Andrea d’Avella

Microstimulation Activates a Handful of Muscle Synergies

Muscle synergies have been proposed as a mechanism to simplify movement control. Whether these coactivation patterns have any physiological reality within the nervous system remains unknown. Here we applied electrical microstimulation to motor cortical areas of rhesus macaques to evoke hand movements. Movements tended to converge toward particular postures, driven by synchronous bursts of muscle activity. Across stimulation sites, the muscle activations were reducible to linear sums of a few basic patterns-each corresponding to a muscle synergy evident in voluntary reach, grasp, and transport movements made by the animal. These synergies were represented nonuniformly over the cortical surface. We argue that the brain exploits these properties of synergies-postural equivalence, low dimensionality, and topographical representation-to simplify motor planning, even for complex hand movements.

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.

Identifying Muscle Synergies from EMG Decomposition: Approaches, Evidence, and Potential Application to Neurorehabilitation

Muscle synergies may simplify healthy motor control by allowing the generation of appropriate motor commands with a small number of parameters. Muscle synergies have been recently identified as basic control modules by decomposing electromyographic (EMG) signals. Here we present two EMG decomposition approaches, we review some of the experimental evidence for muscle synergies deriving from them, and we propose a potential application to neurorehabilitation.

Towards a Myoelectrically Controlled Virtual Reality Interface for Synergy-Based Stroke Rehabilitation

Recent studies endorse the use of robotic and virtual reality (VR) systems for rehabilitation. Myoelectric (EMG) signals have been used for prosthetic control but their application to rehabilitation has been limited so far. Here we present a novel approach using an EMG controlled VR interface to test the synergistic organization of the neural control of arm movements in healthy subjects. EMG control offers the possibility to manipulate visual feedback according to the subject’s muscle activity and to test effects of simulated interventions on the human neuromuscular system that are either compatible or incompatible with the synergies. Such EMG controlled VR interface may open up new possibilities for rehabilitation as it offers the possibility to provide assistance tailored to the individual changes in synergistic organization.

Intercepting virtual balls approaching under different gravity conditions: Evidence for spatial prediction

To accurately time motor responses when intercepting falling balls we rely on an internal model of gravity. However, whether and how such a model is also used to estimate the spatial location of interception is still an open question. Here we addressed this issue by asking 25 participants to intercept balls projected from a fixed location 6 m in front of them and approaching along trajectories with different arrival locations, flight durations, and gravity accelerations (0g and 1g). The trajectories were displayed in an immersive virtual reality system with a wide field of view. Participants intercepted approaching balls with a racket, and they were free to choose the time and place of interception. We found that participants often achieved a better performance with 1g than 0g balls. Moreover, the interception points were distributed along the direction of a 1g path for both 1g and 0g balls. In the latter case, interceptions tended to cluster on the upper half of the racket, indicating that participants aimed at a lower position than the actual 0g path. These results suggest that an internal model of gravity was probably used in predicting the interception locations. However, we found that the difference in performance between 1g and 0g balls was modulated by flight duration, the difference being larger for faster balls. In addition, the number of peaks in the hand speed profiles increased with flight duration, suggesting that visual information was used to adjust the motor response, correcting the prediction to some extent.NEW & NOTEWORTHY Here we show that an internal model of gravity plays a key role in predicting where to intercept a fast-moving target. Participants also assumed an accelerated motion when intercepting balls approaching in a virtual environment at constant velocity. We also show that the role of visual information in guiding interceptive movement increases when more time is available.

Evaluation of a Pose-Shared Synergy-Based Isometric Model for Hand Force Estimation: Towards Myocontrol

In this work the authors investigated whether the muscle synergies concept could improve the isometric hand force estimation. Electromyographic (EMG) activity from 9 arm muscles and hand forces applied at the Light-Exos Exoskeleton end-effector were recorded during isometric contractions in several workspace points lying on the parasagittal plane crossing the shoulder joint. The muscle synergies were extracted in two different ways according to the statements that the muscle primitives are ‘Arm Pose Related’ or ‘Arm Pose Shared’. From the pre-processed EMG signals the authors then estimated the hand forces using three methods. The results showed that the muscle synergy concept improves the isometric force estimation paving the way for a synergy-based myoelectric control.

Where Are You Throwing the Ball? I Better Watch Your Body, Not Just Your Arm!

The ability to intercept or avoid a moving object, whether to catch a ball, snatch one’s prey, or avoid the path of a predator, is a skill that has been acquired throughout evolution by many species in the animal kingdom. This requires processing early visual cues in order to program anticipatory motor responses tuned to the forthcoming event. Here, we explore the nature of the early kinematics cues that could inform an observer about the future direction of a ball projected with an unconstrained overarm throw. Our goal was to pinpoint the body segments that, throughout the temporal course of the throwing action, could provide key cues for accurately predicting the side of the outgoing ball. We recorded whole-body kinematics from twenty non-expert participants performing unconstrained overarm throws at four different targets placed on a vertical plane at 6 m distance. In order to characterize the spatiotemporal structure of the information embedded in the kinematics of the throwing action about the outgoing ball direction, we introduced a novel combination of dimensionality reduction and machine learning techniques. The recorded kinematics clearly shows that throwing styles differed considerably across individuals, with corresponding inter-individual differences in the spatio-temporal structure of the thrower predictability. We found that for most participants it is possible to predict the region where the ball hit the target plane, with an accuracy above 80%, as early as 400–500 ms before ball release. Interestingly, the body parts that provided the most informative cues about the action outcome varied with the throwing style and during the time course of the throwing action. Not surprisingly, at the very end of the action, the throwing arm is the most informative body segment. However, cues allowing for predictions to be made earlier than 200 ms before release are typically associated to other body parts, such as the lower limbs and the contralateral arm. These findings are discussed in the context of the sport-science literature on throwing and catching interactive tasks, as well as from the wider perspective of the role of sensorimotor coupling in interpersonal social interactions.

Changes in Muscle Synergy Organization After Neurological Lesions

The role of the cerebral cortex and the cerebellum in determining the spatiotemporal characteristics of the muscle activation patterns is still largely unknown. Recent studies suggest that the coordination of the muscles relies on flexible combinations of a few muscle synergies. We aim at gaining new insights on the neural organization of the muscle patterns for reaching by using multidimensional decomposition algorithms to identify muscle synergies in patients with damage to the cerebral cortex and to the cerebellum. Understanding the changes in the modular organization of the motor system after neurological lesions is highly relevant for upper limb rehabilitation because it may lead to the development of novel objective and quantitative indicators of motor impairment directly related to a specific pathophysiology.

Consistency of Myoelectric Control Across Multiple Sessions

A recent research line investigates the motor control adaptation after the perturbation of the muscle pulling directions, simulated with myoelectric control of an isometric reaching task in virtual reality. Such perturbations rely on an estimation of the mapping between the electromyographic (EMG) signal of recorded muscles and the end-point forces. However, the consistency of this mapping across sessions performed in different days is not known. In this study we tested the consistency of the EMG-to-force mapping recorded on multiple sessions in different days. We also tested the consistency of the EMG-to-force mapping after subject posture changes and accidental EMG electrodes detachment. A good consistency was identified when all the EMG recordings are normalized to a unique value, even if incorrect electrode positioning remains one of the major issues for reliable use of myoelectric control.

Muscle patterns underlying voluntary modulation of co-contraction

Manipulative actions involving unstable interactions with the environment require controlling mechanical impedance through muscle co-contraction. While much research has focused on how the central nervous system (CNS) selects the muscle patterns underlying a desired movement or end-point force, the coordination strategies used to achieve a desired end-point impedance have received considerably less attention. We recorded isometric forces at the hand and electromyographic (EMG) signals in subjects performing a reaching task with an external disturbance. In a virtual environment, subjects displaced a cursor by applying isometric forces and were instructed to reach targets in 20 spatial locations. The motion of the cursor was then perturbed by disturbances whose effects could be attenuated by increasing co-contraction. All subjects could voluntarily modulate co-contraction when disturbances of different magnitudes were applied. For most muscles, activation was modulated by target direction according to a cosine tuning function with an offset and an amplitude increasing with disturbance magnitude. Co-contraction was characterized by projecting the muscle activation vector onto the null space of the EMG-to-force mapping. Even in the baseline the magnitude of the null space projection was larger than the minimum magnitude required for non-negative muscle activations. Moreover, the increase in co-contraction was not obtained by scaling the baseline null space projection, scaling the difference between the null space projections in any block and the projection of the non-negative minimum-norm muscle vector, or scaling the difference between the null space projections in the perturbed blocks and the baseline null space projection. However, the null space projections in the perturbed blocks were obtained by linear combination of the baseline null space projection and the muscle activation used to increase co-contraction without generating any force. The failure of scaling rules in explaining voluntary modulation of arm co-contraction suggests that muscle pattern generation may be constrained by muscle synergies.