Flexible Control of Safety Margins for Action Based on Environmental Variability

The cerebellum acts as the analog to the medial temporal lobe for sensorimotor memory

The cerebellum is critical for sensorimotor learning. The specific contribution that it makes, however, remains unclear. Inspired by the classic finding that for declarative memories, medial temporal lobe (MTL) structures provide a gateway to the formation of long-term memory but are not required for short-term memory, we hypothesized that for sensorimotor memories, the cerebellum may play an analogous role. Here, we studied the sensorimotor learning of individuals with severe ataxia from cerebellar degeneration. We dissected the memories they formed during sensorimotor learning into a short-term temporally-volatile component, that decays rapidly with a time constant of just 15 to 20 s and thus cannot lead to long-term retention, and a longer-term temporally-persistent component that is stable for 60 s or more and leads to long-term retention. Remarkably, we find that these individuals display dramatically reduced levels of temporally-persistent sensorimotor memory, despite spared and even elevated levels of temporally-volatile sensorimotor memory. In particular, we find both impairment that systematically worsens with memory window duration over shorter memory windows (<12 s) and near-complete impairment of memory maintenance over longer memory windows (>25 s). This dissociation uncovers a unique role for the cerebellum as a gateway for the formation of long-term but not short-term sensorimotor memories, mirroring the role of the MTL for declarative memories. It thus reveals the existence of distinct neural substrates for short-term and long-term sensorimotor memory, and it explains both the trial-to-trial differences identified in this study and long-standing study-to-study differences in the effects of cerebellar damage on sensorimotor learning ability.

Distribution of control during bimanual movement and stabilization

In two-handed actions like baseball batting, the brain can allocate the control to each arm in an infinite number of ways. According to hemispheric specialization theory, the dominant hemisphere is adept at ballistic control, while the non-dominant hemisphere is specialized at postural stabilization, so the brain should divide the control between the arms according to their respective specialization. Here, we tested this prediction by examining how the brain shares the control between the dominant and non-dominant arms during bimanual reaching and postural stabilization. Participants reached with both hands, which were tied together by a stiff virtual spring, to a target surrounded by an unstable repulsive force field. If the brain exploits each hemisphere's specialization, then the dominant arm should be responsible for acceleration early in the movement, and the non-dominant arm will be the prime actor at the end when holding steady against the force field. The power grasp force, which signifies the postural stability of each arm, peaked at movement termination but was equally large in both arms. Furthermore, the brain predominantly used the arm that could use the stronger flexor muscles to mainly accelerate the movement. These results point to the brain flexibly allocating the control to each arm according to the task goal without adhering to a strict specialization scheme.

From neural noise to co-adaptability: Rethinking the multifaceted architecture of motor variability

In the last decade, the source and the functional meaning of motor variability have attracted considerable attention in behavioral and brain sciences. This construct classically combined different levels of description, variable internal robustness or coherence, and multifaceted operational meanings. We provide here a comprehensive review of the literature with the primary aim of building a precise lexicon that goes beyond the generic and monolithic use of motor variability. In the pars destruens of the work, we model three domains of motor variability related to peculiar computational elements that influence fluctuations in motor outputs. Each domain is in turn characterized by multiple sub-domains. We begin with the domains of noise and differentiation. However, the main contribution of our model concerns the domain of adaptability, which refers to variation within the same exact motor representation. In particular, we use the terms learning and (social)fitting to specify the portions of motor variability that depend on our propensity to learn and on our largely constitutive propensity to be influenced by external factors. A particular focus is on motor variability in the context of the sub-domain named co-adaptability. Further groundbreaking challenges arise in the modeling of motor variability. Therefore, in a separate pars construens, we attempt to characterize these challenges, addressing both theoretical and experimental aspects as well as potential clinical implications for neurorehabilitation. All in all, our work suggests that motor variability is neither simply detrimental nor beneficial, and that studying its fluctuations can provide meaningful insights for future research.

Sensory prediction error drives subconscious motor learning outside of the laboratory

Sensorimotor adaptation is supported by at least two parallel learning systems: an intentionally controlled explicit strategy and an involuntary implicit learning system. Past work focused on constrained reaches or finger movements in laboratory environments has shown subconscious learning systems to be driven in part by sensory prediction error (SPE), i.e., the mismatch between the realized and expected outcome of an action. We designed a ball rolling task to explore whether SPEs can drive implicit motor adaptation during complex whole body movements that impart physical motion on external objects. After applying a visual shift, participants rapidly adapted their rolling angles to reduce the error between the ball and the target. We removed all visual feedback and told participants to aim their throw directly toward the primary target, revealing an unintentional 5.06° implicit adjustment to reach angles that decayed over time. To determine whether this implicit adaptation was driven by SPE, we gave participants a second aiming target that would "solve" the visual shift, as in the study by Mazzoni and Krakauer (Mazzoni P, Krakauer JW. J Neurosci 26: 3642-3645, 2006). Remarkably, after rapidly reducing ball-rolling error to zero (due to enhancements in strategic aiming), the additional aiming target caused rolling angles to deviate beyond the primary target by 3.15°. This involuntary overcompensation, which worsened task performance, is a hallmark of SPE-driven implicit learning. These results show that SPE-driven implicit processes, previously observed within simplified finger or planar reaching movements, actively contribute to motor adaptation in more complex naturalistic skill-based tasks.NEW & NOTEWORTHY Implicit and explicit learning systems have been detected using simple, constrained movements inside the laboratory. How these systems impact movements during complex whole body, skill-based tasks has not been established. Here, we demonstrate that sensory prediction errors significantly impact how a person updates their movements, replicating findings from the laboratory in an unconstrained ball-rolling task. This real-world validation is an important step toward explaining how subconscious learning helps humans execute common motor skills in dynamic environments.

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.

The nervous system tunes sensorimotor gains when reaching in variable mechanical environments

Humans often move in the presence of mechanical disturbances that can vary in direction and amplitude throughout movement. These disturbances can jeopardize the outcomes of our actions, such as when drinking from a glass of water on a turbulent flight or carrying a cup of coffee while walking on a busy sidewalk. Here, we examine control strategies that allow the nervous system to maintain performance when reaching in the presence of mechanical disturbances that vary randomly throughout movement. Healthy participants altered their control strategies to make movements more robust against disturbances. The change in control was associated with faster reaching movements and increased responses to proprioceptive and visual feedback that were tuned to the variability of the disturbances. Our findings highlight that the nervous system exploits a continuum of control strategies to increase its responsiveness to sensory feedback when reaching in the presence of increasingly variable physical disturbances.

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.

The effects of explicit and implicit information on modulation of corticospinal excitability during hand-object interactions

Fingertip force scaling during hand-object interactions typically relies on visual information about the object and sensorimotor memories from previous object interactions. Here, we investigated whether contextual information, that is not explicitly linked to the intrinsic object properties (e.g., size or weight) but that is informative for motor control requirements, can mediate force scaling. For this, we relied on two separate behavioral tasks during which we applied transcranial magnetic stimulation (TMS) to probe corticospinal excitability (CSE), as a window onto the primary motor cortex role in controlling fingertip forces. In experiment 1, participants performed a force tracking task, where we manipulated available implicit and explicit visual information. That is, either the force target was fully visible, or only the force error was displayed as a deviation from a horizontal line. We found that participants' performance was better when the force target was fully visible, i.e., when they had explicit access to predictive information. However, we did not find differences in CSE modulation based on the type of visual information. On the other hand, CSE was modulated by the change in muscle contraction, i.e., contraction vs. relaxation and fast vs. slow changes. In sum, these findings indicate that CSE only reflects the ongoing motor command. In experiment 2, other participants performed a sequential object lifting task of visually identical objects that were differently weighted, in a seemingly random order. Within this task, we hid short series of incrementally increasing object weights. This allowed us to investigate whether participants would scale their forces for specific object weights based on the previously lifted object (i.e., sensorimotor effect) or based on the implicit information about the hidden series of incrementally increasing weights (i.e., extrapolation beyond sensorimotor effects). Results showed that participants did not extrapolate fingertip forces based on the hidden series but scaled their forces solely on the previously lifted object. Unsurprisingly, CSE was not modulated differently when lifting series of random weights versus series of increasing weights. Altogether, these results in two different grasping tasks suggest that CSE encodes ongoing motor components but not sensorimotor cues that are hidden within contextual information.

Expectation of volitional arm movement has prolonged effects on the grip force exerted on a pinched object

Humans closely coordinate the grip force exerted on a hand-held object with changes in the load arising from the object's dynamics. Recent work suggests the grip force is responsive to the predictability of the load forces as well. The well-known grip-force-load-force coupling is intermittent when the load arising from volitional movements fluctuates predictably, whereas grip force increases when loads are unpredictable. Here, we studied the influence of expected but uncertain volitional movements on the digit forces during a static grasp. Young, healthy participants used a pinch grasp to hold an instrumented object and track visual targets by moving the object. We quantified the mean grip force, the temporal decline in grip force (slacking), and the coupling between the pressing digit forces that yield the grip force during static prehension with no expectation of movement, and during the static phase of a choice reaction time task, when the participant expected to move the object after a variable duration. Simply expecting to move the object led to sustained (for at least 5 s) higher magnitude and lower slacking in the grip force, and weaker coupling between the pressing digit forces. These effects were modulated by the direction of the expected movement and the object's mass. The changes helped to maintain the safety margin for the current grasp and likely facilitated the transition from static to dynamic object manipulation. Influence of expected actions on the current grasp may have implications for manual dexterity and its well-known loss with age.

Efficient tactile encoding of object slippage

When grasping objects, we rely on our sense of touch to adjust our grip and react against external perturbations. Less than 200 ms after an unexpected event, the sensorimotor system is able to process tactile information to deduce the frictional strength of the contact and to react accordingly. Given that roughly 1,300 afferents innervate the fingertips, it is unclear how the nervous system can process such a large influx of data in a sufficiently short time span. In this study, we measured the deformation of the skin during the initial stages of incipient sliding for a wide range of frictional conditions. We show that the dominant patterns of deformation are sufficient to estimate the distance between the frictional force and the frictional strength of the contact. From these stereotypical patterns, a classifier can predict if an object is about to slide during the initial stages of incipient slip. The prediction is robust to the actual value of the interfacial friction, showing sensory invariance. These results suggest the existence of a possible compact set of bases that we call Eigenstrains. These Eigenstrains are a potential mechanism to rapidly decode the margin from full slip from the tactile information contained in the deformation of the skin. Our findings suggest that only 6 of these Eigenstrains are necessary to classify whether the object is firmly stuck to the fingers or is close to slipping away. These findings give clues about the tactile regulation of grasp and the insights are directly applicable to the design of robotic grippers and prosthetics that rapidly react to external perturbations.

Force Control During the Precision Grip Translates to Virtual Reality

When grasping and manipulating objects we implicitly adapt grip forces according to the physical parameters of the object. We integrate visual, cutaneous, and force feedback to estimate these parameters and adapt our control accordingly. Using virtual reality, both feedback integration and control can be investigated in ways that are not possible using real-life objects. Here, we present our custom-built virtual reality setup and show its validity for use in human studies of fine motor control. Participants grasped and lifted virtual objects with different weights. We show that, consistent with lifting real objects, all participants adapt their grip forces to the object mass, and do so on a trial-by-trial basis. Compared to similar studies with real objects and full feedback, grip forces were increased, and adaptation required more trials. This study successfully demonstrated that grip force control in the precision grip translates to virtual reality. While our setup can be used for similar work in the future, subsequent virtual reality experiments should include a longer adaptation phase compared to classic setups.

Stability of inverted pendulum reveals transition between predictive control and impedance control in grip force modulation

During object manipulation, our sensorimotor sys-tem needs to represent the objects dynamics in order to better control it. This is especially important in the case of grip force control where small forces can cause the object to slip from our fingers, and excessive forces can cause fatigue or even damage the object. While the tradeoff between these two constraints is clear for stable objects, such as lifting a soda can, it is less clear how the sensorimotor system adjusts the grip force for unstable objects. For this purpose, we measured the change in the grip force of individual human participants while they stabilize five different lengths of an inverted pendulum. These lengths set different dynamics of the pendulum, ranging in their degree of controllability. We observed two main states during such manipulation, a marginally stable state of the pendulum and a stabilization state in which participants acted to stabilize the system. While during the stabilization state participants increased their applied grip force, for the stable state we observed a mixed behaviour. For small and less controllable pendulums, grip force increased while for larger pendulums, participants could modulate the the grip force according to the anticipated load forces. Based on these results, we suggest that the pendulum dynamics change the control strategy between predictive control and impedance control.

Motor planning under uncertainty

Actions often require the selection of a specific goal amongst a range of possibilities, like when a softball player must precisely position her glove to field a fast-approaching ground ball. Previous studies have suggested that during goal uncertainty the brain prepares for all potential goals in parallel and averages the corresponding motor plans to command an intermediate movement that is progressively refined as additional information becomes available. Although intermediate movements are widely observed, they could instead reflect a neural decision about the single best action choice given the uncertainty present. Here we systematically dissociate these possibilities using novel experimental manipulations and find that when confronted with uncertainty, humans generate a motor plan that optimizes task performance rather than averaging potential motor plans. In addition to accurate predictions of population-averaged changes in motor output, a novel computational model based on this performance-optimization theory accounted for a majority of the variance in individual differences between participants. Our findings resolve a long-standing question about how the brain selects an action to execute during goal uncertainty, providing fundamental insight into motor planning in the nervous system.

Grip Force Control During Virtual Interaction With Deformable and Rigid Objects Via a Haptic Gripper

Most studies of grip force control focus on the manipulation of rigid objects. However, in virtual and teleoperation applications, objects are often elastic in the pinch degree-of-freedom, and are manipulated using a handle that presents haptic feedback to the user. When designing controllers for haptic grippers, it is crucial to understand how grip force is controlled when manipulating rigid and deformable objects. Here, we used a virtual teleoperation setup with a haptic gripper interface to investigate grip force control in virtual environments. Ten participants lifted virtual objects and performed vertical, cyclic motions using a haptic gripper. We manipulated the control signal to the virtual interface, the haptic properties of the gripper, and the visual properties of the virtual objects to test their effect on the grip force control. We found that participants modulated their grip force as a function of the anticipated load force in all of the experimental conditions. The control signal and properties of the haptic gripper, but not the visual properties of the objects, affected the baseline and the extent of the grip force modulation. These results can provide design guidelines for haptic grippers that elicit natural grasping in virtual and bilateral teleoperation applications.

The Effect of Variability in Stiffness on Perception and Grip Force Adjustment

Haptic information can be used to create our perception of the stiffness of objects and to regulate grip force. Introducing noise into sensory inputs can create uncertainty, yet a method of creating haptic uncertainty without distorting the haptic information has yet to be discovered. Toward this end, in this article, we investigated the effect of varying haptic information between consecutive interactions with an elastic force field on stiffness perception and grip force control. In a stiffness discrimination task, participants interacted with force fields multiple times. Low, medium, and high variability levels were created by drawing the stiffness level applied in each consecutive interaction within a trial from normal distributions. Perceptual haptic uncertainty was created only by the medium variability level. Moreover, all the variability levels affected the grip force control: the modulation of the grip force with the load force decreased with repeated interactions with the force field, whereas no change in the baseline grip force was observed. Additionally, we ascertained that participants formed their perceived stiffness by calculating a weighted average of the different stiffness levels applied by a given force field. We conclude that the medium variability level can be effective in inducing uncertainty in both perception and action.

Design of a fuzzy safety margin derivation system for grip force control of robotic hand in precision grasp task

In this study, the aim was to grasp and lift an unknown object without causing any permanent change on its shape using a robotic hand. When people lift objects, they add extra force for safety above the minimum limit value of the grasp force. This extra force is expressed as the “safety margin” in the literature. In the conducted study, the safety margin is minimized and the grasp force was controlled. For this purpose, the safety margin performance of human beings for object grasping was measured by the developed system. The obtained data were assessed for a fuzzy logic controller (FLC), and the fuzzy safety margin derivation system (SMDS) was designed. In the literature, the safety margin rate was reported to vary between 10% and 40%. To be the basis for this study, in the experimental study conducted to measure the grip performance of humans, safety margin ratios ranging from 9% to 20% for different surface friction properties and different weights were obtained. As a result of performance tests performed in Matlab/Simulink environment of FLC presented in this study, safety margin ratios ranging from 8% to 21% for different surface friction properties and weights were obtained. It was observed that the results of the performance tests of the developed system were very close to the data of human performance. The results obtained demonstrate that the designed fuzzy SMDS can be used safely in the control of the grasp force for the precise grasping task of a robot hand.

Did We Get Sensorimotor Adaptation Wrong? Implicit Adaptation as Direct Policy Updating Rather than Forward-Model-Based Learning

The human motor system can rapidly adapt its motor output in response to errors. The prevailing theory of this process posits that the motor system adapts an internal forward model that predicts the consequences of outgoing motor commands and uses this forward model to plan future movements. However, despite clear evidence that adaptive forward models exist and are used to help track the state of the body, there is no definitive evidence that such models are used in movement planning. An alternative to the forward-model-based theory of adaptation is that movements are generated based on a learned policy that is adjusted over time by movement errors directly ("direct policy learning"). This learning mechanism could act in parallel with, but independent of, any updates to a predictive forward model. Forward-model-based learning and direct policy learning generate very similar predictions about behavior in conventional adaptation paradigms. However, across three experiments with human participants (N = 47, 26 female), we show that these mechanisms can be dissociated based on the properties of implicit adaptation under mirror-reversed visual feedback. Although mirror reversal is an extreme perturbation, it still elicits implicit adaptation; however, this adaptation acts to amplify rather than to reduce errors. We show that the pattern of this adaptation over time and across targets is consistent with direct policy learning but not forward-model-based learning. Our findings suggest that the forward-model-based theory of adaptation needs to be re-examined and that direct policy learning provides a more plausible explanation of implicit adaptation.SIGNIFICANCE STATEMENT The ability of our brain to adapt movements in response to error is one of the most widely studied phenomena in motor learning. Yet, we still do not know the process by which errors eventually result in adaptation. It is known that the brain maintains and updates an internal forward model, which predicts the consequences of motor commands, and the prevailing theory of motor adaptation posits that this updated forward model is responsible for trial-by-trial adaptive changes. Here, we question this view and show instead that adaptation is better explained by a simpler process whereby motor output is directly adjusted by task errors. Our findings cast doubt on long-held beliefs about adaptation.

Distinct adaptation patterns between grip dynamics and arm kinematics when the body is upside-down

In humans, practically all movements are learnt and performed in a constant gravitational field. Yet, studies on arm movements and object manipulation in parabolic flight have highlighted very fast sensorimotor adaptations to altered gravity environments. Here, we wondered if the motor adjustments observed in those altered gravity environments could also be observed on Earth in a situation where the body is upside-down. To address this question, we asked participants to perform rhythmic arm movements in two different body postures (right-side-up and upside-down) while holding an object in precision grip. Analyses of grip-load force coordination and of movement kinematics revealed distinct adaptation patterns between grip and arm control. Grip force and load force were tightly synchronized from the first movements performed in upside-down posture, reflecting a malleable allocentric grip control. In contrast, velocity profiles showed a more progressive adaptation to the upside-down posture and reflected an egocentric planning of arm kinematics. In addition to suggesting distinct mechanisms between grip dynamics and arm kinematics for adaptation to novel contexts, these results also suggest the existence of general mechanisms underlying gravity-dependent motor adaptation that can be used for fast sensorimotor coordination across different postures on Earth and, incidentally, across different gravitational conditions in parabolic flights, in human centrifuges, or in Space.NEW & NOTEWORTHY During rhythmic arm movements performed in an upside-down posture, grip control adapted very quickly, but kinematics adaptation was more progressive. Our results suggest that grip control and movement kinematics planning might operate in different reference frames. Moreover, by comparing our results with previous results from parabolic flight studies, we propose that a common mechanism underlies adaptation to unfamiliar body postures and adaptation to altered gravity.

Predictive sensorimotor control in autism

Autism spectrum disorder has been characterized by atypicalities in how predictions and sensory information are processed in the brain. To shed light on this relationship in the context of sensorimotor control, we assessed prediction-related measures of cognition, perception, gaze and motor functioning in a large general population (n = 92; Experiment 1) and in clinically diagnosed autistic participants (n = 29; Experiment 2). In both experiments perception and action were strongly driven by prior expectations of object weight, with large items typically predicted to weigh more than equally-weighted smaller ones. Interestingly, these predictive action models were used comparably at a sensorimotor level in both autistic and neurotypical individuals with varying levels of autistic-like traits. Specifically, initial fingertip force profiles and resulting action kinematics were both scaled according to participants' pre-lift heaviness estimates, and generic visual sampling behaviours were notably consistent across groups. These results suggest that the weighting of prior information is not chronically underweighted in autism, as proposed by simple Bayesian accounts of the disorder. Instead, our results cautiously implicate context-sensitive processing mechanisms, such as precision modulation and hierarchical volatility inference. Together, these findings present novel implications for both future scientific investigations and the autism community.

A review of the neurobiomechanical processes underlying secure gripping in object manipulation

O'SHEA, H. and S. J. Redmond. A review of the neurobiomechanical processes underlying secure gripping in object manipulation. NEUROSCI BIOBEHAV REV 286-300, 2021. Humans display skilful control over the objects they manipulate, so much so that biomimetic systems have yet to emulate this remarkable behaviour. Two key control processes are assumed to facilitate such dexterity: predictive cognitive-motor processes that guide manipulation procedures by anticipating action outcomes; and reactive sensorimotor processes that provide important error-based information for movement adaptation. Notwithstanding increased interdisciplinary research interest in object manipulation behaviour, the complexity of the perceptual-sensorimotor-cognitive processes involved and the theoretical divide regarding the fundamentality of control mean that the essential mechanisms underlying manipulative action remain undetermined. In this paper, following a detailed discussion of the theoretical and empirical bases for understanding human dexterous movement, we emphasise the role of tactile-related sensory events in secure object handling, and consider the contribution of certain biophysical and biomechanical phenomena. We aim to provide an integrated account of the current state-of-art in skilled human-object interaction that bridges the literature in neuroscience, cognitive psychology, and biophysics. We also propose novel directions for future research exploration in this area.

The coordination between digit forces is altered by anticipated changes in prehensile movement patterns

Stability is the ability of a system to maintain a desired static or dynamic motor pattern. Maneuverability, on the other hand, is the ability to transition between motor patterns, and it is antagonistic to stability. Animals frequently reduce the stability of an ongoing task to facilitate anticipated movement transitions. Such stability-maneuverability tradeoffs are observed in human locomotion. However, the notion applies to other behaviors and this paper reports the first study on the stability-maneuverability tradeoff in human prehension. We tested if the coordination between the digit forces during the manipulation of a hand-held object is altered in response to an expected change in the manipulation pattern. We focused on the coupling between the grip and the load force and between the opposing forces exerted by the thumb and the four fingers, and on the transition from rhythmic vertical oscillation to non-vertical oscillation of the object. The nature of these couplings depends on the oscillation direction. Therefore, the stability-maneuverability tradeoff predicts that an expected volitional change to the object's movement will diminish the strength of these couplings so that the force patterns generating the current movement can efficiently transition into new ones that generate the new movement. The strength of the grip-load coupling did not alter in tasks that required a change in movement compared to tasks that did not. We speculate that participants preferred safety over maneuverability and maintained the grip-load coupling strength to counter high inertial loads and avoid object slip. In contrast, the strength of the coupling between the thumb and the four fingers' opposing forces reduced in tasks that required a change in movement compared to tasks that did not. Thus, the stability-reduction aspect of the stability-maneuverability tradeoff occurs in prehensile behavior. Future work should focus on associating the reduction in stability with gains in maneuverability, and on developing a comprehensive account of this tradeoff in prehensile tasks.

Stretching the skin immediately enhances perceived stiffness and gradually enhances the predictive control of grip force

When manipulating objects, we use kinesthetic and tactile information to form an internal representation of their mechanical properties for cognitive perception and for preventing their slippage using predictive control of grip force. A major challenge in understanding the dissociable contributions of tactile and kinesthetic information to perception and action is the natural coupling between them. Unlike previous studies that addressed this question either by focusing on impaired sensory processing in patients or using local anesthesia, we used a behavioral study with a programmable mechatronic device that stretches the skin of the fingertips to address this issue in the intact sensorimotor system. We found that artificial skin-stretch increases the predictive grip force modulation in anticipation of the load force. Moreover, the stretch causes an immediate illusion of touching a harder object that does not depend on the gradual development of the predictive modulation of grip force.

Muscle synergy for upper limb damping behavior during object transport while walking in healthy young individuals

Transporting an object during locomotion is one of the most common activities humans perform. Previous studies have shown that continuous and predictive control of grip force, along with the inertial load force of the object, is required to complete this task successfully. Another possible CNS strategy to ensure the dynamic stability of the upper limb is to modify the apparent stiffness and damping via altered muscle activation patterns. In this study, the term damping was used to describe a reduction in upper limb vertical oscillation amplitude to maintain the orientation of the hand-held object. The goal of this study was to identify the neuromuscular strategy for controlling the upper limb during object transport while walking. Three-dimensional kinematic and surface electromyography (EMG) data were recorded from eight, right-handed, healthy young adults who were instructed to walk on a treadmill while carrying an object in their dominant/non-dominant hand, with dominant/non-dominant arm positioning but without an object, and without any object or instructed arm-positioning. EMG recordings from the dominant and non-dominant arms were decomposed separately into underlying muscle synergies using non-negative matrix factorization (NNMF). Results revealed that the dominant arm showed higher damping compared to the non-dominant arm. All muscles showed higher mean levels of activation during object transport except for posterior deltoid (PD), with activation peaks occurring around or slightly before heel contact. The muscle synergy analysis revealed an anticipatory stabilization of the shoulder and elbow joints through a proximal-to-distal muscle activation pattern. These activations appear to play an essential role in maintaining the stability of the carried object in addition to the adjustment of grip force against the perturbations caused by heel contact during walking.

Sensory information from a slipping object elicits a rapid and automatic shoulder response

Humans have the remarkable ability to hold, grasp, and manipulate objects. Previous work has reported rapid and coordinated reactions in hand and shoulder muscles in response to external perturbations to the arm during object manipulation; however, little is known about how somatosensory feedback of an object slipping in the hand influences responses of the arm. We built a handheld device to stimulate the sensation of slipping at all five fingertips. The device was integrated into an exoskeleton robot that supported it against gravity. The setup allowed us to decouple somatosensory stimulation in the fingers from forces applied to the arm, two variables that are highly interdependent in real-world scenarios. Fourteen participants performed three experiments in which we measured their arm feedback responses during slip stimulation. Slip stimulations were applied horizontally in one of two directions, and participants were instructed to either follow the slip direction or move the arm in the opposite direction. Participants showed shoulder muscle responses within ∼67 ms of slip onset when following the direction of slip but significantly slower responses when instructed to move in the opposite direction. Shoulder responses were modulated by the speed but not the distance of the slip. Finally, when slip stimulation was combined with mechanical perturbations to the arm, we found that sensory information from the fingertips significantly modulated the shoulder feedback responses. Overall, the results demonstrate the existence of a rapid feedback system that stabilizes handheld objects.NEW & NOTEWORTHY We tested whether the sensation of an object slipping from the fingers modulates shoulder feedback responses. We found rapid shoulder feedback responses when participants were instructed to follow the slip direction with the arm. Shoulder responses following mechanical joint perturbations were also potentiated when combined with slipping. These results demonstrate the existence of fast and automatic feedback responses in the arm in reaction to sensory input to the fingertips that maintain grip on handheld objects.

The effect of tactile augmentation on manipulation and grip force control during force-field adaptation

Background

When exposed to a novel dynamic perturbation, participants adapt by changing their movements’ dynamics. This adaptation is achieved by constructing an internal representation of the perturbation, which allows for applying forces that compensate for the novel external conditions. To form an internal representation, the sensorimotor system gathers and integrates sensory inputs, including kinesthetic and tactile information about the external load. The relative contribution of the kinesthetic and tactile information in force-field adaptation is poorly understood.

Methods

In this study, we set out to establish the effect of augmented tactile information on adaptation to force-field. Two groups of participants received a velocity-dependent tangential skin deformation from a custom-built skin-stretch device together with a velocity-dependent force-field from a kinesthetic haptic device. One group experienced a skin deformation in the same direction of the force, and the other in the opposite direction. A third group received only the velocity-dependent force-field.

Results

We found that adding a skin deformation did not affect the kinematics of the movement during adaptation. However, participants who received skin deformation in the opposite direction adapted their manipulation forces faster and to a greater extent than those who received skin deformation in the same direction of the force. In addition, we found that skin deformation in the same direction to the force-field caused an increase in the applied grip-force per amount of load force, both in response and in anticipation of the stretch, compared to the other two groups.

Conclusions

Augmented tactile information affects the internal representations for the control of manipulation and grip forces, and these internal representations are likely updated via distinct mechanisms. We discuss the implications of these results for assistive and rehabilitation devices.

Robust Control in Human Reaching Movements: A Model-Free Strategy to Compensate for Unpredictable Disturbances

Current models of motor learning suggest that multiple timescales support adaptation to changes in visual or mechanical properties of the environment. These models capture patterns of learning and memory across a broad range of tasks, yet do not consider the possibility that rapid changes in behavior may occur without adaptation. Such changes in behavior may be desirable when facing transient disturbances, or when unpredictable changes in visual or mechanical properties of the task make it difficult to form an accurate model of the perturbation. Whether humans can modulate control strategies without an accurate model of the perturbation remains unknown. Here we frame this question in the context of robust control (H _∞-control), a control strategy that specifically considers unpredictable disturbances by increasing initial movement speed and feedback gains. Correspondingly, we demonstrate in two human reaching experiments including males and females that the occurrence of a single unpredictable disturbance led to an increase in movement speed and in the gain of rapid feedback responses to mechanical disturbances on subsequent movements. This strategy reduced perturbation-related motion regardless of the direction of the perturbation. Furthermore, we found that changes in the control strategy were associated with co-contraction, which amplified the gain of muscle responses to both lengthening and shortening perturbations. These results have important implications for studies on motor adaptation because they highlight that trial-by-trial changes in limb motion also reflected changes in control strategies dissociable from error-based adaptation.SIGNIFICANCE STATEMENT Humans and animals use internal representations of movement dynamics to anticipate the impact of predictable disturbances. However, we are often confronted with transient or unpredictable disturbances, and it remains unknown whether and how the nervous system handles these disturbances over fast time scales. Here we hypothesized that humans can modulate their control strategy to make reaching movements less sensitive to perturbations. We tested this hypothesis in the framework of robust control, and found changes in movement speed and feedback gains consistent with the model predictions. These changes impacted participants' behavior on a trial-by-trial basis. We conclude that compensation for disturbances over fast time scales involves a robust control strategy, which potentially plays a key role in motor planning and execution.

Increase in Grasp Force Reflects a Desire to Improve Movement Precision

Grasping is an action engraved in the human genome, enabling newborn infants to hang from a monkey-bar immediately after birth. The grasp force provides rich information about the brain's control of arm movements. In this study, we tested the hypothesis that the grasp force increases to improve the hand's movement precision during reaching. In two reaching experiments, subjects increased grasp force to suppress movement imprecision that arose from both self-generated motor noise and from an unpredictable environment. Furthermore, the grasp force did not increase constantly, but increased specifically along the movement where the hand's deviation was greatest. The increased grasp was premeditated and was not a reaction to environmental forces, suggesting that the central nervous system has a predictive, state-dependent model of movement precision during reaching. The grasp force provides a high temporal resolution and calibration-less estimate of movement precision adaptation.

Dexterous Manipulation During Rhythmic Arm Movements in Mars, Moon, and Micro-Gravity

Predicting the consequences of one’s own movements can be challenging when confronted with completely novel environmental dynamics, such as microgravity in space. The absence of gravitational force disrupts internal models of the central nervous system (CNS) that have been tuned to the dynamics of a constant 1-g environment since birth. In the context of object manipulation, inadequate internal models produce prediction uncertainty evidenced by increases in the grip force (GF) safety margin that ensures a stable grip during unpredicted load perturbations. This margin decreases with practice in a novel environment. However, it is not clear how the CNS might react to a reduced, but non-zero, gravitational field, and if adaptation to reduced gravity might be beneficial for subsequent microgravity exposure. That is, we wondered if a transfer of learning can occur across various reduced-gravity environments. In this study, we investigated the kinematics and dynamics of vertical arm oscillations during parabolic flight maneuvers that simulate Mars gravity, Moon gravity, and microgravity, in that order. While the ratio of and the correlation between GF and load force (LF) evolved progressively with practice in Mars gravity, these parameters stabilized much quicker to subsequently presented Moon and microgravity conditions. These data suggest that prior short-term adaptation to one reduced-gravity field facilitates the CNS’s ability to update its internal model during exposure to other reduced gravity fields.

Grip Force Adjustments Reflect Prediction of Dynamic Consequences in Varying Gravitoinertial Fields

Humans have a remarkable ability to adjust the way they manipulate tools through a genuine regulation of grip force according to the task. However, rapid changes in the dynamical context may challenge this skill, as shown in many experimental approaches. Most experiments adopt perturbation paradigms that affect only one sensory modality. We hypothesize that very fast adaptation can occur if coherent information from multiple sensory modalities is provided to the central nervous system. Here, we test whether participants can switch between different and never experienced dynamical environments induced by centrifugation of the body. Seven participants lifted an object four times in a row successively in 1, 1.5, 2, 2.5, 2, 1.5, and 1 g. We continuously measured grip force, load force and the gravitoinertial acceleration that was aligned with body axis (perceived gravity). Participants adopted stereotyped grasping movements immediately upon entry in a new environment and needed only one trial to adapt grip forces to a stable performance in each new gravity environment. This result was underlined by good correlations between grip and load forces in the first trial. Participants predictively applied larger grip forces when they expected increasing gravity steps. They also decreased grip force when they expected decreasing gravity steps, but not as much as they could, indicating imperfect anticipation in that condition. The participants' performance could rather be explained by a combination of successful scaling of grip force according to gravity changes and a separate safety factor. The data suggest that in highly unfamiliar dynamic environments, grip force regulation is characterized by a combination of a successful anticipation of the experienced environmental condition, a safety factor reflecting strategic response to uncertainties about the environment and rapid feedback mechanisms to optimize performance under constant conditions.

Improving Fine Control of Grasping Force during Hand-Object Interactions for a Soft Synergy-Inspired Myoelectric Prosthetic Hand

The concept of postural synergies of the human hand has been shown to potentially reduce complexity in the neuromuscular control of grasping. By merging this concept with soft robotics approaches, a multi degrees of freedom soft-synergy prosthetic hand [SoftHand-Pro (SHP)] was created. The mechanical innovation of the SHP enables adaptive and robust functional grasps with simple and intuitive myoelectric control from only two surface electromyogram (sEMG) channels. However, the current myoelectric controller has very limited capability for fine control of grasp forces. We addressed this challenge by designing a hybrid-gain myoelectric controller that switches control gains based on the sensorimotor state of the SHP. This controller was tested against a conventional single-gain (SG) controller, as well as against native hand in able-bodied subjects. We used the following tasks to evaluate the performance of grasp force control: (1) pick and place objects with different size, weight, and fragility levels using power or precision grasp and (2) squeezing objects with different stiffness. Sensory feedback of the grasp forces was provided to the user through a non-invasive, mechanotactile haptic feedback device mounted on the upper arm. We demonstrated that the novel hybrid controller enabled superior task completion speed and fine force control over SG controller in object pick-and-place tasks. We also found that the performance of the hybrid controller qualitatively agrees with the performance of native human hands.

On the Role of Physical Interaction on Performance of Object Manipulation by Dyads

Human physical interactions can be intrapersonal, e.g., manipulating an object bimanually, or interpersonal, e.g., transporting an object with another person. In both cases, one or two agents are required to coordinate their limbs to attain the task goal. We investigated the physical coordination of two hands during an object-balancing task performed either bimanually by one agent or jointly by two agents. The task consisted of a series of static (holding) and dynamic (moving) phases, initiated by auditory cues. We found that task performance of dyads was not affected by different pairings of dominant and non-dominant hands. However, the spatial configuration of the two agents (side-by-side vs. face-to-face) appears to play an important role, such that dyads performed better side-by-side than face-to-face. Furthermore, we demonstrated that only individuals with worse solo performance can benefit from interpersonal coordination through physical couplings, whereas the better individuals do not. The present work extends ongoing investigations on human-human physical interactions by providing new insights about factors that influence dyadic performance. Our findings could potentially impact several areas, including robotic-assisted therapies, sensorimotor learning and human performance augmentation.

The sensorimotor system minimizes prediction error for object lifting when the object's weight is uncertain

A reliable mechanism to predict the heaviness of an object is important for manipulating an object under environmental uncertainty. Recently, Cashaback et al. (Cashaback JGA, McGregor HR, Pun HCH, Buckingham G, Gribble PL. J Neurophysiol 117: 260-274, 2017) showed that for object lifting the sensorimotor system uses a strategy that minimizes prediction error when the object's weight is uncertain. Previous research demonstrates that visually guided reaching is similarly optimized. Although this suggests a unified strategy of the sensorimotor system for object manipulation, the selected strategy appears to be task dependent and subject to change in response to the degree of environmental uncertainty.

The Role of Variability in Motor Learning

Trial-to-trial variability in the execution of movements and motor skills is ubiquitous and widely considered to be the unwanted consequence of a noisy nervous system. However, recent studies have suggested that motor variability may also be a feature of how sensorimotor systems operate and learn. This view, rooted in reinforcement learning theory, equates motor variability with purposeful exploration of motor space that, when coupled with reinforcement, can drive motor learning. Here we review studies that explore the relationship between motor variability and motor learning in both humans and animal models. We discuss neural circuit mechanisms that underlie the generation and regulation of motor variability and consider the implications that this work has for our understanding of motor learning.

Temporal specificity of the initial adaptive response in motor adaptation

Repeated exposure to a novel physical environment eventually leads to a mature adaptive response whereby feedforward changes in motor output mirror both the amplitude and temporal structure of the environmental perturbations. However, adaptive responses at the earliest stages of learning have been found to be not only smaller, but systematically less specific in their temporal structure compared to later stages of learning. This observation has spawned a lively debate as to whether the temporal structure of the initial adaptive response is, in fact, stereotyped and non-specific. To settle this debate, we directly measured the adaptive responses to velocity-dependent and position-dependent force-field perturbations (vFFs and pFFs) at the earliest possible stage of motor learning in humans–after just a single-movement exposure. In line with previous work, we found these earliest stage adaptive responses to be more similar than the perturbations that induced them. However, the single-trial adaptive responses for vFF and pFF perturbations were clearly distinct, and the disparity between them reflected the difference between the temporal structure of the perturbations that drove them. Critically, we observed these differences between single-trial adaptive responses when vFF and pFF perturbations were randomly intermingled from one trial to the next within the same block, indicating perturbation response specificity at the single trial level. These findings demonstrate that the initial adaptive responses to physical perturbations are not stereotyped. Instead, the neural plasticity in sensorimotor areas is sensitive to the temporal structure of a movement perturbation even at the earliest stage in learning. This insight has direct implications for the development of computational models of early-stage motor adaptation and the evolution of this adaptive response with continued training.

With repeated exposure to a perturbation, the sensorimotor system learns to develop an adaptive response that is highly specific to both the amplitude and temporal structure of that perturbation in order to effectively counteract it. It is widely known that the amplitude of the adaptive response starts small and gradually grows to the right size with repeated exposure. However, it is also the case that the temporal structure of the adaptive response starts somewhat generically and gradually grows into the right shape with repeated exposure. A key question is whether the adaptive response to a perturbation begins with a stereotyped temporal structure that only becomes specified with further practice, or if it begins with a degree of specificity for the experienced perturbation that need only to be refined by practice. Here, by precisely measuring the temporal pattern of motor output in the single-trial adaptive response to two different perturbations, we show that the initial adaptive response is indeed specific to the temporal characteristics of the perturbation, even when the disturbance randomly changed from one trial to the next. These results demonstrate that the sensorimotor system is sensitive to the temporal features of a disturbance, even when experienced just once.

Compensating for intersegmental dynamics across the shoulder, elbow, and wrist joints during feedforward and feedback control

Moving the arm is complicated by mechanical interactions that arise between limb segments. Such intersegmental dynamics cause torques applied at one joint to produce movement at multiple joints, and in turn, the only way to create single joint movement is by applying torques at multiple joints. We investigated whether the nervous system accounts for intersegmental limb dynamics across the shoulder, elbow, and wrist joints during self-initiated planar reaching and when countering external mechanical perturbations. Our first experiment tested whether the timing and amplitude of shoulder muscle activity account for interaction torques produced during single-joint elbow movements from different elbow initial orientations and over a range of movement speeds. We found that shoulder muscle activity reliably preceded movement onset and elbow agonist activity, and was scaled to compensate for the magnitude of interaction torques arising because of forearm rotation. Our second experiment tested whether elbow muscles compensate for interaction torques introduced by single-joint wrist movements. We found that elbow muscle activity preceded movement onset and wrist agonist muscle activity, and thus the nervous system predicted interaction torques arising because of hand rotation. Our third and fourth experiments tested whether shoulder muscles compensate for interaction torques introduced by different hand orientations during self-initiated elbow movements and to counter mechanical perturbations that caused pure elbow motion. We found that the nervous system predicted the amplitude and direction of interaction torques, appropriately scaling the amplitude of shoulder muscle activity during self-initiated elbow movements and rapid feedback control. Taken together, our results demonstrate that the nervous system robustly accounts for intersegmental dynamics and that the process is similar across the proximal to distal musculature of the arm as well as between feedforward (i.e., self-initiated) and feedback (i.e., reflexive) control.NEW & NOTEWORTHY Intersegmental dynamics complicate the mapping between applied joint torques and the resulting joint motions. We provide evidence that the nervous system robustly predicts these intersegmental limb dynamics across the shoulder, elbow, and wrist joints during reaching and when countering external perturbations.

Coherent Multimodal Sensory Information Allows Switching between Gravitoinertial Contexts

Whether the central nervous system is capable to switch between contexts critically depends on experimental details. Motor control studies regularly adopt robotic devices to perturb the dynamics of a certain task. Other approaches investigate motor control by altering the gravitoinertial context itself as in parabolic flights and human centrifuges. In contrast to conventional robotic experiments, where only the hand is perturbed, these gravitoinertial or immersive settings coherently plunge participants into new environments. However, radically different they are, perfect adaptation of motor responses are commonly reported. In object manipulation tasks, this translates into a good matching of the grasping force or grip force to the destabilizing load force. One possible bias in these protocols is the predictability of the forthcoming dynamics. Here we test whether the successful switching and adaptation processes observed in immersive environments are a consequence of the fact that participants can predict the perturbation schedule. We used a short arm human centrifuge to decouple the effects of space and time on the dynamics of an object manipulation task by adding an unnatural explicit position-dependent force. We created different dynamical contexts by asking 20 participants to move the object at three different paces. These contextual sessions were interleaved such that we could simulate concurrent learning. We assessed adaptation by measuring how grip force was adjusted to this unnatural load force. We found that the motor system can switch between new unusual dynamical contexts, as reported by surprisingly well-adjusted grip forces, and that this capacity is not a mere consequence of the ability to predict the time course of the upcoming dynamics. We posit that a coherent flow of multimodal sensory information born in a homogeneous milieu allows switching between dynamical contexts.

The biology of skin wetness perception and its implications in manual function and for reproducing complex somatosensory signals in neuroprosthetics

Our perception of skin wetness is generated readily, yet humans have no known receptor (hygroreceptor) to signal this directly. It is easy to imagine the sensation of water running over our hands or the feel of rain on our skin. The synthetic sensation of wetness is thought to be produced from a combination of specific skin thermal and tactile inputs, registered through thermoreceptors and mechanoreceptors, respectively. The present review explores how thermal and tactile afference from the periphery can generate the percept of wetness centrally. We propose that the main signals include information about skin cooling, signaled primarily by thinly myelinated thermoreceptors, and rapid changes in touch, through fast-conducting, myelinated mechanoreceptors. Potential central sites for integration of these signals, and thus the perception of skin wetness, include the primary and secondary somatosensory cortices and the insula cortex. The interactions underlying these processes can also be modeled to aid in understanding and engineering the mechanisms. Furthermore, we discuss the role that sensing wetness could play in precision grip and the dexterous manipulation of objects. We expand on these lines of inquiry to the application of the knowledge in designing and creating skin sensory feedback in prosthetics. The addition of real-time, complex sensory signals would mark a significant advance in the use and incorporation of prosthetic body parts for amputees in everyday life.NEW & NOTEWORTHY Little is known about the underlying mechanisms that generate the perception of skin wetness. Humans have no specific hygroreceptor, and thus temperature and touch information combine to produce wetness sensations. The present review covers the potential mechanisms leading to the perception of wetness, both peripherally and centrally, along with their implications for manual function. These insights are relevant to inform the design of neuroengineering interfaces, such as sensory prostheses for amputees.

Does the sensorimotor system minimize prediction error or select the most likely prediction during object lifting?

The human sensorimotor system is routinely capable of making accurate predictions about an object's weight, which allows for energetically efficient lifts and prevents objects from being dropped. Often, however, poor predictions arise when the weight of an object can vary and sensory cues about object weight are sparse (e.g., picking up an opaque water bottle). The question arises, what strategies does the sensorimotor system use to make weight predictions when one is dealing with an object whose weight may vary? For example, does the sensorimotor system use a strategy that minimizes prediction error (minimal squared error) or one that selects the weight that is most likely to be correct (maximum a posteriori)? In this study we dissociated the predictions of these two strategies by having participants lift an object whose weight varied according to a skewed probability distribution. We found, using a small range of weight uncertainty, that four indexes of sensorimotor prediction (grip force rate, grip force, load force rate, and load force) were consistent with a feedforward strategy that minimizes the square of prediction errors. These findings match research in the visuomotor system, suggesting parallels in underlying processes. We interpret our findings within a Bayesian framework and discuss the potential benefits of using a minimal squared error strategy.

NEW & NOTEWORTHY

Using a novel experimental model of object lifting, we tested whether the sensorimotor system models the weight of objects by minimizing lifting errors or by selecting the statistically most likely weight. We found that the sensorimotor system minimizes the square of prediction errors for object lifting. This parallels the results of studies that investigated visually guided reaching, suggesting an overlap in the underlying mechanisms between tasks that involve different sensory systems.

Simple and Reliable Method to Estimate the Fingertip Static Coefficient of Friction in Precision Grip

The static coefficient of friction (µ_static) plays an important role in dexterous object manipulation. Minimal normal force (i.e., grip force) needed to avoid dropping an object is determined by the tangential force at the fingertip-object contact and the frictional properties of the skin-object contact. Although frequently assumed to be constant for all levels of normal force (NF, the force normal to the contact), µ _static actually varies nonlinearly with NF and increases at low NF levels. No method is currently available to measure the relationship between µ_static and NF easily. Therefore, we propose a new method allowing the simple and reliable measurement of the fingertip µ_static at different NF levels, as well as an algorithm for determining µ_static from measured forces and torques. Our method is based on active, back-and-forth movements of a subject's finger on the surface of a fixed six-axis force and torque sensor. µ_static is computed as the ratio of the tangential to the normal force at slip onset. A negative power law captures the relationship between µ_static and NF. Our method allows the continuous estimation of µ_static as a function of NF during dexterous manipulation, based on the relationship between µ_static and NF measured before manipulation.

Pre-Trial EEG-Based Single-Trial Motor Performance Prediction to Enhance Neuroergonomics for a Hand Force Task

We propose a framework for building electrophysiological predictors of single-trial motor performance variations, exemplified for SVIPT, a sequential isometric force control task suitable for hand motor rehabilitation after stroke. Electroencephalogram (EEG) data of 20 subjects with mean age of 53 years was recorded prior to and during 400 trials of SVIPT. They were executed within a single session with the non-dominant left hand, while receiving continuous visual feedback of the produced force trajectories. The behavioral data showed strong trial-by-trial performance variations for five clinically relevant metrics, which accounted for reaction time as well as for the smoothness and precision of the produced force trajectory. 18 out of 20 tested subjects remained after preprocessing and entered offline analysis. Source Power Comodulation (SPoC) was applied on EEG data of a short time interval prior to the start of each SVIPT trial. For 11 subjects, SPoC revealed robust oscillatory EEG subspace components, whose bandpower activity are predictive for the performance of the upcoming trial. Since SPoC may overfit to non-informative subspaces, we propose to apply three selection criteria accounting for the meaningfulness of the features. Across all subjects, the obtained components were spread along the frequency spectrum and showed a variety of spatial activity patterns. Those containing the highest level of predictive information resided in and close to the alpha band. Their spatial patterns resemble topologies reported for visual attention processes as well as those of imagined or executed hand motor tasks. In summary, we identified subject-specific single predictors that explain up to 36% of the performance fluctuations and may serve for enhancing neuroergonomics of motor rehabilitation scenarios.

Long-Latency Feedback Coordinates Upper-Limb and Hand Muscles during Object Manipulation Tasks

Suppose that someone bumps into your arm at a party while you are holding a glass of wine. Motion of the disturbed arm will engage rapid and goal-directed feedback responses in the upper-limb. Although such responses can rapidly counter the perturbation, it is also clearly desirable not to destabilize your grasp and/or spill the wine. Here we investigated how healthy humans maintain a stable grasp following perturbations by using a paradigm that requires spatial tuning of the motor response dependent on the location of a virtual target. Our results highlight a synchronized expression of target-directed feedback in shoulder and hand muscles occurring at ∼60 ms. Considering that conduction delays are longer for the more distal hand muscles, these results suggest that target-directed responses in hand muscles were initiated before those for the shoulder muscles. These results show that long-latency feedback can coordinate upper limb and hand muscles during object manipulation tasks.

Predictability and Robustness in the Manipulation of Dynamically Complex Objects

Manipulation of complex objects and tools is a hallmark of many activities of daily living, but how the human neuromotor control system interacts with such objects is not well understood. Even the seemingly simple task of transporting a cup of coffee without spilling creates complex interaction forces that humans need to compensate for. Predicting the behavior of an underactuated object with nonlinear fluid dynamics based on an internal model appears daunting. Hence, this research tests the hypothesis that humans learn strategies that make interactions predictable and robust to inaccuracies in neural representations of object dynamics. The task of moving a cup of coffee is modeled with a cart-and-pendulum system that is rendered in a virtual environment, where subjects interact with a virtual cup with a rolling ball inside using a robotic manipulandum. To gain insight into human control strategies, we operationalize predictability and robustness to permit quantitative theory-based assessment. Predictability is quantified by the mutual information between the applied force and the object dynamics; robustness is quantified by the energy margin away from failure. Three studies are reviewed that show how with practice subjects develop movement strategies that are predictable and robust. Alternative criteria, common for free movement, such as maximization of smoothness and minimization of force, do not account for the observed data. As manual dexterity is compromised in many individuals with neurological disorders, the experimental paradigm and its analyses are a promising platform to gain insights into neurological diseases, such as dystonia and multiple sclerosis, as well as healthy aging.

A soft-contact and wrench based approach to study grasp planning and execution

Grasping research in robotics has made remarkable progress in the last three decades and sophisticated computational tools are now available for planning robotic grasping in complex environments. However, studying the neural control of prehension in humans is more complex than studying robotic grasping. The elaborate musculoskeletal geometries and complex neural inputs to the hand facilitate a symphonic interplay of power and precision that allows humans to grasp fragile objects in a stable way without either crushing or dropping them. Most prehension studies have focused on a planar simplification of prehension since planar analyses render the complex problem of prehension tractable with few variables. The caveat is that planar simplification allows researchers to ask only a limited set of questions. In fact, one of the problems with extending prehension studies to three dimensions is the lack of analytical tools for quantifying features of spatial prehension. The current paper provides a theoretical adaptation and a step-by-step implementation of a widely used soft-contact wrench model for spatial human prehension. We propose two indices, grasp caliber and grasp intensity, to quantitatively relate digit placement and digit forces to grasp stability. Grasp caliber is the smallest singular value of the grasp matrix and it indicates the proximity of the current grasp configuration to instability. Grasp intensity is the magnitude of the excessive wrench applied by the digits to counter perturbations. Apart from quantifying stability of spatial grasps, these indices can also be applied to investigate sensory-motor coupling and the role of perception in grasp planning.