Dexterous manipulation: Differential sensitivity of manipulation and grasp forces to task requirements.

How humans coordinate digit forces to perform dexterous manipulation is not well understood. This gap is due to the use of tasks devoid of dexterity requirements and/or the use of analytical techniques that cannot isolate the roles that digit forces play in preventing object slip and controlling object position and orientation (pose). In our recent work, we used a dexterous manipulation task and decomposed digit forces into FG, the internal force that prevents object slip, and FM, the force responsible for object pose control. Unlike FG, FM was modulated from object lift onset to hold, suggesting their different sensitivity to sensory feedback acquired during object lift. However, the extent to which FG and FM can be controlled independently remains to be determined. Importantly, how FG and FM change as a function of object property is mathematically indeterminate and therefore requires active modulation. To address this gap, we systematically changed either object mass or external torque. The FM normal component responsible for object orientation control was modulated to changes in object torque but not mass. In contrast, FG was distinctly modulated to changes in object mass and torque. These findings point to a differential sensitivity of FG and FM to task requirements and provide novel insights into the neural control of dexterous manipulation. Importantly, our results indicate that the proposed digit force decomposition has the potential to capture important differences in how sensory inputs are processed and integrated to simultaneously ensure grasp stability and dexterous object pose control.

Transcranial focused ultrasound to human rIFG improves response inhibition through modulation of the P300 onset latency.

Response inhibition in humans is important to avoid undesirable behavioral action consequences. Neuroimaging and lesion studies point to a locus of inhibitory control in the right inferior frontal gyrus (rIFG). Electrophysiology studies have implicated a downstream event-related potential from rIFG, the fronto-central P300, as a putative neural marker of the success and timing of inhibition over behavioral responses. However, it remains to be established whether rIFG effectively drives inhibition and which aspect of P300 activity uniquely indexes inhibitory control-ERP timing or amplitude. Here, we dissect the connection between rIFG and P300 for inhibition by using transcranial-focused ultrasound (tFUS) to target rIFG of human subjects while they performed a Stop-Signal task. By applying tFUS simultaneously with different task events, we found behavioral inhibition was improved, but only when applied to rIFG simultaneously with a 'stop' signal. Improved inhibition through tFUS to rIFG was indexed by faster stopping times that aligned with significantly shorter N200/P300 onset latencies. In contrast, P300 amplitude was modulated during tFUS across all groups without a paired change in behavior. Using tFUS, we provide evidence for a causal connection between anatomy, behavior, and electrophysiology underlying response inhibition.

Distinct sensorimotor mechanisms underlie the control of grasp and manipulation forces for dexterous manipulation.

Dexterous manipulation relies on the ability to simultaneously attain two goals: controlling object position and orientation (pose) and preventing object slip. Although object manipulation has been extensively studied, most previous work has focused only on the control of digit forces for slip prevention. Therefore, it remains underexplored how humans coordinate digit forces to prevent object slip and control object pose simultaneously. We developed a dexterous manipulation task requiring subjects to grasp and lift a sensorized object using different grasp configurations while preventing it from tilting. We decomposed digit forces into manipulation and grasp forces for pose control and slip prevention, respectively. By separating biomechanically-obligatory from non-obligatory effects of grasp configuration, we found that subjects prioritized grasp stability over efficiency in grasp force control. Furthermore, grasp force was controlled in an anticipatory fashion at object lift onset, whereas manipulation force was modulated following acquisition of somatosensory and visual feedback of object's dynamics throughout object lift. Mathematical modeling of feasible manipulation forces further confirmed that subjects could not accurately anticipate the required manipulation force prior to acquisition of sensory feedback. Our experimental approach and findings open new research avenues for investigating neural mechanisms underlying dexterous manipulation and biomedical applications.

Evaluating the effect of non-invasive force feedback on prosthetic grasp force modulation in participants with and without limb loss.

Grasping an object is one of the most common and complex actions performed by humans. The human brain can adapt and update the grasp dynamics through information received from sensory feedback. Prosthetic hands can assist with the mechanical performance of grasping, however currently commercially available prostheses do not address the disruption of the sensory feedback loop. Providing feedback about a prosthetic hand's grasp force magnitude is a top priority for those with limb loss. This study tested a wearable haptic system, i.e., the Clenching Upper-Limb Force Feedback device (CUFF), which was integrated with a novel robotic hand (The SoftHand Pro). The SoftHand Pro was controlled with myoelectrics of the forearm muscles. Five participants with limb loss and nineteen able-bodied participants completed a constrained grasping task (with and without feedback) which required modulation of the grasp to reach a target force. This task was performed while depriving participants of incidental sensory sources (vision and hearing were significantly limited with glasses and headphones). The data were analyzed with Functional Principal Component Analysis (fPCA). CUFF feedback improved grasp precision for participants with limb loss who typically use body-powered prostheses as well as a sub-set of able-bodied participants. Further testing, that is more functional and allows participants to use all sensory sources, is needed to determine if CUFF feedback can accelerate mastery of myoelectric control or would benefit specific patient sub-groups.

Learning acquisition of consistent leader-follower relationships depends on implicit haptic interactions.

Are leaders made or born? Leader-follower roles have been well characterized in social science, but they remain somewhat obscure in sensory-motor coordination. Furthermore, it is unknown how and why leader-follower relationships are acquired, including innate versus acquired controversies. We developed a novel asymmetrical coordination task in which two participants (dyad) need to collaborate in transporting a simulated beam while maintaining its horizontal attitude. This experimental paradigm was implemented by twin robotic manipulanda, simulated beam dynamics, haptic interactions, and a projection screen. Clear leader-follower relationships were learned only when strong haptic feedback was introduced. This phenomenon occurred despite participants not being informed that they were interacting with each other and the large number of equally-valid alternative dyadic coordination strategies. We demonstrate the emergence of consistent leader-follower relationships in sensory-motor coordination, and further show that haptic interaction is essential for dyadic co-adaptation. These results provide insights into neural mechanisms responsible for the formation of leader-follower relationships in our society.

Distinct adaptation processes underlie multidigit force coordination for dexterous manipulation.

The human sensorimotor system can adapt to various changes in the environmental dynamics by updating motor commands to improve performance after repeated exposure to the same task. However, the characteristics and mechanisms of the adaptation process remain unknown for dexterous manipulation, a unique motor task in which the body physically interacts with the environment with multiple effectors, i.e., digits, in parallel. We addressed this gap by using robotic manipulanda to investigate the changes in the digit force coordination following mechanical perturbation of an object held by tripod grasps. As the participants gradually adapted to lifting the object under perturbations, we quantified two components of digit force coordination. One is the direction-specific manipulation moment that directly counteracts the perturbation, whereas the other one is the direction-independent internal moment that supports the stability and stiffness of the grasp. We found that trial-to-trial improvement of task performance was associated with increased manipulation moment and a gradual decrease of the internal moment. These two moments were characterized by different rates of adaptation. We also examined how these two force coordination components respond to changes in perturbation directions. Importantly, we found that the manipulation moment was sensitive to the extent of repetitive exposure to the previous context that has an opposite perturbation direction, whereas the internal moment did not. However, the internal moment was sensitive to whether the postchange perturbation direction was previously experienced. Our results reveal, for the first time, that two distinct processes underlie the adaptation of multidigit force coordination for dexterous manipulation.NEW & NOTEWORTHY Changes in digit force coordination in multidigit object manipulation were quantified with a novel experimental design in which human participants adapted to mechanical perturbations applied to the object. Our results show that the adaptation of digit force coordination can be characterized by two distinct components that operate at different timescales. We further show that these two components respond to changes in perturbation direction differently.

Modulation of cortical beta oscillations influences motor vigor: A rhythmic TMS-EEG study.

Previous electro- or magnetoencephalography (Electro/Magneto EncephaloGraphic; E/MEG) studies using a correlative approach have shown that ß (13-30 Hz) oscillations emerging in the primary motor cortex (M1) are implicated in regulating motor response vigor and associated with an anti-kinetic role, that is, slowness of movement. However, the functional role of M1 ß oscillations in regulation of motor responses remains unclear. To address this gap, we combined EEG with rhythmic TMS (rhTMS) delivered to M1 at the ß (20 Hz) frequency shortly before subjects performed an isometric ramp-and-hold finger force production task at three force levels. rhTMS is a novel approach that can modulate rhythmic patterns of neural activity. ß-rhTMS over M1 induced a modulation of neural oscillations to ß frequency in the sensorimotor area and reduced peak force rate during the ramp-up period relative to sham and catch trials. Interestingly, this rhTMS effect occurred only in the large force production condition. To distinguish whether the effects of rhTMS on EEG and behavior stemmed from phase-resetting by each magnetic pulse or neural entrainment by the periodicity of rhTMS, we performed a control experiment using arrhythmic TMS (arTMS). arTMS did not induce changes in EEG oscillations nor peak force rate during the rump-up period. Our results provide novel evidence that ß neural oscillations emerging the sensorimotor area influence the regulation of motor response vigor. Furthermore, our findings further demonstrate that rhTMS is a promising tool for tuning neural oscillations to the target frequency.

A low-dimensional representation of arm movements and hand grip forces in post-stroke individuals.

Characterizing post-stroke impairments in the sensorimotor control of arm and hand is essential to better understand altered mechanisms of movement generation. Herein, we used a decomposition algorithm to characterize impairments in end-effector velocity and hand grip force data collected from an instrumented functional task in 83 healthy control and 27 chronic post-stroke individuals with mild-to-moderate impairments. According to kinematic and kinetic raw data, post-stroke individuals showed reduced functional performance during all task phases. After applying the decomposition algorithm, we observed that the behavioural data from healthy controls relies on a low-dimensional representation and demonstrated that this representation is mostly preserved post-stroke. Further, it emerged that reduced functional performance post-stroke correlates to an abnormal variance distribution of the behavioural representation, except when reducing hand grip forces. This suggests that the behavioural repertoire in these post-stroke individuals is mostly preserved, thereby pointing towards therapeutic strategies that optimize movement quality and the reduction of grip forces to improve performance of daily life activities post-stroke.

Inter-personal motor interaction is facilitated by hand pairing.

The extent to which hand dominance may influence how each agent contributes to inter-personal coordination remains unknown. In the present study, right-handed human participants performed object balancing tasks either in dyadic conditions with each agent using one hand (left or right), or in bimanual conditions where each agent performed the task individually with both hands. We found that object load was shared between two hands more asymmetrically in dyadic than single-agent conditions. However, hand dominance did not influence how two hands shared the object load. In contrast, hand dominance was a major factor in modulating hand vertical movement speed. Furthermore, the magnitude of internal force produced by two hands against each other correlated with the synchrony between the two hands' movement in dyads. This finding supports the important role of internal force in haptic communication. Importantly, both internal force and movement synchrony were affected by hand dominance of the paired participants. Overall, these results demonstrate, for the first time, that pairing of one dominant and one non-dominant hand may promote asymmetrical roles within a dyad during joint physical interactions. This appears to enable the agent using the dominant hand to actively maintain effective haptic communication and task performance.

Synergistic Organization of Neural Inputs from Spinal Motor Neurons to Extrinsic and Intrinsic Hand Muscles.

Our current understanding of synergistic muscle control is based on the analysis of muscle activities. Modules (synergies) in muscle coordination are extracted from electromyographic (EMG) signal envelopes. Each envelope indirectly reflects the neural drive received by a muscle; therefore, it carries information on the overall activity of the innervating motor neurons. However, it is not known whether the output of spinal motor neurons, whose number is orders of magnitude greater than the muscles they innervate, is organized in a low-dimensional fashion when performing complex tasks. Here, we hypothesized that motor neuron activities exhibit a synergistic organization in complex tasks and therefore that the common input to motor neurons results in a large dimensionality reduction in motor neuron outputs. To test this hypothesis, we factorized the output spike trains of motor neurons innervating 14 intrinsic and extrinsic hand muscles and analyzed the dimensionality of control when healthy individuals exerted isometric forces using seven grip types. We identified four motor neuron synergies, accounting for >70% of the variance of the activity of 54.1 ± 12.9 motor neurons, and we identified four functionally similar muscle synergies. However, motor neuron synergies better discriminated individual finger forces than muscle synergies and were more consistent with the expected role of muscles actuating each finger. Moreover, in a few cases, motor neurons innervating the same muscle were active in separate synergies. Our findings suggest a highly divergent net neural inputs to spinal motor neurons from spinal and supraspinal structures, contributing to the dimensionality reduction captured by muscle synergies.SIGNIFICANCE STATEMENT We addressed whether the output of spinal motor neurons innervating multiple hand muscles could be accounted for by a modular organization, i.e., synergies, previously described to account for the coordination of multiple muscles. We found that motor neuron synergies presented similar dimensionality (implying a >10-fold reduction in dimensionality) and structure as muscle synergies. Nonetheless, the synergistic behavior of subsets of motor neurons within a muscle was also observed. These results advance our understanding of how neuromuscular control arises from mapping descending inputs to muscle activation signals. We provide, for the first time, insights into the organization of neural inputs to spinal motor neurons which, to date, has been inferred through analysis of muscle synergies.

Transfer and generalization of learned manipulation between unimanual and bimanual tasks.

Successful object manipulation, such as preventing object roll, relies on the modulation of forces and centers of pressure (point of application of digits on each grasp surface) prior to lift onset to generate a compensatory torque. Whether or not generalization of learned manipulation can occur after adding or removing effectors is not known. We examined this by recruiting participants to perform lifts in unimanual and bimanual grasps and analyzed results before and after transfer. Our results show partial generalization of learned manipulation occurred when switching from a (1) unimanual to bimanual grasp regardless of object center of mass, and (2) bimanual to unimanual grasp when the center of mass was on the thumb side. Partial generalization was driven by the modulation of effectors' center of pressure, in the appropriate direction but of insufficient magnitude, while load forces did not contribute to torque generation after transfer. In addition, we show that the combination of effector forces and centers of pressure in the generation of compensatory torque differ between unimanual and bimanual grasping. These findings highlight that (1) high-level representations of learned manipulation enable only partial learning transfer when adding or removing effectors, and (2) such partial generalization is mainly driven by modulation of effectors' center of pressure.

Visual Feedback of Object Motion Direction Influences the Timing of Grip Force Modulation During Object Manipulation.

During manipulation, object slipping is prevented by modulating the grip force (GF) in synchrony with motion-related inertial forces, i.e., load force (LF). However, due to conduction delays of the sensory system, GF must be modulated in advance based on predictions of LF changes. It has been proposed that such predictive force control relies on internal representations, i.e., internal models, of the relation between the dynamic of the environment and movement kinematics. Somatosensory and visual feedback plays a primary role in building these internal representations. For instance, it has been shown that manipulation-dependent somatosensory signals contribute to building internal representations of gravity in normal and altered gravitational contexts. Furthermore, delaying the timing of visual feedback of object displacement has been shown to affect GF. Here, we explored whether and the extent to which spatial features of visual feedback movement, such as motion direction, may contribute to GF control. If this were the case, a spatial mismatch between actual (somatosensory) and visual feedback of object motion would elicit changes in GF modulation. We tested this hypothesis by asking participants to generate vertical object movements while visual feedback of object position was congruent (0° rotation) or incongruent (180° or 90°) with the actual object displacement. The role of vision on GF control was quantified by the temporal shift of GF modulation as a function of visual feedback orientation and actual object motion direction. GF control was affected by visual feedback when this was incongruent in the vertical (180°), but not horizontal dimension. Importantly, 180° visual feedback rotation delayed and anticipated GF modulation during upward and downward actual movements, respectively. Our findings suggest that during manipulation, spatial features of visual feedback motion are used to predict upcoming LF changes. Furthermore, the present study provides evidence that an internal model of gravity contributes to GF control by influencing sensory reweighting processes during object manipulation.

Dexterous Object Manipulation Requires Context-Dependent Sensorimotor Cortical Interactions in Humans.

Dexterous object manipulation is a hallmark of human evolution and a critical skill for everyday activities. A previous work has used a grasping context that predominantly elicits memory-based control of digit forces by constraining where the object should be grasped. For this "constrained" grasping context, the primary motor cortex (M1) is involved in storage and retrieval of digit forces used in previous manipulations. In contrast, when choice of digit contact points is allowed ("unconstrained" grasping), behavioral studies revealed that forces are adjusted, on a trial-to-trial basis, as a function of digit position. This suggests a role of online feedback of digit position for force control. However, despite the ubiquitous nature of unconstrained hand-object interactions in activities of daily living, the underlying neural mechanisms are unknown. Using noninvasive brain stimulation, we found the role of primary motor cortex (M1) and somatosensory cortex (S1) to be sensitive to grasping context. In constrained grasping, M1 but not S1 is involved in storing and retrieving learned digit forces and position. In contrast, in unconstrained grasping, M1 and S1 are involved in modulating digit forces to position. Our findings suggest that the relative contribution of memory and online feedback modulates sensorimotor cortical interactions for dexterous manipulation.

Regression-based reconstruction of human grip force trajectories with noninvasive scalp electroencephalography.

OBJECTIVE: Robotic devices show promise in restoring motor abilities to individuals with upper limb paresis or amputations. However, these systems are still limited in obtaining reliable signals from the human body to effectively control them. We propose that these robotic devices can be controlled through scalp electroencephalography (EEG), a neuroimaging technique that can capture motor commands through brain rhythms. In this work, we studied if EEG can be used to predict an individual's grip forces produced by the hand. APPROACH: Brain rhythms and grip forces were recorded from able-bodied human subjects while they performed an isometric force production task and a grasp-and-lift task. Grip force trajectories were reconstructed with a linear model that incorporated delta band (0.1-1 Hz) voltage potentials and spectral power in the theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz), low gamma (30-50 Hz), mid gamma (70-110 Hz), and high gamma (130-200 Hz) bands. Trajectory reconstruction models were trained and tested through 10-fold cross validation. MAIN RESULTS: Modest accuracies were attained in reconstructing grip forces during isometric force production (median r = 0.42), and the grasp-and-lift task (median r = 0.51). Predicted trajectories were also analyzed further to assess the linear models' performance based on task requirements. For the isometric force production task, we found that predicted grip trajectories did not yield static grip forces that were distinguishable in magnitude across three task conditions. For the grasp-and-lift task, we estimate there would be an approximate 25% error in distinguishing when a user wants to hold or release an object. SIGNIFICANCE: These findings indicate that EEG, a noninvasive neuroimaging modality, has predictive information in neural features associated with finger force control and can potentially contribute to the development of brain machine interfaces (BMI) for performing activities of daily living.

Motor modules account for active perception of force.

Despite longstanding evidence suggesting a relation between action and perception, the mechanisms underlying their integration are still unclear. It has been proposed that to simplify the sensorimotor integration processes underlying active perception, the central nervous system (CNS) selects patterns of movements aimed at maximizing sampling of task-related sensory input. While previous studies investigated the action-perception loop focusing on the role of higher-level features of motor behavior (e.g., kinematic invariants, effort), the present study explored and quantified the contribution of lower-level organization of motor control. We tested the hypothesis that the coordinated recruitment of group of muscles (i.e., motor modules) engaged to counteract an external force contributes to participants' perception of the same force. We found that: 1) a model describing the modulation of a subset of motor modules involved in the motor task accounted for about 70% of participants' perceptual variance; 2) an alternative model, incompatible with the motor modules hypothesis, accounted for significantly lower variance of participants' detection performance. Our results provide empirical evidence of the potential role played by muscle activation patterns in active perception of force. They also suggest that a modular organization of motor control may mediate not only coordination of multiple muscles, but also perceptual inference.

Hand forces and placement are modulated and covary during anticipatory control of bimanual manipulation.

Dexterous object manipulation relies on the feedforward and feedback control of kinetics (forces) and kinematics (hand shaping and digit placement). Lifting objects with an uneven mass distribution involves the generation of compensatory moments at object lift-off to counter object torques. This is accomplished through the modulation and covariation of digit forces and placement, which has been shown to be a general feature of unimanual manipulation. These feedforward anticipatory processes occur before performance-specific feedback. Whether this adaptation is a feature unique to unimanual dexterous manipulation or general across unimanual and bimanual manipulation is not known. We investigated the generation of compensatory moments through hand placement and force modulation during bimanual manipulation of an object with variable center of mass. Participants were instructed to prevent object roll during the lift. Similar to unimanual grasping, we found modulation and covariation of hand forces and placement for successful performance. Thus this motor adaptation of the anticipatory control of compensatory moment is a general feature across unimanual and bimanual effectors. Our results highlight the involvement of high-level representation of manipulation goals and underscore a sensorimotor circuitry for anticipatory control through a continuum of force and placement modulation of object manipulation across a range of effectors. NEW & NOTEWORTHY This is the first study, to our knowledge, to show that successful bimanual manipulation of objects with asymmetrical centers of mass is performed through the modulation and covariation of hand forces and placements to generate compensatory moments. Digit force-to-placement modulation is thus a general phenomenon across multiple effectors, such as the fingers of one hand, and both hands. This adds to our understanding of integrating low-level internal representations of object properties into high-level task representations.

Inter-Limb Transfer of Grasp Force Perception With Closed-Loop Hand Prosthesis.

Sensory feedback of grasp forces provides important information about physical interactions between the hand and objects, enabling both reactive and anticipatory neural control mechanisms. The numerous studies have shown artificial sensory feedback of various forms improves force control during grasping tasks by prosthetic hand users through a closed-feedback loop. However, little is known about how perceptual information is transferred between an intact limb and a closed-loop prosthetic limb, and the extent to which training inter-limb transfer may improve myoelectric prosthetic control. We addressed these gaps by using a contralateral force-matching task in which able-bodied participants were asked to generate grasp forces with their native hand, and then match it using the contralateral hand or a soft-synergy prosthetic hand worn on the contralateral arm that was coupled with a mechanotactile feedback device. We found that absolute matching error and matching time were greater when using the prosthetic system than the native hand. However, with contralateral specific training, subjects were able to produce similar relative matching error with the prosthetic system and the native hand, especially at the untrained force level. These findings suggest that an association can be established between the perception produced by the prosthetic limb and the contralateral intact limb, and provide novel insights about potential applications to training and design of the closed-loop prosthesis.

Linear Integration of Tactile and Non-tactile Inputs Mediates Estimation of Fingertip Relative Position.

While skin, joints and muscles receptors alone provide lower level information about individual variables (e.g., exerted limb force and limb displacement), the distance between limb endpoints (i.e., relative position) has to be extracted from high level integration of somatosensory and motor signals. In particular, estimation of fingertip relative position likely involves more complex sensorimotor transformations than those underlying hand or arm position sense: the brain has to estimate where each fingertip is relative to the hand and where fingertips are relative to each other. It has been demonstrated that during grasping, feedback of digit position drives rapid adjustments of fingers force control. However, it has been shown that estimation of fingertips' relative position can be biased by digit forces. These findings raise the question of how the brain combines concurrent tactile (i.e., cutaneous mechanoreceptors afferents induced by skin pressure and stretch) and non-tactile (i.e., both descending motor command and joint/muscle receptors signals associated to muscle contraction) digit force-related inputs for fingertip distance estimation. Here we addressed this question by quantifying the contribution of tactile and non-tactile force-related inputs for the estimation of fingertip relative position. We asked subjects to match fingertip vertical distance relying only on either tactile or non-tactile inputs from the thumb and index fingertip, and compared their performance with the condition where both types of inputs were combined. We found that (a) the bias in the estimation of fingertip distance persisted when tactile inputs and non-tactile force-related signals were presented in isolation; (b) tactile signals contributed the most to the estimation of fingertip distance; (c) linear summation of the matching errors relying only on either tactile or non-tactile inputs was comparable to the matching error when both inputs were simultaneously available. These findings reveal a greater role of tactile signals for sensing fingertip distance and suggest a linear integration mechanism with non-tactile inputs for the estimation of fingertip relative position.