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During postural responses to perturbations, horizontal plane forces generated by the cat hindlimb are stereotypically directed either towards or away from the animal's center of mass, independent of perturbation direction. We used a static, three-dimensional musculoskeletal model of the hindlimb to investigate possible biomechanical determinants of this "force constraint strategy." We hypothesized that directions in which the hindlimb can produce large forces are preferentially used in postural control. We computed feasible force sets (FFSs) based on hindlimb configurations of three cats during postural equilibrium tasks and compared them to horizontal plane postural force directions. The grand mean FFS was bimodal, with maxima near the posterior-anterior axis (-86+/-8 degrees and 71+/-4 degrees ), and minima near the medial-lateral axis (177+/-8 degrees and 8+/-8 degrees ). Experimental postural force directions clustered near both maxima; there were no medial postural forces near the absolute minimum. However, the medians of the anterior and posterior postural force direction histograms in the right hindlimb were rotated counter-clockwise from the FFS maxima (p

We recently showed that four muscle synergies can reproduce multiple muscle activation patterns in cats during postural responses to support surface translations. We now test the robustness of functional muscle synergies, which specify muscle groupings and the active force vectors produced during postural responses under several biomechanically distinct conditions. We aimed to determine whether such synergies represent a generalized control strategy for postural control or if they are merely specific to each postural task. Postural responses to multidirectional translations at different fore-hind paw distances and to multidirectional rotations at the preferred stance distance were analyzed. Five synergies were required to adequately reconstruct responses to translation at the preferred stance distance—four were similar to our previous analysis of translation, whereas the fifth accounted for the newly added background activity during quiet stance. These five control synergies could account for >80% total variability or r2> 0.6 of the electromyographic and force tuning curves for all other experimental conditions. Forces were successfully reconstructed but only when they were referenced to a coordinate system that rotated with the limb axis as stance distance changed. Finally, most of the functional muscle synergies were similar across all of the six cats in terms of muscle synergy number, synergy activation patterns, and synergy force vectors. The robustness of synergy organization across perturbation types, postures, and animals suggests that muscle synergies controlling task-variables are a general construct used by the CNS for balance control.

This study sought to identify the sensory signals that encode perturbation direction rapidly enough to shape the directional tuning of the automatic postural response. We compared reactions to 16 directions of pitch and roll rotation and 16 directions of linear translation in the horizontal plane in freely standing cats. Rotations and translations that displaced the center of mass in the same direction relative to the feet evoked similar patterns of muscle activity and active ground-reaction force, suggesting the presence of a single, robust postural strategy for stabilizing the center of mass in both rotation and translation. Therefore we postulated there should be a common sensory input that encodes the direction of the perturbation and leads to the directional tuning of the early electromyographic burst in the postural response. We compared the mechanical changes induced by rotations and translations prior to the active, postural response. The only consistent feature common to the full range of rotation and translation directions was the initial change in ground-reaction force angle. Other variables including joint angles, ground-reaction force magnitudes, center of pressure, and center of mass in space showed opposite or nonsignificant changes for rotation and translation. Change in force angle at the paw reflects the ratio of loading force to slip force, analogous to slips during finger grip tasks. We propose that cutaneous sensors in the foot soles detect change in ground-reaction force angle and provide the critical input underlying the directional tuning of the automatic postural response for balance.

Pyridoxine given in large doses is thought to destroy selectively the large-diameter peripheral sensory nerve fibers, leaving motor fibers intact. This study examined the effects of pyridoxine-induced somatosensory loss on automatic postural responses to sudden displacements of the support surface in the standing cat. Two cats were trained to stand on four force plates mounted on a movable platform. They were given pyridoxine (350 mg/kg, i.p.) on 2 successive days (0 and 1). Electromyographic (EMG) activity was recorded from selected hindlimb muscles during linear ramp-and-hold platform displacements in each of 12 directions at 15 cm/sec. In control trials onset latencies of evoked activity in hindlimb flexor and extensor muscles ranged from 40 to 65 msec after the onset of platform acceleration. After injection the EMG latencies increased over days, becoming two to three times longer than controls by day 7. Excursions of the body center of mass (CoM) in the direction opposite to that of platform translation were significantly greater at day 7 compared with controls, and the time at which the CoM subsequently reversed direction was delayed. Both animals were ataxic from day 2 onward. Histological analysis of cutaneous and muscle nerves in the hindlimb revealed a significant loss of fibers in the group I range. Our results suggest that large afferent fibers are critical for the timing of automatic postural responses to ensure coordinated control of the body CoM and balance after unexpected disturbances of the support surface.

Background Deficits in balance control are one of the most common and serious mobility challenges facing individuals with lower limb loss. Yet, dynamic postural balance control among individuals with lower limb loss remains poorly understood. Here we examined the kinematics and kinetics of dynamic balance in individuals with unilateral transtibial limb loss. Methods Five individuals with unilateral transtibial limb loss, and five age- and gender-matched controls completed a series of randomly applied multi-directional support surface translations. Whole-body metrics, e.g. peak center-of-mass displacement and net center-of-pressure displacement were compared across cohorts. Stability margin was computed as the difference between peak center-of-pressure and center-of-mass displacement. Additionally, center-of-pressure and ground reaction force magnitude and direction were compared between the prosthetic, intact, and control legs. Findings Peak center-of-mass displacement and stability margin did not differ between individuals with transtibial limb loss and controls for all perturbation directions except those loading only the prosthetic leg; in such cases the stability margin was actually larger than controls. Despite similar center-of-mass displacement, greater center-of-pressure displacement was observed in the intact leg during anterior–posterior perturbations, and under the prosthetic leg in medial–lateral perturbations. Further, in the prosthetic leg, ground reaction forces were smaller and spanned fewer directions. Interpretation Deficits in balance control among individuals with transtibial limb loss may be due to their inability to use their prosthetic leg to generate forces that are equal in magnitude and direction to those of unimpaired adults. Targeting this force-generating deficit through technological or rehabilitation innovations may improve balance control.

Phase reversal of biomechanical functions and muscle activity in backward pedaling. Computer simulations of pedaling have shown that a wide range of pedaling tasks can be performed if each limb has the capability of executing six biomechanical functions, which are arranged into three pairs of alternating antagonistic functions. An Ext/Flex pair accelerates the limb into extension or flexion, a Plant/Dorsi pair accelerates the foot into plantarflexion or dorsiflexion, and an Ant/Post pair accelerates the foot anteriorly or posteriorly relative to the pelvis. Because each biomechanical function (i.e., Ext, Flex, Plant, Dorsi, Ant, or Post) contributes to crank propulsion during a specific region in the cycle, phasing of a muscle is hypothesized to be a consequence of its ability to contribute to one or more of the biomechanical functions. Analysis of electromyogram (EMG) patterns has shown that this biomechanical framework assists in the interpretation of muscle activity in healthy and hemiparetic subjects during forward pedaling. Simulations show that backward pedaling can be produced with a phase shift of 180° in the Ant/Post pair. No phase shifts in the Ext/Flex and Plant/Dorsi pairs are then necessary. To further test whether this simple yet biomechanically viable strategy may be used by the nervous system, EMGs from 7 muscles in 16 subjects were measured during backward as well as forward pedaling. As predicted, phasing in vastus medialis (VM), tibialis anterior (TA), medial gastrocnemius (MG), and soleus (SL) were unaffected by pedaling direction, with VM and SL contributing to Ext, MG to Plant, and TA to Dorsi. In contrast, phasing in biceps femoris (BF) and semimembranosus (SM) were affected by pedaling direction, as predicted, compatible with their contribution to the directionally sensitive Post function. Phasing of rectus femoris (RF) was also affected by pedaling direction; however, its ability to contribute to the directionally sensitive Ant function may only be expressed in forward pedaling. RF also contributed significantly to the directionally insensitive Ext function in both forward and backward pedaling. Other muscles also appear to have contributed to more than one function, which was especially evident in backward pedaling (i.e., BF, SM, MG, and TA to Flex). We conclude that the phasing of only the Ant and Post biomechanical functions are directionally sensitive. Further, we suggest that task-dependent modulation of the expression of the functions in the motor output provides this biomechanics-based neural control scheme with the capability to execute a variety of lower limb tasks, including walking.

Although cats that have been spinalized can also be trained to stand and step with full weight support, directionally appropriate long-latency responses to perturbations are impaired, suggesting that these behaviors are mediated by distinct neural mechanisms. However, it remains unclear whether these responses reflect an attenuated postural response using the appropriate muscular coordination patterns for balance or are due to fundamentally different neural mechanisms such as increased muscular cocontraction or short-latency stretch responses. Here we used muscle synergy analysis on previously collected data to identify whether there are changes in the spatial organization of muscle activity for balance within an animal after spinalization. We hypothesized that the modular organization of muscle activity for balance control is disrupted by spinal cord transection. In each of four animals, muscle synergies were extracted from postural muscle activity both before and after spinalization with nonnegative matrix factorization. Muscle synergy number was reduced after spinalization in three animals and increased in one animal. However, muscle synergy structure was greatly altered after spinalization with reduced direction tuning, suggesting little consistent organization of muscle activity. Furthermore, muscle synergy recruitment was correlated to subsequent force production in the intact but not spinalized condition. Our results demonstrate that the modular structure of sensorimotor feedback responses for balance control is severely disrupted after spinalization, suggesting that the muscle synergies for balance control are not accessible by spinal circuits alone. Moreover, we demonstrate that spinal mechanisms underlying weight support are distinct from brain stem mechanisms underlying directional balance control.

Measured muscle activation patterns often vary significantly from musculoskeletal model predictions that use optimization to resolve redundancy. Although experimental muscle activity exhibits both inter- and intra-subject variability we lack adequate tools to quantify the biomechanical latitude that the nervous system has when selecting muscle activation patterns. Here, we identified feasible ranges of individual muscle activity during force production in a musculoskeletal model to quantify the degree to which biomechanical redundancy allows for variability in muscle activation patterns. In a detailed cat hindlimb model matched to the posture of three cats, we identified the lower and upper bounds on muscle activity in each of 31 muscles during static endpoint force production across different force directions and magnitudes. Feasible ranges of muscle activation were relatively unconstrained across force magnitudes such that only a few (0–13%) muscles were found to be truly ‘‘necessary’’ (e.g. exhibited non-zero lower bounds) at physiological force ranges. Most of the muscles were ‘‘optional’’, having zero lower bounds, and frequently had ‘‘maximal’’ upper bounds as well. Moreover, ‘‘optional’’ muscles were never selected by optimization methods that either minimized muscle stress, or that scaled the pattern required for maximum force generation. Therefore, biomechanical constraints were generally insufficient to restrict or specify muscle activation levels for producing a force in a given direction, and many muscle patterns exist that could deviate substantially from one another but still achieve the task. Our approach could be extended to identify the feasible limits of variability in muscle activation patterns in dynamic tasks such as walking.

Little is known about the integration of neural mechanisms for balance and locomotion. Muscle synergies have been studied independently in standing balance and walking, but not compared. Here, we hypothesized that reactive balance and walking are mediated by common set of lower-limb muscle synergies. In humans, we examined muscle activity during multidirectional support-surface perturbations during standing and walking, as well as unperturbed walking at two speeds. We show that most muscle synergies used in perturbations responses during standing were also used in perturbation responses during walking, suggesting common neural mechanisms for reactive balance across different contexts. We also show that most muscle synergies using in reactive balance were also used during unperturbed walking, suggesting that neural circuits mediating locomotion and reactive balance recruit a common set of muscle synergies to achieve task-level goals. Differences in muscle synergies across conditions reflected differences in the biomechanical demands of the tasks. For example, muscle synergies specific to walking perturbations may reflect biomechanical challenges associated with single limb stance, and muscle synergies used during sagittal balance recovery in standing but not walking were consistent with maintaining the different desired center of mass motions in standing versus walking. Thus, muscle synergies specifying spatial organization of muscle activation patterns may define a repertoire of biomechanical subtasks available to different neural circuits governing walking and reactive balance and may be recruited based on task-level goals. Muscle synergy analysis may aid in dissociating deficits in spatial versus temporal organization of muscle activity in motor deficits. Muscle synergy analysis may also provide a more generalizable assessment of motor function by identifying whether common modular mechanisms are impaired across the performance of multiple motor tasks.

We hypothesized that motor outputs are hierarchically organized such that descending temporal commands based on desired task-level goals flexibly recruit muscle synergies that specify the spatial patterns of muscle coordination that allow the task to be achieved. According to this hypothesis, it should be possible to predict the patterns of muscle synergy recruitment based on task-level goals. We demonstrated that the temporal recruitment of muscle synergies during standing balance control was robustly predicted across multiple perturbation directions based on delayed sensorimotor feedback of center of mass (CoM) kinematics (displacement, velocity, and acceleration). The modulation of a muscle synergy's recruitment amplitude across perturbation directions was predicted by the projection of CoM kinematic variables along the preferred tuning direction(s), generating cosine tuning functions. Moreover, these findings were robust in biphasic perturbations that initially imposed a perturbation in the sagittal plane and then, before sagittal balance was recovered, perturbed the body in multiple directions. Therefore, biphasic perturbations caused the initial state of the CoM to differ from the desired state, and muscle synergy recruitment was predicted based on the error between the actual and desired upright state of the CoM. These results demonstrate that that temporal motor commands to muscle synergies reflect task-relevant error as opposed to sensory inflow. The proposed hierarchical framework may represent a common principle of motor control across motor tasks and levels of the nervous system, allowing motor intentions to be transformed into motor actions.

We developed wavelet-based functional ANOVA (wfANOVA) as a novel approach for comparing neurophysiological signals that are functions of time. Temporal resolution is often sacrificed by analyzing such data in large time bins, increasing statistical power by reducing the number of comparisons. We performed ANOVA in the wavelet domain because differences between curves tend to be represented by a few temporally localized wavelets, which we transformed back to the time domain for visualization. We compared wfANOVA and ANOVA performed in the time domain (tANOVA) on both experimental electromyographic (EMG) signals from responses to perturbation during standing balance across changes in peak perturbation acceleration (3 levels) and velocity (4 levels) and on simulated data with known contrasts. In experimental EMG data, wfANOVA revealed the continuous shape and magnitude of significant differences over time without a priori selection of time bins. However, tANOVA revealed only the largest differences at discontinuous time points, resulting in features with later onsets and shorter durations than those identified using wfANOVA ( P < 0.02). Furthermore, wfANOVA required significantly fewer (∼¼×; P < 0.015) significant F tests than tANOVA, resulting in post hoc tests with increased power. In simulated EMG data, wfANOVA identified known contrast curves with a high level of precision ( r2 = 0.94 ± 0.08) and performed better than tANOVA across noise levels ( P <

The modular control of muscles in groups, often referred to as muscle synergies, has been proposed to provide a motor repertoire of actions for the robust control of movement. However, it is not clear whether muscle synergies identified in one task are also recruited by different neural pathways subserving other motor behaviors. We tested the hypothesis that voluntary and reactive modifications to walking in humans result from the recruitment of locomotor muscle synergies. We recorded the activity of 16 muscles in the right leg as subjects walked a 7.5 m path at two different speeds. To elicit a second motor behavior, midway through the path we imposed ramp and hold translation perturbations of the support surface in each of four cardinal directions. Variations in the temporal recruitment of locomotor muscle synergies could account for cycle-by-cycle variations in muscle activity across strides. Locomotor muscle synergies were also recruited in atypical phases of gait, accounting for both anticipatory gait modifications before perturbations and reactive feedback responses to perturbations. Our findings are consistent with the idea that a common pool of spatially fixed locomotor muscle synergies can be recruited by different neural pathways, including the central pattern generator for walking, brainstem pathways for balance control, and cortical pathways mediating voluntary gait modifications. Together with electrophysiological studies, our work suggests that muscle synergies may provide a library of motor subtasks that can be flexibly recruited by parallel descending pathways to generate a variety of complex natural movements in the upper and lower limbs.

Stability is fundamental to the performance of terrestrial locomotion. Running cockroaches met the criteria for static stability over a wide range of speeds, yet several locomotor variables changed in a way that revealed an increase in the importance of dynamic stability as speed increased. Duty factors (the fraction of time that a leg spends on the ground relative to the stride period) decreased to 0.5 and below with an increase in speed. The duration of double support (i.e. when both tripods, or all six legs, were on the ground) decreased significantly with an increase in speed. All legs had similar touch-down phases in the tripod, but the shortest leg, the front one, lifted off before the middle and the rear leg, so that only two legs of the tripod were in contact with the ground at the highest speeds. Per cent stability margin (the shortest distance from the center of gravity to the boundaries of support, normalized to the maximum possible stability margin) decreased with increasing speed from 60% at 10 cm s−1 to values less than zero at speeds faster than 50 cm s−1, indicating instances of static instability at fast speeds. The center of mass moved rearward or posteriorly with respect to the base of support as speed increased. Moments about the center of mass, as shown by the center of pressure (the equivalent of a single ‘effective’ leg), were variable, but were balanced by opposing moments over a stride. Thus, hexapods can exploit the advantages of both static and dynamic stability. Static or quasi-static assumptions alone were insufficient to explain straight-ahead, constant-speed locomotion and may hinder discovery of behaviors that are dynamic, where kinetic energy and momentum can act as a bridge from one step to the next.

Muscle coordination may be difficult or impossible to predict accurately based on biomechanical considerations alone because of redundancy in the musculoskeletal system. Because many solutions exist for any given movement, the role of the nervous system in further constraining muscle coordination patterns for movement must be considered in both healthy and impaired motor control. On the basis of computational neuromechanical analyses of experimental data combined with modeling techniques, we have demonstrated several such neural constraints on the temporal and spatial patterns of muscle activity during both locomotion and postural responses to balance perturbations. We hypothesize that subject-specific and trial-by-trial differences in muscle activation can be parameterized and understood by a hierarchical and low-dimensional framework that reflects the neural control of task-level goals. In postural control, we demonstrate that temporal patterns of muscle activity may be governed by feedback control of task-level variables that represent the overall goal-directed motion of the body. These temporal patterns then recruit spatially-fixed patterns of muscle activity called muscle synergies that produce the desired task-level biomechanical functions that require multijoint coordination. Moreover, these principles apply more generally to movement, and in particular to locomotor tasks in both healthy and impaired individuals. Overall, understanding the goals and organization of the neural control of movement may provide useful reduced dimension parameter sets to address the degrees-of-freedom problem in musculoskeletal movement control. More importantly, however, neuromechanical analyses may lend insight and provide a framework for understanding subject-specific and trial-by-trial differences in movement across both healthy and motor-impaired populations.

Recent evidence suggests that complex spatiotemporal patterns of muscle activity can be explained with a low-dimensional set of muscle synergies or M-modes. While it is clear that both spatial and temporal aspects of muscle coordination may be low dimensional, constraints on spatial versus temporal features of muscle coordination likely involve different neural control mechanisms. We hypothesized that the low-dimensional spatial and temporal features of muscle coordination are independent of each other. We further hypothesized that in reactive feedback tasks, spatially fixed muscle coordination patterns—or muscle synergies—are hierarchically recruited via time-varying neural commands based on delayed task-level feedback. We explicitly compared the ability of spatially fixed (SF) versus temporally fixed (TF) muscle synergies to reconstruct the entire time course of muscle activity during postural responses to anterior-posterior support-surface translations. While both SF and TF muscle synergies could account for EMG variability in a postural task, SF muscle synergies produced more consistent and physiologically interpretable results than TF muscle synergies during postural responses to perturbations. Moreover, a majority of SF muscle synergies were consistent in structure when extracted from epochs throughout postural responses. Temporal patterns of SF muscle synergy recruitment were well-reconstructed by delayed feedback of center of mass (CoM) kinematics and reproduced EMG activity of multiple muscles. Consistent with the idea that independent and hierarchical low-dimensional neural control structures define spatial and temporal patterns of muscle activity, our results suggest that CoM kinematics are a task variable used to recruit SF muscle synergies for feedback control of balance.

Equivalent gaits may be present in pedestrians that differ greatly in leg number, leg design and skeletal type. Previous studies on ghost crabs found that the transition from a slow to a fast run may resemble the change from a trot to a gallop in quadrupedal mammals. One indication of the trot–gallop gait change in quadrupedal mammals is a distinct alteration in bone strain. To test the hypothesis that ghost crabs (Ocypode quadrata) change from a trot to a gallop, we measured in vivo strains of the meropodite of the second trailing leg with miniature strain gauges. Exoskeletal strains changed significantly (increased fivefold) during treadmill locomotion at the proposed trot–gallop transition. Maximum strains attained during galloping and jumping (1000×10−6–3000×10−6) were similar to the values reported for mammals. Comparison of the maximum load possible on the leg segment (caused by muscular tension) with the strength of the segment under axial loading revealed a safety factor of 2.7, which is similar to values measured for jumping and running mammals. Equivalent gaits may result from similarities in the operation of pedestrian locomotory systems.

Body stability and, to a greater extent, locomotion in animals involve complex nonlinear interactions between the body and its natural environment; therefore, in order to fully understand physiological movement strategies, we must first quantify the mechanical properties of muscles as they interact with the environment. The purpose of this study was to develop a closed-loop neuromechanical system that applies real-time control to couple an isolated muscle to a physical environment using a robotic device. Our model system consists of a modified four-bar linkage that facilitates variations in stance width and center of mass (CoM) position; a closed-loop control system that virtually embeds a frog muscle into the robot; and a custom compliant multielectrode array (MEA) that facilitates muscle stimulation. Here we demonstrate a very simplistic balance control mechanism using muscle co-contraction in order to validate our hybrid robot system. As was expected, the kinematics of the hybrid robot when subjected to lateral perturbation were representative of increasing stiffness of the hip joints as the amplitude of stimulation was increased. The system was also able to capture the nonlinear relationship between muscle force and length as well as between force and velocity, which can play an important role in balance. Our current system is limited, however, to embedding a single muscle at a time, which we found could produce undesirable asymmetry in the CoM position during perturbation. Although there is room for improvement, this work provides a useful proof-of-concept that lays a foundation for the development of future closed-loop neuromechanical systems.

To study the interaction between feedforward and feedback modes of postural control, we investigated postural responses during unexpected perturbations of the support surface that occurred during forward reaching in a standing position. We examined postural responses in lower limb muscles of nine human subjects. Baseline measures were obtained when subjects executed reaching movements to a target placed in front of them (R condition) and during postural responses to forward and backward support-surface perturbations (no reaching, P condition) during quiet stance. Perturbations were also given at different delays after the onset of reaching movements (RP conditions) as well as with the arm extended in the direction of the target, but not reaching (P/AE condition). Results showed that during perturbations to reaching (RP), the initial automatic postural response, occurring around 100 ms after the onset of perturbations, was relatively unchanged in latency or amplitude compared to control conditions (P and P/AE). However, longer latency postural responses were modulated to aid in the reaching movements during forward perturbations but not during backward perturbations. Our results suggest that the nervous system prioritizes the maintenance of a stable postural base during reaching, and that later components of the postural responses can be modulated to ensure the performance of the voluntary task.

Evidence suggests that the nervous system controls motor tasks using a low-dimensional modular organization of muscle activation. However, it is not clear if such an organization applies to coordination of human walking, nor how nervous system injury may alter the organization of motor modules and their biomechanical outputs. We first tested the hypothesis that muscle activation patterns during walking are produced through the variable activation of a small set of motor modules. In 20 healthy control subjects, EMG signals from eight leg muscles were measured across a range of walking speeds. Four motor modules identified through nonnegative matrix factorization were sufficient to account for variability of muscle activation from step to step and across speeds. Next, consistent with the clinical notion of abnormal limb flexion-extension synergies post-stroke, we tested the hypothesis that subjects with post-stroke hemiparesis would have altered motor modules, leading to impaired walking performance. In post-stroke subjects ( n = 55), a less complex coordination pattern was shown. Fewer modules were needed to account for muscle activation during walking at preferred speed compared with controls. Fewer modules resulted from merging of the modules observed in healthy controls, suggesting reduced independence of neural control signals. The number of modules was correlated to preferred walking speed, speed modulation, step length asymmetry, and propulsive asymmetry. Our results suggest a common modular organization of muscle coordination underlying walking in both healthy and post-stroke subjects. Identification of motor modules may lead to new insight into impaired locomotor coordination and the underlying neural systems.

Many-legged animals, such as crabs and cockroaches, utilize whole-body mechanics similar to that observed for running bipeds and trotting quadrupedal mammals. Despite the diversity in morphology, two legs in a quadrupedal mammal, three legs in an insect and four legs in a crab can function in the same way as one leg of a biped during ground contact. To explain how diverse leg designs can result in common whole-body dynamics, we used a miniature force platform to measure the ground reaction forces produced by individual legs of the cockroach Blaberus discoidalis. Hexapedal runners were not like quadrupeds with an additional set of legs. In trotting quadrupedal mammals each leg develops a similar ground reaction force pattern that sums to produce the whole-body pattern. At a constant average velocity, each leg pair of the cockroach was characterized by a unique ground reaction force pattern. The first leg decelerated the center of mass in the horizontal direction, whereas the third leg was used to accelerate the body. The second leg did both, much like legs in bipedal runners and quadrupedal trotters. Vertical force peaks for each leg were equal in magnitude. In general, peak ground reaction force vectors minimized joint moments and muscle forces by being oriented towards the coxal joints, which articulate with the body. Locomotion with a sprawled posture does not necessarily result in large moments around joints. Calculations on B. discoidalis showed that deviations from the minimum moments may be explained by considering the minimization of the summed muscle forces in more than one leg. Production of horizontal forces that account for most of the mechanical energy generated during locomotion can actually reduce total muscle force by directing the ground reaction forces through the leg joints. Whole-body dynamics common to two-, four-, six- and eight-legged runners is produced in six-legged runners by three pairs of legs that differ in orientation with respect to the body, generate unique ground reaction force patterns, but combine to function in the same way as one leg of a biped.

Recent research suggests that the nervous system controls muscles by activating flexible combinations of muscle synergies to produce a wide repertoire of movements. Muscle synergies are like building blocks, defining characteristic patterns of activation across multiple muscles that may be unique to each individual, but perform similar functions. The identification of muscle synergies has strong implications for the organization and structure of the nervous system, providing a mechanism by which task-level motor intentions are translated into detailed, low-level muscle activation patterns. Understanding the complex interplay between neural circuits and biomechanics that give rise to muscle synergies will be critical to advancing our understanding of neural control mechanisms for movement.

The simple act of standing up is an important and essential motor behavior that most humans and animals achieve with ease. Yet, maintaining standing balance involves complex sensorimotor transformations that must continually integrate a large array of sensory inputs and coordinate multiple motor outputs to muscles throughout the body. Multiple, redundant local sensory signals are integrated to form an estimate of a few global, task-level variables important to postural control, such as body center of mass (CoM) position and body orientation with respect to Earth-vertical. Evidence suggests that a limited set of muscle synergies, reflecting preferential sets of muscle activation patterns, are used to move task-variables such as CoM position in a predictable direction following postural perturbations. We propose a hierarchical feedback control system that allows the nervous system the simplicity of performing goal-directed computations in task-variable space, while maintaining the robustness afforded by redundant sensory and motor systems. We predict that modulation of postural actions occurs in task-variable space, and in the associated transformations between the low-dimensional task-space and high-dimensional sensor and muscle spaces. Development of neuromechanical models that reflect these neural transformations between low- and high-dimensional representations will reveal the organizational principles and constraints underlying sensorimotor transformations for balance control, and perhaps motor tasks in general. This framework and accompanying computational models could be used to formulate specific hypotheses about how specific sensory inputs and motor outputs are generated and altered following neural injury, sensory loss, or rehabilitation.

Postural control requires the coordination of multiple muscles to achieve both endpoint force production and postural stability. Multiple muscle activation patterns can produce the required force for standing, but the mechanical stability associated with any given pattern may vary, and has implications for the degree of delayed neural feedback necessary for postural stability. We hypothesized that muscular redundancy is reduced when muscle activation patterns are chosen with respect to intrinsic musculoskeletal stability as well as endpoint force production. We used a three-dimensional musculoskeletal model of the cat hindlimb with 31 muscles to determine the possible contributions of intrinsic muscle properties to limb stability during isometric force generation. Using dynamic stability analysis we demonstrate that within the large set of activation patterns that satisfy the force requirement for posture, only a reduced subset produce a mechanically stable limb configuration. Greater stability in the frontal-plane suggests that neural control mechanisms are more highly active for sagittal-plane and for ankle joint control. Even when the limb was unstable, the time-constants of instability were sufficiently great to allow long-latency neural feedback mechanisms to intervene, which may be preferential for movements requiring maneuverability versus stability. Local joint stiffness of muscles was determined by the stabilizing or destabilizing effects of moment-arm versus joint angle relationships. By preferentially activating muscles with high local stiffness, muscle activation patterns with feedforward stabilizing properties could be selected. Such a strategy may increase intrinsic postural stability without co-contraction, and may be useful criteria in the force-sharing problem.

Here we have identified a sensorimotor transformation that is used by a mammalian nervous system to produce a multijoint motor behavior. Using a simple biomechanical model, a delayed-feedback rule based on an optimal tradeoff between postural error and neural effort explained patterns of muscle activation in response to a sudden loss of balance in cats. Following the loss of large sensory afferents, changes in these muscle-activation patterns reflected an optimal reweighting of sensory feedback gains to minimize postural instability. Specifically, a loss of center-of-mass-acceleration information, which allowed for a rapid initial rise in the muscle activity in intact animals, was absent after large-fiber sensory neuropathy. Our results demonstrate that a simple and flexible neural feedback control strategy coordinates multiple muscles over time via a small set of extrinsic, task-level variables during complex multijoint natural movements.

We recently demonstrated that a set of five functional muscle synergies were sufficient to characterize both hindlimb muscle activity and active forces during automatic postural responses in cats standing at multiple postural configurations. This characterization depended critically upon the assumption that the endpoint force vector (synergy force vector) produced by the activation of each muscle synergy rotated with the limb axis as the hindlimb posture varied in the sagittal plane. Here, we used a detailed, 3D static model of the hindlimb to confirm that this assumption is biomechanically plausible: as we varied the model posture, simulated synergy force vectors rotated monotonically with the limb axis in the parasagittal plane (r2 = 0.94 ± 0.08). We then tested whether a neural strategy of using these five functional muscle synergies provides the same force-generating capability as controlling each of the 31 muscles individually. We compared feasible force sets (FFS) from the model with and without a muscle synergy organization. FFS volumes were significantly reduced with the muscle synergy organization (F = 1556.01, p ≪ 0.01), and as posture varied, the synergy-limited FFSs changed in shape, consistent with changes in experimentally-measured active forces. In contrast, nominal FFS shapes were invariant with posture, reinforcing prior findings that postural forces cannot be predicted by hindlimb biomechanics alone. We propose that an internal model for postural force generation may coordinate functional muscle synergies that are invariant in intrinsic limb coordinates, and this reduced-dimension control scheme reduces the set of forces available for postural control.

Although the balance difficulties accompanying vestibular loss are well known, the underlying cause remains unclear. We examined the role of vestibular inputs in the automatic postural response (APR) to pitch and roll rotations of the support surface in freely standing cats before and in the first week after bilateral labyrinthectomy. Support surface rotations accelerate the body center of mass toward the downhill side. The normal APR consists of inhibition in the extensors of the uphill limbs and excitation in the downhill limbs to decelerate the body and maintain the alignment of the limbs with respect to earth-vertical. After vestibular lesion, cats were unstable during rotation perturbations and actively pushed themselves downhill rather than uphill, using a postural response that was opposite to that seen in the control trials. The extensors of the uphill rather than downhill limbs were activated, whereas those of the downhill limbs were inhibited rather than being excited. We propose that vestibular inputs provide an important reference to earth-vertical, which is critical to computing the appropriate postural response during active orientation to the vertical. In the absence of this vestibular information, subjects orient to the support surface using proprioceptive inputs, which drives the body downhill resulting in instability and falling. This is consistent with current models of sensory integration for computation of body posture and orientation.

The biomechanical principles underlying the organization of muscle activation patterns during standing balance are poorly understood. The goal of this study was to understand the influence of biomechanical inter-joint coupling on endpoint forces and accelerations induced by the activation of individual muscles during postural tasks. We calculated induced endpoint forces and accelerations of 31 muscles in a 7 degree-of-freedom, three-dimensional model of the cat hindlimb. To test the effects of inter-joint coupling, we systematically immobilized the joints (excluded kinematic degrees of freedom) and evaluated how the endpoint force and acceleration directions changed for each muscle in 7 different conditions. We hypothesized that altered inter-joint coupling due to joint immobilization of remote joints would substantially change the induced directions of endpoint force and acceleration of individual muscles. Our results show that for most muscles crossing the knee or the hip, joint immobilization altered the endpoint force or acceleration direction by more than 90 degrees in the dorsal and sagittal planes. Induced endpoint forces were typically consistent with behaviorally observed forces only when the ankle was immobilized. We then activated a proximal muscle simultaneous with an ankle torque of varying magnitude, which demonstrated that the resulting endpoint force or acceleration direction is modulated by the magnitude of the ankle torque. We argue that this simple manipulation can lend insight into the functional effects of co-activating muscles. We conclude that inter-joint coupling may be an essential biomechanical principle underlying the coordination of proximal and distal muscles to produce functional endpoint actions during motor tasks.

Our long-term goal is to enable a robot to engage in partner dance for use in rehabilitation therapy, assessment, diagnosis, and scientific investigations of two-person whole-body motor coordination. Partner dance has been shown to improve balance and gait in people with Parkinson's disease and in older adults, which motivates our work. During partner dance, dance couples rely heavily on haptic interaction to convey motor intent such as speed and direction. In this paper, we investigate the potential for a wheeled mobile robot with a human-like upper-body to perform partnered stepping with people based on the forces applied to its end effectors. Blindfolded expert dancers (N=10) performed a forward/backward walking step to a recorded drum beat while holding the robot's end effectors. We varied the admittance gain of the robot's mobile base controller and the stiffness of the robot's arms. The robot followed the participants with low lag (M=224, SD=194 ms) across all trials. High admittance gain and high arm stiffness conditions resulted in significantly improved performance with respect to subjective and objective measures. Biomechanical measures such as the human hand to human sternum distance, center-of-mass of leader to center-of-mass of follower (CoM-CoM) distance, and interaction forces correlated with the expert dancers' subjective ratings of their interactions with the robot, which were internally consistent (Cronbach's α=0.92). In response to a final questionnaire, 1/10 expert dancers strongly agreed, 5/10 agreed, and 1/10 disagreed with the statement "The robot was a good follower." 2/10 strongly agreed, 3/10 agreed, and 2/10 disagreed with the statement "The robot was fun to dance with." The remaining participants were neutral with respect to these two questions.

We demonstrate that a limited number of muscle synergies can be used to reconstruct complex muscle activation patterns and forces produced during two types of postural perturbations. Our results suggest that low-dimension neural command signals may activate muscle synergies to produce high-dimension muscle activation patterns. Furthermore, muscle synergies may be used to coordinate multijoint muscle actions for the control of high-level task variables. Muscle synergies may represent natural building blocks for motor behaviors and provide insight into neuroengineered strategies for motor rehabilitation

Pretibial flexor motoneurons were recorded intracellularly in anesthetized cats during unfused isometric contractions of a subpopulation of motor units from either tibialis anterior (TA) or extensor digitorum longus (EDL) muscles. The contractions elicited excitatory postsynaptic potentials in 23 of 28 pretibial flexor motoneurons. No effect was observed in the remaining motoneurons. In control experiments, the effects of electrical stimulation of afferents within the TA nerve were investigated to help identify afferents responsible for the contraction-induced positive feedback. This feedback was ascribed to actions of Ia fibers because the pattern of the contraction-induced excitatory potentials was consistent with the known pattern of Ia discharge; in control experiments, electrical stimulation of group I fibers elicited only monosynaptic excitatory potentials; and the distribution of both the contraction-induced positive feedback among motor nuclei as well as the electrically evoked Ia excitatory monosynaptic potentials were restricted to homonymous and synergic motoneurons. Observation of the Ia contraction-induced positive feedback was facilitated by the absence of Ib autogenic inhibition. This contraction-induced Ia excitatory feedback in ankle flexors might either reinforce Ia-induced reflexes when these muscles are lengthened or help to lift the leg over an obstacle.

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.

Physical interactions between patients and therapists during rehabilitation have served as motivation for the design of rehabilitation robots, yet we lack a fundamental understanding of the principles governing such human-human interactions (HHI). Here we review the literature and pose important open questions regarding sensorimotor interaction during HHI that could facilitate the design of human-robot interactions (HRI) and haptic interfaces for rehabilitation. Based on the goals of physical rehabilitation, three subcategories of sensorimotor interaction are identified: sensorimotor collaboration, sensorimotor assistance, and sensorimotor education. Prior research has focused primarily on sensorimotor collaboration and is generally limited to relatively constrained visuomotor tasks. Moreover, the mechanisms by which performance improvements are achieved during sensorimotor cooperation with haptic interaction remains unknown. We propose that the effects of role assignment, motor redundancy, and skill level in sensorimotor cooperation should be explicitly studied. Additionally, the importance of haptic interactions may be better revealed in tasks that do not require visual feedback. Finally, cooperative motor tasks that allow for motor improvement during solo performance to be examined may be particularly relevant for rehabilitation robotics. Identifying principles that guide human-human sensorimotor interactions may lead to the development of robots that can physically interact with humans in more intuitive and biologically inspired ways, thereby enhancing rehabilitation outcomes. Electronic supplementary material The online version of this article (doi:10.1186/1743-0003-11-142) contains supplementary material, which is available to authorized users.

The importance of bilateral sensorimotor signals in coordination of locomotion has been demonstrated in animals but is difficult to ascertain in humans due to confounding effects of mechanical transmission of forces between the legs (i.e., mechanical interleg coupling). In a previous pedaling study, by eliminating mechanical interleg coupling, we showed that muscle coordination of a unipedal task can be shaped by interlimb sensorimotor pathways. Interlimb neural pathways were shown to alter pedaling coordination as subjects pedaling unilaterally exhibited increased flexion-phase muscle activity compared with bilateral pedaling even though the task mechanics performed by the pedaling leg(s) in the unilateral and bilateral pedaling tasks were identical. To further examine the relationship between contralateral sensorimotor state and ipsilateral flexion-phase muscle coordination during pedaling, subjects in this study pedaled with one leg while the contralateral leg either generated an extensor force or relaxed as a servomotor either held that leg stationary or moved it in antiphase with the pedaling leg. In the presence of contralateral extensor force generation, muscle activity in the pedaling leg during limb flexion was reduced. Integrated electromyographic activity of the pedaling-leg hamstring muscles (biceps femoris and semimembranosus) during flexion decreased by 25–30%, regardless of either the amplitude of force generated by the nonpedaling leg or whether the leg was stationary or moving. In contrast, rectus femoris and tibialis anterior activity during flexion decreased only when the contralateral leg generated high rhythmic force concomitant with leg movement. The results are consistent with a contralateral feedforward mechanism triggering flexion-phase hamstrings activity and a contralateral feedback mechanism modulating rectus femoris and tibialis anterior activity during flexion. Because only muscles that contribute to flexion as a secondary function were observed, it is impossible to know whether the modulatory effect also acts on primary, unifunctional, limb flexors or is specific to multifunctional muscles contributing to flexion. The influence of contralateral extensor-phase sensorimotor signals on ipsilateral flexion may reflect bilateral coupling of gain control mechanisms. More generally, these interlimb neural mechanisms may coordinate activity between muscles that perform antagonistic functions on opposite sides of the body. Because pedaling and walking share biomechanical and neuronal control features, these mechanisms may be operational in walking as well as pedaling.

Ting, Lena H., Christine C. Raasch, David A. Brown, Steven A. Kautz, and Felix E. Zajac. Sensorimotor state of the contralateral leg affects ipsilateral muscle coordination of pedaling. J. Neurophysiol. 80: 1341-1351, 1998. The objective of this study was to determine if independent central pattern generating elements controlling the legs in bipedal and unipedal locomotion is a viable theory for locomotor propulsion in humans. Coordinative coupling of the limbs could then be accomplished through mechanical interactions and ipsilateral feedback control rather than through central interlimb neural pathways. Pedaling was chosen as the locomotor task to study because interlimb mechanics can be significantly altered, as pedaling can be executed with the use of either one leg or two legs (cf. walking) and because the load on the limb can be well-controlled. Subjects pedaled a modified bicycle ergometer in a two-legged (bilateral) and a one-legged (unilateral) pedaling condition. The loading on the leg during unilateral pedaling was designed to be identical to the loading experienced by the leg during bilateral pedaling. This loading was achieved by having a trained human “motor” pedal along with the subject and exert on the opposite crank the torque that the subject's contralateral leg generated in bilateral pedaling. The human “motor” was successful at reproducing each subject's one-leg crank torque. The shape of the motor's torque trajectory was similar to that of subjects, and the amount of work done during extension and flexion was not significantly different. Thus the same muscle coordination pattern would allow subjects to pedal successfully in both the bilateral and unilateral conditions, and the afferent signals from the pedaling leg could be the same for both conditions. Although the overall work done by each leg did not change, an 86% decrease in retarding (negative) crank torque during limb flexion was measured in all 11 subjects during the unilateral condition. This corresponded to an increase in integrated electromyography of tibialis anterior (70%), rectus femoris (43%), and biceps femoris (59%) during flexion. Even given visual torque feedback in the unilateral condition, subjects still showed a 33% decrease in negative torque during flexion. These results are consistent with the existence of an inhibitory pathway from elements controlling extension onto contralateral flexion elements, with the pathway operating during two-legged pedaling but not during one-legged pedaling, in which case flexor activity increases. However, this centrally mediated coupling can be overcome with practice, as the human “motor” was able to effectively match the bilateral crank torque after a longer practice regimen. We conclude that the sensorimotor control of a unipedal task is affected by interlimb neural pathways. Thus a task performed unilaterally is not performed with the same muscle coordination utilized in a bipedal condition, even if such coordination would be equally effective in the execution of the unilateral task.

Optimality principles have been proposed as a general framework for understanding motor control in animals and humans largely based on their ability to predict general features movement in idealized motor tasks. However, generalizing these concepts past proof-of-principle to understand the neuromechanical transformation from task-level control to detailed execution-level muscle activity and forces during behaviorally-relevant motor tasks has proved difficult. In an unrestrained balance task in cats, we demonstrate that achieving task-level constraints center of mass forces and moments while minimizing control effort predicts detailed patterns of muscle activity and ground reaction forces in an anatomically-realistic musculoskeletal model. Whereas optimization is typically used to resolve redundancy at a single level of the motor hierarchy, we simultaneously resolved redundancy across both muscles and limbs and directly compared predictions to experimental measures across multiple perturbation directions that elicit different intra- and interlimb coordination patterns. Further, although some candidate task-level variables and cost functions generated indistinguishable predictions in a single biomechanical context, we identified a common optimization framework that could predict up to 48 experimental conditions per animal (n = 3) across both perturbation directions and different biomechanical contexts created by altering animals' postural configuration. Predictions were further improved by imposing experimentally-derived muscle synergy constraints, suggesting additional task variables or costs that may be relevant to the neural control of balance. These results suggested that reduced-dimension neural control mechanisms such as muscle synergies can achieve similar kinetics to the optimal solution, but with increased control effort (≈2×) compared to individual muscle control. Our results are consistent with the idea that hierarchical, task-level neural control mechanisms previously associated with voluntary tasks may also be used in automatic brainstem-mediated pathways for balance., Author Summary The nervous system has the ability to rapidly and flexibly coordinate many muscles and limbs to produce movements. This neuromechanical transformation must robustly achieve motor goals under the changing mechanics of the body and environment, and select one solution amongst many alternatives. What computational principles govern such decisions? Although optimality principles have predicted features of biological movement in simple models, here we show that this computational principle can robustly predict detailed experimental measures in an unrestrained, whole-body balance task. Detailed patterns of muscle activity and forces across multiple movement directions and body configurations were predicted based on interactions between musculoskeletal mechanics of the limbs, and task-level neural strategy of controlling the CoM mechanics while minimizing control effort. Moreover, similar muscle activity and forces were generated when muscles were coupled together in groups called muscle synergies, reducing the number of independent variables that are controlled. Our work is consistent with the idea that the nervous system may learn to coordinate muscles and limbs by minimizing effort in producing natural movements, and may use approximate solutions based on muscle synergies. Understanding such neural mechanisms may allow us to predict the effects of neural injury and disease on motor function.

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.

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.