, using this pattern of coactivation control we were able to replicate an asymmetric pattern of rotation of the stiffness ellipse that was observed empirically. These findings are consistent with the idea that arm stiffness is controlled through the use of at least two independent co-contraction commands.