Jevin E. Scrivens

Bio: Jevin E. Scrivens is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Postural Balance & Balance (ability). The author has an hindex of 3, co-authored 3 publications receiving 77 citations.

Neuromechanical tuning of nonlinear postural control dynamics

Abstract: Postural control may be an ideal physiological motor task for elucidating general questions about the organization, diversity, flexibility, and variability of biological motor behaviors using nonlinear dynamical analysis techniques. Rather than presenting "problems" to the nervous system, the redundancy of biological systems and variability in their behaviors may actually be exploited to allow for the flexible achievement of multiple and concurrent task-level goals associated with movement. Such variability may reflect the constant "tuning" of neuromechanical elements and their interactions for movement control. The problem faced by researchers is that there is no one-to-one mapping between the task goal and the coordination of the underlying elements. We review recent and ongoing research in postural control with the goal of identifying common mechanisms underlying variability in postural control, coordination of multiple postural strategies, and transitions between them. We present a delayed-feedback model used to characterize the variability observed in muscle coordination patterns during postural responses to perturbation. We emphasize the significance of delays in physiological postural systems, requiring the modulation and coordination of both the instantaneous, "passive" response to perturbations as well as the delayed, "active" responses to perturbations. The challenge for future research lies in understanding the mechanisms and principles underlying neuromechanical tuning of and transitions between the diversity of postural behaviors. Here we describe some of our recent and ongoing studies aimed at understanding variability in postural control using physical robotic systems, human experiments, dimensional analysis, and computational models that could be enhanced from a nonlinear dynamics approach.

A robotic device for understanding neuromechanical interactions during standing balance control.

Abstract: Postural stability in standing balance results from the mechanics of body dynamics as well as active neural feedback control processes. Even when an animal or human has multiple legs on the ground, active neural regulation of balance is required. When the postural configuration, or stance, changes, such as when the feet are placed further apart, the mechanical stability of the organism changes, but the degree to which this alters the demands on neural feedback control for postural stability is unknown. We developed a robotic system that mimics the neuromechanical postural control system of a cat in response to lateral perturbations. This simple robotic system allows us to study the interactions between various parameters that contribute to postural stability and cannot be independently varied in biological systems. The robot is a 'planar', two-legged device that maintains compliant balance control in a variety of stance widths when subject to perturbations of the support surface, and in this sense reveals principles of lateral balance control that are also applicable to bipeds. Here we demonstrate that independent variations in either stance width or delayed neural feedback gains can have profound and often surprisingly detrimental effects on the postural stability of the system. Moreover, we show through experimentation and analysis that changing stance width alters fundamental mechanical relationships important in standing balance control and requires a coordinated adjustment of delayed feedback control to maintain postural stability.

Effects of stance width on control gain in standing balance

Abstract: Standing in a wide stance during a lateral perturbation is considered to be easier than standing in a narrow stance, but the basis for this ease of stance is not understood. To study the effects of increased stance width in balance control, we created a standing model of a cat with variable stance width and subjected it to lateral displacement perturbations. We studied balance control while varying postural orientation and control parameters that are not accessible in a biological cat. We determined that delayed feedback in the postural controller necessitates the reduction of active feedback gain as stance width increases from narrow to wide stance. By establishing the change in control requirements in a system that resembles a biological configuration, we can predict that similar control changes may occur in biological systems. I. INTRODUCTION ALANCE control is an important function for the life and survival of animals of all different sizes, shapes, and configurations. The mechanisms of balance control must work to maintain balance across a wide range of postural configurations. In general, balance control comes from the rejection of disturbances to posture. The mechanism of rejection is the generation of a force to counteract the disturbance. This force may come from an active muscle response or the passive viscoelestic properties of the physical system or body. The magnitude of the required force response is heavily dependent on the perturbation and shape and orientation of the body. Together, the passive viscoelestic properties and orientation of the body provide mechanical stability to reject some of the perturbation (Kubow and Full 1999). Active control may then be required to provide additional response and maintain a stable posture. A system with high mechanical stability may require less active response to perturbation than less stable one. An example of this is the difference in effort to stand with ones legs together vs. legs apart while on an accelerating train. Standing with legs apart is considered easier, but the implications on active control are not understood. The active response to postural perturbation is the generation of corrective muscle activity. In humans and cats these postural responses can be described as a feedback

Common muscle synergies for control of center of mass and force in nonstepping and stepping postural behaviors

Abstract: We investigated muscle activity, ground reaction forces, and center of mass (CoM) acceleration in two different postural behaviors for standing balance control in humans to determine whether common neural mechanisms are used in different postural tasks. We compared nonstepping responses, where the base of support is stationary and balance is recovered by returning CoM back to its initial position, with stepping responses, where the base of support is enlarged and balance is recovered by pushing the CoM away from the initial position. In response to perturbations of the same direction, these two postural behaviors resulted in different muscle activity and ground reaction forces. We hypothesized that a common pool of muscle synergies producing consistent task-level biomechanical functions is used to generate different postural behaviors. Two sets of support-surface translations in 12 horizontal-plane directions were presented, first to evoke stepping responses and then to evoke nonstepping responses. Electromyographs in 16 lower back and leg muscles of the stance leg were measured. Initially (∼100-ms latency), electromyographs, CoM acceleration, and forces were similar in nonstepping and stepping responses, but these diverged in later time periods (∼200 ms), when stepping occurred. We identified muscle synergies using non-negative matrix factorization and functional muscle synergies that quantified correlations between muscle synergy recruitment levels and biomechanical outputs. Functional muscle synergies that produce forces to restore CoM position in nonstepping responses were also used to displace the CoM during stepping responses. These results suggest that muscle synergies represent common neural mechanisms for CoM movement control under different dynamic conditions: stepping and nonstepping postural responses.

The Brain in Its Body: Motor Control and Sensing in a Biomechanical Context

Abstract: Although it is widely recognized that adaptive behavior emerges from the ongoing interactions among the nervous system, the body, and the environment, it has only become possible in recent years to experimentally study and to simulate these interacting systems. We briefly review work on molluscan feeding, maintenance of postural control in cats and humans, simulations of locomotion in lamprey, insect, cat and salamander, and active vibrissal sensing in rats to illustrate the insights that can be derived from studies of neural control and sensing within a biomechanical context. These studies illustrate that control may be shared between the nervous system and the periphery, that neural activity organizes degrees of freedom into biomechanically meaningful subsets, that mechanics alone may play crucial roles in enforcing gait patterns, and that mechanics of sensors is crucial for their function.

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

Abstract: 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.

Mechanisms of motor adaptation in reactive balance control.

Abstract: Balance control must be rapidly modified to provide stability in the face of environmental challenges. Although changes in reactive balance over repeated perturbations have been observed previously, only anticipatory postural adjustments preceding voluntary movements have been studied in the framework of motor adaptation and learning theory. Here, we hypothesized that adaptation occurs in task-level balance control during responses to perturbations due to central changes in the control of both anticipatory and reactive components of balance. Our adaptation paradigm consisted of a Training set of forward support-surface perturbations, a Reversal set of novel countermanding perturbations that reversed direction, and a Washout set identical to the Training set. Adaptation was characterized by a change in a motor variable from the beginning to the end of each set, the presence of aftereffects at the beginning of the Washout set when the novel perturbations were removed, and a return of the variable at the end of the Washout to a level comparable to the end of the Training set. Task-level balance performance was characterized by peak center of mass (CoM) excursion and velocity, which showed adaptive changes with repetitive trials. Only small changes in anticipatory postural control, characterized by body lean and background muscle activity were observed. Adaptation was found in the evoked long-latency muscular response, and also in the sensorimotor transformation mediating that response. Finally, in each set, temporal patterns of muscle activity converged towards an optimum predicted by a trade-off between maximizing motor performance and minimizing muscle activity. Our results suggest that adaptation in balance, as well as other motor tasks, is mediated by altering central sensitivity to perturbations and may be driven by energetic considerations.

Stability in a frontal plane model of balance requires coupled changes to postural configuration and neural feedback control

Abstract: Postural stability depends on interactions between the musculoskeletal system and neural control mechanisms. We present a frontal plane model stabilized by delayed feedback to analyze the effects of altered stance width on postural responses to perturbations. We hypothesized that changing stance width alters the mechanical dynamics of the body and limits the range of delayed feedback gains that produce stable postural behaviors. Surprisingly, mechanical stability was found to decrease as stance width increased due to decreased effective inertia. Furthermore, due to sensorimotor delays and increased leverage of hip joint torque on center-of-mass motion, the magnitudes of the stabilizing delayed feedback gains decreased as stance width increased. Moreover, the ranges of the stable feedback gains were nonoverlapping across different stance widths such that using a single neural feedback control strategy at both narrow and wide stances could lead to instability. The set of stable feedback gains was further reduced by constraints on foot lift-off and perturbation magnitude. Simulations were fit to experimentally measured kinematics, and the identified feedback gains corroborated model predictions. In addition, analytical gain margin of the linearized system was found to predict step transitions without the need for simulation. In conclusion, this model offers a method to dissociate the complex interactions between postural configuration, delayed sensorimotor feedback, and nonlinear foot lift-off constraints. The model demonstrates that stability at wide stances can only be achieved if delayed neural feedback gains decrease. This model may be useful in explaining both expected and paradoxical changes in stance width in healthy and neurologically impaired individuals.