Biomedical subjects

Theodore E Milner

Publications and source records attributed to Theodore E Milner.

14 recordsLinked to original sources

PubMed2006

Position information but not force information is used in adapting to changes in environmental dynamics.

This study investigated how movement error is evaluated and used to change feedforward commands following a change in the environmental dynamics. In particular, we addressed the question of whether only position-error information is used or whether information about the force-field direction can also be used for rapid adaptation to changes in the environmental dynamics. Subjects learned to move in a position-dependent force field (PF) with a parabolic profile and the dynamics of a negative spring, which produced lateral force to the left of the target hand path. They adapted very rapidly, dramatically reducing lateral error after a single trial. Several times during training, the strength of the PF was unexpectedly doubled (PF2) for two trials. This again created a large leftward deviation, which was greatly reduced on the second PF2 trial, and an aftereffect when the force field subsequently returned to its original strength. The aftereffect was abolished if the second PF2 trial was replaced by an oppositely directed velocity-dependent force field (VF). During subsequent training in the VF, immediately after having adapted to the PF, subjects applied a force that assisted the force field for approximately 15 trials, indicating that they did not use information about the force-field direction. We concluded that the CNS uses only the position error for updating the internal model of the environmental dynamics and modifying feedforward commands. Although this strategy is not necessarily optimal, it may be the most reliable strategy for iterative improvement in performance.

Adaptation, Physiological↗

PubMed2005

Central representation of dynamics when manipulating handheld objects.

To explore the neural mechanisms related to representation of the manipulation dynamics of objects, we performed whole-brain fMRI while subjects balanced an object in stable and highly unstable states and while they balanced a rigid object and a flexible object in the same unstable state, in all cases without vision. In this way, we varied the extent to which an internal model of the manipulation dynamics was required in the moment-to-moment control of the object's orientation. We hypothesized that activity in primary motor cortex would reflect the amount of muscle activation under each condition. In contrast, we hypothesized that cerebellar activity would be more strongly related to the stability and complexity of the manipulation dynamics because the cerebellum has been implicated in internal model-based control. As hypothesized, the dynamics-related activation of the cerebellum was quite different from that of the primary motor cortex. Changes in cerebellar activity were much greater than would have been predicted from differences in muscle activation when the stability and complexity of the manipulation dynamics were contrasted. On the other hand, the activity of the primary motor cortex more closely resembled the mean motor output necessary to execute the task. We also discovered a small region near the anterior edge of the ipsilateral (right) inferior parietal lobule where activity was modulated with the complexity of the manipulation dynamics. We suggest that this is related to imagining the location and motion of an object with complex manipulation dynamics.

Brain Mapping↗

PubMed2005

Impedance control and internal model use during the initial stage of adaptation to novel dynamics in humans.

This study investigated the neuromuscular mechanisms underlying the initial stage of adaptation to novel dynamics. A destabilizing velocity-dependent force field (VF) was introduced for sets of three consecutive trials. Between sets a random number of 4-8 null field trials were interposed, where the VF was inactivated. This prevented subjects from learning the novel dynamics, making it possible to repeatedly recreate the initial adaptive response. We were able to investigate detailed changes in neural control between the first, second and third VF trials. We identified two feedforward control mechanisms, which were initiated on the second VF trial and resulted in a 50% reduction in the hand path error. Responses to disturbances encountered on the first VF trial were feedback in nature, i.e. reflexes and voluntary correction of errors. However, on the second VF trial, muscle activation patterns were modified in anticipation of the effects of the force field. Feedforward cocontraction of all muscles was used to increase the viscoelastic impedance of the arm. While stiffening the arm, subjects also exerted a lateral force to counteract the perturbing effect of the force field. These anticipatory actions indicate that the central nervous system responds rapidly to counteract hitherto unfamiliar disturbances by a combination of increased viscoelastic impedance and formation of a crude internal dynamics model.

Adaptation, Physiological↗

PubMed2005

Novel strategies in feedforward adaptation to a position-dependent perturbation.

To investigate the control mechanisms used in adapting to position-dependent forces, subjects performed 150 horizontal reaching movements over 25 cm in the presence of a position-dependent parabolic force field (PF). The PF acted only over the first 10 cm of the movement. On every fifth trial, a virtual mechanical guide (double wall) constrained subjects to move along a straight-line path between the start and target positions. Its purpose was to register lateral force to track formation of an internal model of the force field, and to look for evidence of possible alternative adaptive strategies. The force field produced a force to the right, which initially caused subjects to deviate in that direction. They reacted by producing deviations to the left, "into" the force field, as early as the second trial. Further adaptation resulted in rapid exponential reduction of kinematic error in the latter portion of the movement, where the greatest perturbation to the handpath was initially observed, whereas there was little modification of the handpath in the region where the PF was active. Significant force directed to counteract the PF was measured on the first guided trial, and was modified during the first half of the learning set. The total force impulse in the region of the PF increased throughout the learning trials, but it always remained less than that produced by the PF. The force profile did not resemble a mirror image of the PF in that it tended to be more trapezoidal than parabolic in shape. As in previous studies of force-field adaptation, we found that changes in muscle activation involved a general increase in the activity of all muscles, which increased arm stiffness, and selectively-greater increases in the activation of muscles which counteracted the PF. With training, activation was exponentially reduced, albeit more slowly than kinematic error. Progressive changes in kinematics and EMG occurred predominantly in the region of the workspace beyond the force field. We suggest that constraints on muscle mechanics limit the ability of the central nervous system to employ an inverse dynamics model to nullify impulse-like forces by generating mirror-image forces. Consequently, subjects adopted a strategy of slightly overcompensating for the first half of the force field, then allowing the force field to push them in the opposite direction. Muscle activity patterns in the region beyond the boundary of the force field were subsequently adjusted because of the relatively-slow response of the second-order mechanics of muscle impedance to the force impulse.

Adaptation, Physiological↗

PubMed2004

Accuracy of internal dynamics models in limb movements depends on stability.

This study investigated the ability to use an internal model of the environmental dynamics when the dynamics were predictable but unstable. Subjects performed goal-directed movements using a robot manipulandum while counteracting a force field, which created instability by assisting the movement in proportion to hand velocity. Subjects' performance was better on the last trial than on the first trial in the force field for all four movement directions tested: out, in, right and left. Subjects adapted to the force field primarily by increasing muscle co-contraction, compared to null field movements, during all phases of movement. This co-contraction generally declined for both the deceleration and stabilization phases during the course of the first 25 movements in each direction, but tended not to decrease significantly thereafter. Catch trials at the end of the learning period suggested that increased viscoelastic impedance due to muscle co-contraction was used to counteract the force field. Only in the case of outward movements were aftereffects observed that were consistent with formation of an accurate internal model of the force field dynamics. Stabilization of the hand for outward movements required less muscle co-contraction than for movements in other directions due to stability conferred by the geometry of the arm. The results suggest that the accuracy of an internal model depends critically on the stability of the coupled dynamics of the limb and the environment.

Adaptation, Physiological↗

PubMed2004

Impedance control balances stability with metabolically costly muscle activation.

Humans are able to stabilize their movements in environments with unstable dynamics by selectively modifying arm impedance independently of force and torque. We further investigated adaptation to unstable dynamics to determine whether the CNS maintains a constant overall level of stability as the instability of the environmental dynamics is varied. Subjects performed reaching movements in unstable force fields of varying strength, generated by a robotic manipulator. Although the force fields disrupted the initial movements, subjects were able to adapt to the novel dynamics and learned to produce straight trajectories. After adaptation, the endpoint stiffness of the arm was measured at the midpoint of the movement. The stiffness had been selectively modified in the direction of the instability. The stiffness in the stable direction was relatively unchanged from that measured during movements in a null force field prior to exposure to the unstable force field. This impedance modification was achieved without changes in force and torque. The overall stiffness of the arm and environment in the direction of instability was adapted to the force field strength such that it remained equivalent to that of the null force field. This suggests that the CNS attempts both to maintain a minimum level of stability and minimize energy expenditure.

Arm↗

PubMed2003

Adaptive control of stiffness to stabilize hand position with large loads.

The goal of this work was to investigate stability in relation to the magnitude and direction of forces applied by the hand. The endpoint stiffness and joint stiffness of the arm were measured during a postural task in which subjects exerted up to 30% maximum voluntary force in each of four directions while controlling the position of the hand. All four coefficients of the joint stiffness matrix were found to vary linearly with both elbow and shoulder torque. This contrasts with the results of a previous study, which employed a force control task and concluded that the joint stiffness coefficients varied linearly with either shoulder or elbow torque but not both. Joint stiffness was transformed into endpoint stiffness to compare the effect on stability as endpoint force increased. When the joint stiffness coefficients were modeled as varying with the net torque at only one joint, as in the previous study, we found that hand position became unstable if endpoint force exceeded about 22 N in a specific direction. This did not occur when the joint stiffness coefficients were modeled as varying with the net torque at both joints, as in the present study. Rather, hand position became increasingly more stable as endpoint force increased for all directions of applied force. Our analysis suggests that co-contraction of biarticular muscles was primarily responsible for the increased stability. This clearly demonstrates how the central nervous system can selectively adapt the impedance of the arm in a specific direction to stabilize hand position when the force applied by the hand has a destabilizing effect in that direction.

Adaptation, Physiological↗

PubMed2003

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.

Adaptation, Physiological↗

PubMed2003

The case for an internal dynamics model versus equilibrium point control in human movement.

The equilibrium point hypothesis (EPH) was conceived as a means whereby the central nervous system could control limb movements by a relatively simple shift in equilibrium position without the need to explicitly compensate for task dynamics. Many recent studies have questioned this view with results that suggest the formation of an internal dynamics model of the specific task. However, supporters of the EPH have argued that these results are not incompatible with the EPH and that there is no reason to abandon it. In this study, we have tested one of the fundamental predictions of the EPH, namely, equifinality. Subjects learned to perform goal-directed wrist flexion movements while a motor provided assistance in proportion to the instantaneous velocity. It was found that the subjects stopped short of the target on the trials where the magnitude of the assistance was randomly decreased, compared to the preceding control trials (P = 0.003), i.e. equifinality was not achieved. This is contrary to the EPH, which predicts that final position should not be affected by external loads that depend purely on velocity. However, such effects are entirely consistent with predictions based on the formation of an internal dynamics model.

Adult↗

PubMed2003

Different mechanisms involved in adaptation to stable and unstable dynamics.

Recently, we demonstrated that humans can learn to make accurate movements in an unstable environment by controlling magnitude, shape, and orientation of the endpoint impedance. Although previous studies of human motor learning suggest that the brain acquires an inverse dynamics model of the novel environment, it is not known whether this control mechanism is operative in unstable environments. We compared learning of multijoint arm movements in a "velocity-dependent force field" (VF), which interacted with the arm in a stable manner, and learning in a "divergent force field" (DF), where the interaction was unstable. The characteristics of error evolution were markedly different in the 2 fields. The direction of trajectory error in the DF alternated to the left and right during the early stage of learning; that is, signed error was inconsistent from movement to movement and could not have guided learning of an inverse dynamics model. This contrasted sharply with trajectory error in the VF, which was initially biased and decayed in a manner that was consistent with rapid feedback error learning. EMG recorded before and after learning in the DF and VF are also consistent with different learning and control mechanisms for adapting to stable and unstable dynamics, that is, inverse dynamics model formation and impedance control. We also investigated adaptation to a rotated DF to examine the interplay between inverse dynamics model formation and impedance control. Our results suggest that an inverse dynamics model can function in parallel with an impedance controller to compensate for consistent perturbing force in unstable environments.

Adaptation, Physiological↗

PubMed2003

Adaptation to stable and unstable dynamics achieved by combined impedance control and inverse dynamics model.

This study compared adaptation in novel force fields where trajectories were initially either stable or unstable to elucidate the processes of learning novel skills and adapting to new environments. Subjects learned to move in a null force field (NF), which was unexpectedly changed either to a velocity-dependent force field (VF), which resulted in perturbed but stable hand trajectories, or a position-dependent divergent force field (DF), which resulted in unstable trajectories. With practice, subjects learned to compensate for the perturbations produced by both force fields. Adaptation was characterized by an initial increase in the activation of all muscles followed by a gradual reduction. The time course of the increase in activation was correlated with a reduction in hand-path error for the DF but not for the VF. Adaptation to the VF could have been achieved solely by formation of an inverse dynamics model and adaptation to the DF solely by impedance control. However, indices of learning, such as hand-path error, joint torque, and electromyographic activation and deactivation suggest that the CNS combined these processes during adaptation to both force fields. Our results suggest that during the early phase of learning there is an increase in endpoint stiffness that serves to reduce hand-path error and provides additional stability, regardless of whether the dynamics are stable or unstable. We suggest that the motor control system utilizes an inverse dynamics model to learn the mean dynamics and an impedance controller to assist in the formation of the inverse dynamics model and to generate needed stability.

Adaptation, Physiological↗

PubMed2002

Activation of intrinsic and extrinsic finger muscles in relation to the fingertip force vector.

Surface EMG was recorded from two intrinsic and two extrinsic muscles of the index finger during a two-dimensional isometric force task in the plane of flexion and extension. Subjects applied force isometrically at the fingertip in eight equally spaced directions, encompassing 360 degrees. Target forces spanned the range from 20% to 50% of maximum for each direction. The effect of varying the metacarpophalangeal (MCP) and interphalangeal (IP) joint angles was investigated. We found that when applying isometric force with the fingertip, the intrinsic muscles of the index finger behaved as a single unit whose region of activation overlapped that of the extrinsic flexor and extensor muscles. The activation region of the intrinsic muscles also spanned a range of force directions for which the extrinsic muscles were virtually inactive. The activation of all muscles, with the exception of the extrinsic extensor, was modified by changing the MCP and IP joint angles. Both IP flexion and MCP extension produced rotation of the resultant activity vector in the direction of MCP flexion. However, the relative rotation was much greater with IP flexion than MCP extension. The effect of IP flexion is linked to rotation of the force direction where joint torque switches from extension to flexion, while the effect of MCP extension is more likely related to changes in muscle length and MCP moment arm. Our results suggest that the primary role of intrinsic finger muscles is to precisely control the direction of fingertip force, while extrinsic muscles provide stability of the joints.

Female↗

PubMed2002

Contribution of geometry and joint stiffness to mechanical stability of the human arm.

This study investigates the ability to maintain a stable position of the hand when confronted with environmental instability. Subjects were required to hold the hand inside a 0.4-mm square while counteracting the destabilizing effect of a force field, which pushed the hand away from a line in the horizontal plane. The endpoint stiffness of the relaxed arm proved to be a reliable predictor of stability. Subjects were most successful in stabilizing hand position when the direction of the force field was aligned with the direction of greatest endpoint stiffness. They were least successful when the force field was aligned in the orthogonal direction, the direction of least endpoint stiffness. Subjects increased their endpoint stiffness as the strength of the force field was increased, but when the force field was in the direction of least stiffness they eventually failed in stabilizing the hand at the highest force field strength. In contrast, they were as successful in stabilizing the hand at the highest force field strength as at the lowest, when the force field was aligned with the direction of greatest stiffness. With the elbow flexed, endpoint stiffness of the relaxed arm becomes more uniform than with the elbow extended. This was reflected in subjects' performance, which improved considerably compared to the extended elbow posture, as force field strength was increased in the direction of lesser stiffness. The results indicate that posture was more effective than joint stiffness in stabilizing hand position.

Analysis of Variance↗

PubMed2002

Adaptation to destabilizing dynamics by means of muscle cocontraction.

Adaptive control of wrist mechanics was investigated by means of destabilizing dynamics created by a torque motor. Subjects performed a 20 degrees movement to a 3 degrees target under the constraint that no motion should occur outside of the target zone once 800 ms had elapsed from movement onset. This constraint served as the minimum acceptable level of postural stability. The ability of subjects to modify their muscle activation patterns in order to successfully achieve this stability was investigated by creating three types of destabilizing dynamics with markedly different features: negative stiffness, negative damping, and square-wave vibration. Subjects performed sets of trials with the first type of destabilizing dynamics and were then required to adapt to the second and third. The adaptive response was quantified in terms of the rms electromyographic (EMG) activity recorded during various phases of the task. Surface EMG activity was recorded from three muscles contributing to wrist flexion and three muscles contributing to wrist extension. With negative stiffness, a significant compensatory increase in cocontraction of wrist flexor and extensor muscles was observed for slow movements, but there was little change in the muscle activity for rapid movements. With negative damping, muscle cocontraction was elevated to stabilize rapid movements, declining only gradually after the target was reached. For slow movements, cocontraction occurred only when negative damping was high. The response to square-wave vibration (10 Hz, +/-0.5 Nm), beginning at movement onset, was similar to that of negative damping, in that it resulted in elevated cocontraction. However, because the vibration persisted after the target was reached, there was no subsequent decrease in muscle activity. When the frequency was reduced to 5.5 Hz, but with the same torque impulse, cocontraction increased. This is consistent with greater mechanical instability. In summary, agonist-antagonist cocontraction was adapted to the stability of the task. This generally resulted in less of a change in muscle activity during the movement phase, when the task was performed quickly compared with slowly. On the other hand, the change in muscle activity during stabilization depended more on the nature of the instability than the movement speed.

Adaptation, Physiological↗