Decomposition of variability in the execution of goal-oriented tasks: three components of skill improvement

Locomotor control of limb force switches from minimal intervention principle in early adaptation to noise reduction in late adaptation

During movement, errors are typically corrected only if they hinder performance. Preferential correction of task-relevant deviations is described by the minimal intervention principle but has not been demonstrated in the joints during locomotor adaptation. We studied hopping as a tractable model of locomotor adaptation of the joints within the context of a limb-force-specific task space. Subjects hopped while adapting to shifted visual feedback that induced them to increase peak ground reaction force (GRF). We hypothesized subjects would preferentially reduce task-relevant joint torque deviations over task-irrelevant deviations to increase peak GRF. We employed a modified uncontrolled manifold analysis to quantify task-relevant and task-irrelevant joint torque deviations for each individual hop cycle. As would be expected by the explicit goal of the task, peak GRF errors decreased in early adaptation before reaching steady state during late adaptation. Interestingly, during the early adaptation performance improvement phase, subjects reduced GRF errors by decreasing only the task-relevant joint torque deviations. In contrast, during the late adaption performance maintenance phase, all torque deviations decreased in unison regardless of task relevance. In deadaptation, when the shift in visual feedback was removed, all torque deviations decreased in unison, possibly because performance improvement was too rapid to detect changes in only the task-relevant dimension. We conclude that limb force adaptation in hopping switches from a minimal intervention strategy during performance improvement to a noise reduction strategy during performance maintenance, which may represent a general control strategy for locomotor adaptation of limb force in other bouncing gaits, such as running.

Emergence of virtual reality as a tool for upper limb rehabilitation: incorporation of motor control and motor learning principles

The primary focus of rehabilitation for individuals with loss of upper limb movement as a result of acquired brain injury is the relearning of specific motor skills and daily tasks. This relearning is essential because the loss of upper limb movement often results in a reduced quality of life. Although rehabilitation strives to take advantage of neuroplastic processes during recovery, results of traditional approaches to upper limb rehabilitation have not entirely met this goal. In contrast, enriched training tasks, simulated with a wide range of low- to high-end virtual reality-based simulations, can be used to provide meaningful, repetitive practice together with salient feedback, thereby maximizing neuroplastic processes via motor learning and motor recovery. Such enriched virtual environments have the potential to optimize motor learning by manipulating practice conditions that explicitly engage motivational, cognitive, motor control, and sensory feedback-based learning mechanisms. The objectives of this article are to review motor control and motor learning principles, to discuss how they can be exploited by virtual reality training environments, and to provide evidence concerning current applications for upper limb motor recovery. The limitations of the current technologies with respect to their effectiveness and transfer of learning to daily life tasks also are discussed.

Is intraindividual variability different between unimanual and bimanual speed-accuracy movements?

Dominant (right) and nondominant (left) hand differences in motor performance variables were investigated during targeted rapid aiming unimanual and bimanual (to two separate targets) speed-accuracy tasks. The performance of the dominant and nondominant hands were compared during rapid targeted unimanual and bimanual reaching tasks (50 repetitions) in adult, neurologically intact, right-handed men (n = 20). As task difficulty increased from unimanual to bimanual tasks, reaction time increased and velocity (average and maximal) of performance decreased significantly. The effect of hand was significant only on average movement velocity and on intraindividual variability of accuracy (in both cases performance in the left hand was worse). Variability of movement path (accuracy) was less in the right hand during both unimanual and bimanual tasks.

Uncontrolled manifold analysis of arm joint angle variability during robotic teleoperation and freehand movement of surgeons and novices

Teleoperated robot-assisted surgery (RAS) is used to perform a wide variety of minimally invasive procedures. However, current understanding of the effect of robotic manipulation on the motor coordination of surgeons is limited. Recent studies in human motor control suggest that we optimize hand movement stability and task performance while minimizing control effort and improving robustness to unpredicted disturbances. To achieve this, the variability of joint angles and muscle activations is structured to reduce task-relevant variability and increase task-irrelevant variability. In this study, we determine whether teleoperation of a da Vinci Si surgical system in a nonclinical task of simple planar movements changes this structure of variability in experienced surgeons and novices. To answer this question, we employ the UnControlled manifold analysis that partitions users' joint angle variability into task-irrelevant and task-relevant manifolds. We show that experienced surgeons coordinate their joint angles to stabilize hand movements more than novices, and that the effect of teleoperation depends on experience--experts increase teleoperated stabilization relative to freehand whereas novices decrease it. We suggest that examining users' exploitation of the task-irrelevant manifold for stabilization of hand movements may be applied to: (1) evaluation and optimization of teleoperator design and control parameters, and (2) skill assessment and optimization of training in RAS.

Movement pattern variability in stone knapping: implications for the development of percussive traditions

The earliest direct evidence for tool-use by our ancestors are 2.6 million year old stone tools from Africa. These earliest artifacts show that, already, early hominins had developed the required advanced movement skills and cognitive capacities to manufacture stone tools. Currently, it is not well understood, however, which specific movement skills are required for successful stone knapping and accordingly it is unknown how these skills emerged during early hominin evolution. In particular, it is not clear which striking movements are indicative of skilled performance, how striking movement patterns vary with task and environmental constraints, and how movement patterns are passed on within social groups. The present study addresses these questions by investigating striking movement patterns and striking variability in 18 modern stone knappers (nine experienced and nine novices). The results suggest that no single movement pattern characterizes successful stone knapping. Participants showed large inter-individual movement variability of the elementary knapping action irrespective of knapping experience and knapping performance. Changes in task- and environmental constraints led knappers to adapt their elementary striking actions using a combination of individual and common strategies. Investigation of striking pattern similarities within social groups showed only partial overlap of striking patterns across related individuals. The results therefore suggest that striking movement patterns in modern stone knappers are largely specific to the individual and movement variability is not indicative of knapping performance. The implications of these results for the development of percussive traditions are discussed.

Task complexity and maximal isometric strength gains through motor learning

This study compared the effects of a simple versus complex contraction pattern on the acquisition, retention, and transfer of maximal isometric strength gains and reductions in force variability. A control group (N = 12) performed simple isometric contractions of the wrist flexors. An experimental group (N = 12) performed complex proprioceptive neuromuscular facilitation (PNF) contractions consisting of maximal isometric wrist extension immediately reversing force direction to wrist flexion within a single trial. Ten contractions were completed on three consecutive days with a retention and transfer test 2‐weeks later. For the retention test, the groups performed their assigned contraction pattern followed by a transfer test that consisted of the other contraction pattern for a cross‐over design. Both groups exhibited comparable increases in strength (20.2%, P < 0.01) and reductions in mean torque variability (26.2%, P < 0.01), which were retained and transferred. There was a decrease in the coactivation ratio (antagonist/agonist muscle activity) for both groups, which was retained and transferred (35.2%, P < 0.01). The experimental group exhibited a linear decrease in variability of the torque‐ and sEMG‐time curves, indicating transfer to the simple contraction pattern (P < 0.01). The control group underwent a decrease in variability of the torque‐ and sEMG‐time curves from the first day of training to retention, but participants returned to baseline levels during the transfer condition (P < 0.01). However, the difference between torque RMS error versus the variability in torque‐ and sEMG‐time curves suggests the demands of the complex task were transferred, but could not be achieved in a reproducible way.

This study examines the effect of task complexity on the acquisition, retention, and transfer of increases in maximal strength and decreases in force variability, which is novel. Simple agonist‐only contractions are compared to a more complex reversal contraction pattern as used during proprioceptive neuromuscular facilitation (PNF). The goal was to determine if the more complex contraction pattern interferes with the strength gains and reduced variability by impeding the development of agonist‐antagonist coordination.

Neuroplasticity of imagined wrist actions after spinal cord injury: a pilot study

Motor imagery (MI - i.e., the mental representation of an action without physically executing it) stimulates brain motor networks and promotes motor learning after spinal cord injury (SCI). An interesting issue is whether the brain networks controlling MI are being reorganized with reference to spared motor functions. In this pilot study, we tested using magnetoencephalography (MEG) whether changes in cortical recruitment during MI were related to the motor changes elicited by rehabilitation. Over a 1-year period of inclusion, C6 SCI participants (n = 4) met stringent criteria for inclusion in a rehabilitation program focused on the tenodesis prehension (i.e., a compensatory prehension enabling seizing of objects in spite of hand and forearm muscles paralysis). After an extended baseline period of 5 weeks including repeated MEG and chronometric assessments of motor performance, MI training was embedded to the classical course of physiotherapy for five additional weeks. Posttest MEG and motor performance data were collected. A group of matched healthy control participants underwent a similar procedure. The MI intervention resulted in changes in the variability of the wrist extensions, i.e., a key movement of the tenodesis grasp (p < .05). Interestingly, the extent of cortical recruitment, quantified by the number of MEG activation sources recorded within Brodmann areas 1-8 during MI of the wrist extension, significantly predicted actual movement variability changes across sessions (p < .001). However, no such relationship was present for movement times. Repeated measurements afforded a reliable statistical power (range .70-.97). This pilot study does not provide straightforward evidence of MI efficacy, which would require a randomized controlled trial. Nonetheless, the data showed that the relationship between action and imagery of spared actions may be preserved after SCI.

Feeling the force: returning haptic signals influence effort inference during motor coordination

Our brain is known to automatically optimize effort expenditure during motor coordination, such that for example, during bimanual braking of a bicycle, a well-oiled brake will automatically be used more than a corroded, heavy brake. But how does our brain infer the effort expenditure? All previous motor coordination models have believed that the effort in a task is known precisely to our brain, solely from the motor commands it generates. Here we show that this belief is incorrect. Through experiments and simulation we exhibit that in addition to the motor commands, the returning haptic signals play a crucial role in the inference of the effort during a force sharing task. Our results thus elucidate a previously unknown sensory-motor association that has major ramifications for our understanding of motor coordination and provides new insights into how sensory modifications due to ergonomics, stroke and disease can affect motor coordination in humans.

Effect of feedback during virtual training of grip force control with a myoelectric prosthesis

The aim of this study was to determine whether virtual training improves grip force control in prosthesis use, and to examine which type of augmented feedback facilitates its learning most. Thirty-two able-bodied participants trained grip force with a virtual ball-throwing game for five sessions in a two-week period, using a myoelectric simulator. They received either feedback on movement outcome or on movement execution. Sixteen controls received training that did not focus on force control. Variability over learning was examined with the Tolerance-Noise-Covariation approach, and the transfer of grip force control was assessed in five test-tasks that assessed different aspects of force control in a pretest, a posttest and a retention test. During training performance increased while the variability in performance was decreased, mainly by reduction in noise. Grip force control only improved in the test-tasks that provided information on performance. Starting the training with a task that required low force production showed no transfer of the learned grip force. Feedback on movement execution was detrimental to grip force control, whereas feedback on movement outcome enhanced transfer of grip force control to tasks other than trained. Clinical implications of these results regarding virtual training of grip force control are discussed.

Learning the spatial features of a locomotor task is slowed after stroke

The capacity for humans to learn a new walking pattern has been explored with a split-belt treadmill during single sessions of adaptation, but the split-belt treadmill can also be used to study longer-term motor learning. Although the literature provides some information about motor learning after stroke, existing studies have primarily involved the upper extremity and the results are mixed. The purpose of this study was to characterize learning of a novel locomotor task in stroke survivors. We hypothesized that the presence of neurological dysfunction from stroke would result in slower learning of a locomotor task and decreased retention of what was learned and that these deficits would be related to level of sensorimotor impairment. Sixteen participants with stroke and sixteen neurologically intact participants walked on a split-belt treadmill for 15 min on 5 consecutive days and during a retention test. Step length and limb phase were measured to capture learning of the spatial and temporal aspects of walking. Learning the spatial pattern of split-belt treadmill walking was slowed after stroke compared with neurologically intact subjects, whereas there were no differences between these two groups in learning the temporal pattern. During the retention test, poststroke participants demonstrated equal retention of the split-belt treadmill walking pattern compared with those who were neurologically intact. The results suggest that although stroke survivors are slower to learn a new spatial pattern of gait, if given sufficient time they are able to do so to the same extent as those who are neurologically intact.

Changes in performance over time while learning to use a myoelectric prosthesis

BACKGROUND

Training increases the functional use of an upper limb prosthesis, but little is known about how people learn to use their prosthesis. The aim of this study was to describe the changes in performance with an upper limb myoelectric prosthesis during practice. The results provide a basis to develop an evidence-based training program.

METHODS

Thirty-one able-bodied participants took part in an experiment as well as thirty-one age- and gender-matched controls. Participants in the experimental condition, randomly assigned to one of four groups, practiced with a myoelectric simulator for five sessions in a two-weeks period. Group 1 practiced direct grasping, Group 2 practiced indirect grasping, Group 3 practiced fixating, and Group 4 practiced a combination of all three tasks. The Southampton Hand Assessment Procedure (SHAP) was assessed in a pretest, posttest, and two retention tests. Participants in the control condition performed SHAP two times, two weeks apart with no practice in between. Compressible objects were used in the grasping tasks. Changes in end-point kinematics, joint angles, and grip force control, the latter measured by magnitude of object compression, were examined.

RESULTS

The experimental groups improved more on SHAP than the control group. Interestingly, the fixation group improved comparable to the other training groups on the SHAP. Improvement in global position of the prosthesis leveled off after three practice sessions, whereas learning to control grip force required more time. The indirect grasping group had the smallest object compression in the beginning and this did not change over time, whereas the direct grasping and the combination group had a decrease in compression over time. Moreover, the indirect grasping group had the smallest grasping time that did not vary over object rigidity, while for the other two groups the grasping time decreased with an increase in object rigidity.

CONCLUSIONS

A training program should spend more time on learning fine control aspects of the prosthetic hand during rehabilitation. Moreover, training should start with the indirect grasping task that has the best performance, which is probably due to the higher amount of useful information available from the sound hand.

A theory for how sensorimotor skills are learned and retained in noisy and nonstationary neural circuits

During the process of skill learning, synaptic connections in our brains are modified to form motor memories of learned sensorimotor acts. The more plastic the adult brain is, the easier it is to learn new skills or adapt to neurological injury. However, if the brain is too plastic and the pattern of synaptic connectivity is constantly changing, new memories will overwrite old memories, and learning becomes unstable. This trade-off is known as the stability-plasticity dilemma. Here a theory of sensorimotor learning and memory is developed whereby synaptic strengths are perpetually fluctuating without causing instability in motor memory recall, as long as the underlying neural networks are sufficiently noisy and massively redundant. The theory implies two distinct stages of learning--preasymptotic and postasymptotic--because once the error drops to a level comparable to that of the noise-induced error, further error reduction requires altered network dynamics. A key behavioral prediction derived from this analysis is tested in a visuomotor adaptation experiment, and the resultant learning curves are modeled with a nonstationary neural network. Next, the theory is used to model two-photon microscopy data that show, in animals, high rates of dendritic spine turnover, even in the absence of overt behavioral learning. Finally, the theory predicts enhanced task selectivity in the responses of individual motor cortical neurons as the level of task expertise increases. From these considerations, a unique interpretation of sensorimotor memory is proposed--memories are defined not by fixed patterns of synaptic weights but, rather, by nonstationary synaptic patterns that fluctuate coherently.

Martial arts striking hand peak acceleration, accuracy and consistency

The goal of this paper was to investigate the possible trade-off between peak hand acceleration and accuracy and consistency of hand strikes performed by martial artists of different training experiences. Ten male martial artists with training experience ranging from one to nine years volunteered to participate in the experiment. Each participant performed 12 maximum effort goal-directed strikes. Hand acceleration during the strikes was obtained using a tri-axial accelerometer block. A pressure sensor matrix was used to determine the accuracy and consistency of the strikes. Accuracy was estimated by the radial distance between the centroid of each subject's 12 strikes and the target, whereas consistency was estimated by the square root of the 12 strikes mean squared distance from their centroid. We found that training experience was significantly correlated to hand peak acceleration prior to impact (r(2)=0.456, p =0.032) and accuracy (r(2)=0. 621, p=0.012). These correlations suggest that more experienced participants exhibited higher hand peak accelerations and at the same time were more accurate. Training experience, however, was not correlated to consistency (r(2)=0.085, p=0.413). Overall, our results suggest that martial arts training may lead practitioners to achieve higher striking hand accelerations with better accuracy and no change in striking consistency.

The database for reaching experiments and models

Reaching is one of the central experimental paradigms in the field of motor control, and many computational models of reaching have been published. While most of these models try to explain subject data (such as movement kinematics, reaching performance, forces, etc.) from only a single experiment, distinct experiments often share experimental conditions and record similar kinematics. This suggests that reaching models could be applied to (and falsified by) multiple experiments. However, using multiple datasets is difficult because experimental data formats vary widely. Standardizing data formats promises to enable scientists to test model predictions against many experiments and to compare experimental results across labs. Here we report on the development of a new resource available to scientists: a database of reaching called the Database for Reaching Experiments And Models (DREAM). DREAM collects both experimental datasets and models and facilitates their comparison by standardizing formats. The DREAM project promises to be useful for experimentalists who want to understand how their data relates to models, for modelers who want to test their theories, and for educators who want to help students better understand reaching experiments, models, and data analysis.

Movement variability near goal equivalent manifolds: fluctuations, control, and model-based analysis

Fluctuations in the repeated performance of human movements have been the subject of intense scrutiny because they are generally believed to contain important information about the function and health of the neuromotor system. A variety of approaches has been brought to bear to study these fluctuations. However it is frequently difficult to understand how to synthesize different perspectives to give a coherent picture. Here, we describe a conceptual framework for the experimental study of motor variability that helps to unify geometrical methods, which focus on the role of motor redundancy, with dynamical methods that characterize the error-correcting processes regulating the performance of skilled tasks. We describe how goal functions, which mathematically specify the task strategy being employed, together with ideas from the control of redundant systems, allow one to formulate simple, experimentally testable dynamical models of inter-trial fluctuations. After reviewing the basic theory, we present a list of five general hypotheses on the structure of fluctuations that can be expected in repeated trials of goal-directed tasks. We review recent experimental applications of this general approach, and show how it can be used to precisely characterize the error-correcting control used by human subjects.

Reward-based learning of a redundant task

Motor skill learning has different components. When we acquire a new motor skill we have both to learn a reliable action-value map to select a highly rewarded action (task model) and to develop an internal representation of the novel dynamics of the task environment, in order to execute properly the action previously selected (internal model). Here we focus on a 'pure' motor skill learning task, in which adaptation to a novel dynamical environment is negligible and the problem is reduced to the acquisition of an action-value map, only based on knowledge of results. Subjects performed point-to-point movement, in which start and target positions were fixed and visible, but the score provided at the end of the movement depended on the distance of the trajectory from a hidden viapoint. Subjects did not have clues on the correct movement other than the score value. The task is highly redundant, as infinite trajectories are compatible with the maximum score. Our aim was to capture the strategies subjects use in the exploration of the task space and in the exploitation of the task redundancy during learning. The main findings were that (i) subjects did not converge to a unique solution; rather, their final trajectories are determined by subject-specific history of exploration. (ii) with learning, subjects reduced the trajectory's overall variability, but the point of minimum variability gradually shifted toward the portion of the trajectory closer to the hidden via-point.

Effects of a foot placement constraint on use of motor equivalence during human hopping

Humans can robustly locomote over complex terrains even while simultaneously attending to other tasks such as accurate foot placement on the ground. We investigated whether subjects would exploit motor redundancy across the joints of the leg to stabilize overall limb kinematics when presented with a hopping task that constrained foot placement position. Subjects hopped in place on one leg (2.2 Hz) while having to place their foot into one of three target sizes upon landing (0.250, 0.063, 0.010 m(2)). As takeoff and landing angles are critical to this task performance, we hypothesized smaller target sizes would increase the need to stabilize (i.e., make more consistent) the leg orientation through motor equivalent combinations of segment angles. As it was not critical to the targeting task, we hypothesized no changes for leg length stabilization across target size. With smaller target sizes, we saw total segment angle variance increase due to greater signal-dependent noise associated with an increased activation of leg extensor muscles (medial and lateral gastrocnemius, vastus medialis, vastus lateralis and rectus femoris). At smaller target sizes, more segment angle variance was aligned to kinematic deviations with the goal of maintaining leg orientation trajectory. We also observed a decrease in the variance structure for stabilizing leg length at the smallest target conditions. This trade-off effect is explained by the nearly orthogonal relationship between the two goal-equivalent manifolds for leg length vs. leg orientation stabilization. Our results suggest humans increasingly rely on kinematic redundancy in their legs to achieve robust, consistent locomotion when faced with novel conditions that constrain performance requirements. These principles may generalize to other human locomotor gaits and provide important insights into the control of the legs during human walking and running.

Directionality in distribution and temporal structure of variability in skill acquisition

Observable structure of variability presents a window into the underlying processes of skill acquisition, especially when the task affords a manifold of solutions to the desired task result. This study examined skill acquisition by analyzing variability in both its distributional and temporal structure. Using a virtual throwing task, data distributions were analyzed by the Tolerance, Noise, Covariation-method (TNC); the temporal structure was quantified by autocorrelation and detrended fluctuation analysis (DFA). We tested four hypotheses: (1) Tolerance and Covariation, not Noise, are major factors underlying long-term performance improvement. (2) Trial-to-trial dynamics in execution space exhibits preferred directions. (3) The direction-dependent organization of variability becomes more pronounced with practice. (4) The anisotropy is in directions orthogonal and parallel to the solution manifold. Results from 13 subjects practicing for 6 days revealed that performance improvement correlated with increasing Tolerance and Covariation; Noise remained relatively constant. Temporal fluctuations and their directional modulation were identified by a novel rotation method that was a priori ignorant about orthogonality. Results showed a modulation of time-dependent characteristics that became enhanced with practice. However, this directionality was not coincident with orthogonal and parallel directions of the solution manifold. A state-space model with two sources of noise replicated not only the observed temporal structure but also its deviations from orthogonality. Simulations suggested that practice-induced changes were associated with an increase in the feedback gain and a subtle weighting of the two noise sources. The directionality in the structure of variability depended on the scaling of the coordinates, a result that highlights that analysis of variability sensitively depends on the chosen coordinates.

Movement trajectory smoothness is not associated with the endpoint accuracy of rapid multi-joint arm movements in young and older adults

The minimum variance theory proposes that motor commands are corrupted by signal-dependent noise and smooth trajectories with low noise levels are selected to minimize endpoint error and endpoint variability. The purpose of the study was to determine the contribution of trajectory smoothness to the endpoint accuracy and endpoint variability of rapid multi-joint arm movements. Young and older adults performed arm movements (4 blocks of 25 trials) as fast and as accurately as possible to a target with the right (dominant) arm. Endpoint accuracy and endpoint variability along with trajectory smoothness and error were quantified for each block of trials. Endpoint error and endpoint variance were greater in older adults compared with young adults, but decreased at a similar rate with practice for the two age groups. The greater endpoint error and endpoint variance exhibited by older adults were primarily due to impairments in movement extent control and not movement direction control. The normalized jerk was similar for the two age groups, but was not strongly associated with endpoint error or endpoint variance for either group. However, endpoint variance was strongly associated with endpoint error for both the young and older adults. Finally, trajectory error was similar for both groups and was weakly associated with endpoint error for the older adults. The findings are not consistent with the predictions of the minimum variance theory, but support and extend previous observations that movement trajectories and endpoints are planned independently.

What autocorrelation tells us about motor variability: insights from dart throwing

In sports such as golf and darts it is important that one can produce ballistic movements of an object towards a goal location with as little variability as possible. A factor that influences this variability is the extent to which motor planning is updated from movement to movement based on observed errors. Previous work has shown that for reaching movements, our motor system uses the learning rate (the proportion of an error that is corrected for in the planning of the next movement) that is optimal for minimizing the endpoint variability. Here we examined whether the learning rate is hard-wired and therefore automatically optimal, or whether it is optimized through experience. We compared the performance of experienced dart players and beginners in a dart task. A hallmark of the optimal learning rate is that the lag-1 autocorrelation of movement endpoints is zero. We found that the lag-1 autocorrelation of experienced dart players was near zero, implying a near-optimal learning rate, whereas it was negative for beginners, suggesting a larger than optimal learning rate. We conclude that learning rates for trial-by-trial motor learning are optimized through experience. This study also highlights the usefulness of the lag-1 autocorrelation as an index of performance in studying motor-skill learning.

How language production shapes language form and comprehension

Language production processes can provide insight into how language comprehension works and language typology-why languages tend to have certain characteristics more often than others. Drawing on work in memory retrieval, motor planning, and serial order in action planning, the Production-Distribution-Comprehension (PDC) account links work in the fields of language production, typology, and comprehension: (1) faced with substantial computational burdens of planning and producing utterances, language producers implicitly follow three biases in utterance planning that promote word order choices that reduce these burdens, thereby improving production fluency. (2) These choices, repeated over many utterances and individuals, shape the distributions of utterance forms in language. The claim that language form stems in large degree from producers' attempts to mitigate utterance planning difficulty is contrasted with alternative accounts in which form is driven by language use more broadly, language acquisition processes, or producers' attempts to create language forms that are easily understood by comprehenders. (3) Language perceivers implicitly learn the statistical regularities in their linguistic input, and they use this prior experience to guide comprehension of subsequent language. In particular, they learn to predict the sequential structure of linguistic signals, based on the statistics of previously-encountered input. Thus, key aspects of comprehension behavior are tied to lexico-syntactic statistics in the language, which in turn derive from utterance planning biases promoting production of comparatively easy utterance forms over more difficult ones. This approach contrasts with classic theories in which comprehension behaviors are attributed to innate design features of the language comprehension system and associated working memory. The PDC instead links basic features of comprehension to a different source: production processes that shape language form.

Healthy and dystonic children compensate for changes in motor variability

Successful reaching requires that we plan movements to compensate for variability in motor output. Previous studies have shown that healthy adults optimally incorporate estimates of motor variability when planning a pointing task. Children with dystonia have increased variability compared with healthy children. It is not known whether they are able to compensate appropriately for the increased variability and whether this compensation leads to changes in reaching behavior. We examined healthy children and those with increased motor variability due to secondary dystonia. Using a simple virtual display, children performed a motor task where the variability of their movements was manipulated. Results showed that both subject groups changed their movement strategies in response to changes in the level of perceived motor variability. Both groups changed their strategy in a way that improved performance relative to the perceived motor variability. Importantly, dystonic children faced with decreased motor variability adapted their movement strategy to perform better and more similarly to healthy children. These findings show that both healthy and dystonic children are able to respond to changes in motor variability and alter their movement strategies.

Trial-to-trial dynamics and learning in a generalized, redundant reaching task

If humans exploit task redundancies as a general strategy, they should do so even if the redundancy is decoupled from the physical implementation of the task itself. Here, we derived a family of goal functions that explicitly defined infinite possible redundancies between distance (D) and time (T) for unidirectional reaching. All [T, D] combinations satisfying any specific goal function defined a goal-equivalent manifold (GEM). We tested how humans learned two such functions, D/T = c (constant speed) and D·T = c, that were very different but could both be achieved by neurophysiologically and biomechanically similar reaching movements. Subjects were never explicitly shown either relationship, but only instructed to minimize their errors. Subjects exhibited significant learning and consolidation of learning for both tasks. Initial error magnitudes were higher, but learning rates were faster, for the D·T task than for the D/T task. Learning the D/T task first facilitated subsequent learning of the D·T task. Conversely, learning the D·T task first interfered with subsequent learning of the D/T task. Analyses of trial-to-trial dynamics demonstrated that subjects actively corrected deviations perpendicular to each GEM faster than deviations along each GEM to the same degree for both tasks, despite exhibiting significantly greater variance ratios for the D/T task. Variance measures alone failed to capture critical features of trial-to-trial control. Humans actively exploited these abstract task redundancies, even though they did not have to. They did not use readily available alternative strategies that could have achieved the same performance.

Energy margins in dynamic object manipulation

Many tasks require humans to manipulate dynamically complex objects and maintain appropriate safety margins, such as placing a cup of coffee on a coaster without spilling. This study examined how humans learn such safety margins and how they are shaped by task constraints and changing variability with improved skill. Eighteen subjects used a manipulandum to transport a shallow virtual cup containing a ball to a target without losing the ball. Half were to complete the cup transit in a comfortable target time of 2 s (a redundant task with infinitely many equivalent solutions), and the other half in minimum time (a nonredundant task with one explicit cost to optimize). The safety margin was defined as the ball energy relative to escape, i.e., as an energy margin. The first hypothesis, that subjects converge to a single strategy in the minimum-time task but choose different strategies in the less constrained target-time task, was not supported. Both groups developed individualized strategies with practice. The second hypothesis, that subjects decrease safety margins in the minimum-time task but increase them in the target-time task, was supported. The third hypothesis, that in both tasks subjects modulate energy margins according to their execution variability, was partially supported. In the target-time group, changes in energy margins correlated positively with changes in execution variability; in the minimum-time group, such a relation was observed only at the end of practice, not across practice. These results show that when learning a redundant object manipulation task, most subjects increase their safety margins and shape their movement strategies in accordance with their changing variability.

The influence of movement initiation deficits on the quantification of retention in Parkinson's disease

In patients with an impaired motor system, like Parkinson’s disease (PD), deficits in motor learning are expected and results of various studies seem to confirm these expectations. However, most studies in this regard are behaviorally based and quantify learning by performance changes between at least two points in time, e.g., baseline and retention. But, performance in a retention test is also dependent on other factors than learning. Especially in patients, the functional capacity of the control system might be altered unspecific to a certain task and learning episode. The aim of the study is to test whether characteristic temporal deficits exist in PD patients that affect retention performance. We tested the confounding effects of typical PD motor control deficits, here movement initiation deficits, on retention performance in the motor learning process. 12 PD patients and 16 healthy control participants practiced a virtual throwing task over 3 days with 24 h rest between sessions. Retention was tested comparing performance before rest with performance after rest. Movement initiation deficits were quantified by the timing of throwing release that should be affected by impairments in movement initiation. To scrutinize the influence of the initiation deficits on retention performance we gave participants a specific initiation intervention prior to practice on one of the three practice days. We found that only for the PD patients, post-rest performance as well as release timing was better with intervention as compared to without intervention. Their performance could be enhanced through a tuning of release initiation. Thus, we suggest that in PD patients, performance decline after rest that might be easily interpreted as learning deficits could rather result from disease-related deficiencies in motor control.

Functional synergies underlying control of upright posture during changes in head orientation

Background

Studies of human upright posture typically have stressed the need to control ankle and hip joints to achieve postural stability. Recent studies, however, suggest that postural stability involves multi degree-of-freedom (DOF) coordination, especially when performing supra-postural tasks. This study investigated kinematic synergies related to control of the body’s position in space (two, four and six DOF models) and changes in the head’s orientation (six DOF model).

Methodology/Principal Findings

Subjects either tracked a vertically moving target with a head-mounted laser pointer or fixated a stationary point during 4-min trials. Uncontrolled manifold (UCM) analysis was performed across tracking cycles at each point in time to determine the structure of joint configuration variance related to postural stability or tracking consistency. The effect of simulated removal of covariance among joints on that structure was investigated to further determine the role of multijoint coordination. Results indicated that cervical joint motion was poorly coordinated with other joints to stabilize the position of the body center of mass (CM). However, cervical joints were coordinated in a flexible manner with more caudal joints to achieve consistent changes in head orientation.

Conclusions/Significance

An understanding of multijoint coordination requires reference to the stability/control of important performance variables. The nature of that coordination differs depending on the reference variable. Stability of upright posture primarily involved multijoint coordination of lower extremity and lower trunk joints. Consistent changes in the orientation of the head, however, required flexible coordination of those joints with motion of the cervical spine. A two-segment model of postural control was unable to account for the observed stability of the CM position during the tracking task, further supporting the need to consider multijoint coordination to understand postural stability.

How is a motor skill learned? Change and invariance at the levels of task success and trajectory control

The public pays large sums of money to watch skilled motor performance. Notably, however, in recent decades motor skill learning (performance improvement beyond baseline levels) has received less experimental attention than motor adaptation (return to baseline performance in the setting of an external perturbation). Motor skill can be assessed at the levels of task success and movement quality, but the link between these levels remains poorly understood. We devised a motor skill task that required visually guided curved movements of the wrist without a perturbation, and we defined skill learning at the task level as a change in the speed-accuracy trade-off function (SAF). Practice in restricted speed ranges led to a global shift of the SAF. We asked how the SAF shift maps onto changes in trajectory kinematics, to establish a link between task-level performance and fine motor control. Although there were small changes in mean trajectory, improved performance largely consisted of reduction in trial-to-trial variability and increase in movement smoothness. We found evidence for improved feedback control, which could explain the reduction in variability but does not preclude other explanations such as an increased signal-to-noise ratio in cortical representations. Interestingly, submovement structure remained learning invariant. The global generalization of the SAF across a wide range of difficulty suggests that skill for this task is represented in a temporally scalable network. We propose that motor skill acquisition can be characterized as a slow reduction in movement variability, which is distinct from faster model-based learning that reduces systematic error in adaptation paradigms.

The bliss (not the problem) of motor abundance (not redundancy)

Motor control is an area of natural science exploring how the nervous system interacts with other body parts and the environment to produce purposeful, coordinated actions. A central problem of motor control-the problem of motor redundancy-was formulated by Nikolai Bernstein as the problem of elimination of redundant degrees-of-freedom. Traditionally, this problem has been addressed using optimization methods based on a variety of cost functions. This review draws attention to a body of recent findings suggesting that the problem has been formulated incorrectly. An alternative view has been suggested as the principle of abundance, which considers the apparently redundant degrees-of-freedom as useful and even vital for many aspects of motor behavior. Over the past 10 years, dozens of publications have provided support for this view based on the ideas of synergic control, computational apparatus of the uncontrolled manifold hypothesis, and the equilibrium-point (referent configuration) hypothesis. In particular, large amounts of "good variance"-variance in the space of elements that has no effect on the overall performance-have been documented across a variety of natural actions. "Good variance" helps an abundant system to deal with secondary tasks and unexpected perturbations; its amount shows adaptive modulation across a variety of conditions. These data support the view that there is no problem of motor redundancy; there is bliss of motor abundance.

Synergistic control of joint angle variability: influence of target shape

Reaching movements are often used to study the effectiveness of motor control processes with respect to the final position of arm and hand. Empirical evidence shows that different targets can be grasped with similar final position accuracy. However, movements that achieve similar accuracy at their final position may nevertheless be controlled differently. In particular, control strategies may differ in the control of the abundant degrees of freedom with respect to the task-specific costs. The objective of the present study was to investigate whether the applied control strategy was influenced by the shape of the target to be grasped. It was investigated whether mechanical constraints, imposed on final hand orientation or final hand position by the shape of the targets, affected the synergistic coordination of the kinematic degrees of freedom of the arm. Subjects were asked to grasp either a cylindrical or a spherical target, which imposed different constraints on final hand orientation and position. Besides temporal movement aspects, variability of the joint angles of the arm, as well as variability of hand orientation and hand position was analyzed over the whole time course of movement execution, using the uncontrolled manifold method. Overall movement duration differed between cylindrical and spherical target condition, due to differences in deceleration duration. Reaching movements towards the cylindrical target, which was more constraint in final hand orientation and position, took longer than movements towards the spherical target. Analysis further revealed that the degrees of freedom of the arm were synergistically coordinated to stabilize both hand orientation and hand position, when grasping either the spherical or the cylindrical target. This suggests that the applied control strategy in natural reaching movements can simultaneously account for multiple task constraints. The analysis further revealed that stabilization of hand orientation was stronger when reaching towards a cylindrical target, which imposed more constraints on final hand orientation. In contrast, hand position was more strongly stabilized in the spherical target shape condition, where stronger constraints on final hand position were applied. This suggests that different target shapes do influence the control strategy of reaching movements even though variability at movement end was not affected.

State space analysis of timing: exploiting task redundancy to reduce sensitivity to timing

Timing is central to many coordinated actions, and the temporal accuracy of central nervous system commands presents an important limit to skilled performance. Using target-oriented throwing in a virtual environment as an example task, this study presents a novel analysis that quantifies contributions of timing accuracy and shaping of hand trajectories to performance. Task analysis reveals that the result of a throw is fully determined by the projectile position and velocity at release; zero error can be achieved by a manifold of position and velocity combinations (solution manifold). Four predictions were tested. 1) Performers learn to release the projectile closer to the optimal moment for a given arm trajectory, achieving timing accuracy levels similar to those reported in other timing tasks (~10 ms). 2) Performers develop a hand trajectory that follows the solution manifold such that zero error can be achieved without perfect timing. 3) Skilled performers exploit both routes to improvement more than unskilled performers. 4) Long-term improvement in skilled performance relies on continued optimization of the arm trajectory as timing limits are reached. Average and skilled subjects practiced for 6 and 15 days, respectively. In 6 days, both timing and trajectory alignment improved for all subjects, and skilled subjects showed an advantage in timing. With extended practice, performance continued to improve due to continued shaping of the trajectory, whereas timing accuracy reached an asymptote at 9 ms. We conclude that skilled subjects first maximize timing accuracy and then optimize trajectory shaping to compensate for intrinsic limitations of timing accuracy.

Learning to Control Orientation and Force in a Hammering Task

The ability to create stone tools is considered an important step in the emergence of human cognition. To further our understanding of these evolutionary processes we focused on the initial learning processes with which this percussive skill may be acquired. We studied a hammering task in which participants had to create a ground force vector by hitting a target on a force plate with a hammerstone. The produced ground force vector was presented as an arrow on a computer screen and had to end in a displayed target. The target could vary in its angle of azimuth and inclination. Over 5 days, three of the five participants adapted a wrist joint angle and two of these three participants adapted a shoulder joint angle that affected only angle of inclination of the ground force vector. Length and angle of azimuth of the ground force vector were not affected. In learning to control a hammering task, the first parameter to be manipulated seems to be the angle of inclination by adjusting the wrist and shoulder joint angles. This suggests that in the initial stages of learning a hammering task only one parameter is adapted.

Are we ready for a natural history of motor learning?

Here we argue that general principles with regard to the contributions of the cerebellum, basal ganglia, and primary motor cortex to motor learning can begin to be inferred from explicit comparison across model systems and consideration of phylogeny. Both the cerebellum and the basal ganglia have highly conserved circuit architecture in vertebrates. The cerebellum has consistently been shown to be necessary for adaptation of eye and limb movements. The precise contribution of the basal ganglia to motor learning remains unclear but one consistent finding is that they are necessary for early acquisition of novel sequential actions. The primary motor cortex allows independent control of joints and construction of new movement synergies. We suggest that this capacity of the motor cortex implies that it is a necessary locus for motor skill learning, which we argue is the ability to execute selected actions with increasing speed and precision.

Finger coordination under artificial changes in finger strength feedback: a study using analytical inverse optimization

A recently developed method of analytical inverse optimization (ANIO) was used to compute cost functions based on sets of experimental observations in 4-finger pressing tasks with accurate total force and moment production. In different series, feedback on total force and moment was provided using the index finger force at its value, doubled, or halved. Finger force data across different force-moment combinations formed a plane. This allowed reconstructing cost functions as 2nd-order polynomials with linear terms. Changes in the coefficients of the cost function across the 3 series allowed the authors to offer a biomechanical interpretation related to constraints on finger forces with different lever arms. ANIO allows the authors to describe preferred regions within the space of solutions for redundant tasks in terms of cost functions.

The CNS stochastically selects motor plan utilizing extrinsic and intrinsic representations

Traditionally motor studies have assumed that motor tasks are executed according to a single plan characterized by regular patterns, which corresponds to the minimum of a cost function in extrinsic or intrinsic coordinates. However, the novel via-point task examined in this paper shows distinct planning and execution stages in motion production and demonstrates that subjects randomly select from several available motor plans to perform a task. Examination of the effect of pre-training and via-point orientation on subject behavior reveals that the selection of a plan depends on previous movements and is affected by constraints both intrinsic and extrinsic of the body. These results provide new insights into the hierarchical structure of motion planning in humans, which can only be explained if the current models of motor control integrate an explicit plan selection stage.

Neuromotor noise, error tolerance and velocity-dependent costs in skilled performance

In motor tasks with redundancy neuromotor noise can lead to variations in execution while achieving relative invariance in the result. The present study examined whether humans find solutions that are tolerant to intrinsic noise. Using a throwing task in a virtual set-up where an infinite set of angle and velocity combinations at ball release yield throwing accuracy, our computational approach permitted quantitative predictions about solution strategies that are tolerant to noise. Based on a mathematical model of the task expected results were computed and provided predictions about error-tolerant strategies (Hypothesis 1). As strategies can take on a large range of velocities, a second hypothesis was that subjects select strategies that minimize velocity at release to avoid costs associated with signal- or velocity-dependent noise or higher energy demands (Hypothesis 2). Two experiments with different target constellations tested these two hypotheses. Results of Experiment 1 showed that subjects chose solutions with high error-tolerance, although these solutions also had relatively low velocity. These two benefits seemed to outweigh that for many subjects these solutions were close to a high-penalty area, i.e. they were risky. Experiment 2 dissociated the two hypotheses. Results showed that individuals were consistent with Hypothesis 1 although their solutions were distributed over a range of velocities. Additional analyses revealed that a velocity-dependent increase in variability was absent, probably due to the presence of a solution manifold that channeled variability in a task-specific manner. Hence, the general acceptance of signal-dependent noise may need some qualification. These findings have significance for the fundamental understanding of how the central nervous system deals with its inherent neuromotor noise.

Task goals influence online corrections and adaptation of reaching movements

Everyday movements often have multiple solutions. Many of these solutions arise from biomechanical redundancies. Often, however, the goal does not require a unique movement. To examine how people exploit task-related redundancy, we observed as participants produced three-dimensional (3-D) reaching movements, moving to one of two rectangular targets that were diagonally oriented in the frontal (x, y) plane. On most trials, the movement was perturbed by a vertical, velocity-dependent force. Since participants were free to move in 3-D space, online corrections could involve movement along the perturbed, vertical dimension, as well as the nonperturbed, horizontal dimension. If the motor system exploits task redundancies, then corrections along the horizontal dimension should depend on the orientation of the target. Consistent with this prediction, participants modified both the horizontal and vertical coordinates of the trajectory over the course of learning, and the horizontal component was sensitive to the orientation of the target. Furthermore, participants produced online corrections with a horizontal component that brought the hand closer to the target. These results suggest that we not only correct for mismatches between expected and experienced forces but also exploit task-specific redundancies to efficiently improve performance.

Movement variability and skill level of various throwing techniques

In team-handball, skilled athletes are able to adapt to different game situations that may lead to differences in movement variability. Whether movement variability affects the performance of a team-handball throw and is affected by different skill levels or throwing techniques has not yet been demonstrated. Consequently, the aims of the study were to determine differences in performance and movement variability for several throwing techniques in different phases of the throwing movement, and of different skill levels. Twenty-four team-handball players of different skill levels (n=8) performed 30 throws using various throwing techniques. Upper body kinematics was measured via an 8 camera Vicon motion capture system and movement variability was calculated. Results indicated an increase in movement variability in the distal joint movements during the acceleration phase. In addition, there was a decrease in movement variability in highly skilled and skilled players in the standing throw with run-up, which indicated an increase in the ball release speed, which was highest when using this throwing technique. We assert that team-handball players had the ability to compensate an increase in movement variability in the acceleration phase to throw accurately, and skilled players were able to control the movement, although movement variability decreased in the standing throw with run-up.

Human sensorimotor learning: adaptation, skill, and beyond

Recent studies of upper limb movements have provided insights into the computations, mechanisms, and taxonomy of human sensorimotor learning. Motor tasks differ with respect to how they weight different learning processes. These include adaptation, an internal-model based process that reduces sensory-prediction errors in order to return performance to pre-perturbation levels, use-dependent plasticity, and operant reinforcement. Visuomotor rotation and force-field tasks impose systematic errors and thereby emphasize adaptation. In skill learning tasks, which for the most part do not involve a perturbation, improved performance is manifest as reduced motor variability and probably depends less on adaptation and more on success-based exploration. Explicit awareness and declarative memory contribute, to varying degrees, to motor learning. The modularity of motor learning processes maps, at least to some extent, onto distinct brain structures.

Motor Skill Learning, Retention, and Control Deficits in Parkinson's Disease

Parkinson's disease, which affects the basal ganglia, is known to lead to various impairments of motor control. Since the basal ganglia have also been shown to be involved in learning processes, motor learning has frequently been investigated in this group of patients. However, results are still inconsistent, mainly due to skill levels and time scales of testing. To bridge across the time scale problem, the present study examined de novo skill learning over a long series of practice sessions that comprised early and late learning stages as well as retention. 19 non-demented, medicated, mild to moderate patients with Parkinson's disease and 19 healthy age and gender matched participants practiced a novel throwing task over five days in a virtual environment where timing of release was a critical element. Six patients and seven control participants came to an additional long-term retention testing after seven to nine months. Changes in task performance were analyzed by a method that differentiates between three components of motor learning prominent in different stages of learning: Tolerance, Noise and Covariation. In addition, kinematic analysis related the influence of skill levels as affected by the specific motor control deficits in Parkinson patients to the process of learning. As a result, patients showed similar learning in early and late stages compared to the control subjects. Differences occurred in short-term retention tests; patients' performance constantly decreased after breaks arising from poorer release timing. However, patients were able to overcome the initial timing problems within the course of each practice session and could further improve their throwing performance. Thus, results demonstrate the intact ability to learn a novel motor skill in non-demented, medicated patients with Parkinson's disease and indicate confounding effects of motor control deficits on retention performance.

Stages in learning motor synergies: a view based on the equilibrium-point hypothesis

This review describes a novel view on stages in motor learning based on recent developments of the notion of synergies, the uncontrolled manifold hypothesis, and the equilibrium-point hypothesis (referent configuration) that allow to merge these notions into a single scheme of motor control. The principle of abundance and the principle of minimal final action form the foundation for analyses of natural motor actions performed by redundant sets of elements. Two main stages of motor learning are introduced corresponding to (1) discovery and strengthening of motor synergies stabilizing salient performance variable(s) and (2) their weakening when other aspects of motor performance are optimized. The first stage may be viewed as consisting of two steps, the elaboration of an adequate referent configuration trajectory and the elaboration of multi-joint (multi-muscle) synergies stabilizing the referent configuration trajectory. Both steps are expected to lead to more variance in the space of elemental variables that is compatible with a desired time profile of the salient performance variable ("good variability"). Adjusting control to other aspects of performance during the second stage (for example, esthetics, energy expenditure, time, fatigue, etc.) may lead to a drop in the "good variability". Experimental support for the suggested scheme is reviewed.

Motor memory and local minimization of error and effort, not global optimization, determine motor behavior

Many real life tasks that require impedance control to minimize motion error are characterized by multiple solutions where the task can be performed either by co-contracting muscle groups, which requires a large effort, or, conversely, by relaxing muscles. However, human motor optimization studies have focused on tasks that are always satisfied by increasing impedance and that are characterized by a single error-effort optimum. To investigate motor optimization in the presence of multiple solutions and hence optima, we introduce a novel paradigm that enables us to let subjects repetitively (but inconspicuously) use different solutions and observe how exploration of multiple solutions affect their motor behavior. The results show that the behavior is largely influenced by motor memory with subjects tending to involuntarily repeat a recent suboptimal task-satisfying solution even after sufficient experience of the optimal solution. This suggests that the CNS does not optimize co-activation tasks globally but determines the motor behavior in a tradeoff of motor memory, error, and effort minimization.

Uncertainty of feedback and state estimation determines the speed of motor adaptation

Humans can adapt their motor behaviors to deal with ongoing changes. To achieve this, the nervous system needs to estimate central variables for our movement based on past knowledge and new feedback, both of which are uncertain. In the Bayesian framework, rates of adaptation characterize how noisy feedback is in comparison to the uncertainty of the state estimate. The predictions of Bayesian models are intuitive: the nervous system should adapt slower when sensory feedback is more noisy and faster when its state estimate is more uncertain. Here we want to quantitatively understand how uncertainty in these two factors affects motor adaptation. In a hand reaching experiment we measured trial-by-trial adaptation to a randomly changing visual perturbation to characterize the way the nervous system handles uncertainty in state estimation and feedback. We found both qualitative predictions of Bayesian models confirmed. Our study provides evidence that the nervous system represents and uses uncertainty in state estimate and feedback during motor adaptation.

Coordinate dependence of variability analysis

Analysis of motor performance variability in tasks with redundancy affords insight about synergies underlying central nervous system (CNS) control. Preferential distribution of variability in ways that minimally affect task performance suggests sophisticated neural control. Unfortunately, in the analysis of variability the choice of coordinates used to represent multi-dimensional data may profoundly affect analysis, introducing an arbitrariness which compromises its conclusions. This paper assesses the influence of coordinates. Methods based on analyzing a covariance matrix are fundamentally dependent on an investigator's choices. Two reasons are identified: using anisotropy of a covariance matrix as evidence of preferential distribution of variability; and using orthogonality to quantify relevance of variability to task performance. Both are exquisitely sensitive to coordinates. Unless coordinates are known a priori, these methods do not support unambiguous inferences about CNS control. An alternative method uses a two-level approach where variability in task execution (expressed in one coordinate frame) is mapped by a function to its result (expressed in another coordinate frame). An analysis of variability in execution using this function to quantify performance at the level of results offers substantially less sensitivity to coordinates than analysis of a covariance matrix of execution variables. This is an initial step towards developing coordinate-invariant analysis methods for movement neuroscience.