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Although the neural basis of balance control remains unknown, recent studies suggest that a feedback law on center-of-mass (CoM) kinematics determines the temporal patterning of muscle activity during human postural responses. We hypothesized that the same feedback law would also explain variations in muscle activity to support-surface translation as perturbation characteristics vary. Subject CoM motion was experimentally modulated using 34 different anterior-posterior support-surface translations of varying peak acceleration and velocity but the same total displacement. Electromyographic (EMG) recordings from several muscles of the lower limbs and trunk were compared to predicted EMG patterns from an inverted pendulum model under delayed feedback control. In both recorded and predicted EMG patterns, the initial burst of muscle activity scaled linearly with peak acceleration, whereas the tonic "plateau" region scaled with peak velocity. The relatively invariant duration of the initial burst was modeled by incorporating a transient, time-limited encoding of CoM acceleration inspired by muscle spindle primary afferent dynamic responses. The entire time course of recorded and predicted muscle activity compared favorably across all conditions, suggesting that the initial burst of muscle activity is not generated by feedforward neural mechanisms. Perturbation conditions were presented randomly and subjects maintained relatively constant feedback gains across all conditions. In contrast, an optimal feedback solution based on a trade-off between CoM stabilization and energy expenditure predicted that feedback gains should change with perturbation characteristics. These results suggest that an invariant feedback law was used to generate the entire time course of muscle activity across a variety of postural disturbances.

A Feedback Model Explains the Differential Scaling of Human Postural Responses to Perturbation Acceleration and Velocity