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Neuromechanical tuning of nonlinear postural control dynamics
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Image of FIG. 1.
FIG. 1.

Conceptual framework for understanding tuning and coordination of neuromechanical elements contributing to postural stability. The intrinsic dynamics of the musculoskeletal system at the time of a perturbation depends upon the feedforward contributions of postural configuration and postural muscle tone, which are selected in advance by the nervous system. (a) The chosen postural configuration determines the basic skeletal mechanics of the body, which in standing balance control is unstable due to the divergence of the gravitational force field. Because of the redundancy of joints and limbs, there are many possible postural configurations that can be chosen during standing. (b) The selection of postural muscle tone during standing can also alter the stability of the body, as the instantaneous stiffness and viscosity of muscles vary as a function of their level of activation. Due to the redundancy of muscles across each joint, a large manifold of muscle activation patterns satisfies the static equilibrium requirements for maintaining the selected postural configuration and differs in the stability afforded to the body. Postural muscle tone may increase the time constant of instability of the body or provide a degree of local stability to very small perturbations. (c) When a perturbation to the body is sensed, directionally specific feedback postural responses are elicited, which alter muscle activity after a long delay. During the initial 150 ms following the onset of a perturbation, the dynamics of the body are determined by the intrinsic dynamics set by the feedforward neuromechanical elements in (a) and (b). Postural responses that allow the feet to remain in place have differential stabilizing capacities, which will depend upon the pattern and magnitude of muscle activation elicited. Generally, postural strategies that use primarily hip torques can generate larger restoring forces than those that rely on ankle torques due to limitations in maximum muscle force generation. (d) If the feet-in-place strategy is insufficient to stabilize the body, a step response that expands the base of support and generates a different fixed-point location can occur. Steps can vary in size and can also be elicited as the primary feedback response following a perturbation.

Image of FIG. 2.
FIG. 2.

Recorded and simulated CoM kinematics and muscle activation patterns in cats. (a) Recorded (gray lines) and simulated (black lines) CoM displacement, velocity, and acceleration. (b) Recorded (gray line) muscle activity in a calf muscle occurs about 40 ms after the onset of the perturbation. The initial burst of muscle activity resembles the temporal features of the CoM acceleration. The simulated (black line) muscle activity is derived by identifying the feedback gains and delay that minimize the squared error between recorded and simulated EMGs. (c) Decomposition of simulated muscle activity (black line) into components arising from CoM position feedback (gray dashed line), CoM velocity feedback (gray dotted line), and CoM acceleration feedback (gray solid line). Note that the initial burst is due primarily to delayed acceleration feedback, whereas later muscle activity is primarily from delayed velocity and position feedback.

Image of FIG. 3.
FIG. 3.

Simple feedback model of postural control used to predict muscle activity during balance responses. (a) The mechanics of the CoM during the balance task is approximated as an inverted pendulum on a moving cart. Experimentally measured accelerations of the platform were applied to the cart so that realistic acceleration, velocity, and displacement trajectories of the platform were modeled. (b) The perturbation acceleration generates a disturbance torque at the base of the pendulum. Kinematics of the horizontal CoM were controlled with a delayed-feedback law that generated model muscle activation patterns, which were compared to those measured experimentally. The model muscle activation was passed through a first-order muscle model to generate a stabilizing torque about the representative joint.

Image of FIG. 4.
FIG. 4.

A robotic model of postural control allows the neuromechanical tuning of postural stability to be studied. The robot is essentially a three-link chain that can be arranged to stand on a moving platform. When the support surface is perturbed in the horizontal plane, a delayed linear feedback loop (90 ms) generated torques at the “hip” joint based on the position and velocity of the joints. (a) A model of the robot feedback demonstrates that successful feet-in-place responses depend upon interactions between postural configuration and postural muscle tone. The set of feedback gains that allows the robot to remain standing without losing ground contact varies as the stance width changes. At a narrow stance width, high position and velocity feedback gains are necessary to maintain stability. As the stance width increases, the region of successful feedback gains shifts to lower nonoverlapping values. Postural muscle tone is simulated by adding intrinsic stiffness that simulates a spring at the joints. With no intrinsic stiffness, the tolerance to variation in feedback gains is low (lightest gray area). As intrinsic stiffness is increased, the regions of gain that allow the system to remain standing is increased as shading gets darker. Note that for the largest value of intrinsic stiffness, the system was still unable to recover balance without the delayed-feedback mechanism. (b) Emergent stepping can occur and be modulated by varying the feedback gain values, as well as the set point of the joint position. Here, the limbs generate a constant outward force while standing quietly, similar to that observed in humans in animals. Under this condition, the robot spontaneously steps upon perturbation, whereas if the outward force decreases, the step would not occur.

Image of FIG. 5.
FIG. 5.

Phase-plane CoM trajectories during postural responses to identical forward perturbations of the support surface. At the beginning of the experiment, subjects were able to maintain balance with feet in place to a 12 cm, 35 m/s forward perturbation. Subjects were then adapted to a series of backward perturbations, and without warning in trial 91, the original forward perturbation was presented. Subjects now had to take a step to maintain balance. The horizontal CoM dynamics also change dramatically with subsequent presentations of the same forward perturbation. In trial 91, the CoM falls backward during the perturbation. Although the CoM velocity begins to return toward zero, an abrupt change in the phase-plane trajectory indicates that a step was taken, which shifts the trajectory to a different orbit that eventually returns near the original state. Note, however, that subjects do not return to the original positions; this is common in postural control. On trial 92, the subject was able to maintain balance with the feet in place, although the reversal in the phase-plane trajectory suggests an aborted step response. On subsequent trials, the subjects are able to decrease both peak CoM displacement and velocity and return the CoM closer to the original position. These changes probably depend upon the modulation of both feedforward and feedback neuromechanical elements that modify postural stability dynamics.


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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Neuromechanical tuning of nonlinear postural control dynamics