Output units of motor behavior: an experimental and modeling study

Optimal Muscular Arrangement Using Genetic Algorithm for Musculoskeletal Potential Method with Muscle Viscosity

Muscle contractions (or equivalent mechanical elements) are responsible for joint movement in systems with musculoskeletal structure. Because muscles can only transmit force in the tensile direction in such systems, the internal force exists between the muscles. By utilizing the potential field generated by the internal force, the musculoskeletal potential method makes it possible to control the position without complex real-time calculations or sensory feedback by entering step-inputs of the balanced internal force at the target posture. However, the conditions of convergence to the target posture strongly depend on muscular arrangement. Previous studies have elucidated the mathematical conditions of the muscular arrangement; however, they provide sufficient conditions that must be satisfied by the muscular arrangement to converge to the target posture, which do not necessarily lead to optimal muscular arrangement conditions. This study proposes a method to determine the optimal muscular arrangement of a two-joint six-muscle system, wherein muscle viscosity is considered, that uses a genetic algorithm and an evaluation function considering the motion response time. The effect of the obtained muscular arrangement is verified in a simulation.

Quantal biomechanical effects in speech postures of the lips

The unique biomechanical and functional constraints on human speech make it a promising area for research investigating modular control of movement. The present article illustrates how a modular control approach to speech can provide insights relevant to understanding both motor control and observed variation across languages. We specifically explore the robust typological finding that languages produce different degrees of labial constriction using distinct muscle groupings and concomitantly distinct lip postures. Research has suggested that these lip postures exploit biomechanical regions of nonlinearity between neural activation and movement, also known as quantal regions, to allow movement goals to be realized despite variable activation signals. We present two sets of computer simulations showing that these labial postures can be generated under the assumption of modular control and that the corresponding modules are biomechanically robust: first to variation in the activation levels of participating muscles, and second to interference from surrounding muscles. These results provide support for the hypothesis that biomechanical robustness is an important factor in selecting the muscle groupings used for speech movements and provide insight into the neurological control of speech movements and how biomechanical and functional constraints govern the emergence of speech motor modules. We anticipate that future experimental work guided by biomechanical simulation results will provide new insights into the neural organization of speech movements.NEW & NOTEWORTHY This article provides additional evidence that speech motor control is organized in a modular fashion and that biomechanics constrain the kinds of motor modules that may emerge. It also suggests that speech can be a fruitful domain for the study of modularity and that a better understanding of speech motor modules will be useful for speech research. Finally, it suggests that biomechanical modeling can serve as a useful complement to experimental work when studying modularity.

The lumbar multifidus is characterised by larger type I muscle fibres compared to the erector spinae

The metabolic capacity of a muscle is one of the determinants of muscle function. Muscle fiber type characteristics give an indication about this metabolic capacity. Therefore it might be expected that the lumbar multifidus (MF) as a local stabilizer contains higher proportions of slow type I fibers, compared to the erector spinae (ES) as a global mobilizer. The aim of this study is to determine the muscle fiber characteristics of the ES and MF to provide insight into their structural and metabolic characteristics, and thereby the functional capacity of both muscles. Muscle fiber type characteristics in the ES and MF were investigated with an immunofluorescence staining of the myosin heavy chain isoforms. In both the ES and MF, type I muscle fibers are predominantly present. The cross-sectional area (CSA) of type I muscle fibers is significantly larger in the lumbar MF compared to the ES. However, the mean muscle fiber type percentage for type I was not significantly different, which resulted in an insignificant difference in relative cross-sectional area (RCSA) for type I. No significant differences were found for all other muscle fiber types. This may indicate that the MF displays muscle fiber type characteristics that tend to be more appropriate to maintain stability of the spine. However, because we could not demonstrate significant differences in RCSA between ES and MF, we cannot firmly state that there are functional differences between the ES an MF based only on structural characteristics.

How does the brain solve muscle redundancy? Filling the gap between optimization and muscle synergy hypotheses

The question of how the central nervous system coordinates redundant muscles has been a long-standing problem in motor neuroscience. The optimization hypothesis posits that the brain can select the muscle activation pattern that minimizes the motor effort cost from among many solutions that satisfy the requirements of the task. On the other hand, the muscle-synergy hypothesis proposes that neurally established functional groupings of muscles alleviate the computational burden associated with motor control and learning. Although the two hypotheses are not mutually exclusive, the relationship between them has not been well analyzed. This is probably because both hypotheses are formulated mathematically without a clear concept of their neural implementation. Here, we introduce a biologically plausible hypothesis ("the forgetting hypothesis") for how optimization is realized by a population of neurons. We further demonstrate that low-dimensional structure can be detected in an optimal network even if no muscle-synergies are explicitly assumed. Finally, we briefly discuss an inherent difficulty in testing the muscle-synergy hypothesis, which arises when population level optimization is assumed.

Synergy temporal sequences and topography in the spinal cord: evidence for a traveling wave in frog locomotion

Locomotion is produced by a central pattern generator. Its spinal cord organization is generally considered to be distributed, with more rhythmogenic rostral lumbar segments. While this produces a rostrocaudally traveling wave in undulating species, this is not thought to occur in limbed vertebrates, with the exception of the interneuronal traveling wave demonstrated in fictive cat scratching (Cuellar et al. J Neurosci 29:798-810, 2009). Here, we reexamine this hypothesis in the frog, using the seven muscle synergies A to G previously identified with intraspinal NMDA (Saltiel et al. J Neurophysiol 85:605-619, 2001). We find that locomotion consists of a sequence of synergy activations (A-B-G-A-F-E-G). The same sequence is observed when focal NMDA iontophoresis in the spinal cord elicits a caudal extension-lateral force-flexion cycle (flexion onset without the C synergy). Examining the early NMDA-evoked motor output at 110 sites reveals a rostrocaudal topographic organization of synergy encoding by the lumbar cord. Each synergy is preferentially activated from distinct regions, which may be multiple, and partially overlap between different synergies. Comparing the sequence of synergy activation in locomotion with their spinal cord topography suggests that the locomotor output is achieved by a rostrocaudally traveling wave of activation in the swing-stance cycle. A two-layer circuitry model, based on this topography and a traveling wave reproduces this output and explores its possible modifications under different afferent inputs. Our results and simulations suggest that a rostrocaudally traveling wave of excitation takes advantage of the topography of interneuronal regions encoding synergies, to activate them in the proper sequence for locomotion.

Speech function of the oropharyngeal isthmus: A modeling study

A finite element method (FEM) based numerical model of upper airway structures (jaw, tongue, maxilla, soft palate) was implemented to observe interactions between the soft palate and tongue, and in particular to distinguish the contributions of individual muscles in producing speech-relevant constrictions of the oropharyngeal isthmus (OPI), or "uvular" region of the oral tract. Simulations revealed a sphincter-like general operation for the OPI, particularly with regard to the function of the palatoglossus muscle. Further, as has been observed with the lips, the OPI can be controlled by multiple distinct muscular mechanisms, each reliably producing a different sized opening and robust to activation noise, suggestive of a modular view of speech motor control. As off-midline structures of the OPI are difficult to observe during speech production, biomechanical simulation offers a promising approach to studying these structures.

The neural origin of muscle synergies

Muscle synergies are neural coordinative structures that function to alleviate the computational burden associated with the control of movement and posture. In this commentary, we address two critical questions: the explicit encoding of muscle synergies in the nervous system, and how muscle synergies simplify movement production. We argue that shared and task-specific muscle synergies are neurophysiological entities whose combination, orchestrated by the motor cortical areas and the afferent systems, facilitates motor control and motor learning.

Muscle synergies in neuroscience and robotics: from input-space to task-space perspectives

In this paper we review the works related to muscle synergies that have been carried-out in neuroscience and control engineering. In particular, we refer to the hypothesis that the central nervous system (CNS) generates desired muscle contractions by combining a small number of predefined modules, called muscle synergies. We provide an overview of the methods that have been employed to test the validity of this scheme, and we show how the concept of muscle synergy has been generalized for the control of artificial agents. The comparison between these two lines of research, in particular their different goals and approaches, is instrumental to explain the computational implications of the hypothesized modular organization. Moreover, it clarifies the importance of assessing the functional role of muscle synergies: although these basic modules are defined at the level of muscle activations (input-space), they should result in the effective accomplishment of the desired task. This requirement is not always explicitly considered in experimental neuroscience, as muscle synergies are often estimated solely by analyzing recorded muscle activities. We suggest that synergy extraction methods should explicitly take into account task execution variables, thus moving from a perspective purely based on input-space to one grounded on task-space as well.

Challenges and new approaches to proving the existence of muscle synergies of neural origin

Muscle coordination studies repeatedly show low-dimensionality of muscle activations for a wide variety of motor tasks. The basis vectors of this low-dimensional subspace, termed muscle synergies, are hypothesized to reflect neurally-established functional muscle groupings that simplify body control. However, the muscle synergy hypothesis has been notoriously difficult to prove or falsify. We use cadaveric experiments and computational models to perform a crucial thought experiment and develop an alternative explanation of how muscle synergies could be observed without the nervous system having controlled muscles in groups. We first show that the biomechanics of the limb constrains musculotendon length changes to a low-dimensional subspace across all possible movement directions. We then show that a modest assumption—that each muscle is independently instructed to resist length change—leads to the result that electromyographic (EMG) synergies will arise without the need to conclude that they are a product of neural coupling among muscles. Finally, we show that there are dimensionality-reducing constraints in the isometric production of force in a variety of directions, but that these constraints are more easily controlled for, suggesting new experimental directions. These counter-examples to current thinking clearly show how experimenters could adequately control for the constraints described here when designing experiments to test for muscle synergies—but, to the best of our knowledge, this has not yet been done.

How the brain and spinal cord control the body is a fundamental question of critical scientific and clinical importance. The preferred experimental approach to answer this question has been to infer the neural control strategy by analyzing recordings of muscle activity and limb mechanics collected while animals and people use their limbs. This has led to a popular, but not yet proven, hypothesis that the brain and spinal cord simplify the control of the numerous muscles by grouping them into few functional units called neural synergies. Our detailed experiments and simulations challenge the utility of this approach and the validity of its interpretation. We point out that mechanical constraints can also explain those experimental recordings. In particular, the anatomy of the limb combined with the type of tasks studied and analysis used, suffice to give the appearance of neural synergies. To be clear, we do not disprove the neural synergy hypothesis. Rather, in the tradition of scientific debate, by showing an alternative explanation to the available data we challenge the community and ourselves to design novel experiments and analyses to conclusively test that hypothesis by ruling out the confounds we point out.

Transducer and base compliance alter the in situ 6 dof force measured from muscle during an isometric contraction in a multi-joint limb

Although musculoskeletal models are commonly used, validating the muscle actions predicted by such models is often difficult. In situ isometric measurements are a possible solution. The base of the skeleton is immobilized and the endpoint of the limb is rigidly attached to a 6-axis force transducer. Individual muscles are stimulated and the resulting forces and moments recorded. Such analyses generally assume idealized conditions. In this study we have developed an analysis taking into account the compliances due to imperfect fixation of the skeleton, imperfect attachment of the force transducer, and extra degrees of freedom (dof) in the joints that sometimes become necessary in fixed end contractions. We use simulations of the rat hindlimb to illustrate the consequences of such compliances. We show that when the limb is overconstrained, i.e., when there are fewer dof within the limb than are restrained by the skeletal fixation, the compliances of the skeletal fixation and of the transducer attachment can significantly affect measured forces and moments. When the limb dofs and restrained dofs are matched, however, the measured forces and moments are independent of these compliances. We also show that this framework can be used to model limb dofs, so that rather than simply omitting dofs in which a limb does not move (e.g., abduction at the knee), the limited motion of the limb in these dofs can be more realistically modeled as a very low compliance. Finally, we discuss the practical implications of these results to experimental measurements of muscle actions.

Estimation of musculoskeletal models from in situ measurements of muscle action in the rat hindlimb

Musculoskeletal models are often created by making detailed anatomical measurements of muscle properties. These measurements can then be used to determine the parameters of canonical models of muscle action. We describe here a complementary approach for developing and validating muscle models, using in situ measurements of muscle actions. We characterized the actions of two rat hindlimb muscles: the gracilis posticus (GRp) and the posterior head of biceps femoris (BFp; excluding the anterior head with vertebral origin). The GRp is a relatively simple muscle, with a circumscribed origin and insertion. The BFp is more complex, with an insertion distributed along the tibia. We measured the six-dimensional isometric forces and moments at the ankle evoked from stimulating each muscle at a range of limb configurations. The variation of forces and moments across the workspace provides a succinct characterization of muscle action. We then used this data to create a simple muscle model with a single point insertion and origin. The model parameters were optimized to best explain the observed force-moment data. This model explained the relatively simple muscle, GRp, very well (R(2)>0.85). Surprisingly, this simple model was also able to explain the action of the BFp, despite its greater complexity (R(2)>0.84). We then compared the actions observed here with those predicted using recently published anatomical measurements. Although the forces and moments predicted for the GRp were very similar to those observed here, the predictions for the BFp differed. These results show the potential utility of the approach described here for the development and refinement of musculoskeletal models based on in situ measurements of muscle actions.

Chapter 8--challenging the adaptive capacity of rhythmic movement control: from denervation to force field adaptation

The neural control of walking involves voluntary descending drive, automatic rhythm and pattern-generating circuits, and sensory feedback to produce appropriate motor output. This control system has to be both robust and adaptable to remain appropriately calibrated to the changes in body size and in environmental demands that occur throughout life. In this chapter, current experimental models that are used to study the adaptive capacity of rhythmic movement control will be presented. Overall, while walking is a complex movement requiring extremely well-timed muscle activation sequences, and considering the presence of automatic rhythm generating circuits, its neural control nevertheless shows a large potential for adaptive modification. Regardless if the need for motor output modification is of internal (e.g., denervations) or external (e.g., changes in environment dynamics) origin, the system copes with the challenge rapidly and efficiently. Neural structures involved in adaptation are distributed, and even reduced preparations such as low spinal cats show extensive adaptive capacity. The degree of adaptive capacity is not unlimited, however. Functional flexors cannot be turned into extensors, and vice versa. In addition, recent evidence suggest that adaptive capacity may be dependent on the timing in the movement where adaptation is required (phase dependency), some phases being more amendable to change than others. Clearly, while important progress has been achieved using denervations and motor adaptation protocols, many questions remain to be answered regarding the mechanisms underlying adaptation and retention of adapted motor output, as well as regarding how sensory inputs are used to trigger adaptation. Recent advances in robotics, together with the design of simple, yet clever protocols such as catch trials are very promising tools to provide more answers.

Chapter 7--interindividual variability and its implications for locomotor adaptation following peripheral nerve and/or spinal cord injury

Following injury to the nervous system, there is a range of possible functional outcomes that can only be partly explained by the extent of injury. Moreover, treatments effective in certain individuals might not work in others. Why such variability from one individual to another, in terms of functional outcomes and responsiveness to a given treatment following a similar injury? The answer to that question is not simple, and to begin to answer we must first consider that individuals of the same species can be quite variable in terms of neuronal circuit parameters involved in performing a given task. Interindividual variability can be subtle but the term "variability" in this chapter will be used to denote marked differences between individuals at the systems level (e.g., spinal reflexes, bursts of muscle activity, kinematics) during the same motor behavior, with an emphasis on locomotion. Injury to any level of the nervous system, in turn, can further compound this variability by altering spared neuronal connections. The aim of the present chapter is to (1) review studies that have investigated interindividual variability, (2) review studies that have described variable adaptive mechanisms following spinal and/or peripheral nerve lesions during locomotion, and (3) discuss the implications of intersubject variability for locomotor adaptation.

A simple experimentally based model using proprioceptive regulation of motor primitives captures adjusted trajectory formation in spinal frogs

Spinal circuits may organize trajectories using pattern generators and synergies. In frogs, prior work supports fixed-duration pulses of fixed composition synergies, forming primitives. In wiping behaviors, spinal frogs adjust their motor activity according to the starting limb position and generate fairly straight and accurate isochronous trajectories across the workspace. To test whether a compact description using primitives modulated by proprioceptive feedback could reproduce such trajectory formation, we built a biomechanical model based on physiological data. We recorded from hindlimb muscle spindles to evaluate possible proprioceptive input. As movement was initiated, early skeletofusimotor activity enhanced many muscle spindles firing rates. Before movement began, a rapid estimate of the limb position from simple combinations of spindle rates was possible. Three primitives were used in the model with muscle compositions based on those observed in frogs. Our simulations showed that simple gain and phase shifts of primitives based on published feedback mechanisms could generate accurate isochronous trajectories and motor patterns that matched those observed. Although on-line feedback effects were omitted from the model after movement onset, our primitive-based model reproduced the wiping behavior across a range of starting positions. Without modifications from proprioceptive feedback, the model behaviors missed the target in a manner similar to that in deafferented frogs. These data show how early proprioception might be used to make a simple estimate initial limb state and to implicitly plan a movement using observed spinal motor primitives. Simulations showed that choice of synergy composition played a role in this simplicity. To generate froglike trajectories, a hip flexor synergy without sartorius required motor patterns with more proprioceptive knee flexor control than did patterns built with a more natural synergy including sartorius. Such synergy choices and control strategies may simplify the circuitry required for reflex trajectory construction and adaptation.

Individual premotor drive pulses, not time-varying synergies, are the units of adjustment for limb trajectories constructed in spinal cord

Complex actions may arise by combining simple motor primitives. Our studies support individual premotor drive pulses or bursts as execution primitives in spinal cord. Alternatively, the fundamental execution primitives at the segmental level could be time-varying synergies. To distinguish these hypotheses, we examined sensory feedback effects during targeted wiping organized in spinal cord. This behavior comprises three bursts. We tested (1) whether feedback altered the structure of individual premotor drive bursts or primitives, and (2) whether feedback differentially modulated different drive bursts or pulses in the three burst sequence. At least two of the three bursts would need to always be comodulated to support a time-varying synergy. We used selective muscle vibration to control spindle feedback from a single muscle (biceps/iliofibularis). The structures of premotor drive bursts were conserved. However, biceps vibration (1) scaled the amplitudes of two bursts coactivated during the initial phase of wiping independently of one another without altering their phase, and (2) independently phase regulated the third burst but preserved its amplitude. Thus, all three bursts were regulated separately. Durations were unaffected. The independent effects depended on (1) time of vibration during wiping, (2) frequency of vibration, and (3) limb configuration. Because each of the three bursts was independently modulated, these data strongly support execution using individual premotor bursts rather than time-varying synergies at the spinal level of motor organization. Our data show that both sensory feedback and central systems of the spinal cord act in concert to adjust the individual premotor bursts in support of the straight and unimodal wiping trajectory.

Functional muscle synergies constrain force production during postural tasks

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 (FFSs) 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.

Learning effects on muscle modes and multi-mode postural synergies

We used the framework of the uncontrolled manifold hypothesis to explore the effects of practice on the composition of muscle groups (M-modes) and multi-M-mode synergies stabilizing the location of the center of pressure (COP). In particular, we tested a hypothesis that practice could lead to a transition from co-contraction muscle activation patterns to reciprocal patterns. We also tested a hypothesis that new sets of M-modes would form stronger synergies stabilizing COP location. Subjects practiced load release tasks for five days while standing on a board with a narrow support surface (unstable board). Their M-modes and indices of multi-M-mode synergies were computed during standing without instability and during standing on an unstable board before practice, in the middle of practice, and at the end of practice. During standing without instability, subjects showed two consistent M-modes uniting dorsal and ventral muscles of the body respectively (reciprocal modes). While standing on an unstable board, prior to practice, subjects commonly showed M-modes uniting muscle pairs with opposing actions at major leg joints-co-contraction modes. Such sets of M-modes failed to stabilize the COP location in the anterior-posterior direction. Practice led to better task performance reflected in fewer incidences of lost balance. This was accompanied by a drop in the occurrence of co-contraction M-modes and the emergence of multi-mode synergies stabilizing the COP location. We conclude that the central nervous system uses flexible sets of elemental variables (modes) to ensure stable trajectories of important performance variables (such as COP location). Practice can lead to adjustments in both the composition of M-modes and M-mode co-variation patterns resulting in stronger synergies stabilizing COP location.

Role of biomechanics and muscle activation strategy in the production of endpoint force patterns in the cat hindlimb

We used a musculoskeletal model of the cat hindlimb to compare the patterns of endpoint forces generated by all possible combination of 12 hindlimb muscles under three different muscle activation rules: homogeneous activation of muscles based on uniform activation levels, homogeneous activation of muscles based on uniform (normalized) force production, and activation based on the topography of spinal motoneuron pools. Force patterns were compared with the patterns obtained experimentally by microstimulation of the lumbar spinal cord in spinal intact cats. Magnitude and orientation of the force patterns were compared, as well as the proportion of the types found, and the proportions of patterns exhibiting points of zero force (equilibrium points). The force patterns obtained with the homogenous activation and motoneuron topography models were quite similar to those measured experimentally, with the differences being larger for the patterns from the normalized endpoint forces model. Differences in the proportions of types of force patterns between the three models and the experimental results were significant for each model. Both homogeneous activation and normalized endpoint force models produced similar proportions of equilibrium points as found experimentally. The results suggest that muscle biomechanics play an important role in limiting the number of endpoint force pattern types, and that muscle combinations activated at similar levels reproduced best the experimental results obtained with intraspinal microstimulation.

Muscle modes and synergies during voluntary body sway

We studied the coordination of muscle activity during voluntary body sway performed by human subjects at different frequencies. Subjects stood on the force platform and performed cyclic shifts of the center of pressure (COP) while being paced by the metronome. A major question was: does the makeup of muscle synergies and their ability to assure reproducible sway trajectory vary with the speed of the sway? Principal component analysis was used to identify three muscle groups (M-modes) within the space of integrated indices of muscle activity. M-mode vectors were similar across both subjects and sway frequencies. There were also similar relations between changes in the magnitudes of all three M-modes and COP shifts (the Jacobians) across the sway frequencies. Variance in the M-mode space across sway cycles was partitioned into two components, one that did not affect the average value of COP shift ("good variance") and the other that did. An index (DeltaV) was computed reflecting the relative amount of the "good variance"; this index has been interpreted as reflecting a multi-M-mode synergy stabilizing the COP trajectory. The average value of DeltaV was similar across all sway frequencies; DeltaV showed a within-a-cycle modulation at low but not at high sway frequencies. The modulation was mostly due to variations in the "good variance". We conclude that muscle modes and their mapping on COP shifts are robust across a wide range of rates of COP shifts. Multi-M-mode synergies stabilize COP shifts (assure its reproducibility) within a wide range of its speeds, but only during cyclic COP changes. Taken together with earlier studies that showed weak or absent multi-M-mode synergies during fast discrete COP shifts, the results suggest a basic difference between the neural control assuring stability of steady-state processes (postural or oscillatory) and transient processes (such as discrete actions). Current results provide the most comprehensive support for the notion of multi-M-mode synergies stabilizing time profiles of important performance variables in motor tasks involving large muscle groups.

Dimensional reduction in sensorimotor systems: a framework for understanding muscle coordination of posture

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.

Changes in muscle coordination with training

Three core concepts, activity-dependent coupling, the composition of muscle synergies, and Hebbian adaptation, are discussed with a view to illustrating the nature of the constraints imposed by the organization of the central nervous system on the changes in muscle coordination induced by training. It is argued that training invoked variations in the efficiency with which motor actions can be generated influence the stability of coordination by altering the potential for activity-dependent coupling between the cortical representations of the focal muscles recruited in a movement task and brain circuits that do not contribute directly to the required behavior. The behaviors that can be generated during training are also constrained by the composition of existing intrinsic muscle synergies. In circumstances in which attempts to produce forceful or high velocity movements would otherwise result in the generation of inappropriate actions, training designed to promote the development of control strategies specific to the desired movement outcome may be necessary to compensate for protogenic muscle recruitment patterns. Hebbian adaptation refers to processes whereby, for neurons that release action potentials at the same time, there is an increased probability that synaptic connections will be formed. Neural connectivity induced by the repetition of specific muscle recruitment patterns during training may, however, inhibit the subsequent acquisition of new skills. Consideration is given to the possibility that, in the presence of the appropriate sensory guidance, it is possible to gate Hebbian plasticity and to promote greater subsequent flexibility in the recruitment of the trained muscles in other task contexts.

Animal Models for Studying Potential Training Strategies in Persons with Spinal Cord Injury

In the late 1980s, it was clearly demonstrated that adult spinal cats can be re-trained to walk after a complete spinal cord transection, using treadmill training. This has led to profound changes in the rehabilitation of persons with spinal cord injury. The use of animal models to study training-induced locomotor plasticity after spinal cord injury has expanded since this original demonstration. The goal of the present review is to summarize findings obtained with these animal models that may be of relevance to the re-training of humans with spinal cord injury. From the complete spinal cord transection models, adaptive capacity, retention of training, task-specificity, role of cutaneous inputs, effect of training with robotic devices, and spinal cord stimulation will be discussed. From the partial spinal lesion models, the effect of ventral or dorsal lesions of the cord will be presented. Finally, the effects of drugs on training will be compared between the complete and partial spinal lesions models.

Localization and connectivity in spinal interneuronal networks: the adduction-caudal extension-flexion rhythm in the frog

We have previously reported that focal intraspinal N-methyl-d-aspartate (NMDA) iontophoresis in the frog elicits a motor output, which is organized in terms of its constituent isometric force directions at the ipsilateral ankle and its topography. Furthermore, the associated EMG patterns can be reconstructed as the linear combinations of seven muscle synergies, labeled A to G. We now focus on one of the most common NMDA-elicited outputs, the adduction-caudal extension-flexion rhythm, and examine the relationship between the different force phases in terms of synergies and topography. Two distinct EMG patterns produce caudal extensions, and only one of the two patterns is used at most sites. The key synergy combinations for the two patterns are B + e and D + c (strongest synergies capitalized). These two patterns map at distinct locations in the lumbar cord. Within individual sites rhythms, we find linkages among the synergies used to produce adductions, the onsets of flexions after caudal extensions, and the synergy pattern producing the caudal extensions. For example, the synergy composition of adductions at B + e caudal extension sites is dominated by E + b and at D + c caudal extension sites by C + d. The two types of adductions map at distinct locations, situated between the two caudal extension regions. Specifically the linked patterns of caudal extension-adduction interleave rostrocaudally in a CE2-ADD1-ADD2-CE1 sequence, where 1 and 2 refer to the two pattern types. The implications of this topography and connectivity with respect to motor systems organization and behaviors are discussed.

Motor control: basic units of cortical output?

Observing movement evoked by stimulating a single cortical neuron has proven technically impossible - until now. A new study using intracellular stimulation has revealed that the basic unit of cortical output is not necessarily basic.

Muscle synergies encoded within the spinal cord: evidence from focal intraspinal NMDA iontophoresis in the frog

This paper relates to the problem of the existence of muscle synergies, that is whether the CNS command to muscles is simplified by controlling their activity in subgroups or synergies, rather than individually. We approach this problem with two methods that have been recently introduced: intraspinal N-methyl-D-aspartate (NMDA) microstimulation and a synergy-extracting algorithm. To search for a common set of synergies encoded for by the spinal cord whose combinations would account for a large range of electromyographic (EMG) patterns, we chose, rather than examining a large range of natural behaviors, to chemically microstimulate a large number of spinal cord interneuronal sites in different frogs. A possible advantage of this complementary method is that it is task-independent. Visual inspection suggested that the NMDA-elicited EMG patterns recorded from 12 leg muscles might indeed be constructed from smaller subgroups of muscles whose activity co-varied, suggestive of synergies. We used a modification of our extracting computational algorithm whereby a nonnegative least-squares method was employed to iteratively update both the synergies and their coefficients of activation in reconstructing the EMG patterns. Using this algorithm, a limited set of seven synergies was found whose linear combinations accounted for more than 91% of the variance in the pooled EMG data from 10 frogs, and more than 96% in individual frogs. The extracted synergies were similar among frogs. Further, preferred combinations of these synergies were clearly identified. This was found by extracting smaller sets of four, five, or six synergies and fitting each synergy from those sets as a combination from the set of seven synergies extracted from the same frog; the synergy combinations from each frog were then pooled together to examine their frequency of occurrence. Concordance with this method of identifying synergy combinations was found by examining how the synergies from the set of seven correlated pair-wise as they reconstructed the EMG data. These results support the existence of muscle synergies encoded within the spinal cord, which through preferred combinations, account for a large repertoire of spinal cord motor output. These findings are contrasted with previous approaches to the problem of synergies.

Functional rewiring of brain and spinal cord after injury: the three Rs of neural repair and neurological rehabilitation

Gains in the use of the upper extremities and in walking after brain and spinal cord injury or stroke depend especially upon the effectiveness of spared sensorimotor nodes in the networks for motor control. Biological interventions for neural repair and motor recovery may involve strategies that replace cells or signalling molecules and stimulate the regrowth of axons. The greatest success of these interventions will depend upon the functional incorporation of spared and new cells and their processes into motor networks. The distributed and modular organization of the motor neurons of the cortex and spinal cord offer a substrate that arranges or represents particular patterns of movement, yet is highly adaptable to training. Neurological impairments and related disabilities can be reduced through rehabilitative retraining protocols that engage these critical components of the sensorimotor network to promote use-dependent adaptations and functional rewiring.

New perspectives on spinal motor systems

The production and control of complex motor functions are usually attributed to central brain structures such as cortex, basal ganglia and cerebellum. In traditional schemes the spinal cord is assigned a subservient function during the production of movement, playing a predominantly passive role by relaying the commands dictated to it by supraspinal systems. This review challenges this idea by presenting evidence that the spinal motor system is an active participant in several aspects of the production of movement, contributing to functions normally ascribed to 'higher' brain regions.

Rapid correction of aimed movements by summation of force-field primitives

Spinal circuits form building blocks for movement construction. In the frog, such building blocks have been described as isometric force fields. Microstimulation studies showed that individual force fields can be combined by vector summation. Summation and scaling of a few force-field types can, in theory, produce a large range of dynamic force-field structures associated with limb behaviors. We tested for the first time whether force-field summation underlies the construction of real limb behavior in the frog. We examined the organization of correction responses that circumvent path obstacles during hindlimb wiping trajectories. Correction responses were triggered on-line during wiping by cutaneous feedback signaling obstacle collision. The correction response activated a force field that summed with an ongoing sequence of force fields activated during wiping. Both impact force and time of impact within the wiping motor pattern scaled the evoked correction response amplitude. However, the duration of the correction response was constant and similar to the duration of other muscles activated in different phases of wiping. Thus, our results confirm that both force-field summation and scaling occur during real limb behavior, that force fields represent fixed-timing motor elements, and that these motor elements are combined in chains and in combination contingent on the interaction of feedback and central motor programs.