Movement Imitation via an Abstract Trajectory Representation in Dorsal Premotor Cortex.

Humans are particularly good at copying novel and meaningless gestures. The mechanistic and anatomical basis for this specialized imitation ability remains largely unknown. One idea is that imitation occurs by matching body configurations. Here we propose an alternative route to imitation that depends on a body-independent representation of the trajectory path of the end-effector. We studied a group of patients with strokes in the left frontoparietal cortices. We found that they were equally impaired at imitating movement trajectories using the ipsilesional limb (i.e., the nonparetic side) that were cued either by an actor using their whole arm or just by a cursor, suggesting that body configuration information is not always critical for imitation and that a representation of abstract trajectory shape may suffice. In addition, imitation ability was uncorrelated to the ability to identify the trajectory shape, suggesting that imitation deficits were unlikely to arise from perceptual impairments. Finally, a lesion-symptom mapping analysis found that imitation deficits were associated with lesions in left dorsal premotor but not parietal cortex. Together, these findings suggest a novel body-independent route to imitation that relies on the ability to plan abstract movement trajectories within dorsal premotor cortex.SIGNIFICANCE STATEMENT The ability to imitate is critical for rapidly learning to produce new gestures and actions, but how the brain translates observed movements into motor commands is poorly understood. Examining the ability of patients with strokes affecting the left hemisphere revealed that meaningless gestures can be imitated by succinctly representing only the motion of the hand in space, rather than the posture of the entire arm. Moreover, performance deficits correlated with lesions in dorsal premotor cortex, an area not previously associated with impaired imitation of arm postures. These findings thus describe a novel route to imitation that may also be impaired in some patients with apraxia.

Can patients with cerebellar disease switch learning mechanisms to reduce their adaptation deficits?

Systematic perturbations in motor adaptation tasks are primarily countered by learning from sensory-prediction errors, with secondary contributions from other learning processes. Despite the availability of these additional processes, particularly the use of explicit re-aiming to counteract observed target errors, patients with cerebellar degeneration are surprisingly unable to compensate for their sensory-prediction error deficits by spontaneously switching to another learning mechanism. We hypothesized that if the nature of the task was changed-by allowing vision of the hand, which eliminates sensory-prediction errors-patients could be induced to preferentially adopt aiming strategies to solve visuomotor rotations. To test this, we first developed a novel visuomotor rotation paradigm that provides participants with vision of their hand in addition to the cursor, effectively setting the sensory-prediction error signal to zero. We demonstrated in younger healthy control subjects that this promotes a switch to strategic re-aiming based on target errors. We then showed that with vision of the hand, patients with cerebellar degeneration could also switch to an aiming strategy in response to visuomotor rotations, performing similarly to age-matched participants (older controls). Moreover, patients could retrieve their learned aiming solution after vision of the hand was removed (although they could not improve beyond what they retrieved), and retain it for at least 1 year. Both patients and older controls, however, exhibited impaired overall adaptation performance compared to younger healthy controls (age 18-33 years), likely due to age-related reductions in spatial and working memory. Patients also failed to generalize, i.e. they were unable to adopt analogous aiming strategies in response to novel rotations. Hence, there appears to be an inescapable obligatory dependence on sensory-prediction error-based learning-even when this system is impaired in patients with cerebellar disease. The persistence of sensory-prediction error-based learning effectively suppresses a switch to target error-based learning, which perhaps explains the unexpectedly poor performance by patients with cerebellar degeneration in visuomotor adaptation tasks.

Impaired Motor Learning in a Disorder of the Inferior Olive: Is the Cerebellum Confused?

An attractive hypothesis about how the brain learns to keep its motor commands accurate is centered on the idea that the cerebellar cortex associates error signals carried by climbing fibers with simultaneous activity in parallel fibers. Motor learning can be impaired if the error signals are not transmitted, are incorrect, or are misinterpreted by the cerebellar cortex. Learning might also be impaired if the brain is overwhelmed with a sustained barrage of meaningless information unrelated to simultaneously appearing error signals about incorrect performance. We test this concept in subjects with syndrome of oculopalatal tremor (OPT), a rare disease with spontaneous, irregular, roughly pendular oscillations of the eyes thought to reflect an abnormal, synchronous, spontaneous discharge to the cerebellum from the degenerating neurons in the inferior olive. We examined motor learning during a short-term, saccade adaptation paradigm in patients with OPT and found a unique pattern of disturbed adaptation, quite different from the abnormal adaption when the cerebellum is involved directly. Both fast (seconds) and slow (minutes) timescales of learning were impaired. We suggest that the spontaneous, continuous, synchronous output from the inferior olive prevents the cerebellum from receiving the error signals it needs for appropriate motor learning. The important message from this study is that impaired motor adaptation and resultant dysmetria is not the exclusive feature of cerebellar disorders, but it also highlights disorders of the inferior olive and its connections to the cerebellum.

A motor planning stage represents the shape of upcoming movement trajectories.

Interactions with our environment require curved movements that depend not only on the final position of the hand but also on the path used to achieve it. Current studies in motor control, however, largely focus on point-to-point movements and do not consider how movements with specific desired trajectories might arise. In this study, we examined intentionally curved reaching movements that navigate paths around obstacles. We found that the preparation of these movements incurred a large reaction-time cost. This cost could not be attributed to nonmotor task requirements (e.g., stimulus perception) and was independent of the execution difficulty (i.e., extent of curvature) of the movement. Additionally, this trajectory representation cost was not observed for point-to-point reaches but could be optionally included if the task encouraged consideration of straight trajectories. Therefore, when the path of a movement is task relevant, the shape of the desired trajectory is overtly represented as a stage of motor planning. This trajectory representation ability may help explain the vast repertoire of human motor behaviors.

Explicit knowledge enhances motor vigor and performance: motivation versus practice in sequence tasks.

Motor skill learning involves a practice-induced improvement in the speed and/or accuracy of a discrete movement. It is often thought that paradigms involving repetitive practice of discrete movements performed in a fixed sequence result in a further enhancement of skill beyond practice of the individual movements in a random order. Sequence-specific performance improvements could, however, arise without practice as a result of knowledge of the sequence order; knowledge could operate by either enabling advanced motor planning of the known sequence elements or by increasing overall motivation. Here, we examined how knowledge and practice contribute to performance of a sequence of movements. We found that explicit knowledge provided through instruction produced practice-independent improvements in reaction time and execution quality. These performance improvements occurred even for random elements within a partially known sequence, indicative of a general motivational effect rather than a sequence-specific effect of advanced planning. This motivational effect suggests that knowledge influences performance in a manner analogous to reward. Additionally, practice led to similar improvements in execution quality for both known and random sequences. The lack of interaction between knowledge and practice suggests that any skill acquisition occurring during discrete sequence tasks arises solely from practice of the individual movement elements, independent of their order. We conclude that performance improvements in discrete sequence tasks arise from the combination of knowledge-based motivation and sequence-independent practice; investigating this interplay between cognition and movement may facilitate a greater understanding of the acquisition of skilled behavior.

Keeping your head on target.

The mechanisms by which the human brain controls eye movements are reasonably well understood, but those for the head less so. Here, we show that the mechanisms for keeping the head aimed at a stationary target follow strategies similar to those for holding the eyes steady on stationary targets. Specifically, we applied the neural integrator hypothesis that originally was developed for holding the eyes still in eccentric gaze positions to describe how the head is held still when turned toward an eccentric target. We found that normal humans make head movements consistent with the neural integrator hypothesis, except that additional sensory feedback is needed, from proprioceptors in the neck, to keep the head on target. We also show that the complicated patterns of head movements in patients with cervical dystonia can be predicted by deficits in a neural integrator for head motor control. These results support ideas originally developed from animal studies that suggest fundamental similarities between oculomotor and cephalomotor control, as well as a conceptual framework for cervical dystonia that departs considerably from current clinical views.

Similarities in error processing establish a link between saccade prediction at baseline and adaptation performance.

Adaptive processes are crucial in maintaining the accuracy of body movements and rely on error storage and processing mechanisms. Although classically studied with adaptation paradigms, evidence of these ongoing error-correction mechanisms should also be detectable in other movements. Despite this connection, current adaptation models are challenged when forecasting adaptation ability with measures of baseline behavior. On the other hand, we have previously identified an error-correction process present in a particular form of baseline behavior, the generation of predictive saccades. This process exhibits long-term intertrial correlations that decay gradually (as a power law) and are best characterized with the tools of fractal time series analysis. Since this baseline task and adaptation both involve error storage and processing, we sought to find a link between the intertrial correlations of the error-correction process in predictive saccades and the ability of subjects to alter their saccade amplitudes during an adaptation task. Here we find just such a relationship: the stronger the intertrial correlations during prediction, the more rapid the acquisition of adaptation. This reinforces the links found previously between prediction and adaptation in motor control and suggests that current adaptation models are inadequate to capture the complete dynamics of these error-correction processes. A better understanding of the similarities in error processing between prediction and adaptation might provide the means to forecast adaptation ability with a baseline task. This would have many potential uses in physical therapy and the general design of paradigms of motor adaptation.

Cognitive neuropsychological and neuroanatomic predictors of naturalistic action performance in left hemisphere stroke: a retrospective analysis.

Individuals who have experienced a left hemisphere cerebrovascular accident (LCVA) have been shown to make errors in naturalistic action tasks designed to assess the ability to perform everyday activities such as preparing a cup of coffee. Naturalistic action errors in this population are often attributed to limb apraxia, a common deficit in the representation and performance of object-related actions. However, naturalistic action impairments are also observed in right hemisphere stroke and traumatic brain injury, populations infrequently associated with apraxia, and errors across all these populations are influenced by overall severity. Based on these and other data, an alternative (though not mutually exclusive) account is that naturalistic action errors in LCVA are also a consequence of deficits in general attentional resource availability or allocation. In this study, we conducted a retrospective analysis of data from a large group of 51 individuals with LCVA who had completed a test of naturalistic action, along with a battery of tests assessing praxis, attention allocation and control, reasoning, and language abilities to determine which of these capacities contribute uniquely to naturalistic action impairments. Using a regularized regression method, we found that naturalistic action impairments are predicted by both praxis deficits (hand posture sequencing and gesture recognition), as well as attention allocation and control deficits (orienting and dividing attention), along with language comprehension ability and age. Using support vector regression-lesion symptom mapping (SVR-LSM), we also demonstrated that naturalistic action impairments are associated with lesions to posterior middle temporal gyrus and anterior inferior parietal lobule - regions known to be implicated in praxis; as well the middle frontal gyrus that has been implicated in both praxis and attention allocation and control. Taken together, these findings support the hypothesis that naturalistic action impairments in LCVA are a consequence of apraxia as well as deficits in attention allocation and control.

Different Sensory Information Is Used for State Estimation when Stationary or Moving.

The accurate estimation of limb state is necessary for movement planning and execution. While state estimation requires both feedforward and feedback information, we focus here on the latter. Prior literature has shown that integrating visual and proprioceptive feedback improves estimates of static limb position. However, differences in visual and proprioceptive feedback delays suggest that multisensory integration could be disadvantageous when the limb is moving. We formalized this hypothesis by modeling feedback-based state estimation using the long-standing maximum likelihood estimation model of multisensory integration, which we updated to account for sensory delays. Our model predicted that the benefit of multisensory integration was largely lost when the limb was passively moving. We tested this hypothesis in a series of experiments in human subjects that compared the degree of interference created by discrepant visual or proprioceptive feedback when estimating limb position either statically at the end of the movement or dynamically at movement midpoint. In the static case, we observed significant interference: discrepant feedback in one modality systematically biased sensory estimates based on the other modality. However, no interference was seen in the dynamic case: participants could ignore sensory feedback from one modality and accurately reproduce the motion indicated by the other modality. Together, these findings suggest that the sensory feedback used to compute a state estimate differs depending on whether the limb is stationary or moving. While the former may tend toward multimodal integration, the latter is more likely to be based on feedback from a single sensory modality.

Shared and distinct routes in speech and gesture imitation: Evidence from stroke.

Dual-route models of high-level (praxis) actions distinguish between an "indirect" semantic route mediating meaningful gesture imitation, and a "direct" sensory-motor route mediates meaningless gesture imitation. Similarly, dual-route language models distinguish between an indirect route mediating production and repetition of words, and a direct route mediating non-word repetition. Although aphasia and limb apraxia frequently co-occur following left-hemisphere cerebrovascular accident (LCVA), it is unclear which aspects of these functional-neuroanatomic dual-route architectures are shared across praxis and language domains. This study focused on gesture imitation to test the hypothesis that semantic information (and portions of the indirect route) are shared across domains, whereas two distinct dorsal routes mediate sensory-motor mapping. Forty chronic LCVA and 17 neurotypical controls completed semantic memory and language tasks and imitated 3 types of gesture stimuli: (1) labeled/"named" meaningful, (2) unnamed meaningful, and (3) meaningless gestures. The comparison of accuracy between meaningless versus unnamed meaningful gestures examined the benefits of semantic information, while the comparison of unnamed meaningful versus named meaningful imitation examined additional benefits of linguistic cueing. Mixed-effects models examined group by task interaction effects on gesture ability. We found that for patients with LCVA, unnamed meaningful gestures were imitated more accurately than meaningless gestures, suggesting that semantic information was beneficial, but there was no benefit of labeling. Reduced benefit of semantic information on gesture accuracy was associated with lesions to inferior frontal and posterior temporal regions as well as semantic memory performance on a pictorial (non-gesture) task. In contrast, there was no relationship between meaningless gesture imitation and nonword repetition, indicating that measures of direct route performance are not associated across language and action. These results provide preliminary evidence that portions of the indirect semantic route are shared across the language and action domains, while two direct sensory-motor mapping routes mediate word repetition and gesture imitation.

Different sensory information is used for state estimation when stationary or moving.

Accurate estimation of limb state is necessary for movement planning and execution. State estimation requires both feedforward and feedback information; here we focus on the latter. Prior literature has shown that integrating visual and proprioceptive feedback improve estimates of static limb position. However, differences in visual and proprioceptive feedback delays suggest that multisensory integration could be disadvantageous when the limb is moving. To investigate multisensory integration in different passive movement contexts, we compared the degree of interference created by discrepant visual or proprioceptive feedback when estimating the position of the limb either statically at the end of the movement or dynamically at movement midpoint. In the static context, we observed idiosyncratic interference: discrepant proprioceptive feedback significantly interfered with reports of the visual target location, leading to a bias of the reported position toward the proprioceptive cue. In the dynamic context, no interference was seen: participants could ignore sensory feedback from one modality and accurately reproduce the motion indicated by the other modality. We modeled feedback-based state estimation by updating the longstanding maximum likelihood estimation model of multisensory integration to account for sensory delays. Consistent with our behavioral results, the model showed that the benefit of multisensory integration was largely lost when the limb was passively moving. Together, these findings suggest that the sensory feedback used to compute a state estimate differs depending on whether the limb is stationary or moving. While the former may tend toward multimodal integration, the latter is more likely to be based on feedback from a single sensory modality.

Using prediction errors to drive saccade adaptation: the implicit double-step task.

A prediction-based error signal, neurally computed as the difference between predicted and observed movement outcomes, has been proposed as the driving force for motor learning. This suggests that the generation of predictive saccades to periodically paced targets-whose performance accuracy is actively maintained using this same error signal-invokes the motor-learning network. We examined whether a simple predictive-saccade task (implicit double-step adaptation, in which targets are gradually displaced outward to exaggerate normal hypometric movement errors) can stand in place of a traditional double-step saccade-adaptation task to induce an increase in saccade gain. We find that the implicit double-step adaptation task can induce significant gain-increase adaptation (of comparable magnitude to that of the standard double-step task) in normal control subjects. Unlike control subjects, patients with impaired cerebella are unable to adapt their saccades in response to this paradigm; this implies that the cerebellum is crucial for processing prediction-based error signals for motor learning.

Proprioception-based movement goals support imitation and are disrupted in apraxia.

The ability to imitate observed actions serves as an efficient method for learning novel movements and is specifically impaired (without concomitant gross motor impairments) in the neurological disorder of limb apraxia, a disorder common after left hemisphere stroke. Research with apraxic patients has advanced our understanding of how people imitate. However, the role of proprioception in imitation has been rarely assessed directly. Prior work has proposed that proprioceptively sensed body position is transformed into a visual format, supporting the attainment of a desired imitation goal represented visually (i.e., how the movement should look when performed). In contrast, we hypothesized a more direct role for proprioception: we suggest that movement goals are also represented proprioceptively (i.e., how a desired movement should feel when performed), and the ability to represent or access such proprioceptive goals is deficient in apraxia. Using a novel imitation task in which a robot cued meaningless trajectories proprioceptively or visually, we probed the role of each sensory modality. We found that patients with left hemisphere stroke were disproportionately worse than controls at imitating when cued proprioceptively versus visually. This proprioceptive versus visual disparity was associated with apraxia severity as assessed by a traditional imitation task, but could not be explained by general proprioceptive impairment or speed-accuracy trade-offs. These data suggest that successful imitation depends in part on the ability to represent movement goals in terms of how those movements should feel, and that deficits in this ability contribute to imitation impairments in patients with apraxia.

Motor Plans under Uncertainty Reflect a Trade-Off between Maximizing Reward and Success.

When faced with multiple potential movement options, individuals either reach directly to one of the options, or initiate a reach intermediate between the options. It remains unclear why people generate these two types of behaviors. Using the go-before-you-know task (commonly used to study behavior under choice uncertainty) in humans, we examined two key questions. First, do these two types of responses actually reflect distinct movement strategies? If so, the relative desirability (i.e., weighing the success likelihood vs the attainable reward) of the two target options would not need to be computed identically for direct and intermediate reaches. We showed that indeed, when reward and success likelihood differed between the two options, reach direction was preferentially biased toward different directions for direct versus intermediate reaches. Importantly, this suggests that the computation of subjective values depends on the choice of movement strategy. Second, what drives individual differences in how people respond under uncertainty? We found that risk/reward-seeking individuals tended to generate more intermediate reaches and were more responsive to changes in reward, suggesting these movements may reflect a strategy to maximize reward versus success. Together, these findings suggest that when faced with choice uncertainty, individuals adopt movement strategies consistent with their risk/reward attitude, preferentially biasing behavior toward exogenous rewards or endogenous success and consequently modulating the relative desirability of the available options.

Does spatial perspective in virtual reality affect imitation accuracy in stroke patients?

Imitation is an important daily activity involved in social interactions, motor learning, and is commonly used for rehabilitation after stroke. Moreover, deficits in imitation of novel movements commonly occur after left hemisphere stroke (LCVA) in the syndrome of limb apraxia. In the current study, we used a novel virtual reality (VR) imitation paradigm to assess two factors that have remained underexplored in novel movement imitation: the imitation of complex, dynamic full-arm movements, and the effect of spatial perspective. VR holds promise as a tool for a number of clinical assessments and treatments, but has very rarely been studied in the context of imitation or diagnosis of apraxia. Thirty participants (18 with LCVA and 12 age- and education-matched controls) wore a VR headset and observed and imitated an instructor avatar demonstrating arm movements. Three spatial perspectives were examined within-subjects: first-person, third-person mirror, and third-person anatomical. Movements of the ipsilesional (left) arm were recorded and qualitatively coded for accuracy compared to the instructor avatar. Participants also completed embodiment questionnaires, a measure of limb apraxia (imitation of video-recorded meaningless movements), and three computerized background tasks that were hypothesized to evoke some of the same processing requirements of each of the three perspective conditions: a block-matching task, a block-mirroring task, and a mental rotation task. Imitation accuracy was highest in the first-person perspective, consistent with predictions, but did not differ between third-person mirror and anatomical. Surprisingly, patients and controls performed similarly on the imitation task for all spatial perspectives, with overall modest accuracy in both groups, and both patients and controls felt a moderate level of embodiment of their own avatar. Higher imitation accuracy related to quicker block-matching reaction times and higher mental rotation accuracy, regardless of perspective, but was unrelated to imitation of video-recorded meaningless movements. In sum, virtual reality provides advantages in terms of experimental manipulation and control but may present challenges in detecting clinical imitation deficits (limb apraxia).

Action imitation via trajectory-based or posture-based planning.

Imitation is a significant daily activity involved in social interaction and motor learning. Imitation has been theorized to be performed in at least two ways. In posture-based imitation, individuals reproduce how the body should look and feel, and are sensitive to the relative positioning of body parts. In trajectory imitation, individuals mimic the spatiotemporal motion path of the end effector. There are clear anecdotal situations in which one might benefit from imitating postures (when learning ballet) or trajectories (when learning to reach around objects). However, whether these are in fact distinct methods of imitation, and if so, whether they may be applied interchangeably to perform the same task, remain unknown. If these are indeed separate mechanisms that rely on different computational and neural resources, a cost should be incurred when switching from using one mechanism to the other within the context of a single task. Therefore, observing a processing cost would both provide evidence that these are indeed two distinct mechanisms, and that they may be used interchangeably when trying to imitate the same stimulus. To test this, twenty-five healthy young adults performed a sequential multitasking imitation task. Participants were first instructed to pay attention to the limb postures or the hand path of a video-recorded model, then performed a neutral, congruent, or incongruent intervening motor task. Finally, participants imitated the modeled movement. We examined both spatial and temporal imitation accuracy as well as individual spatial consistency. When the primary task involved imitating trajectories, analysis of individual consistency suggested a processing cost: movements following the posture-matching intervening task were less consistent with baseline (neutral) performance, suggesting performance may be disrupted by the incongruence. This effect was not observed when imitating limb postures. In summary, we present initial evidence for a difference between posture matching and trajectory imitation as a result of instructions and intervening tasks that is consistent with the existence of two computationally distinct imitation mechanisms.

Sensorimotor adaptation error signals are derived from realistic predictions of movement outcomes.

Neural systems that control movement maintain accuracy by adaptively altering motor commands in response to errors. It is often assumed that the error signal that drives adaptation is equivalent to the sensory error observed at the conclusion of a movement; for saccades, this is typically the visual (retinal) error. However, we instead propose that the adaptation error signal is derived as the difference between the observed visual error and a realistic prediction of movement outcome. Using a modified saccade-adaptation task in human subjects, we precisely controlled the amount of error experienced at the conclusion of a movement by back-stepping the target so that the saccade is hypometric (positive retinal error), but less hypometric than if the target had not moved (smaller retinal error than expected). This separates prediction error from both visual errors and motor corrections. Despite positive visual errors and forward-directed motor corrections, we found an adaptive decrease in saccade amplitudes, a finding that is well-explained by the employment of a prediction-based error signal. Furthermore, adaptive changes in movement size were linearly correlated to the disparity between the predicted and observed movement outcomes, in agreement with the forward-model hypothesis of motor learning, which states that adaptation error signals incorporate predictions of motor outcomes computed using a copy of the motor command (efference copy).

Mechanisms of Human Motor Learning Do Not Function Independently.

Human motor learning is governed by a suite of interacting mechanisms each one of which modifies behavior in distinct ways and rely on different neural circuits. In recent years, much attention has been given to one type of motor learning, called motor adaptation. Here, the field has generally focused on the interactions of three mechanisms: sensory prediction error SPE-driven, explicit (strategy-based), and reinforcement learning. Studies of these mechanisms have largely treated them as modular, aiming to model how the outputs of each are combined in the production of overt behavior. However, when examined closely the results of some studies also suggest the existence of additional interactions between the sub-components of each learning mechanism. In this perspective, we propose that these sub-component interactions represent a critical means through which different motor learning mechanisms are combined to produce movement; understanding such interactions is critical to advancing our knowledge of how humans learn new behaviors. We review current literature studying interactions between SPE-driven, explicit, and reinforcement mechanisms of motor learning. We then present evidence of sub-component interactions between SPE-driven and reinforcement learning as well as between SPE-driven and explicit learning from studies of people with cerebellar degeneration. Finally, we discuss the implications of interactions between learning mechanism sub-components for future research in human motor learning.

Why Are Sequence Representations in Primary Motor Cortex So Elusive?

In this issue of Neuron, Yokoi and Diedrichsen (2019) use a finger keyboard task to show that sequences are widely represented across cortex but that only single elements are represented in primary motor cortex. These results suggest that sequence tasks primarily probe the ability to order discreet actions rather than to execute a skilled continuous sequential action.

Motor Learning.

Motor learning encompasses a wide range of phenomena, ranging from relatively low-level mechanisms for maintaining calibration of our movements, to making high-level cognitive decisions about how to act in a novel situation. We survey the major existing approaches to characterizing motor learning at both the behavioral and neural level. In particular, we critically review two long-standing paradigms used in motor learning research-adaptation and sequence learning. We discuss the extent to which these paradigms can be considered models of motor skill acquisition, defined as the incremental improvement in our ability to rapidly select and then precisely execute appropriate actions, and conclude that they fall short of doing so. We then discuss two classes of emerging research paradigms-learning of arbitrary visuomotor mappings de novo and learning to execute movements with improved acuity-that more effectively address the acquisition of motor skill. Future work will be needed to determine the degree to which laboratory-based studies of skill, as described in this review, will relate to true expertise, which is likely dependent on the effects of practice on multiple cognitive processes that go beyond traditional sensorimotor neural architecture. © 2019 American Physiological Society. Compr Physiol 9:613-663, 2019.