Action initiation and action inhibition follow the same time course when compared under matched experimental conditions.

The ability to initiate an action quickly when needed and the ability to cancel an impending action are both fundamental to action control. It is often presumed that they are qualitatively distinct processes, yet they have largely been studied in isolation and little is known about how they relate to one another. Comparing previous experimental results shows a similar time course for response initiation and response inhibition. However, the exact time course varies widely depending on experimental conditions, including the frequency of different trial types and the urgency to respond. For example, in the stop-signal task, where both action initiation and action inhibition are involved and could be compared, action inhibition is typically found to be much faster. However, this apparent difference is likely due to there being much greater urgency to inhibit an action than to initiate one in order to avoid failing at the task. This asymmetry in the urgency between action initiation and action inhibition makes it impossible to compare their relative time courses in a single task. Here, we demonstrate that when action initiation and action inhibition are measured separately under conditions that are matched as closely as possible, their speeds are not distinguishable and are positively correlated across participants. Our results raise the possibility that action initiation and action inhibition may not necessarily be qualitatively distinct processes but may instead reflect complementary outcomes of a single decision process determining whether or not to act.NEW & NOTEWORTHY The time courses of initiating an action and canceling an action have largely been studied in isolation, and little is known about their relationship. Here, we show that when measured under comparable conditions the speeds of action initiation and action inhibition are the same. This finding raises the possibility that these two functions may be more closely related than previously assumed, with potentially important implications for their underlying neural basis.

Evidence for a common mechanism supporting invigoration of action selection and action execution.

The speed, or vigor, of our movements can vary depending on circumstances. For instance, the promise of a reward leads to faster movements. Reward also leads us to move with a lower reaction time, suggesting that the process of action selection can also be invigorated by reward. It has been proposed that invigoration of action selection and of action execution might occur through a common mechanism, and thus these aspects of behavior might be coupled. To test this hypothesis, we asked participants to make reaching movements to "shoot" through a target at varying speeds to assess whether moving more quickly was also associated with more rapid action selection. We found that, when participants were required to move with a lower velocity, the speed of their action selection was also significantly slowed. This finding was recapitulated in a further dataset in which participants determined their own movement speed, but had to move slowly to stop their movement inside the target. By reanalyzing a previous dataset, we also found evidence for the converse relationship between action execution and action selection; when pressured to select actions more rapidly, people also executed movements with higher velocity. Our results establish that invigoration of action selection and action execution vary in tandem with one another, supporting the hypothesis of a common underlying mechanism.NEW & NOTEWORTHY We show that voluntary increases in the vigor of action execution lead action selection to also occur more rapidly. Conversely, hastening action selection by imposing a deadline to act also leads to increases in movement speed. These findings provide evidence that these two distinct aspects of behavior are modulated by a common underlying mechanism.

Interactions between sensory prediction error and task error during implicit motor learning.

Implicit motor recalibration allows us to flexibly move in novel and changing environments. Conventionally, implicit recalibration is thought to be driven by errors in predicting the sensory outcome of movement (i.e., sensory prediction errors). However, recent studies have shown that implicit recalibration is also influenced by errors in achieving the movement goal (i.e., task errors). Exactly how sensory prediction errors and task errors interact to drive implicit recalibration and, in particular, whether task errors alone might be sufficient to drive implicit recalibration remain unknown. To test this, we induced task errors in the absence of sensory prediction errors by displacing the target mid-movement. We found that task errors alone failed to induce implicit recalibration. In additional experiments, we simultaneously varied the size of sensory prediction errors and task errors. We found that implicit recalibration driven by sensory prediction errors could be continuously modulated by task errors, revealing an unappreciated dependency between these two sources of error. Moreover, implicit recalibration was attenuated when the target was simply flickered in its original location, even though this manipulation did not affect task error - an effect likely attributed to attention being directed away from the feedback cursor. Taken as a whole, the results were accounted for by a computational model in which sensory prediction errors and task errors, modulated by attention, interact to determine the extent of implicit recalibration.

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

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

Control becomes habitual early on when learning a novel motor skill.

When people perform the same task repeatedly, their behavior becomes habitual, or inflexible to changes in the goals or structure of a task. Although habits have been hypothesized to be a key aspect of motor skill acquisition, there has been little empirical work investigating the relationship between skills and habits. To better understand this relationship, we examined whether and when people's behavior would become habitual as they learned a challenging new motor skill: maneuvering an on-screen cursor with a nonintuitive bimanual mapping from hand to cursor position. After participants practiced using this mapping for up to 10 days, we altered the mapping between the hands and the cursor to assess whether participants could flexibly adjust their behavior or would habitually persist in performing the task the way they had originally learned. We found that participants' behavior became habitual within 2 days of practice, at which point they were still relatively unskilled. Further practice led to improved skill but did not alter the strength of habitual behavior. These data demonstrate that motor skills become habitual after relatively little training but can nevertheless further improve with practice. We suggest that building habits early in learning may be a crucial step in acquiring new motor skills.NEW & NOTEWORTHY Habits and motor skills have often been thought to be deeply related, but very few studies have empirically examined the relationship between the two. We present evidence that habits emerge early in learning, long before a motor skill has been fully learned. Our results suggest that habits may play an integral role in the learning and performance of motor skills from even the early stages of acquiring a new skill.

De novo motor learning of a bimanual control task over multiple days of practice.

Although much research on motor learning has focused on how we adapt our movements to maintain performance in the face of imposed perturbations, in many cases, we must learn new skills from scratch or de novo. Compared with adaptation, relatively little is known about de novo learning. In part, this is because learning a new skill can involve many challenges, including learning to recognize new patterns of sensory input and generate new patterns of motor output. However, even with familiar sensory cues and well-practiced movements, the problem of quickly selecting the appropriate actions in response to the current state is challenging. Here, we devised a bimanual hand-to-cursor mapping that isolates this control problem. We find that participants initially struggled to control the cursor under this bimanual mapping, despite explicit knowledge of the mapping. Performance improved steadily over multiple days of practice, however. Participants exhibited no aftereffects when reverting to a veridical cursor, confirming that participants learned the new task de novo, rather than through adaptation. Corrective responses to mid-movement perturbations of the target were initially weak, but with practice, participants gradually became able to respond rapidly and robustly to perturbations. After 4 days of practice, participants' behavior under the bimanual mapping almost matched performance using a veridically mapped cursor. However, there remained a small but persistent difference in performance level. Our findings illustrate the dynamics and limitations of learning a novel controller and introduce a promising paradigm for tractably investigating this aspect of motor skill learning.NEW & NOTEWORTHY We examine motor learning in a novel task in which participants must use both hands to control an on-screen cursor via a nonintuitive interface. Participants gradually improved their ability to control the cursor over multiple practice sessions, but their control was worse than baseline even after 4 days. These results reveal the timescale and limitations of de novo learning-an important but understudied form of learning.

Age-related increases in reaction time result from slower preparation, not delayed initiation.

Recent work indicates that healthy younger adults can prepare accurate responses faster than their voluntary reaction times would suggest, leaving a seemingly unnecessary delay of 80-100 ms before responding. Here, we examined how the preparation of movements, initiation of movements, and the delay between them are affected by aging. Participants made planar reaching movements in two conditions. The "free reaction time" condition assessed the voluntary reaction times with which participants responded to the appearance of a stimulus. The "forced reaction time" condition assessed the minimum time actually needed to prepare accurate movements by controlling the time allowed for movement preparation. The time taken to both initiate movements in the free reaction time and to prepare movements in the forced response condition increased with age. Notably, the time required to prepare accurate movements was significantly shorter than participants' self-selected initiation times; however, the delay between movement preparation and initiation remained consistent across the lifespan (∼90 ms). These results indicate that the slower reaction times of healthy older adults are not due to an increased hesitancy to respond, but can instead be attributed to changes in their ability to process stimuli and prepare movements accordingly, consistent with age-related changes in brain structure and function.NEW & NOTEWORTHY Previous research argues that older adults have slower response times because they hesitate to react, favoring accuracy over speed. The present results challenge this proposal. We found the delay between the minimum time required to prepare movements and the self-selected time at which they initiated remained consistent at ∼90 ms from ages 21 to 80. We therefore suggest older adults' slower response times can be attributed to changes in their ability to process stimuli and prepare movements.

Practice induces a qualitative change in the memory representation for visuomotor learning.

Adaptation of our movements to changes in the environment is known to be supported by multiple learning processes that operate in parallel. One is an implicit recalibration process driven by sensory-prediction errors; the other process counters the perturbation through more deliberate compensation. Prior experience is known to enable adaptation to occur more rapidly, a phenomenon known as "savings," but exactly how experience alters each underlying learning process remains unclear. We measured the relative contributions of implicit recalibration and deliberate compensation to savings across 2 days of practice adapting to a visuomotor rotation. The rate of implicit recalibration showed no improvement with repeated practice. Instead, practice led to deliberate compensation being expressed even when preparation time was very limited. This qualitative change is consistent with the proposal that practice establishes a cached association linking target locations to appropriate motor output, facilitating a transition from deliberate to automatic action selection.NEW & NOTEWORTHY Recent research has shown that savings for visuomotor adaptation is attributable to retrieval of intentional, strategic compensation. This does not seem consistent with the implicit nature of memory for motor skills and calls into question the validity of visuomotor adaptation of reaching movements as a model for motor skill learning. Our findings suggest a solution: that additional practice adapting to a visuomotor perturbation leads to the caching of the initially explicit strategy for countering it.

Independence of Movement Preparation and Movement Initiation.

Initiating a movement in response to a visual stimulus takes significantly longer than might be expected on the basis of neural transmission delays, but it is unclear why. In a visually guided reaching task, we forced human participants to move at lower-than-normal reaction times to test whether normal reaction times are strictly necessary for accurate movement. We found that participants were, in fact, capable of moving accurately ∼80 ms earlier than their reaction times would suggest. Reaction times thus include a seemingly unnecessary delay that accounts for approximately one-third of their duration. Close examination of participants' behavior in conventional reaction-time conditions revealed that they generated occasional, spontaneous errors in trials in which their reaction time was unusually short. The pattern of these errors could be well accounted for by a simple model in which the timing of movement initiation is independent of the timing of movement preparation. This independence provides an explanation for why reaction times are usually so sluggish: delaying the mean time of movement initiation relative to preparation reduces the risk that a movement will be initiated before it has been appropriately prepared. Our results suggest that preparation and initiation of movement are mechanistically independent and may have a distinct neural basis. The results also demonstrate that, even in strongly stimulus-driven tasks, presentation of a stimulus does not directly trigger a movement. Rather, the stimulus appears to trigger an internal decision whether to make a movement, reflecting a volitional rather than reactive mode of control.

The influence of movement preparation time on the expression of visuomotor learning and savings.

Following a change in the environment or motor apparatus, human subjects are able to rapidly compensate their movements to recover accurate performance. This ability to adapt is thought to be achieved through multiple, qualitatively distinct learning processes acting in parallel. It is unclear, however, what the relative contributions of these multiple processes are during learning. In particular, long-term memories in such paradigms have been extensively studied through the phenomenon of savings-faster adaptation to a given perturbation the second time it is experienced-but it is unclear which components of learning contribute to this effect. Here we show that distinct components of learning in an adaptation task can be dissociated based on the amount of preparation time they require. During adaptation, we occasionally forced subjects to generate movements at very low preparation times. Early in learning, subjects expressed only a limited amount of their prior learning in these trials, though performance improved gradually with further practice. Following washout, subjects exhibited a strong and persistent aftereffect in trials in which preparation time was limited. When subjects were exposed to the same perturbation twice in successive days, they adapted faster the second time. This savings effect was, however, not seen in movements generated at low preparation times. These results demonstrate that preparation time plays a critical role in the expression of some components of learning but not others. Savings is restricted to those components that require prolonged preparation to be expressed and might therefore reflect a declarative rather than procedural form of memory.

Persistent residual errors in motor adaptation tasks: reversion to baseline and exploratory escape.

When movements are perturbed in adaptation tasks, humans and other animals show incomplete compensation, tolerating small but sustained residual errors that persist despite repeated trials. State-space models explain this residual asymptotic error as interplay between learning from error and reversion to baseline, a form of forgetting. Previous work using zero-error-clamp trials has shown that reversion to baseline is not obligatory and can be overcome by manipulating feedback. We posited that novel error-clamp trials, in which feedback is constrained but has nonzero error and variance, might serve as a contextual cue for recruitment of other learning mechanisms that would then close the residual error. When error clamps were nonzero and had zero variance, human subjects changed their learning policy, using exploration in response to the residual error, despite their willingness to sustain such an error during the training block. In contrast, when the distribution of feedback in clamp trials was naturalistic, with persistent mean error but also with variance, a state-space model accounted for behavior in clamps, even in the absence of task success. Therefore, when the distribution of errors matched those during training, state-space models captured behavior during both adaptation and error-clamp trials because error-based learning dominated; when the distribution of feedback was altered, other forms of learning were triggered that did not follow the state-space model dynamics exhibited during training. The residual error during adaptation appears attributable to an error-dependent learning process that has the property of reversion toward baseline and that can suppress other forms of learning.

Hedging your bets: intermediate movements as optimal behavior in the context of an incomplete decision.

Existing theories of movement planning suggest that it takes time to select and prepare the actions required to achieve a given goal. These theories often appeal to circumstances where planning apparently goes awry. For instance, if reaction times are forced to be very low, movement trajectories are often directed between two potential targets. These intermediate movements are generally interpreted as errors of movement planning, arising either from planning being incomplete or from parallel movement plans interfering with one another. Here we present an alternative view: that intermediate movements reflect uncertainty about movement goals. We show how intermediate movements are predicted by an optimal feedback control model that incorporates an ongoing decision about movement goals. According to this view, intermediate movements reflect an exploitation of compatibility between goals. Consequently, reducing the compatibility between goals should reduce the incidence of intermediate movements. In human subjects, we varied the compatibility between potential movement goals in two distinct ways: by varying the spatial separation between targets and by introducing a virtual barrier constraining trajectories to the target and penalizing intermediate movements. In both cases we found that decreasing goal compatibility led to a decreasing incidence of intermediate movements. Our results and theory suggest a more integrated view of decision-making and movement planning in which the primary bottleneck to generating a movement is deciding upon task goals. Determining how to move to achieve a given goal is rapid and automatic.

Formation of a long-term memory for visuomotor adaptation following only a few trials of practice.

The term savings refers to faster motor adaptation upon reexposure to a previously experienced perturbation, a phenomenon thought to reflect the existence of a long-term motor memory. It is commonly assumed that sustained practice during the first perturbation exposure is necessary to create this memory. Here we sought to test this assumption by determining the minimum amount of experience necessary during initial adaptation to a visuomotor rotation to bring about savings the following day. Four groups of human subjects experienced 2, 5, 10, or 40 trials of a counterclockwise 30° cursor rotation during reaching movements on one day and were retested the following day to assay for savings. Groups that experienced five trials or more of adaptation on day 1 showed clear savings on day 2. Subjects in all groups learned significantly more from the first rotation trial on day 2 than on day 1, but this learning rate advantage was maintained only in groups that had reached asymptote during the initial exposure. Additional experiments revealed that savings occurred when the magnitude, but not the direction, of the rotation differed across exposures, and when a 5-min break, rather than an overnight one, separated the first and second exposure. The overall pattern of savings we observe across conditions can be explained as rapid retrieval of the state of learning attained during the first exposure rather than as modulation of sensitivity to error. We conclude that a long-term memory for compensating for a perturbation can be rapidly acquired and rapidly retrieved.

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.

Contributions of the cerebellum and the motor cortex to acquisition and retention of motor memories.

We investigated the contributions of the cerebellum and the motor cortex (M1) to acquisition and retention of human motor memories in a force field reaching task. We found that anodal transcranial direct current stimulation (tDCS) of the cerebellum, a technique that is thought to increase neuronal excitability, increased the ability to learn from error and form an internal model of the field, while cathodal cerebellar stimulation reduced this error-dependent learning. In addition, cathodal cerebellar stimulation disrupted the ability to respond to error within a reaching movement, reducing the gain of the sensory-motor feedback loop. By contrast, anodal M1 stimulation had no significant effects on these variables. During sham stimulation, early in training the acquired motor memory exhibited rapid decay in error-clamp trials. With further training the rate of decay decreased, suggesting that with training the motor memory was transformed from a labile to a more stable state. Surprisingly, neither cerebellar nor M1 stimulation altered these decay patterns. Participants returned 24hours later and were re-tested in error-clamp trials without stimulation. The cerebellar group that had learned the task with cathodal stimulation exhibited significantly impaired retention, and retention was not improved by M1 anodal stimulation. In summary, non-invasive cerebellar stimulation resulted in polarity-dependent up- or down-regulation of error-dependent motor learning. In addition, cathodal cerebellar stimulation during acquisition impaired the ability to retain the motor memory overnight. Thus, in the force field task we found a critical role for the cerebellum in both formation of motor memory and its retention.

Evidence for hyperbolic temporal discounting of reward in control of movements.

Suppose that the purpose of a movement is to place the body in a more rewarding state. In this framework, slower movements may increase accuracy and therefore improve the probability of acquiring reward, but the longer durations of slow movements produce devaluation of reward. Here we hypothesize that the brain decides the vigor of a movement (duration and velocity) based on the expected discounted reward associated with that movement. We begin by showing that durations of saccades of varying amplitude can be accurately predicted by a model in which motor commands maximize expected discounted reward. This result suggests that reward is temporally discounted even in timescales of tens of milliseconds. One interpretation of temporal discounting is that the true objective of the brain is to maximize the rate of reward-which is equivalent to a specific form of hyperbolic discounting. A consequence of this idea is that the vigor of saccades should change as one alters the intertrial intervals between movements. We find experimentally that in healthy humans, as intertrial intervals are varied, saccade peak velocities and durations change on a trial-by-trial basis precisely as predicted by a model in which the objective is to maximize the rate of reward. Our results are inconsistent with theories in which reward is discounted exponentially. We suggest that there exists a single cost, rate of reward, which provides a unifying principle that may govern control of movements in timescales of milliseconds, as well as decision making in timescales of seconds to years.

Overcoming motor "forgetting" through reinforcement of learned actions.

The human motor system rapidly adapts to systematic perturbations but the adapted behavior seems to be forgotten equally rapidly. The reason for this forgetting is unclear, as is how to overcome it to promote long-term learning. Here we show that adapted behavior can be stabilized by a period of binary feedback about success and failure in the absence of vector error feedback. We examined the time course of decay after adaptation to a visuomotor rotation through a visual error-clamp condition--trials in which subjects received false visual feedback showing perfect directional performance, regardless of the movements they actually made. Exposure to this error-clamp following initial visuomotor adaptation led to a rapid reversion to baseline behavior. In contrast, exposure to binary feedback after initial adaptation turned the adapted state into a new baseline, to which subjects reverted after transient exposure to another visuomotor rotation. When both binary feedback and vector error were present, some subjects exhibited rapid decay to the original baseline, while others persisted in the new baseline. We propose that learning can be decomposed into two components--a fast-learning, fast-forgetting adaptation process that is sensitive to vector errors and insensitive to task success, and a second process driven by success that learns more slowly but is less susceptible to forgetting. These two learning systems may be recruited to different degrees across individuals. Understanding this competitive balance and exploiting the long-term retention properties of learning through reinforcement is likely to be essential for successful neuro-rehabilitation.

Kinematic coordinations capture learning during human-exoskeleton interaction.

Human-exoskeleton interactions have the potential to bring about changes in human behavior for physical rehabilitation or skill augmentation. Despite significant advances in the design and control of these robots, their application to human training remains limited. The key obstacles to the design of such training paradigms are the prediction of human-exoskeleton interaction effects and the selection of interaction control to affect human behavior. In this article, we present a method to elucidate behavioral changes in the human-exoskeleton system and identify expert behaviors correlated with a task goal. Specifically, we observe the joint coordinations of the robot, also referred to as kinematic coordination behaviors, that emerge from human-exoskeleton interaction during learning. We demonstrate the use of kinematic coordination behaviors with two task domains through a set of three human-subject studies. We find that participants (1) learn novel tasks within the exoskeleton environment, (2) demonstrate similarity of coordination during successful movements within participants, (3) learn to leverage these coordination behaviors to maximize success within participants, and (4) tend to converge to similar coordinations for a given task strategy across participants. At a high level, we identify task-specific joint coordinations that are used by different experts for a given task goal. These coordinations can be quantified by observing experts and the similarity to these coordinations can act as a measure of learning over the course of training for novices. The observed expert coordinations may further be used in the design of adaptive robot interactions aimed at teaching a participant the expert behaviors.

Sensitivity to prediction error in reach adaptation.

It has been proposed that the brain predicts the sensory consequences of a movement and compares it to the actual sensory feedback. When the two differ, an error signal is formed, driving adaptation. How does an error in one trial alter performance in the subsequent trial? Here we show that the sensitivity to error is not constant but declines as a function of error magnitude. That is, one learns relatively less from large errors compared with small errors. We performed an experiment in which humans made reaching movements and randomly experienced an error in both their visual and proprioceptive feedback. Proprioceptive errors were created with force fields, and visual errors were formed by perturbing the cursor trajectory to create a visual error that was smaller, the same size, or larger than the proprioceptive error. We measured single-trial adaptation and calculated sensitivity to error, i.e., the ratio of the trial-to-trial change in motor commands to error size. We found that for both sensory modalities sensitivity decreased with increasing error size. A reanalysis of a number of previously published psychophysical results also exhibited this feature. Finally, we asked how the brain might encode sensitivity to error. We reanalyzed previously published probabilities of cerebellar complex spikes (CSs) and found that this probability declined with increasing error size. From this we posit that a CS may be representative of the sensitivity to error, and not error itself, a hypothesis that may explain conflicting reports about CSs and their relationship to error.

The relationship between habits and motor skills in humans.

How do habit and skill relate to one another? Among many traditions of habit research, we suggest that 'slip-of-action' habits are the type most likely to relate to motor skill. Habits are traditionally thought of as a property of behavior as a whole. We suggest, however, that habits are better understood at the level of intermediate computations and, at this level, habits can be considered to be equivalent to the phenomenon of automaticity in skill learning - improving speed of performance at the cost of flexibility. We also consider the importance of habits in learning complex tasks given limited cognitive resources, and suggest that deliberate practice can be viewed as an iterative process of breaking and restructuring habits to improve performance.