Impedance control reduces instability that arises from motor noise.

There is ample evidence that humans are able to control the endpoint impedance of their arms in response to active destabilizing force fields. However, such fields are uncommon in daily life. Here, we examine whether the CNS selectively controls the endpoint impedance of the arm in the absence of active force fields but in the presence of instability arising from task geometry and signal-dependent noise (SDN) in the neuromuscular system. Subjects were required to generate forces, in two orthogonal directions, onto four differently curved rigid objects simulated by a robotic manipulandum. The endpoint stiffness of the limb was estimated for each object curvature. With increasing curvature, the endpoint stiffness increased mainly parallel to the object surface and to a lesser extent in the orthogonal direction. Therefore, the orientation of the stiffness ellipses did not orient to the direction of instability. Simulations showed that the observed stiffness geometries and their pattern of change with instability are the result of a tradeoff between maximizing the mechanical stability and minimizing the destabilizing effects of SDN. Therefore, it would have been suboptimal to align the stiffness ellipse in the direction of instability. The time course of the changes in stiffness geometry suggests that modulation takes place both within and across trials. Our results show that an increase in stiffness relative to the increase in noise can be sufficient to reduce kinematic variability, thereby allowing stiffness control to improve stability in natural tasks.

Specificity of reflex adaptation for task-relevant variability.

The motor system responds to perturbations with reflexes, such as the vestibulo-ocular reflex or stretch reflex, whose gains adapt in response to novel and fixed changes in the environment, such as magnifying spectacles or standing on a tilting platform. Here we demonstrate a reflex response to shifts in the hand's visual location during reaching, which occurs before the onset of voluntary reaction time, and investigate how its magnitude depends on statistical properties of the environment. We examine the change in reflex response to two different distributions of visuomotor discrepancies, both of which have zero mean and equal variance across trials. Critically one distribution is task relevant and the other task irrelevant. The task-relevant discrepancies are maintained to the end of the movement, whereas the task-irrelevant discrepancies are transient such that no discrepancy exists at the end of the movement. The reflex magnitude was assessed using identical probe trials under both distributions. We find opposite directions of adaptation of the reflex response under these two distributions, with increased reflex magnitudes for task-relevant variability and decreased reflex magnitudes for task-irrelevant variability. This demonstrates modulation of reflex magnitudes in the absence of a fixed change in the environment, and shows that reflexes are sensitive to the statistics of tasks with modulation depending on whether the variability is task relevant or task irrelevant.

Short- and long-term changes in joint co-contraction associated with motor learning as revealed from surface EMG.

In the field of motor control, two hypotheses have been controversial: whether the brain acquires internal models that generate accurate motor commands, or whether the brain avoids this by using the viscoelasticity of musculoskeletal system. Recent observations on relatively low stiffness during trained movements support the existence of internal models. However, no study has revealed the decrease in viscoelasticity associated with learning that would imply improvement of internal models as well as synergy between the two hypothetical mechanisms. Previously observed decreases in electromyogram (EMG) might have other explanations, such as trajectory modifications that reduce joint torques. To circumvent such complications, we required strict trajectory control and examined only successful trials having identical trajectory and torque profiles. Subjects were asked to perform a hand movement in unison with a target moving along a specified and unusual trajectory, with shoulder and elbow in the horizontal plane at the shoulder level. To evaluate joint viscoelasticity during the learning of this movement, we proposed an index of muscle co-contraction around the joint (IMCJ). The IMCJ was defined as the summation of the absolute values of antagonistic muscle torques around the joint and computed from the linear relation between surface EMG and joint torque. The IMCJ during isometric contraction, as well as during movements, was confirmed to correlate well with joint stiffness estimated using the conventional method, i.e., applying mechanical perturbations. Accordingly, the IMCJ during the learning of the movement was computed for each joint of each trial using estimated EMG-torque relationship. At the same time, the performance error for each trial was specified as the root mean square of the distance between the target and hand at each time step over the entire trajectory. The time-series data of IMCJ and performance error were decomposed into long-term components that showed decreases in IMCJ in accordance with learning with little change in the trajectory and short-term interactions between the IMCJ and performance error. A cross-correlation analysis and impulse responses both suggested that higher IMCJs follow poor performances, and lower IMCJs follow good performances within a few successive trials. Our results support the hypothesis that viscoelasticity contributes more when internal models are inaccurate, while internal models contribute more after the completion of learning. It is demonstrated that the CNS regulates viscoelasticity on a short- and long-term basis depending on performance error and finally acquires smooth and accurate movements while maintaining stability during the entire learning process.

Functional significance of stiffness in adaptation of multijoint arm movements to stable and unstable dynamics.

This study compared the mechanisms of adaptation to stable and unstable dynamics from the perspective of changes in joint mechanics. Subjects were instructed to make point to point movements in force fields generated by a robotic manipulandum which interacted with the arm in either a stable or an unstable manner. After subjects adjusted to the initial disturbing effects of the force fields they were able to produce normal straight movements to the target. In the case of the stable interaction, subjects modified the joint torques in order to appropriately compensate for the force field. No change in joint torque or endpoint force was required or observed in the case of the unstable interaction. After adaptation, the endpoint stiffness of the arm was measured by applying displacements to the hand in eight different directions midway through the movements. This was compared to the stiffness measured similarly during movements in a null force field. After adaptation, the endpoint stiffness under both the stable and unstable dynamics was modified relative to the null field. Adaptation to unstable dynamics was achieved by selective modification of endpoint stiffness in the direction of the instability. To investigate whether the change in endpoint stiffness could be accounted for by change in joint torque or endpoint force, we estimated the change in stiffness on each trial based on the change in joint torque relative to the null field. For stable dynamics the change in endpoint stiffness was accurately predicted. However, for unstable dynamics the change in endpoint stiffness could not be reproduced. In fact, the predicted endpoint stiffness was similar to that in the null force field. Thus, the change in endpoint stiffness seen after adaptation to stable dynamics was directly related to changes in net joint torque necessary to compensate for the dynamics in contrast to adaptation to unstable dynamics, where a selective change in endpoint stiffness occurred without any modification of net joint torque.