Patterns of muscle activity underlying object-specific grasp by the macaque monkey

Spatial and Temporal Muscle Synergies Provide a Dual Characterization of Low-dimensional and Intermittent Control of Upper-limb Movements

Muscle synergy analysis investigates the neurophysiological mechanisms that the central nervous system employs to coordinate muscles. Several models have been developed to decompose electromyographic (EMG) signals into spatial and temporal synergies. However, using multiple approaches can complicate the interpretation of results. Spatial synergies represent invariant muscle weights modulated with variant temporal coefficients; temporal synergies are invariant temporal profiles that coordinate variant muscle weights. While non-negative matrix factorization allows to extract both spatial and temporal synergies, the comparison between the two approaches was rarely investigated targeting a large set of multi-joint upper-limb movements. Spatial and temporal synergies were extracted from two datasets with proximal (16 subjects, 10M, 6F) and distal upper-limb movements (30 subjects, 21M, 9F), focusing on their differences in reconstruction accuracy and inter-individual variability. We showed the existence of both spatial and temporal structure in the EMG data, comparing synergies with those from a surrogate dataset in which the phases were shuffled preserving the frequency content of the original data. The two models provide a compact characterization of motor coordination at the spatial or temporal level, respectively. However, a lower number of temporal synergies are needed to achieve the same reconstruction R²: spatial and temporal synergies may capture different hierarchical levels of motor control and are dual approaches to the characterization of low-dimensional coordination of the upper-limb. Last, a detailed characterization of the structure of the temporal synergies suggested that they can be related to intermittent control of the movement, allowing high flexibility and dexterity. These results improve neurophysiology understanding in several fields such as motor control, rehabilitation, and prosthetics.

The Effects of Fatigue on Muscle Synergies in the Shoulders of Baseball Players

BACKGROUND

Muscle synergies are defined as the central nervous system's organizational structure for movement. Muscle synergies change after muscular fatigue, with certain synergies assuming the primary role to compensate for fatigue within another muscle synergy. Owing to the high eccentric forces imposed upon the external rotators (ie, posterior rotator cuff), pitchers that continue to throw while fatigued are at a significantly higher risk of shoulder and/or elbow injury; however, the neuromuscular compensation strategies of baseball players in response to fatigue are currently unknown.

HYPOTHESIS

Players would utilize the same muscle synergy structure following external rotation (ER) fatigue; however, muscle coefficients of nonfatigued muscles would increase (ie, compensate for the external rotators) after fatigue.

STUDY DESIGN

Cross-sectional study conducted in a controlled, laboratory setting.

METHODS

Nine players from an intercollegiate competitive club baseball team voluntarily participated in this study. Surface electromyography was used on 14 muscles of the glenohumeral and scapulothoracic joints of the dominant arm during a reaching protocol. Players completed a baseline reaching protocol (prefatigue), then an ER fatigue protocol until maximum concentric ER was reduced by 40%, and finally repeated the same reaching protocol (postfatigue). Principal component analysis was used to extract muscle synergies, the variance accounted for (VAF) of each synergy, and muscle coefficients. Prefatigue was compared with postfatigue using paired t tests for all dependent variables.

RESULTS

Four muscle synergies were extracted for both pre- and postfatigue. The VAF for the ER/abduction synergy decreased significantly (prefatigue, 34.6%; postfatigue, 32.4%; P = 0.03), showing a decreased reliance on ER/abduction during the reaching task after fatigue. Within synergy 1, the pectoralis major muscle coefficient (-0.489 vs -0.552; P = 0.01; effect size = 1.68) decreased significantly from prefatigue to postfatigue, indicating that the pectoralis major assumed more of an antagonist role during ER/abduction. Within synergy 2 (forward reaching), there were no significant changes in VAF or muscle coefficients observed. For the third synergy, muscle coefficients increased for the serratus anterior (P = 0.02) and middle deltoid (P = 0.01), whereas in the fourth synergy, the pectoralis major (P = 0.01) increased and teres major (P = 0.01) and biceps brachii (P = 0.05) muscle coefficients decreased.

CONCLUSION

The decreased VAF of the ER/abduction synergy after fatigue indicate that other muscles within that synergy could not fully compensate to maintain function. Interestingly, the changes in muscle coefficients suggest that players relied less on the internal rotation (IR) synergy and more on the cross-body synergy following fatigue. This may be due to imbalances between ER and IR while maintaining balance between cross-abduction and adduction.

CLINICAL RELEVANCE

Clinicians may consider implementing low-load, high-repetition training programs to develop posterior shoulder endurance and prolong the onset of muscular fatigue.

Chronic Adaptations of Shoulder Muscle Synergies in Healthy Baseball Players

BACKGROUND

Previous research has demonstrated that muscle synergy structure can adapt owing to training and injury; however, muscle synergies have not been evaluated in baseball players.

HYPOTHESIS

The throwing arm would have a similar muscle synergy structure but different levels of individual muscle activity within each synergy, relative to the nonthrowing arm.

STUDY DESIGN

Cross-sectional study in a controlled laboratory setting.

METHODS

Fourteen healthy competitive baseball players were included. Participants were tested bilaterally during a center-out planar reaching task using the KINARM robot, where kinematic data and surface electromyography data from 14 glenohumeral and scapular muscles were synchronized. Principal component analysis was used to extract muscle synergies, the variance accounted for (VAF) of each synergy, and individual muscle coefficients. The dominant (DOM) arm was compared with the nondominant (NDOM) arm using paired t tests for all dependent variables.

RESULTS

The same number of muscle synergies were extracted on the DOM and NDOM arms, along with no differences in VAF. In the first synergy, the infraspinatus (DOM 0.798 vs NDOM 0.587, P = 0.038) and lower trapezius (DOM 0.872 vs NDOM 0.480, P = 0.005) muscle coefficients significantly increased on the DOM arm. The second synergy had a significantly increased anterior deltoid (DOM 0.764 vs NDOM 0.374, P = 0.003) and a significantly decreased posterior deltoid (DOM -0.069 vs NDOM 0.197, P = 0.041) muscle coefficient on the DOM arm.

CONCLUSION

The DOM shoulder exhibits a higher proportion of infraspinatus and lower trapezius muscle activation during the external rotation and abduction synergy. Also, the DOM shoulder has increased muscle activation of the teres major and latissimus dorsi during the internal rotation synergy, and increased muscle activation of the pectoralis major during the cross-body adduction synergy, compared with the NDOM shoulder.

CLINICAL RELEVANCE

By exploring these neuromuscular adaptations, the improved understanding of muscle synergy adaptations in baseball players will help optimize injury prevention and rehabilitation techniques.

The neural mechanisms of manual dexterity

The hand endows us with unparalleled precision and versatility in our interactions with objects, from mundane activities such as grasping to extraordinary ones such as virtuoso pianism. The complex anatomy of the human hand combined with expansive and specialized neuronal control circuits allows a wide range of precise manual behaviours. To support these behaviours, an exquisite sensory apparatus, spanning the modalities of touch and proprioception, conveys detailed and timely information about our interactions with objects and about the objects themselves. The study of manual dexterity provides a unique lens into the sensorimotor mechanisms that endow the nervous system with the ability to flexibly generate complex behaviour.

Upper-Limb Electromyogram Classification of Reaching-to-Grasping Tasks Based on Convolutional Neural Networks for Control of a Prosthetic Hand

In recent years, myoelectric interfaces using surface electromyogram (EMG) signals have been developed for assisting people with physical disabilities. Especially, in the myoelectric interfaces for robotic hands or arms, decoding the user’s upper-limb movement intentions is cardinal to properly control the prosthesis. However, because previous experiments were implemented with only healthy subjects, the possibility of classifying reaching-to-grasping based on the EMG signals from the residual limb without the below-elbow muscles was not investigated yet. Therefore, we aimed to investigate the possibility of classifying reaching-to-grasping tasks using the EMG from the upper arm and upper body without considering wrist muscles for prosthetic users. In our study, seven healthy subjects, one trans-radial amputee, and one wrist amputee were participated and performed 10 repeatable 12 reaching-to-grasping tasks based on the Southampton Hand Assessment Procedure (SHAP) with 12 different weighted (light and heavy) objects. The acquired EMG was processed using the principal component analysis (PCA) and convolutional neural network (CNN) to decode the tasks. The PCA–CNN method showed that the average accuracies of the healthy subjects were 69.4 ± 11.4%, using only the EMG signals by the upper arm and upper body. The result with the PCA–CNN method showed 8% significantly higher accuracies than the result with the widely used time domain and auto-regressive-support vector machine (TDAR–SVM) method as 61.6 ± 13.7%. However, in the cases of the amputees, the PCA–CNN showed slightly lower performance. In addition, in the aspects of assistant daily living, because grip force is also important when grasping an object after reaching, the possibility of classifying the two light and heavy objects in each reaching-to-grasping task was also investigated. Consequently, the PCA–CNN method showed higher accuracy at 70.1 ± 9.8%. Based on our results, the PCA–CNN method can help to improve the performance of classifying reaching-to-grasping tasks without wrist EMG signals. Our findings and decoding method can be implemented to further develop a practical human–machine interface using EMG signals.

Intrafascicular peripheral nerve stimulation produces fine functional hand movements in primates

[Figure: see text].

Biomechanical demands of percussive techniques in the context of early stone toolmaking

Recent discoveries in archaeology and palaeoanthropology highlight that stone tool knapping could have emerged first within the genera Australopithecus or Kenyanthropus rather than Homo. To explore the implications of this hypothesis determining the physical demands and motor control needed for performing the percussive movements during the oldest stone toolmaking technology (i.e. Lomekwian) would help. We analysed the joint angle patterns and muscle activity of a knapping expert using three stone tool replication techniques: unipolar flaking on the passive hammer (PH), bipolar (BP) flaking on the anvil, and multidirectional and multifacial flaking with free hand (FH). PH presents high levels of activity for Biceps brachii and wrist extensors and flexors. By contrast, BP and FH are characterized by high solicitation of forearm pronation. The synergy analyses depict a high muscular and kinematic coordination. Whereas the muscle pattern is very close between the techniques, the kinematic pattern is more variable, especially for PH. FH displays better muscle coordination and conversely lesser joint angle coordination. These observations suggest that the transition from anvil and hammer to freehand knapping techniques in early hominins would have been made possible by the acquisition of a behavioural repertoire producing an evolutionary advantage that gradually would have been beneficial for stone tool production.

Movement initiation and grasp representation in premotor and primary motor cortex mirror neurons

Pyramidal tract neurons (PTNs) within macaque rostral ventral premotor cortex (F5) and (M1) provide direct input to spinal circuitry and are critical for skilled movement control. Contrary to initial hypotheses, they can also be active during action observation, in the absence of any movement. A population-level understanding of this phenomenon is currently lacking. We recorded from single neurons, including identified PTNs, in (M1) (n = 187), and F5 (n = 115) as two adult male macaques executed, observed, or withheld (NoGo) reach-to-grasp actions. F5 maintained a similar representation of grasping actions during both execution and observation. In contrast, although many individual M1 neurons were active during observation, M1 population activity was distinct from execution, and more closely aligned to NoGo activity, suggesting this activity contributes to withholding of self-movement. M1 and its outputs may dissociate initiation of movement from representation of grasp in order to flexibly guide behaviour.

A versatile robotic platform for the design of natural, three-dimensional reaching and grasping tasks in monkeys

OBJECTIVE

Translational studies on motor control and neurological disorders require detailed monitoring of sensorimotor components of natural limb movements in relevant animal models. However, available experimental tools do not provide a sufficiently rich repertoire of behavioral signals. Here, we developed a robotic platform that enables the monitoring of kinematics, interaction forces, and neurophysiological signals during user-defined upper limb tasks for monkeys.

APPROACH

We configured the platform to position instrumented objects in a three-dimensional workspace and provide an interactive dynamic force-field.

MAIN RESULTS

We show the relevance of our platform for fundamental and translational studies with three example applications. First, we study the kinematics of natural grasp in response to variable interaction forces. We then show simultaneous and independent encoding of kinematic and forces in single unit intra-cortical recordings from sensorimotor cortical areas. Lastly, we demonstrate the relevance of our platform to develop clinically relevant brain computer interfaces in a kinematically unconstrained motor task.

SIGNIFICANCE

Our versatile control structure does not depend on the specific robotic arm used and allows for the design and implementation of a variety of tasks that can support both fundamental and translational studies of motor control.

Altered Recruitment of Motor Cortex Neuronal Activity During the Grasping Phase of Skilled Reaching in a Chronic Rat Model of Unilateral Parkinsonism

Parkinson's disease causes prominent difficulties in the generation and execution of voluntary limb movements, including regulation of distal muscles and coordination of proximal and distal movement components to achieve accurate grasping. Difficulties with manual dexterity have a major impact on activities of daily living. We used extracellular single neuron recordings to investigate the neural underpinnings of parkinsonian movement deficits in the motor cortex of chronic unilateral 6-hydroxydopamine lesion male rats performing a skilled reach-to-grasp task the. Both normal movements and parkinsonian deficits in this task have striking homology to human performance. In lesioned animals there were several differences in the activity of cortical neurons during reaches by the affected limb compared with control rats. These included an increase in proportions of neurons showing rate decreases, along with increased amplitude of their average rate-decrease response at specific times during the reach, suggesting a shift in the balance of net excitation and inhibition of cortical neurons; a significant increase in the duration of rate-increase responses, which could result from reduced coupling of cortical activity to specific movement components; and changes in the timing and incidence of neurons with pure rate-increase or biphasic responses, particularly at the end of reach when grasping would normally be occurring. The changes in cortical activity may account for the deficits that occur in skilled distal motor control following dopamine depletion, and highlight the need for treatment strategies targeted toward modulating cortical mechanisms for fine distal motor control in patients.SIGNIFICANCE STATEMENT We show for the first time in a chronic lesion rat model of Parkinson's disease movement deficits that there are specific changes in motor cortex neuron activity associated with the grasping phase of a skilled motor task. Such changes provide a possible mechanism underpinning the problems with manual dexterity seen in Parkinson's patients and highlight the need for treatment strategies targeted toward distal motor control.

An automated behavioral apparatus to combine parameterized reaching and grasping movements in 3D space

BACKGROUND

The neural principles underlying reaching and grasping movements have been studied extensively in primates for decades. However, few experimental apparatuses have been developed to enable a flexible combination of reaching and grasping in one task in three-dimensional (3D) space.

NEW METHOD

By combining a custom turning table with a 3D translational device, we have developed a highly flexible apparatus that enables the subject to reach multiple positions in 3D space, and grasp differently shaped objects with multiple grip types in each position. Meanwhile, hand trajectory and grip types can be recorded via optical motion tracking cameras and touch sensors, respectively.

RESULTS

We have used the apparatus to successfully train a macaque monkey to accomplish a visually-guided reach-to-grasp task, in which, six objects, fixed on the turning table, were grasped appropriately when they were transported to multiple positions in 3D space. A preliminary analysis of neural signals recorded in primary motor cortex, shows that plenty of neurons exhibit significant tuning to both target position and grip type.

COMPARISON WITH EXISTING METHOD(S)

Our apparatus realizes an arbitrary combination of parameterized reaching and grasping movements in a single task, which were usually separated or fixed in other systems. Meanwhile, the apparatus has high expansibility in terms of dynamic range, object shapes and applicable subjects.

CONCLUSIONS

The apparatus provides a valuable platform to study upper limb functions in behavioral and neurophysiological studies, and may facilitate simultaneous reconstruction of reaching and grasping movements in brain-machine interfaces (BMIs).

The impact of hand proportions on tool grip abilities in humans, great apes and fossil hominins: A biomechanical analysis using musculoskeletal simulation

Differences in grip techniques used across primates are usually attributed to variation in thumb-finger proportions and muscular anatomy of the hand. However, this cause-effect relationship is not fully understood because little is known about the biomechanical functioning and mechanical loads (e.g., muscle or joint forces) of the non-human primate hand compared to that of humans during object manipulation. This study aims to understand the importance of hand proportions on the use of different grip strategies used by humans, extant great apes (bonobos, gorillas and orangutans) and, potentially, fossil hominins (Homo naledi and Australopithecus sediba) using a musculoskeletal model of the hand. Results show that certain grips are more challenging for some species, particularly orangutans, than others, such that they require stronger muscle forces for a given range of motion. Assuming a human-like range of motion at each hand joint, simulation results show that H. naledi and A. sediba had the biomechanical potential to use the grip techniques considered important for stone tool-related behaviors in humans. These musculoskeletal simulation results shed light on the functional consequences of the different hand proportions among extant and extinct hominids and the different manipulative abilities found in humans and great apes.

Deciphering the functional role of spatial and temporal muscle synergies in whole-body movements

Voluntary movement is hypothesized to rely on a limited number of muscle synergies, the recruitment of which translates task goals into effective muscle activity. In this study, we investigated how to analytically characterize the functional role of different types of muscle synergies in task performance. To this end, we recorded a comprehensive dataset of muscle activity during a variety of whole-body pointing movements. We decomposed the electromyographic (EMG) signals using a space-by-time modularity model which encompasses the main types of synergies. We then used a task decoding and information theoretic analysis to probe the role of each synergy by mapping it to specific task features. We found that the temporal and spatial aspects of the movements were encoded by different temporal and spatial muscle synergies, respectively, consistent with the intuition that there should a correspondence between major attributes of movement and major features of synergies. This approach led to the development of a novel computational method for comparing muscle synergies from different participants according to their functional role. This functional similarity analysis yielded a small set of temporal and spatial synergies that describes the main features of whole-body reaching movements.

A Systematic Review on Muscle Synergies: From Building Blocks of Motor Behavior to a Neurorehabilitation Tool

The central nervous system (CNS) is believed to utilize specific predefined modules, called muscle synergies (MS), to accomplish a motor task. Yet questions persist about how the CNS combines these primitives in different ways to suit the task conditions. The MS hypothesis has been a subject of debate as to whether they originate from neural origins or nonneural constraints. In this review article, we present three aspects related to the MS hypothesis: (1) the experimental and computational evidence in support of the existence of MS, (2) algorithmic approaches for extracting them from surface electromyography (EMG) signals, and (3) the possible role of MS as a neurorehabilitation tool. We note that recent advances in computational neuroscience have utilized the MS hypothesis in motor control and learning. Prospective advances in clinical, medical, and engineering sciences and in fields such as robotics and rehabilitation stand to benefit from a more thorough understanding of MS.

Neuronal Correlates of Functional Coupling between Reach- and Grasp-Related Components of Muscle Activity

Coordinated reach-to-grasp movements require precise spatiotemporal synchrony between proximal forelimb muscles (shoulder, elbow) that transport the hand toward a target during reach, and distal muscles (wrist, digit) that simultaneously preshape and orient the hand for grasp. The precise mechanisms through which the redundant neuromuscular circuitry coordinates reach with grasp, however, remain unclear. Recently, Geed and Van Kan (2016) demonstrated, using exploratory factor analysis (EFA), that limited numbers of global, template-like transport/preshape- and grasp-related muscle components underlie the complexity and variability of intramuscular electromyograms (EMGs) of up to 21 distal and proximal muscles recorded while monkeys performed reach-to-grasp tasks. Importantly, transport/preshape- and grasp-related muscle components showed invariant spatiotemporal coupling, which provides a potential mechanism for coordinating forelimb muscles during reach-to-grasp movements. In the present study, we tested whether ensemble discharges of forelimb neurons in the cerebellar nucleus interpositus (NI) and its target, the magnocellular red nucleus (RNm), a source of rubrospinal fibers, function as neuronal correlates of the transport/preshape- and grasp-related muscle components we identified. EFA applied to single-unit discharges of populations of NI and RNm neurons recorded while the same monkeys that were used previously performed the same reach-to-grasp tasks, revealed neuronal components in the ensemble discharges of both NI and RNm neuronal populations with characteristics broadly similar to muscle components. Subsets of NI and RNm neuronal components were strongly and significantly crosscorrelated with subsets of muscle components, suggesting that similar functional units of reach-to-grasp behavior are expressed by NI and RNm neuronal populations and forelimb muscles. Importantly, like transport/preshape- and grasp-related muscle components, their NI and RNm neuronal correlates showed invariant spatiotemporal coupling. Clinical and lesion studies have reported disruption of coupling between reach and grasp following cerebellar damage; the present results expand on those studies by identifying a neuronal mechanism that may underlie cerebellar contributions to spatiotemporal coordination of distal and proximal limb muscles during reaching to grasp. We conclude that finding similar functional units of behavior expressed at multiple levels of information processing along interposito-rubrospinal pathways and forelimb muscles supports the hypothesis that functionally related populations of NI and RNm neurons act synergistically in the control of complex coordinated motor behaviors.

Grasp-Based Functional Coupling Between Reach- and Grasp-Related Components of Forelimb Muscle Activity

How are appropriate combinations of forelimb muscles selected during reach-to-grasp movements in the presence of neuromotor redundancy and important task-related constraints? The authors tested whether grasp type or target location preferentially influence the selection and synergistic coupling between forelimb muscles during reach-to-grasp movements. Factor analysis applied to 14-20 forelimb electromyograms recorded from monkeys performing reach-to-grasp tasks revealed 4-6 muscle components that showed transport/preshape- or grasp-related features. Weighting coefficients of transport/preshape-related components demonstrated strongest similarities for reaches that shared the same grasp type rather than the same target location. Scaling coefficients of transport/preshape- and grasp-related components showed invariant temporal coupling. Thus, grasp type influenced strongly both transport/preshape- and grasp-related muscle components, giving rise to grasp-based functional coupling between forelimb muscles.

Modulatory Effects of the Ipsi and Contralateral Ventral Premotor Cortex (PMv) on the Primary Motor Cortex (M1) Outputs to Intrinsic Hand and Forearm Muscles in Cebus apella

The ventral premotor cortex (PMv) is a key node in the neural network involved in grasping. One way PMv can carry out this function is by modulating the outputs of the primary motor cortex (M1) to intrinsic hand and forearm muscles. As many PMv neurons discharge when grasping with either arm, both PMv within the same hemisphere (ipsilateral; iPMv) and in the opposite hemisphere (contralateral; cPMv) could modulate M1 outputs. Our objective was to compare modulatory effects of iPMv and cPMv on M1 outputs to intrinsic hand and forearm muscles. We used paired-pulse protocols with intracortical microstimulations in capuchin monkeys. A conditioning stimulus was applied in either iPMv or cPMv simultaneously or prior to a test stimulus in M1 and the effects quantified in electromyographic signals. Modulatory effects from iPMv were predominantly facilitatory, and facilitation was much more common and powerful on intrinsic hand than forearm muscles. In contrast, while the conditioning of cPMv could elicit facilitatory effects, in particular to intrinsic hand muscles, it was much more likely to inhibit M1 outputs. These data show that iPMv and cPMv have very different modulatory effects on the outputs of M1 to intrinsic hand and forearm muscles.

Spatiotemporal distribution of location and object effects in the electromyographic activity of upper extremity muscles during reach-to-grasp

In reaching to grasp an object, proximal muscles that act on the shoulder and elbow classically have been viewed as transporting the hand to the intended location, while distal muscles that act on the fingers simultaneously shape the hand to grasp the object. Prior studies of electromyographic (EMG) activity in upper extremity muscles therefore have focused, by and large, either on proximal muscle activity during reaching to different locations or on distal muscle activity as the subject grasps various objects. Here, we examined the EMG activity of muscles from the shoulder to the hand, as monkeys reached and grasped in a task that dissociated location and object. We quantified the extent to which variation in the EMG activity of each muscle depended on location, on object, and on their interaction-all as a function of time. Although EMG variation depended on both location and object beginning early in the movement, an early phase of substantial location effects in muscles from proximal to distal was followed by a later phase in which object effects predominated throughout the extremity. Interaction effects remained relatively small. Our findings indicate that neural control of reach-to-grasp may occur largely in two sequential phases: the first, serving to project the entire upper extremity toward the intended location, and the second, acting predominantly to shape the entire extremity for grasping the object.

Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands

The term 'synergy' - from the Greek synergia - means 'working together'. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments. The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project "The Hand Embodied" (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies.

Representation of Muscle Synergies in the Primate Brain

Evidence suggests that the CNS uses motor primitives to simplify movement control, but whether it actually stores primitives instead of computing solutions on the fly to satisfy task demands is a controversial and still-unanswered possibility. Also in contention is whether these primitives take the form of time-invariant muscle coactivations ("spatial" synergies) or time-varying muscle commands ("spatiotemporal" synergies). Here, we examined forelimb muscle patterns and motor cortical spiking data in rhesus macaques (Macaca mulatta) handling objects of variable shape and size. From these data, we extracted both spatiotemporal and spatial synergies using non-negative decomposition. Each spatiotemporal synergy represents a sequence of muscular or neural activations that appeared to recur frequently during the animals' behavior. Key features of the spatiotemporal synergies (including their dimensionality, timing, and amplitude modulation) were independently observed in the muscular and neural data. In addition, both at the muscular and neural levels, these spatiotemporal synergies could be readily reconstructed as sequential activations of spatial synergies (a subset of those extracted independently from the task data), suggestive of a hierarchical relationship between the two levels of synergies. The possibility that motor cortex may execute even complex skill using spatiotemporal synergies has novel implications for the design of neuroprosthetic devices, which could gain computational efficiency by adopting the discrete and low-dimensional control that these primitives imply.

SIGNIFICANCE STATEMENT

We studied the motor cortical and forearm muscular activity of rhesus macaques (Macaca mulatta) as they reached, grasped, and carried objects of varied shape and size. We applied non-negative matrix factorization separately to the cortical and muscular data to reduce their dimensionality to a smaller set of time-varying "spatiotemporal" synergies. Each synergy represents a sequence of cortical or muscular activity that recurred frequently during the animals' behavior. Salient features of the synergies (including their dimensionality, timing, and amplitude modulation) were observed at both the cortical and muscular levels. The possibility that the brain may execute even complex behaviors using spatiotemporal synergies has implications for neuroprosthetic algorithm design, which could become more computationally efficient by adopting the discrete and low-dimensional control that they afford.

Analysis of surface EMG activation in hand percussion playing depending on the grasping type and the tempo

Although instrument playing-based training has been repeatedly reported to improve functional hand movements including grasping, the attempts to present quantitative information on physiological mechanism of grasping have been relatively insufficient to determine the type and the intensity of the exercises involved. This study aimed to examine the muscle activation during hand percussion playing depending on the grasping type and the playing tempo. A total of twelve healthy older adults with a mean age of 71.5 years participated in this study. Surface electrodes were placed on three grasping-related muscles: Flexor digitorum superficialis, extensor digitorum, and flexor pollicis brevis. Participants were instructed to play with the egg shaker, paddle drum mallet and clave involving different types of grasp at three different tempi (i.e., 80, 100, and 120 bpm) and sEMG data were collected during each playing. Significantly greater muscle activation was generated with the small sphere type of egg shaker, compared to the handle type of paddle drum mallet and the small cylinder type of clave. Playing at faster tempo also elicited significantly greater muscle activation than at slower tempo. With regard to the rise time of muscle activation, while tempo significantly affected the rise time, the time to peak muscle did not significantly change depending on the grasping type. This study confirmed that grasping pattern and the tempo of movement significantly influence the muscular activation of grasping involved in instrument playing. Based on these results, clinical implication for instrument selection and structured instrument playing would be suggested.

Task-discriminative space-by-time factorization of muscle activity

Movement generation has been hypothesized to rely on a modular organization of muscle activity. Crucial to this hypothesis is the ability to perform reliably a variety of motor tasks by recruiting a limited set of modules and combining them in a task-dependent manner. Thus far, existing algorithms that extract putative modules of muscle activations, such as Non-negative Matrix Factorization (NMF), identify modular decompositions that maximize the reconstruction of the recorded EMG data. Typically, the functional role of the decompositions, i.e., task accomplishment, is only assessed a posteriori. However, as motor actions are defined in task space, we suggest that motor modules should be computed in task space too. In this study, we propose a new module extraction algorithm, named DsNM3F, that uses task information during the module identification process. DsNM3F extends our previous space-by-time decomposition method (the so-called sNM3F algorithm, which could assess task performance only after having computed modules) to identify modules gauging between two complementary objectives: reconstruction of the original data and reliable discrimination of the performed tasks. We show that DsNM3F recovers the task dependence of module activations more accurately than sNM3F. We also apply it to electromyographic signals recorded during performance of a variety of arm pointing tasks and identify spatial and temporal modules of muscle activity that are highly consistent with previous studies. DsNM3F achieves perfect task categorization without significant loss in data approximation when task information is available and generalizes as well as sNM3F when applied to new data. These findings suggest that the space-by-time decomposition of muscle activity finds robust task-discriminating modular representations of muscle activity and that the insertion of task discrimination objectives is useful for describing the task modulation of module recruitment.

Finger muscle attachments for an OpenSim upper-extremity model

We determined muscle attachment points for the index, middle, ring and little fingers in an OpenSim upper-extremity model. Attachment points were selected to match both experimentally measured locations and mechanical function (moment arms). Although experimental measurements of finger muscle attachments have been made, models differ from specimens in many respects such as bone segment ratio, joint kinematics and coordinate system. Likewise, moment arms are not available for all intrinsic finger muscles. Therefore, it was necessary to scale and translate muscle attachments from one experimental or model environment to another while preserving mechanical function. We used a two-step process. First, we estimated muscle function by calculating moment arms for all intrinsic and extrinsic muscles using the partial velocity method. Second, optimization using Simulated Annealing and Hooke-Jeeves algorithms found muscle-tendon paths that minimized root mean square (RMS) differences between experimental and modeled moment arms. The partial velocity method resulted in variance accounted for (VAF) between measured and calculated moment arms of 75.5% on average (range from 48.5% to 99.5%) for intrinsic and extrinsic index finger muscles where measured data were available. RMS error between experimental and optimized values was within one standard deviation (S.D) of measured moment arm (mean RMS error = 1.5 mm < measured S.D = 2.5 mm). Validation of both steps of the technique allowed for estimation of muscle attachment points for muscles whose moment arms have not been measured. Differences between modeled and experimentally measured muscle attachments, averaged over all finger joints, were less than 4.9 mm (within 7.1% of the average length of the muscle-tendon paths). The resulting non-proprietary musculoskeletal model of the human fingers could be useful for many applications, including better understanding of complex multi-touch and gestural movements.

Differences between kinematic synergies and muscle synergies during two-digit grasping

The large number of mechanical degrees of freedom of the hand is not fully exploited during actual movements such as grasping. Usually, angular movements in various joints tend to be coupled, and EMG activities in different hand muscles tend to be correlated. The occurrence of covariation in the former was termed kinematic synergies, in the latter muscle synergies. This study addresses two questions: (i) Whether kinematic and muscle synergies can simultaneously accommodate for kinematic and kinetic constraints. (ii) If so, whether there is an interrelation between kinematic and muscle synergies. We used a reach-grasp-and-pull paradigm and recorded the hand kinematics as well as eight surface EMGs. Subjects had to either perform a precision grip or side grip and had to modify their grip force in order to displace an object against a low or high load. The analysis was subdivided into three epochs: reach, grasp-and-pull, and static hold. Principal component analysis (PCA, temporal or static) was performed separately for all three epochs, in the kinematic and in the EMG domain. PCA revealed that (i) Kinematic- and muscle-synergies can simultaneously accommodate kinematic (grip type) and kinetic task constraints (load condition). (ii) Upcoming grip and load conditions of the grasp are represented in kinematic- and muscle-synergies already during reach. Phase plane plots of the principal muscle-synergy against the principal kinematic synergy revealed (iii) that the muscle-synergy is linked (correlated, and in phase advance) to the kinematic synergy during reach and during grasp-and-pull. Furthermore (iv), pair-wise correlations of EMGs during hold suggest that muscle-synergies are (in part) implemented by coactivation of muscles through common input. Together, these results suggest that kinematic synergies have (at least in part) their origin not just in muscular activation, but in synergistic muscle activation. In short: kinematic synergies may result from muscle synergies.

A learning scheme for reach to grasp movements: on EMG-based interfaces using task specific motion decoding models

A learning scheme based on random forests is used to discriminate between different reach to grasp movements in 3-D space, based on the myoelectric activity of human muscles of the upper-arm and the forearm. Task specificity for motion decoding is introduced in two different levels: Subspace to move toward and object to be grasped. The discrimination between the different reach to grasp strategies is accomplished with machine learning techniques for classification. The classification decision is then used in order to trigger an EMG-based task-specific motion decoding model. Task specific models manage to outperform "general" models providing better estimation accuracy. Thus, the proposed scheme takes advantage of a framework incorporating both a classifier and a regressor that cooperate advantageously in order to split the task space. The proposed learning scheme can be easily used to a series of EMG-based interfaces that must operate in real time, providing data-driven capabilities for multiclass problems, that occur in everyday life complex environments.

Motor cortical function and the precision grip

While task‐dependent changes in motor cortical outputs have been previously reported, the issue of whether such changes are specific for complex hand tasks remains unresolved. The aim of the present study was to determine whether cortical inhibitory tone and cortical output were greater during precision grip and power grip. Motor cortex excitability was undertaken by using the transcranial magnetic stimulation threshold tracking technique in 15 healthy subjects. The motor‐evoked potential (MEP) responses were recorded over the abductor pollicis brevis (APB), with the hand in the following positions: (1) rest, (2) precision grip and (3) power grip. The MEP amplitude (MEP amplitude _REST 23.6 ± 3.3%; MEP amplitude _{PRECISIONGRIP} 35.2 ± 5.6%; MEP amplitude _POWERGRIP 19.6 ± 3.4%, F = 2.4, P < 0.001) and stimulus‐response gradient (SLOPE_REST 0.06 ± 0.01; SLOPE_PRCISIONGRIP 0.15 ± 0.04; SLOPE _POWERGRIP 0.07 ± 0.01, P < 0.05) were significantly increased during precision grip. Short interval intracortical inhibition (SICI) was significantly reduced during the precision grip (SICI _REST 15.0 ± 2.3%; SICI _{PRECISIONGRIP} 9.7 ± 1.5%, SICI _POWERGRIP 15.9 ± 2.7%, F = 2.6, P < 0.05). The present study suggests that changes in motor cortex excitability are specific for precision grip, with functional coupling of descending corticospinal pathways controlling thumb and finger movements potentially forming the basis of these cortical changes.

This manuscript establishes that specific cortical mechanisms underlie the maintenance of the precision grip. The mechanisms appear distinct to the processes maintaining the power grip.

Task discrimination from myoelectric activity: a learning scheme for EMG-based interfaces

A learning scheme based on Random Forests is used to discriminate the task to be executed using only myoelectric activity from the upper limb. Three different task features can be discriminated: subspace to move towards, object to be grasped and task to be executed (with the object). The discrimination between the different reach to grasp movements is accomplished with a random forests classifier, which is able to perform efficient features selection, helping us to reduce the number of EMG channels required for task discrimination. The proposed scheme can take advantage of both a classifier and a regressor that cooperate advantageously to split the task space, providing better estimation accuracy with task-specific EMG-based motion decoding models, as reported in [1] and [2]. The whole learning scheme can be used by a series of EMG-based interfaces, that can be found in rehabilitation cases and neural prostheses.

Distinct neural patterns enable grasp types decoding in monkey dorsal premotor cortex

OBJECTIVE

Recent studies have shown that dorsal premotor cortex (PMd), a cortical area in the dorsomedial grasp pathway, is involved in grasp movements. However, the neural ensemble firing property of PMd during grasp movements and the extent to which it can be used for grasp decoding are still unclear.

APPROACH

To address these issues, we used multielectrode arrays to record both spike and local field potential (LFP) signals in PMd in macaque monkeys performing reaching and grasping of one of four differently shaped objects.

MAIN RESULTS

Single and population neuronal activity showed distinct patterns during execution of different grip types. Cluster analysis of neural ensemble signals indicated that the grasp related patterns emerged soon (200-300 ms) after the go cue signal, and faded away during the hold period. The timing and duration of the patterns varied depending on the behaviors of individual monkey. Application of support vector machine model to stable activity patterns revealed classification accuracies of 94% and 89% for each of the two monkeys, indicating a robust, decodable grasp pattern encoded in the PMd. Grasp decoding using LFPs, especially the high-frequency bands, also produced high decoding accuracies.

SIGNIFICANCE

This study is the first to specify the neuronal population encoding of grasp during the time course of grasp. We demonstrate high grasp decoding performance in PMd. These findings, combined with previous evidence for reach related modulation studies, suggest that PMd may play an important role in generation and maintenance of grasp action and may be a suitable locus for brain-machine interface applications.

Muscle synergies evoked by microstimulation are preferentially encoded during behavior

Electrical microstimulation studies provide some of the most direct evidence for the neural representation of muscle synergies. These synergies, i.e., coordinated activations of groups of muscles, have been proposed as building blocks for the construction of motor behaviors by the nervous system. Intraspinal or intracortical microstimulation (ICMS) has been shown to evoke muscle patterns that can be resolved into a small set of synergies similar to those seen in natural behavior. However, questions remain about the validity of microstimulation as a probe of neural function, particularly given the relatively long trains of supratheshold stimuli used in these studies. Here, we examined whether muscle synergies evoked during ICMS in two rhesus macaques were similarly encoded by nearby motor cortical units during a purely voluntary behavior involving object reach, grasp, and carry movements. At each microstimulation site we identified the synergy most strongly evoked among those extracted from muscle patterns evoked over all microstimulation sites. For each cortical unit recorded at the same microstimulation site, we then identified the synergy most strongly encoded among those extracted from muscle patterns recorded during the voluntary behavior. We found that the synergy most strongly evoked at an ICMS site matched the synergy most strongly encoded by proximal units more often than expected by chance. These results suggest a common neural substrate for microstimulation-evoked motor responses and for the generation of muscle patterns during natural behaviors.

Corticospinal mirror neurons

Here, we report the properties of neurons with mirror-like characteristics that were identified as pyramidal tract neurons (PTNs) and recorded in the ventral premotor cortex (area F5) and primary motor cortex (M1) of three macaque monkeys. We analysed the neurons' discharge while the monkeys performed active grasp of either food or an object, and also while they observed an experimenter carrying out a similar range of grasps. A considerable proportion of tested PTNs showed clear mirror-like properties (52% F5 and 58% M1). Some PTNs exhibited 'classical' mirror neuron properties, increasing activity for both execution and observation, while others decreased their discharge during observation ('suppression mirror-neurons'). These experiments not only demonstrate the existence of PTNs as mirror neurons in M1, but also reveal some interesting differences between M1 and F5 mirror PTNs. Although observation-related changes in the discharge of PTNs must reach the spinal cord and will include some direct projections to motoneurons supplying grasping muscles, there was no EMG activity in these muscles during action observation. We suggest that the mirror neuron system is involved in the withholding of unwanted movement during action observation. Mirror neurons are differentially recruited in the behaviour that switches rapidly between making your own movements and observing those of others.

Somato-motor haptic processing in posterior inner perisylvian region (SII/pIC) of the macaque monkey

The posterior inner perisylvian region including the secondary somatosensory cortex (area SII) and the adjacent region of posterior insular cortex (pIC) has been implicated in haptic processing by integrating somato-motor information during hand-manipulation, both in humans and in non-human primates. However, motor-related properties during hand-manipulation are still largely unknown. To investigate a motor-related activity in the hand region of SII/pIC, two macaque monkeys were trained to perform a hand-manipulation task, requiring 3 different grip types (precision grip, finger exploration, side grip) both in light and in dark conditions. Our results showed that 70% (n = 33/48) of task related neurons within SII/pIC were only activated during monkeys’ active hand-manipulation. Of those 33 neurons, 15 (45%) began to discharge before hand-target contact, while the remaining neurons were tonically active after contact. Thirty-percent (n = 15/48) of studied neurons responded to both passive somatosensory stimulation and to the motor task. A consistent percentage of task-related neurons in SII/pIC was selectively activated during finger exploration (FE) and precision grasping (PG) execution, suggesting they play a pivotal role in control skilled finger movements. Furthermore, hand-manipulation-related neurons also responded when visual feedback was absent in the dark. Altogether, our results suggest that somato-motor neurons in SII/pIC likely contribute to haptic processing from the initial to the final phase of grasping and object manipulation. Such motor-related activity could also provide the somato-motor binding principle enabling the translation of diachronic somatosensory inputs into a coherent image of the explored object.

Motor cortical regulation of sparse synergies provides a framework for the flexible control of precision walking

We have previously described a modular organization of the locomotor step cycle in the cat in which a number of sparse synergies are activated sequentially during the swing phase of the step cycle (Krouchev et al., 2006). Here, we address how these synergies are modified during voluntary gait modifications. Data were analysed from 27 bursts of muscle activity (recorded from 18 muscles) recorded in the forelimb of the cat during locomotion. These were grouped into 10 clusters, or synergies, during unobstructed locomotion. Each synergy was comprised of only a small number of muscles bursts (sparse synergies), some of which included both proximal and distal muscles. Eight (8/10) of these synergies were active during the swing phase of locomotion. Synergies observed during the gait modifications were very similar to those observed during unobstructed locomotion. Constraining these synergies to be identical in both the lead (first forelimb to pass over the obstacle) and the trail (second limb) conditions allowed us to compare the changes in phase and magnitude of the synergies required to modify gait. In the lead condition, changes were observed particularly in those synergies responsible for transport of the limb and preparation for landing. During the trail condition, changes were particularly evident in those synergies responsible for lifting the limb from the ground at the onset of the swing phase. These changes in phase and magnitude were adapted to the size and shape of the obstacle over which the cat stepped. These results demonstrate that by modifying the phase and magnitude of a finite number of muscle synergies, each comprised of a small number of simultaneously active muscles, descending control signals could produce very specific modifications in limb trajectory during locomotion. We discuss the possibility that these changes in phase and magnitude could be produced by changes in the activity of neurones in the motor cortex.

Activation of individual extrinsic thumb muscles and compartments of extrinsic finger muscles

Mechanical and neurological couplings exist between musculotendon units of the human hand and digits. Studies have begun to understand how these muscles interact when accomplishing everyday tasks, but there are still unanswered questions regarding the control limitations of individual muscles. Using intramuscular electromyographic (EMG) electrodes, this study examined subjects' ability to individually initiate and sustain three levels of normalized muscular activity in the index and middle finger muscle compartments of extensor digitorum communis (EDC), flexor digitorum profundus (FDP), and flexor digitorum superficialis (FDS), as well as the extrinsic thumb muscles abductor pollicis longus (APL), extensor pollicis brevis (EPB), extensor pollicis longus (EPL), and flexor pollicis longus (FPL). The index and middle finger compartments each sustained activations with significantly different levels of coactivity from the other finger muscle compartments. The middle finger compartment of EDC was the exception. Only two extrinsic thumb muscles, EPL and FPL, were capable of sustaining individual activations from the other thumb muscles, at all tested activity levels. Activation of APL was achieved at 20 and 30% MVC activity levels with significantly different levels of coactivity. Activation of EPB elicited coactivity levels from EPL and APL that were not significantly different. These results suggest that most finger muscle compartments receive unique motor commands, but of the four thumb muscles, only EPL and FPL were capable of individually activating. This work is encouraging for the neural control of prosthetic limbs because these muscles and compartments may potentially serve as additional user inputs to command prostheses.

Co-registering kinematics and evoked related potentials during visually guided reach-to-grasp movements

Background

In non-human primates grasp-related sensorimotor transformations are accomplished in a circuit involving the anterior intraparietal sulcus (area AIP) and both the ventral and the dorsal sectors of the premotor cortex (vPMC and dPMC, respectively). Although a human homologue of such a circuit has been identified, the time course of activation of these cortical areas and how such activity relates to specific kinematic events has yet to be investigated.

Methodology/Principal Findings

We combined kinematic and event-related potential techniques to explicitly test how activity within human grasping-related brain areas is modulated in time. Subjects were requested to reach towards and grasp either a small stimulus using a precision grip (i.e., the opposition of index finger and thumb) or a large stimulus using a whole hand grasp (i.e., the flexion of all digits around the stimulus). Results revealed a time course of activation starting at the level of parietal regions and continuing at the level of premotor regions. More specifically, we show that activity within these regions was tuned for specific grasps well before movement onset and this early tuning was carried over - as evidenced by kinematic analysis - during the preshaping period of the task.

Conclusions/Significance

Data are discussed in terms of recent findings showing a marked differentiation across different grasps during premovement phases which was carried over into subsequent movement phases. These findings offer a substantial contribution to the current debate about the nature of the sensorimotor transformations underlying grasping. And provide new insights into the detailed movement information contained in the human preparatory activity for specific hand movements.

Synaptic and functional linkages between spinal premotor interneurons and hand-muscle activity during precision grip

Grasping is a highly complex movement that requires the coordination of a number of hand joints and muscles. Previous studies showed that spinal premotor interneurons (PreM-INs) in the primate cervical spinal cord have divergent synaptic effects on hand motoneurons and that they might contribute to hand-muscle synergies. However, the extent to which these PreM-IN synaptic connections functionally contribute to modulating hand-muscle activity is not clear. In this paper, we explored the contribution of spinal PreM-INs to hand-muscle activation by quantifying the synaptic linkage (SL) and functional linkage (FL) of the PreM-INs with hand-muscle activities. The activity of 23 PreM-INs was recorded from the cervical spinal cord (C6–T1), with EMG signals measured simultaneously from hand and arm muscles in two macaque monkeys performing a precision grip task. Spike-triggered averages (STAs) of rectified EMGs were compiled for 456 neuron–muscle pairs; 63 pairs showed significant post-spike effects (PSEs; i.e., SL). Conversely, 231 of 456 pairs showed significant cross-correlations between the IN firing rate and rectified EMG (i.e., FL). Importantly, a greater proportion of the neuron–muscle pairs with SL showed FL (43/63 pairs, 68%) compared with the pairs without SL (203/393, 52%), and the presence of SL was significantly associated with that of FL. However, a significant number of pairs had SL without FL (SL∩!FL, n = 20) or FL without SL (!SL∩FL, n = 203), and the proportions of these incongruities exceeded the number expected by chance. These results suggested that spinal PreM-INs function to significantly modulate hand-muscle activity during precision grip, but the contribution of other neural structures is also needed to recruit an adequate combination of hand-muscle motoneurons.

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.

Neural bases of hand synergies

The human hand has so many degrees of freedom that it may seem impossible to control. A potential solution to this problem is “synergy control” which combines dimensionality reduction with great flexibility. With applicability to a wide range of tasks, this has become a very popular concept. In this review, we describe the evolution of the modern concept using studies of kinematic and force synergies in human hand control, neurophysiology of cortical and spinal neurons, and electromyographic (EMG) activity of hand muscles. We go beyond the often purely descriptive usage of synergy by reviewing the organization of the underlying neuronal circuitry in order to propose mechanistic explanations for various observed synergy phenomena. Finally, we propose a theoretical framework to reconcile important and still debated concepts such as the definitions of “fixed” vs. “flexible” synergies and mechanisms underlying the combination of synergies for hand control.

Evidence of muscle synergies during human grasping

Motor synergies have been investigated since the 1980s as a simplifying representation of motor control by the nervous system. This way of representing finger positional data is in particular useful to represent the kinematics of the human hand. Whereas, so far, the focus has been on kinematic synergies, that is common patterns in the motion of the hand and fingers, we hereby also investigate their force aspects, evaluated through surface electromyography (sEMG). We especially show that force-related motor synergies exist, i.e. that muscle activation during grasping, as described by the sEMG signal, can be grouped synergistically; that these synergies are largely comparable to one another across human subjects notwithstanding the disturbances and inaccuracies typical of sEMG; and that they are physiologically feasible representations of muscular activity during grasping. Potential applications of this work include force control of mechanical hands, especially when many degrees of freedom must be simultaneously controlled.

Mapping the spatio-temporal structure of motor cortical LFP and spiking activities during reach-to-grasp movements

Grasping an object involves shaping the hand and fingers in relation to the object's physical properties. Following object contact, it also requires a fine adjustment of grasp forces for secure manipulation. Earlier studies suggest that the control of hand shaping and grasp force involve partially segregated motor cortical networks. However, it is still unclear how information originating from these networks is processed and integrated. We addressed this issue by analyzing massively parallel signals from population measures (local field potentials, LFPs) and single neuron spiking activities recorded simultaneously during a delayed reach-to-grasp task, by using a 100-electrode array chronically implanted in monkey motor cortex. Motor cortical LFPs exhibit a large multi-component movement-related potential (MRP) around movement onset. Here, we show that the peak amplitude of each MRP component and its latency with respect to movement onset vary along the cortical surface covered by the array. Using a comparative mapping approach, we suggest that the spatio-temporal structure of the MRP reflects the complex physical properties of the reach-to-grasp movement. In addition, we explored how the spatio-temporal structure of the MRP relates to two other measures of neuronal activity: the temporal profile of single neuron spiking activity at each electrode site and the somatosensory receptive field properties of single neuron activities. We observe that the spatial representations of LFP and spiking activities overlap extensively and relate to the spatial distribution of proximal and distal representations of the upper limb. Altogether, these data show that, in motor cortex, a precise spatio-temporal pattern of activation is involved for the control of reach-to-grasp movements and provide some new insight about the functional organization of motor cortex during reaching and object manipulation.

Modulations of EEG beta power during planning and execution of grasping movements

Although beta oscillations (≈ 13–35 Hz) are often considered as a sensorimotor rhythm, their functional role remains debated. In particular, the modulations of beta power during preparation and execution of complex movements in different contexts were barely investigated. Here, we analysed the beta oscillations recorded with electroencephalography (EEG) in a precued grasping task in which we manipulated two critical parameters: the grip type (precision vs. side grip) and the force (high vs. low force) required to pull an object along a horizontal axis. A cue was presented 3 s before a GO signal and provided full, partial or no information about the two movement parameters. We measured beta power over the centro-parietal areas during movement preparation and execution as well as during object hold. We explored the modulations of power in relation to the amount and type of prior information provided by the cue. We also investigated how beta power was affected by the grip and force parameters.

We observed an increase in beta power around the cue onset followed by a decrease during movement preparation and execution. These modulations were followed by a transient power increase during object hold. This pattern of modulations did not differ between the 4 movement types (2 grips ×2 forces). However, the amount and type of prior information provided by the cue had a significant effect on the beta power during the preparatory delay. We discuss how these results fit with current hypotheses on the functional role of beta oscillations.

Quantitative evaluation of muscle synergy models: a single-trial task decoding approach

Muscle synergies, i.e., invariant coordinated activations of groups of muscles, have been proposed as building blocks that the central nervous system (CNS) uses to construct the patterns of muscle activity utilized for executing movements. Several efficient dimensionality reduction algorithms that extract putative synergies from electromyographic (EMG) signals have been developed. Typically, the quality of synergy decompositions is assessed by computing the Variance Accounted For (VAF). Yet, little is known about the extent to which the combination of those synergies encodes task-discriminating variations of muscle activity in individual trials. To address this question, here we conceive and develop a novel computational framework to evaluate muscle synergy decompositions in task space. Unlike previous methods considering the total variance of muscle patterns (VAF based metrics), our approach focuses on variance discriminating execution of different tasks. The procedure is based on single-trial task decoding from muscle synergy activation features. The task decoding based metric evaluates quantitatively the mapping between synergy recruitment and task identification and automatically determines the minimal number of synergies that captures all the task-discriminating variability in the synergy activations. In this paper, we first validate the method on plausibly simulated EMG datasets. We then show that it can be applied to different types of muscle synergy decomposition and illustrate its applicability to real data by using it for the analysis of EMG recordings during an arm pointing task. We find that time-varying and synchronous synergies with similar number of parameters are equally efficient in task decoding, suggesting that in this experimental paradigm they are equally valid representations of muscle synergies. Overall, these findings stress the effectiveness of the decoding metric in systematically assessing muscle synergy decompositions in task space.

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.