A central issue in motor control is how the central nervous system generates the muscle activity patterns necessary to achieve a variety of behavioral goals. The many degrees of freedom of the musculoskeletal apparatus provide great flexibility but make the control problem extremely complex. Muscle synergies--coherent activations, in space or time, of a group of muscles--have been proposed as building blocks that could simplify the construction of motor behaviors. To evaluate this hypothesis, we developed a new method to extract invariant spatiotemporal components from the simultaneous recordings of the activity of many muscles. We used this technique to analyze the muscle patterns of intact and unrestrained frogs during kicking, a natural defensive behavior. Here we show that combinations of three time-varying muscle synergies underlie the variety of muscle patterns required to kick in different directions, that the recruitment of these synergies is related to movement kinematics, and that there are similarities among the synergies extracted from different behaviors.

Learning a motor skill sets in motion neural processes that continue to evolve after practice has ended, a phenomenon known as consolidation. Here we present psychophysical evidence for this, and show that consolidation of a motor skill was disrupted when a second motor task was learned immediately after the first. There was no disruption if four hours elapsed between learning the two motor skills, with consolidation occurring gradually over this period. Previous studies in humans and other primates have found this time-dependent disruption of consolidation only in explicit memory tasks, which rely on brain structures in the medial temporal lobe. Our results indicate that motor memories, which do not depend on the medial temporal lobe, can be transformed by a similar process of consolidation. By extending the phenomenon of consolidation to motor memory, our results indicate that distinct neural systems share similar characteristics when encoding and storing new information.

The experimental findings herein reported are aimed at gaining a perspective on the complex neural events that follow lesions of the motor cortical areas. Cortical damage, whether by trauma or stroke, interferes with the flow of descending signals to the modular interneuronal structures of the spinal cord. These spinal modules subserve normal motor behaviors by activating groups of muscles as individual units (muscle synergies). Damage to the motor cortical areas disrupts the orchestration of the modules, resulting in abnormal movements. To gain insights into this complex process, we recorded myoelectric signals from multiple upper-limb muscles in subjects with cortical lesions. We used a factorization algorithm to identify the muscle synergies. Our factorization analysis revealed, in a quantitative way, three distinct patterns of muscle coordination-including preservation, merging, and fractionation of muscle synergies-that reflect the multiple neural responses that occur after cortical damage. These patterns varied as a function of both the severity of functional impairment and the temporal distance from stroke onset. We think these muscle-synergy patterns can be used as physiological markers of the status of any patient with stroke or trauma, thereby guiding the development of different rehabilitation approaches, as well as future physiological experiments for a further understanding of postinjury mechanisms of motor control and recovery.motor primitive | electromyography | neurorehabilitation | nonnegative matrix factorization | Virtual Reality Rehabilitation System

When the hand is displaced from an equilibrium posture by an external disturbance, a force is generated to restore the original position. We developed a new experimental method to measure and represent the field of elastic forces associated with posture of the hand in the horizontal plane. While subjects maintained a given posture, small displacements of the hand along different directions were delivered by torque motors. The hand was held in the displaced positions and, at that time, we measured the corresponding restoring forces before the onset of any voluntary reaction. The stiffness in the vicinity of the hand equilibrium position was estimated by analyzing the force and displacement vectors. We chose to represent the stiffness both numerically, as a matrix, and graphically, as an ellipse characterized by three parameters: magnitude (the area), shape (the ratio of axis) and orientation (direction of the major axis). The latter representation captures the main geometrical features of the elastic force field associated with posture. We also evaluated the conservative and nonconservative components of this elastic force field. We found that the former were much larger than the latter and concluded that the behavior of the neuromuscular system of the multiarticular arm is predominantly spring-like. Our data indicated that the shape and orientation of the stiffness were invariant over subjects and over time. We also investigated the ability of our subjects to produce voluntary and adaptive changes in the stiffness. Our findings indicated that, when a disturbance acting along a fixed and predictable direction was imposed, the magnitude of the stiffness was increased but only minor changes in shape and orientation occurred. Taken together, all of these experiments represent a step toward the understanding of the interactions between geometrical and neural factors involved in maintaining hand posture and its interactions with the environment.

Previous studies have suggested that the motor system may simplify control by combining a small number of muscle synergies represented as activation profiles across a set of muscles. The role of sensory feedback in the activation and organization of synergies has remained an open question. Here, we assess to what extent the motor system relies on centrally organized synergies activated by spinal and/or supraspinal commands to generate motor outputs by analyzing electromyographic (EMG) signals collected from 13 hindlimb muscles of the bullfrog during swimming and jumping, before and after deafferentation. We first established that, for both behaviors, the intact and deafferented data sets possess low and similar dimensionalities. Subsequently, we used a novel reformulation of the nonnegative matrix factorization algorithm to simultaneously search for synergies shared by, and synergies specific to, the intact and deafferented data sets. Most muscle synergies were identified as shared synergies, suggesting that EMGs of locomotor behaviors are generated primarily by centrally organized synergies. Both the amplitude and temporal patterns of the activation coefficients of most shared synergies, however, were altered by deafferentation, suggesting that sensory inflow modulates activation of those centrally organized synergies. For most synergies, effects of deafferentation on the activation coefficients were not consistent across frogs, indicating substantial interanimal variability of feedback actions. We speculate that sensory feedback might adapt recruitment of muscle synergies to behavioral constraints, and the few synergies specific to the intact or deafferented states might represent afferent-specific modules or feedback reorganization of spinal neuronal networks.

Production of voluntary movements relies critically on the functional integration of several motor cortical areas, such as the primary motor cortex, and the spinal circuitries. Surprisingly, after almost 40 years of research, how the motor cortices specify descending neural signals destined for the downstream interneurons and motoneurons has remained elusive. In light of the many recent experimental demonstrations that the motor system may coordinate muscle activations through a linear combination of muscle synergies, we hypothesize that the motor cortices may function to select and activate fixed muscle synergies specified by the spinal or brainstem networks. To test this hypothesis, we recorded electromyograms (EMGs) from 12-16 upper arm and shoulder muscles from both the unaffected and the stroke-affected arms of stroke patients having moderate-to-severe unilateral ischemic lesions in the frontal motor cortical areas. Analyses of EMGs using a nonnegative matrix factorization algorithm revealed that in seven of eight patients the muscular compositions of the synergies for both the unaffected and the affected arms were strikingly similar to each other despite differences in motor performance between the arms, and differences in cerebral lesion sizes and locations between patients. This robustness of muscle synergies that we observed supports the notion that descending cortical signals represent neuronal drives that select, activate, and flexibly combine muscle synergies specified by networks in the spinal cord and/or brainstem. Our conclusion also suggests an approach to stroke rehabilitation by focusing on those synergies with altered activations after stroke.motor control ͉ motor modules ͉ neurorehabilitation ͉ motor primitives ͉ electromyography

We used a computational analysis to identify the basic elements with which the vertebrate spinal cord constructs one complex behavior. This analysis extracted a small set of muscle synergies from the range of muscle activations generated by cutaneous stimulation of the frog hindlimb. The flexible combination of these synergies was able to account for the large number of different motor patterns produced by different animals. These results therefore demonstrate one strategy used by the vertebrate nervous system to produce movement in a computationally simple manner.

We investigated how human subjects adapt to forces perturbing the motion of their arms. We found that this kind of learning is based on the capacity of the central nervous system (CNS) METHODSWe tested 15 right-handed individuals, ranging in age from 18 to 35 years and with no known history of neuromotor disorders. Subjects were seated on a chair and instructed to grasp the handle of a robot manipulandum with their right hand (see Fig. 1A).They were asked to execute arm movements to targets displayed on a computer screen. They used the manipulandum to guide a cursor on the screen to the targets. Full visual feedback (target and cursor) was given during the experiment.In the first part of each experiment, subjects practiced movements until they achieved a stable performance (baseline) and the desired timing. Subsequently, the torque motors of the robot generated a programmed pattern of force perturbations. The programmed forces were proportional to the subject's hand velocity. An example of a perturbation pattern is shown in Fig. 1B, where the force exerted by the manipulandum is plotted as a function of the hand's velocity. Initially, the subjects' trajectories were highly distorted by this perturbation (Fig. 1D), but as training progressed, they recovered the baseline pattern (Fig. 1E). On random trials, no perturbation was applied, and compensatory trajectories, referred to as aftereffects, were observed (Fig. 1F).A quantitative study of the distortions in the trajectories was performed by analyzing the velocity profiles. We defined our measure of similarity, or correlation coefficient, as the inner product between the velocity profile of the baseline trajectory and the trajectory itself. The baseline trajectories were chosen among the unperturbed trajectories as those having the highest mean correlation coefficient with the other unperturbed trajectories. The average score for the trajectories in Fig. 1C was 0.97. Each trajectory during the experiment was then compared with the typical trajectory (1). RESULTSTo estimate the generalization of motor learning, we trained subjects over a region of the workspace and tested for evidence of adaptation by observing the aftereffects inside and outside this region.We asked subjects to execute movements to targets placed as shown in Fig. 1A. Fig. 2A shows the baseline trajectories