The value of the follow-through derives from motor learning depending on future actions

Decision uncertainty as a context for motor memory

The current view of perceptual decision-making suggests that once a decision is made, only a single motor programme associated with the decision is carried out, irrespective of the uncertainty involved in decision making. In contrast, we show that multiple motor programmes can be acquired on the basis of the preceding uncertainty of the decision, indicating that decision uncertainty functions as a contextual cue for motor memory. The actions learned after making certain (uncertain) decisions are only partially transferred to uncertain (certain) decisions. Participants were able to form distinct motor memories for the same movement on the basis of the preceding decision uncertainty. Crucially, this contextual effect generalizes to novel stimuli with matched uncertainty levels, demonstrating that decision uncertainty is itself a contextual cue. These findings broaden the understanding of contextual inference in motor memory, emphasizing that it extends beyond direct motor control cues to encompass the decision-making process.

The effects of auditory consequences on visuomotor adaptation and motor memory

Sensorimotor adaptation is a form of motor learning that is essential for maintaining motor performance across the lifespan and is integral to recovery of function after neurological injury. Recent research indicates that experiencing a balance-threatening physical consequence when making a movement error during adaptation can enhance subsequent motor memory. This is perhaps not surprising, as learning to avoid injury is critical for our survival and well-being. Reward and punishment can also differentially modify aspects of motor learning. However, it remains unclear whether other forms of non-physical consequences can impact motor learning. Here we tested the hypothesis that a loud acoustic stimulus linked to a movement error during adaptation could lead to greater generalization and consolidation. Two groups of participants (n = 12 each) adapted to a new, prism-induced visuomotor mapping while performing a precision walking task. One group experienced an unexpected loud acoustic stimulus (85 dB tone) when making foot-placement errors during adaptation. This auditory consequence group adapted faster and showed greater generalization with an interlimb transfer task, but not greater generalization to an obstacle avoidance task. Both groups showed faster relearning (i.e., savings) during the second testing session one week later despite the presence of an interference block of trials following initial adaptation, indicating successful consolidation. However, we did not find significant differences between groups with relearning during session 2. Overall, our results suggest that auditory consequences may serve as a useful method to improve motor learning, though further research is required.

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

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

Significance Statement

A key discovery about the neural underpinnings of memory, made more than half a century ago, is that long-term, but not short-term, memory formation depends on neural structures in the brain's medial temporal lobe (MTL). However, this dichotomy holds only for declarative memories - memories for explicit facts such as names and dates - as long-term procedural memories - memories for implicit knowledge such as sensorimotor skills - are largely unaffected even with substantial MTL damage. Here we demonstrate that the formation of long-term, but not short-term, sensorimotor memory depends on a neural structure known as the cerebellum, and we show that this finding explains the variability previously reported in the extent to which cerebellar damage affects sensorimotor learning.

Explicit learning based on reward prediction error facilitates agile motor adaptations

Error based motor learning can be driven by both sensory prediction error and reward prediction error. Learning based on sensory prediction error is termed sensorimotor adaptation, while learning based on reward prediction error is termed reward learning. To investigate the characteristics and differences between sensorimotor adaptation and reward learning, we adapted a visuomotor paradigm where subjects performed arm movements while presented with either the sensory prediction error, signed end-point error, or binary reward. Before each trial, perturbation indicators in the form of visual cues were presented to inform the subjects of the presence and direction of the perturbation. To analyse the interconnection between sensorimotor adaptation and reward learning, we designed a computational model that distinguishes between the two prediction errors. Our results indicate that subjects adapted to novel perturbations irrespective of the type of prediction error they received during learning, and they converged towards the same movement patterns. Sensorimotor adaptations led to a pronounced aftereffect, while adaptation based on reward consequences produced smaller aftereffects suggesting that reward learning does not alter the internal model to the same degree as sensorimotor adaptation. Even though all subjects had learned to counteract two different perturbations separately, only those who relied on explicit learning using reward prediction error could timely adapt to the randomly changing perturbation. The results from the computational model suggest that sensorimotor and reward learning operate through distinct adaptation processes and that only sensorimotor adaptation changes the internal model, whereas reward learning employs explicit strategies that do not result in aftereffects. Additionally, we demonstrate that when humans learn motor tasks, they utilize both learning processes to successfully adapt to the new environments.

Age-specific walking speed during locomotor adaptation leads to more generalization across contexts

Previous work has shown that compared with young adults, older adults generalize their walking patterns more across environments that impose different motor demands (i.e., split-belt treadmill vs. overground). However, in this previous study, all participants walked at a speed that was more comfortable for older adults than young participants, which leads to the question of whether young adults would generalize more their walking patterns than older adults when exposed to faster speeds that are more comfortable for them. To address this question, we examined the interaction between healthy aging and walking speed on the generalization of a pattern learned on a split-belt treadmill (i.e., legs moving at different speeds) to overground. We hypothesized that walking speed during split-belt walking regulates the generalization of walking patterns in an age-specific manner. To this end, groups of young (<30 y/o) and older (65+ y/o) adults adapted their gait on a split-belt treadmill at either slower or faster walking speeds. We assessed the generalization of movements between the groups by quantifying their aftereffects during overground walking, where larger overground aftereffects represent more generalization, and zero aftereffects represent no generalization. We found an interaction between age and walking speed in the generalization of walking patterns. More specifically, older adults generalized more when adapted at slower speeds, whereas younger adults did so when adapted at faster speeds. These results suggest that comfortable walking speeds lead to more generalization of newly acquired motor patterns beyond the training contexts.

Contextual effects in sensorimotor adaptation adhere to associative learning rules

Traditional associative learning tasks focus on the formation of associations between salient events and arbitrary stimuli that predict those events. This is exemplified in cerebellar-dependent delay eyeblink conditioning, where arbitrary cues such as a tone or light act as conditioned stimuli (CSs) that predict aversive sensations at the cornea (unconditioned stimulus [US]). Here, we ask if a similar framework could be applied to another type of cerebellar-dependent sensorimotor learning - sensorimotor adaptation. Models of sensorimotor adaptation posit that the introduction of an environmental perturbation results in an error signal that is used to update an internal model of a sensorimotor map for motor planning. Here, we take a step toward an integrative account of these two forms of cerebellar-dependent learning, examining the relevance of core concepts from associative learning for sensorimotor adaptation. Using a visuomotor adaptation reaching task, we paired movement-related feedback (US) with neutral auditory or visual contextual cues that served as CSs. Trial-by-trial changes in feedforward movement kinematics exhibited three key signatures of associative learning: differential conditioning, sensitivity to the CS-US interval, and compound conditioning. Moreover, after compound conditioning, a robust negative correlation was observed between responses to the two elemental CSs of the compound (i.e. overshadowing), consistent with the additivity principle posited by theories of associative learning. The existence of associative learning effects in sensorimotor adaptation provides a proof-of-concept for linking cerebellar-dependent learning paradigms within a common theoretical framework.

Motor learning without movement

Prediction errors guide many forms of learning, providing teaching signals that help us improve our performance. Implicit motor adaptation, for instance, is thought to be driven by sensory prediction errors (SPEs), which occur when the expected and observed consequences of a movement differ. Traditionally, SPE computation is thought to require movement execution. However, recent work suggesting that the brain can generate sensory predictions based on motor imagery or planning alone calls this assumption into question. Here, by measuring implicit motor adaptation during a visuomotor task, we tested whether motor planning and well-timed sensory feedback are sufficient for adaptation. Human participants were cued to reach to a target and were, on a subset of trials, rapidly cued to withhold these movements. Errors displayed both on trials with and without movements induced single-trial adaptation. Learning following trials without movements persisted even when movement trials had never been paired with errors and when the direction of movement and sensory feedback trajectories were decoupled. These observations indicate that the brain can compute errors that drive implicit adaptation without generating overt movements, leading to the adaptation of motor commands that are not overtly produced.

Contextual cues are not unique for motor learning: Task-dependant switching of feedback controllers

The separation of distinct motor memories by contextual cues is a well known and well studied phenomenon of feedforward human motor control. However, there is no clear evidence of such context-induced separation in feedback control. Here we test both experimentally and computationally if context-dependent switching of feedback controllers is possible in the human motor system. Specifically, we probe visuomotor feedback responses of our human participants in two different tasks—stop and hit—and under two different schedules. The first, blocked schedule, is used to measure the behaviour of stop and hit controllers in isolation, showing that it can only be described by two independent controllers with two different sets of control gains. The second, mixed schedule, is then used to compare how such behaviour evolves when participants regularly switch from one task to the other. Our results support our hypothesis that there is contextual switching of feedback controllers, further extending the accumulating evidence of shared features between feedforward and feedback control.

Extensive evidence has demonstrated that humans can learn distinct motor memories (i.e. independent feedforward controllers) using contextual cues. However, there is little evidence that such contextual cues produce similar separation of feedback controllers. As accumulating evidence highlights the connection between feedforward and feedback control, we propose that context may be used to separate feedback controllers as well. It has not been trivial to test experimentally whether a change in context also modulates the feedback control, as the controller output is affected by other non-contextual factors such as movement kinematics, time-to-target or the properties of the perturbation used to probe the control. Here we present a computational approach based on normative modelling where we separate the effects of the context from other non-contextual effects on the visuomotor feedback system. We then show experimentally that task context independently modulates the feedback control in a particular manner that can be reliably predicted using optimal feedback control.

Context-Specificity of Locomotor Learning Is Developed during Childhood

Humans can perform complex movements with speed and agility in the face of constantly changing task demands. To accomplish this, motor plans are adapted to account for errors in our movements because of changes in our body (e.g., growth or injury) or in the environment (e.g., walking on sand vs ice). It has been suggested that adaptation that occurs in response to changes in the state of our body will generalize across different movement contexts and environments, whereas adaptation that occurs with alterations in the external environment will be context-specific. Here, we asked whether the ability to form generalizable versus context-specific motor memories develops during childhood. We performed a cross-sectional study of context-specific locomotor adaptation in 35 children (3-18 years old) and 7 adults (19-31 years old). Subjects first adapted their gait and learned a new walking pattern on a split-belt treadmill, which has two belts that move each leg at a different speed. Then, subjects walked overground to assess the generalization of the adapted walking pattern across different environments. Our results show that the generalization of treadmill after-effects to overground walking decreases as subjects' age increases, indicating that age and experience are critical factors regulating the specificity of motor learning. Our results suggest that although basic locomotor patterns are established by two years of age, brain networks required for context-specific locomotor learning are still being developed throughout youth.

Same Action, Different Meaning: Neural Substrates of Action Semantic Meaning

Voluntary actions are shaped by desired goals and internal intentions. Multiple factors, including the planning of subsequent actions and the expectation of sensory outcome, were shown to modulate kinetics and neural activity patterns associated with similar goal-directed actions. Notably, in many real-world tasks, actions can also vary across the semantic meaning they convey, although little is known about how semantic meaning modulates associated neurobehavioral measures. Here, we examined how behavioral and functional magnetic resonance imaging measures are modulated when subjects execute similar actions (button presses) for two different semantic meanings-to answer "yes" or "no" to a binary question. Our findings reveal that, when subjects answer using their right hand, the two semantic meanings are differentiated based on voxel patterns in the frontoparietal cortex and lateral-occipital complex bilaterally. When using their left hand, similar regions were found, albeit only with a more liberal threshold. Although subjects were faster to answer "yes" versus "no" when using their right hand, the neural differences cannot be explained by these kinetic differences. To the best of our knowledge, this is the first evidence showing that semantic meaning is embedded in the neural representation of actions, independent of alternative modulating factors such as kinetic and sensory features.

Using EEG to study sensorimotor adaptation

Sensorimotor adaptation, or the capacity to flexibly adapt movements to changes in the body or the environment, is crucial to our ability to move efficiently in a dynamic world. The field of sensorimotor adaptation is replete with rigorous behavioural and computational methods, which support strong conceptual frameworks. An increasing number of studies have combined these methods with electroencephalography (EEG) to unveil insights into the neural mechanisms of adaptation. We review these studies: discussing EEG markers of adaptation in the frequency and the temporal domain, EEG predictors for successful adaptation and how EEG can be used to unmask latent processes resulting from adaptation, such as the modulation of spatial attention. With its high temporal resolution, EEG can be further exploited to deepen our understanding of sensorimotor adaptation.

Separation of multiple motor memories through implicit and explicit processes

Acquisition of multiple motor skills without interference is a remarkable ability in daily life. During adaptation to opposing perturbations, a common paradigm to study this ability, each perturbation can be successfully learned when a contextual follow-through movement is associated with the direction of the perturbation. It is still unclear, however, to what extent this learning engages the cognitive explicit process and the implicit process. Here, we untangled the individual contributions of the explicit and implicit components while participants learned opposing visuomotor perturbations, with a second unperturbed follow-through movement. In Exp. 1 we replicated previous adaptation results and showed that follow-through movements also allow learning for opposing visuomotor rotations. For one group of participants in Exp. 2 we isolated strategic explicit learning, while for another group we isolated the implicit component. Our data showed that opposing perturbations could be fully learned by explicit strategies; but when strategy was restricted, distinct implicit processes contributed to learning. In Exp.3, we examined whether learning is influenced by the disparity between the follow-through contexts. We found that the location of follow-through targets had little effect on total learning, yet it led to more instances in which participants failed to learn the task. In Exp. 4, we explored the generalization capability to untrained targets. Participants showed near-flat generalization of the implicit and explicit processes. Overall, our results indicate that follow-through contextual cues might activate, in part, top-down cognitive factors that influence not only the dynamics of the explicit learning, but also the implicit process.

Anterograde interference emerges along a gradient as a function of task similarity: A behavioural study

Anterograde interference emerges when two opposite (B → A) or identical tasks (A → A) are learned in close temporal succession, suggesting that interference cannot be fully accounted for by competing memories. Informed by neurobiological evidence, this work tested the hypothesis that interference depends upon the degree of overlap between the neural networks involved in the learning of two tasks. In a fully within‐subject and counterbalanced design, participants (n = 24) took part in two learning sessions where the putative overlap between learning‐specific neural networks was behaviourally manipulated across four conditions by modifying reach direction and the effector used during gradual visuomotor adaptation. The results showed that anterograde interference emerged regardless of memory competition—that is, to a similar extent in the B → A and A → A conditions—and along a gradient as a function of the tasks' similarity. Specifically, learning under similar reaching conditions generated more anterograde interference than learning under dissimilar reaching conditions, suggesting that putatively overlapping neural networks are required to generate interference. Overall, these results indicate that competing memories are not the sole contributor to anterograde interference and suggest that overlapping neural networks between two learning sessions are required to trigger interference. One discussed possibility is that initial learning modifies the properties of its neural networks to constrain further plasticity induction and learning capabilities, therefore causing anterograde interference in a network‐dependent manner. One implication is that learning‐specific neural networks must be maximally dissociated to minimize the interfering influences of previous learning on subsequent learning.

Direct and indirect cues can enable dual adaptation, but through different learning processes

Switching between motor tasks requires accurate adjustments for changes in dynamics (grasping a cup) or sensorimotor transformations (moving a computer mouse). Dual-adaptation studies have investigated how learning of context-dependent dynamics or transformations is enabled by sensory cues. However, certain cues, such as color, have shown mixed results. We propose that these mixed results may arise from two major classes of cues: "direct" cues, which are part of the dynamic state and "indirect" cues, which are not. We hypothesized that explicit strategies would primarily account for the adaptation of an indirect color cue but would be limited to simple tasks, whereas a direct visual separation cue would allow implicit adaptation regardless of task complexity. To test this idea, we investigated the relative contribution of implicit and explicit learning in relation to contextual cue type (colored or visually shifted workspace) and task complexity (1 or 8 targets) in a dual-adaptation task. We found that the visual workspace location cue enabled adaptation across conditions primarily through implicit adaptation. In contrast, we found that the color cue was largely ineffective for dual adaptation, except in a small subset of participants who appeared to use explicit strategies. Our study suggests that the previously inconclusive role of color cues in dual adaptation may be explained by differential contribution of explicit strategies across conditions.NEW & NOTEWORTHY We present evidence that learning of context-dependent dynamics proceeds via different processes depending on the type of sensory cue used to signal the context. Visual workspace location enabled learning different dynamics implicitly, presumably because it directly enters the dynamic state estimate. In contrast, a color cue was only successful where learners were apparently able to leverage explicit strategies to account for changed dynamics. This suggests a unification for the previously inconclusive role of color cues.

Implicit learning of temporal behavior in complex dynamic environments

Humans can automatically detect and learn to exploit repeated aspects (regularities) of the environment. Timing research suggests that such learning is not only used to anticipate what will happen, but also when it will happen. However, in timing experiments, the intervals to be timed are presented in isolation from other stimuli and explicitly cued, contrasting with naturalistic environments in which intervals are embedded in a constant stream of events and individuals are hardly aware of them. It is unclear whether laboratory findings from timing research translate to a more ecologically valid, implicit environment. Here we show in a game-like experiment, specifically designed to measure naturalistic behavior, that participants implicitly use regular intervals to anticipate future events, even when these intervals are constantly interrupted by irregular yet behaviorally relevant events. This finding extends previous research by showing that individuals not only detect such regularities but can also use this knowledge to decide when to act in a complex environment. Furthermore, this finding demonstrates that this type of learning can occur independently from the ordinal sequence of motor actions, which contrasts this work with earlier motor learning studies. Taken together, our results demonstrate that regularities in the time between events are implicitly monitored and used to predict and act on what happens when, thereby showing that laboratory findings from timing research can generalize to naturalistic environments. Additionally, with the development of our game-like experiment, we demonstrate an approach to test cognitive theories in less controlled, ecologically more valid environments.

Differential contributions of implicit and explicit learning mechanisms to various contextual cues in dual adaptation

The ability to switch between different visuomotor maps accurately and efficiently is an invaluable feature to a flexible and adaptive human motor system. This can be examined in dual adaptation paradigms where the motor system is challenged to perform under randomly switching, opposing perturbations. Typically, dual adaptation doesn’t proceed unless each mapping is trained in association with a predictive cue. To investigate this, we first explored whether dual adaptation occurs under a variety of contextual cues including active follow-through movements, passive follow-through movements, active lead-in movements, and static visual cues. In the second experiment, we provided one group with a compensatory strategy about the perturbations (30° CW and 30° CCW rotations) and their relationships to each context (static visual cues). We found that active, but not passive, movement cues elicited dual adaptation. Expectedly, we didn’t find evidence for dual adaptation using static visual cues, but those in the Instruction group compensated by implementing aiming strategies. Then, across all experimental conditions, we explored the extent by which dual learning is supported by both implicit and explicit mechanisms, regardless of whether they elicited dual adaptation across all the various cues. To this end, following perturbed training, participants from all experiments were asked to either use or ignore the strategy as they reached without visual feedback. This Process Dissociation Procedure teased apart the implicit and explicit contributions to dual adaptation. Critically, we didn’t find evidence for implicit learning for those given instructions, suggesting that when explicit aiming strategies are implemented in dual adaptation, implicit mechanisms are likely not involved. Thus, by implementing conscious strategies, dual adaptation can be easily facilitated even in cases where learning would not occur otherwise.

Foot clearance when crossing obstacles of different heights with the lead and trail limbs

BACKGROUND

In order to predict and prevent falls and fall-related injuries, it is crucial to understand the motor control for crossing obstacles. In real life, since obstacles do not always take regular shapes like rectangles, the lead and trail limbs sometimes need to negotiate different obstacle heights. The interlimb interaction in this process has remained unknown, since obstacle crossing studies commonly use a single-obstacle paradigm in which the obstacle height is the same for the lead and trail limbs.

RESEARCH QUESTION

We used a dual-obstacle paradigm to test whether the foot clearance over one obstacle was influenced by the contralateral obstacle's height.

METHODS

Sixteen healthy young male and female participants (age: 22.5 ± 1.9 years) crossed over two obstacles placed side by side. Four obstacle conditions were made by combining obstacles of two heights (low, L, 9.0 cm; high, H, 22.5 cm) of the obstacles.In the LL condition, both obstacles were low, and in the LH condition, there was a low obstacle for the lead limb and a high one for the trail limb. Similarly, we also arranged HL and HH conditions. Each subject performed 20 trials per condition. We compared the vertical foot clearance, prestep distance, and poststep distance between the conditions.

RESULT

The foot trajectory to step over the obstacles were affected by the contralateral obstacle's height. The vertical foot clearance of the trail limb was greater in the HL condition than in the LL condition. The vertical foot clearance of the lead limb was greater in the LH condition than in the LL condition.

SIGNIFICANCE

The results suggest that the foot trajectory was not determined exclusively by the obstacle to be crossed. Instead, comprehensive information, including the height of the obstacle for the other limb, might be used for motor control during obstacle crossing.

Increasing the gradient of energetic cost does not initiate adaptation in human walking

When in a new situation, the nervous system may benefit from adapting its control policy. In determining whether or not to initiate this adaptation, the nervous system may rely on some features of the new situation. Here, we tested whether one such feature is salient cost savings. We changed cost saliency by manipulating the gradient of participants' energetic cost landscape during walking. We hypothesized that steeper gradients would cause participants to spontaneously adapt their step frequency to lower costs. To manipulate the gradient, a mechatronic system applied controlled fore-aft forces to the waist of participants as a function of their step frequency as they walked on a treadmill. These forces increased the energetic cost of walking at high step frequencies and reduced it at low step frequencies. We successfully created three cost landscapes of increasing gradients, where the natural variability in participants' step frequency provided cost changes of 3.6% (shallow), 7.2% (intermediate), and 10.2% (steep). Participants did not spontaneously initiate adaptation in response to any of the gradients. Using metronome-guided walking-a previously established protocol for eliciting initiation of adaptation-participants next experienced a step frequency with a lower cost. Participants then adapted by -1.41 ± 0.81 (P = 0.007) normalized units away from their originally preferred step frequency obtaining cost savings of 4.80% ± 3.12%. That participants would adapt under some conditions, but not in response to steeper cost gradients, suggests that the nervous system does not solely rely on the gradient of energetic cost to initiate adaptation in novel situations.NEW & NOTEWORTHY People can adapt to novel conditions but often require cues to initiate the adaptation. Using a mechatronic system to reshape energetic cost gradients during treadmill walking, we tested whether the nervous system can use information present in the cost gradient to spontaneously initiate adaptation. We found that our participants did not spontaneously initiate adaptation even in the steepest gradient. The nervous system does not rely solely on the cost gradient when initiating adaptation.

Embodied virtual reality for the study of real-world motor learning

Motor-learning literature focuses on simple laboratory-tasks due to their controlled manner and the ease to apply manipulations to induce learning and adaptation. Recently, we introduced a billiards paradigm and demonstrated the feasibility of real-world-neuroscience using wearables for naturalistic full-body motion-tracking and mobile-brain-imaging. Here we developed an embodied virtual-reality (VR) environment to our real-world billiards paradigm, which allows to control the visual feedback for this complex real-world task, while maintaining sense of embodiment. The setup was validated by comparing real-world ball trajectories with the trajectories of the virtual balls, calculated by the physics engine. We then ran our short-term motor learning protocol in the embodied VR. Subjects played billiard shots when they held the physical cue and hit a physical ball on the table while seeing it all in VR. We found comparable short-term motor learning trends in the embodied VR to those we previously reported in the physical real-world task. Embodied VR can be used for learning real-world tasks in a highly controlled environment which enables applying visual manipulations, common in laboratory-tasks and rehabilitation, to a real-world full-body task. Embodied VR enables to manipulate feedback and apply perturbations to isolate and assess interactions between specific motor-learning components, thus enabling addressing the current questions of motor-learning in real-world tasks. Such a setup can potentially be used for rehabilitation, where VR is gaining popularity but the transfer to the real-world is currently limited, presumably, due to the lack of embodiment.

Rapid Changes in Movement Representations during Human Reaching Could Be Preserved in Memory for at Least 850 ms

Humans adapt to mechanical perturbations such as forcefields (FFs) during reaching within tens of trials. However, recent findings suggested that this adaptation may start within one single trial, i.e., online corrective movements can become tuned to the unanticipated perturbations within a trial. This was highlighted in previous works with a reaching experiment in which participants had to stop at a via-point (VP) located between the start and the goal. An FF was applied during the first and second parts of the movement and then occasionally unexpectedly switched off at the VP during catch trials. The results showed an after-effect during the second part of the movement when participants exited the VP. This behavioral result was interpreted as a standard after-effect, but it remained unclear how it was related to conventional trial-by-trial learning. The current study aimed to investigate how long do such changes in movement representations last in memory. For this, we have studied the same reaching task with VP in two situations: one with very short residing time in the VP and the second with an imposed minimum 500 ms dwell time in the VP. In both situations, during the unexpected absence of the FF after VP, after-effects were observed. This suggests that online corrections to the internal representation of reach dynamics can be preserved in memory for around 850 ms of resting time on average. Therefore, rapid changes occurring within movements can thus be preserved in memory long enough to influence trial-by-trial motor adaptation.

Motor learning in real-world pool billiards

The neurobehavioral mechanisms of human motor-control and learning evolved in free behaving, real-life settings, yet this is studied mostly in reductionistic lab-based experiments. Here we take a step towards a more real-world motor neuroscience using wearables for naturalistic full-body motion-tracking and the sports of pool billiards to frame a real-world skill learning experiment. First, we asked if well-known features of motor learning in lab-based experiments generalize to a real-world task. We found similarities in many features such as multiple learning rates, and the relationship between task-related variability and motor learning. Our data-driven approach reveals the structure and complexity of movement, variability, and motor learning, enabling an in-depth understanding of the structure of motor learning in three ways: First, while expecting most of the movement learning is done by the cue-wielding arm, we find that motor learning affects the whole body, changing motor-control from head to toe. Second, during learning, all subjects decreased their movement variability and their variability in the outcome. Subjects who were initially more variable were also more variable after learning. Lastly, when screening the link across subjects between initial variability in individual joints and learning, we found that only the initial variability in the right forearm supination shows a significant correlation to the subjects' learning rates. This is in-line with the relationship between learning and variability: while learning leads to an overall reduction in movement variability, only initial variability in specific task-relevant dimensions can facilitate faster learning.

Timescales of motor memory formation in dual-adaptation

The timescales of adaptation to novel dynamics are well explained by a dual-rate model with slow and fast states. This model can predict interference, savings and spontaneous recovery, but cannot account for adaptation to multiple tasks, as each new task drives unlearning of the previously learned task. Nevertheless, in the presence of appropriate contextual cues, humans are able to adapt simultaneously to opposing dynamics. Consequently this model was expanded, suggesting that dual-adaptation occurs through a single fast process and multiple slow processes. However, such a model does not predict spontaneous recovery within dual-adaptation. Here we assess the existence of multiple fast processes by examining the presence of spontaneous recovery in two experimental variations of an adaptation-de-adaptation-error-clamp paradigm within dual-task adaptation in humans. In both experiments, evidence for spontaneous recovery towards the initially learned dynamics (A) was found in the error-clamp phase, invalidating the one-fast-two-slow dual-rate model. However, as adaptation is not only constrained to two timescales, we fit twelve multi-rate models to the experimental data. BIC model comparison again supported the existence of two fast processes, but extended the timescales to include a third rate: the ultraslow process. Even within our single day experiment, we found little evidence for decay of the learned memory over several hundred error-clamp trials. Overall, we show that dual-adaptation can be best explained by a two-fast-triple-rate model over the timescales of adaptation studied here. Longer term learning may require even slower timescales, explaining why we never forget how to ride a bicycle.

Retaining motor skills is crucial to perform basic daily life tasks. However we still have limited understanding of the computational structure of these motor memories, an understanding that is critical for designing rehabilitation. Here we demonstrate that learning any task involves adaptation of independent fast, slow and ultraslow processes to build a motor memory. The selection of the appropriate motor memory is gated through a contextual cue. Together this work extends our understanding of the architecture of motor memories, by merging disparate computational theories to propose a new model.

The Psychology of Reaching: Action Selection, Movement Implementation, and Sensorimotor Learning

The study of motor planning and learning in humans has undergone a dramatic transformation in the 20 years since this journal's last review of this topic. The behavioral analysis of movement, the foundational approach for psychology, has been complemented by ideas from control theory, computer science, statistics, and, most notably, neuroscience. The result of this interdisciplinary approach has been a focus on the computational level of analysis, leading to the development of mechanistic models at the psychological level to explain how humans plan, execute, and consolidate skilled reaching movements. This review emphasizes new perspectives on action selection and motor planning, research that stands in contrast to the previously dominant representation-based perspective of motor programming, as well as an emerging literature highlighting the convergent operation of multiple processes in sensorimotor learning.

Motor memories in manipulation tasks are linked to contact goals between objects

Skillful manipulation requires forming memories of object dynamics, linking applied force to motion. Although it has been assumed that such memories are linked to objects, a recent study showed that people can form separate memories when these are linked to different controlled points on an object (Heald JB, Ingram JN, Flanagan JR, Wolpert DM. Nat Hum Behav 2: 300-311, 2018). In that study, participants controlled the handle of a robotic device to move a virtual bar with circles (control points) on the left and right sides. Participants were instructed to move either the left or right control point to a target on the left or right, respectively, such that the required movement was constant. When these control points were paired with opposing force fields, adaptation was observed. In this previous study, both the controlled point and the target changed between contexts. To assess which of these factors is critical for learning, here, we used a similar paradigm but with a bar that automatically rotated as it was moved. In the first experiment, the bar rotated, such that the left and right control points moved to a common target. In the second experiment, the bar rotated such that a single control point moved to a target located on either the left or right. In both experiments, participants were able to learn opposing force fields applied in the two contexts. We conclude that separate memories of dynamics can be formed for different "contact goals," involving a unique combination of the controlled point on an object and the target location this point "contacts."NEW & NOTEWORTHY Skilled manipulation requires forming memories of object dynamics, previously assumed to be associated with entire objects. However, we recently demonstrated that people can form multiple motor memories when explicitly instructed to move different locations on an object to different targets. Here, we show that separate motor memories can be learned for different contact goals, which involve a unique combination of a control point and target.

Altering attention to split-belt walking increases the generalization of motor memories across walking contexts

Little is known about the impact of attention during motor adaptation tasks on how movements adapted in one context generalize to another. We investigated this by manipulating subjects' attention to their movements while exposing them to split-belt walking (i.e., legs moving at different speeds), which is known to induce locomotor adaptation. We hypothesized that reducing subjects' attention to their movements by distracting them as they adapted their walking pattern would facilitate the generalization of recalibrated movements beyond the training environment. We reasoned that awareness of the novel split-belt condition could be used to consciously contextualize movements to that particular situation. To test this hypothesis, young adults adapted their gait on a split-belt treadmill while they observed visual information that either distracted them or made them aware of the belt's speed difference. We assessed adaptation and aftereffects of spatial and temporal gait features known to adapt and generalize differently in different environments. We found that all groups adapted similarly by reaching the same steady-state values for all gait parameters at the end of the adaptation period. In contrast, both groups with altered attention to the split-belts environment (distraction and awareness groups) generalized their movements from the treadmill to overground more than controls, who walked without altered attention. This was specifically observed in the generalization of step time (temporal gait feature), which might be less susceptible to online corrections during walking overground. These results suggest that altering attention to one's movements during sensorimotor adaptation facilitates the generalization of movement recalibration.NEW & NOTEWORTHY Little is known about how attention affects the generalization of motor recalibration induced by sensorimotor adaptation paradigms. We showed that altering attention to movements on a split-belt treadmill led to greater adaptation effects in subjects walking overground. Thus our results suggest that altering patients' attention to their actions during sensorimotor adaptation protocols could lead to greater generalization of corrected movements when moving without the training device.

Assessing explicit strategies in force field adaptation

In recent years, it has become increasingly clear that a number of learning processes are at play in visuomotor adaptation tasks. In addition to implicitly adapting to a perturbation, learners can develop explicit knowledge allowing them to select better actions in responding to it. Advances in visuomotor rotation experiments have underscored the important role of such "explicit learning" in shaping adaptation to kinematic perturbations. Yet, in adaptation to dynamic perturbations, its contribution has been largely overlooked. We therefore sought to approach the assessment of explicit learning in adaptation to dynamic perturbations, by developing two novel modifications of a force field experiment. First, we asked learners to abandon any cognitive strategy before selected force channel trials to expose consciously accessible parts of overall learning. Here, learners indeed reduced compensatory force compared with standard Catch channels. Second, we instructed a group of learners to mimic their right hand's adaptation by moving with their naïve left hand. While a control group displayed negligible left hand force compensation, the mimicking group reported forces that approximated right hand adaptation but appeared to under-report the velocity component of the force field in favor of a more position-based component. Our results highlight the viability of explicit learning as a potential contributor to force field adaptation, though the fraction of learning under participants' deliberate control on average remained considerably smaller than that of implicit learning, despite task conditions favoring explicit learning. The methods we employed provide a starting point for investigating the contribution of explicit strategies to force field adaptation.NEW & NOTEWORTHY While the contribution of explicit learning has been increasingly studied in visuomotor adaptation, its contribution to force field adaptation has not been studied extensively. We employed two novel methods to assay explicit learning in a force field adaptation task and found that learners can voluntarily control aspects of compensatory force production and manually report it with their untrained limb. This supports the general viability of the contribution of explicit learning also in force field adaptation.

Asymmetry in kinematic generalization between visual and passive lead-in movements are consistent with a forward model in the sensorimotor system

In our daily life we often make complex actions comprised of linked movements, such as reaching for a cup of coffee and bringing it to our mouth to drink. Recent work has highlighted the role of such linked movements in the formation of independent motor memories, affecting the learning rate and ability to learn opposing force fields. In these studies, distinct prior movements (lead-in movements) allow adaptation of opposing dynamics on the following movement. Purely visual or purely passive lead-in movements exhibit different angular generalization functions of this motor memory as the lead-in movements are modified, suggesting different neural representations. However, we currently have no understanding of how different movement kinematics (distance, speed or duration) affect this recall process and the formation of independent motor memories. Here we investigate such kinematic generalization for both passive and visual lead-in movements to probe their individual characteristics. After participants adapted to opposing force fields using training lead-in movements, the lead-in kinematics were modified on random trials to test generalization. For both visual and passive modalities, recalled compensation was sensitive to lead-in duration and peak speed, falling off away from the training condition. However, little reduction in force was found with increasing lead-in distance. Interestingly, asymmetric transfer between lead-in movement modalities was also observed, with partial transfer from passive to visual, but very little vice versa. Overall these tuning effects were stronger for passive compared to visual lead-ins demonstrating the difference in these sensory inputs in regulating motor memories. Our results suggest these effects are a consequence of state estimation, with differences across modalities reflecting their different levels of sensory uncertainty arising as a consequence of dissimilar feedback delays.

How different effectors and action effects modulate the formation of separate motor memories

Humans can operate a variety of modern tools, which are often associated with different visuomotor transformations. Studies investigating this ability have shown that separate motor memories can be acquired implicitly when different sensorimotor transformations are associated with distinct (intended) postures or explicitly when abstract contextual cues are leveraged by aiming strategies. It still remains unclear how different transformations are remembered implicitly when postures are similar. We investigated whether features of planning to manipulate a visual tool, such as its visual identity or the environmental effect intended by its use (i.e. action effect) would enable implicit learning of opposing visuomotor rotations. Results show that neither contextual cue led to distinct implicit motor memories, but that cues only affected implicit adaptation indirectly through generalization around explicit strategies. In contrast, a control experiment where participants practiced opposing transformations with different hands did result in contextualized aftereffects differing between hands across generalization targets. It appears that different (intended) body states are necessary for separate aftereffects to emerge, suggesting that the role of sensory prediction error-based adaptation may be limited to the recalibration of a body model, whereas establishing separate tool models may proceed along a different route.

The visual geometry of a tool modulates generalization during adaptation

Knowledge about a tool’s dynamics can be acquired from the visual configuration of the tool and through physical interaction. Here, we examine how visual information affects the generalization of dynamic learning during tool use. Subjects rotated a virtual hammer-like object while we varied the object dynamics separately for two rotational directions. This allowed us to quantify the coupling of adaptation between the directions, that is, how adaptation transferred from one direction to the other. Two groups experienced the same dynamics of the object. For one group, the object’s visual configuration was displayed, while for the other, the visual display was uninformative as to the dynamics. We fit a range of context-dependent state-space models to the data, comparing different forms of coupling. We found that when the object’s visual configuration was explicitly provided, there was substantial coupling, such that 31% of learning in one direction transferred to the other. In contrast, when the visual configuration was ambiguous, despite experiencing the same dynamics, the coupling was reduced to 12%. Our results suggest that generalization of dynamic learning of a tool relies, not only on its dynamic behaviour, but also on the visual configuration with which the dynamics is associated.

Separate motor memories are formed when controlling different implicitly specified locations on a tool

Skillful manipulation requires forming and recalling memories of the dynamics of objects linking applied force to motion. It has been assumed that such memories are associated with entire objects. However, we often control different locations on an object, and these locations may be associated with different dynamics. We have previously demonstrated that multiple memories can be formed when participants are explicitly instructed to control different visual points marked on an object. A key question is whether this novel finding generalizes to more natural situations in which control points are implicitly defined by the task. To answer this question, we used objects with no explicit control points and tasks designed to encourage the use of distinct implicit control points. Participants moved a handle, attached to a robotic interface, to control the position of a rectangular object ("eraser") in the horizontal plane. Participants were required to move the eraser straight ahead to wipe away a column of dots ("dust"), located to either the left or right. We found that participants adapted to opposing dynamics when linked to the left and right dust locations, even though the movements required for these two contexts were the same. Control conditions showed this learning could not be accounted for by contextual cues or the fact that the task goal required moving in a straight line. These results suggest that people naturally control different locations on manipulated objects depending on the task context and that doing so affords the formation of separate motor memories. NEW & NOTEWORTHY Skilled manipulation requires forming motor memories of object dynamics, which have been assumed to be associated with entire objects. However, we recently demonstrated that people can form multiple memories when explicitly instructed to control different visual points on an object. In this article we show that this novel finding generalizes to more natural situations in which control points are implicitly defined by the task.

The effect of consistent and varied follow-through practice schedules on learning a table tennis backhand

In table tennis the follow-through action after a shot is an important part of skill execution. In this experiment, we aimed to extend literature around the contextual interference effect by investigating whether the way the follow-through is organised in practice affects learning of the backhand shot in table tennis. Thirty unskilled participants were allocated to blocked-variable practice, random-variable practice or a control-constant group and aimed backhand shots towards a target following ball projection from a machine. Each group completed these shots in a pre-test, a training phase with follow-through manipulations, a post-test, and a retention test. The random-variable group improved their shot accuracy from pre-test to post-test and from pre-test to retention test (both P < 0.01, d = 1.03), whereas neither the blocked-variable nor the control-constant group displayed any change in shot accuracy. Practising the follow-through in a random-variable fashion enhanced learning of the preceding shot compared with blocked-variable practice or no follow-through instructions. The benefits of learning motor skills under conditions of high contextual interference also apply to how follow-through actions are organised. The findings are valuable to coaches and suggest that instructions related to the follow-through action should be considered as well as the primary skill itself.

A Dynamical Systems Perspective on Flexible Motor Timing

A hallmark of higher brain function is the ability to rapidly and flexibly adjust behavioral responses based on internal and external cues. Here, we examine the computational principles that allow decisions and actions to unfold flexibly in time. We adopt a dynamical systems perspective and outline how temporal flexibility in such a system can be achieved through manipulations of inputs and initial conditions. We then review evidence from experiments in nonhuman primates that support this interpretation. Finally, we explore the broader utility and limitations of the dynamical systems perspective as a general framework for addressing open questions related to the temporal control of movements, as well as in the domains of learning and sequence generation.

Imagery of movements immediately following performance allows learning of motor skills that interfere

Motor imagery, that is the mental rehearsal of a motor skill, can lead to improvements when performing the same skill. Here we show a powerful and complementary role, in which motor imagery of different movements after actually performing a skill allows learning that is not possible without imagery. We leverage a well-studied motor learning task in which subjects reach in the presence of a dynamic (force-field) perturbation. When two opposing perturbations are presented alternately for the same physical movement, there is substantial interference, preventing any learning. However, when the same physical movement is associated with follow-through movements that differ for each perturbation, both skills can be learned. Here we show that when subjects perform the skill and only imagine the follow-through, substantial learning occurs. In contrast, without such motor imagery there was no learning. Therefore, motor imagery can have a profound effect on skill acquisition even when the imagery is not of the skill itself. Our results suggest that motor imagery may evoke different neural states for the same physical state, thereby enhancing learning.

Context-dependent concurrent adaptation to static and moving targets

Is the neural control of movements towards moving targets independent to that of static targets? In the following experiments, we used a visuomotor rotation adaptation paradigm to examine the extent to which adapting arm movements to static targets generalize to that of moving targets (i.e. pursuit or tracking). In the first and second experiments, we showed that adaptation to perturbed tracking movements generalizes to reaching movements; reach aftereffects following perturbed tracking were about half the size (≈9°) of those produced following reach training (≈ 19°). Given these findings, in the final experiment we associated opposing perturbations (-30° and +30°) with either reaching or tracking movements and presented them within the same experimental block to determine whether these contexts allow for dual adaptation. We found that the group that experienced opposing perturbations was able to reduce both reaching and tracking errors, as well as produce reach aftereffects following dual training of ≈7°, which were substantially smaller than those produced when reach training was not concurrent with tracking training. This reduction in reach aftereffects is consistent with the extent of the interference from tracking training as measured by the reach aftereffects produced when only that condition was performed. These results suggest partial, but not complete, overlap in the learning processes involved in the acquisition of tracking and reaching movements.

An error-tuned model for sensorimotor learning

Current models of sensorimotor control posit that motor commands are generated by combining multiple modules which may consist of internal models, motor primitives or motor synergies. The mechanisms which select modules based on task requirements and modify their output during learning are therefore critical to our understanding of sensorimotor control. Here we develop a novel modular architecture for multi-dimensional tasks in which a set of fixed primitives are each able to compensate for errors in a single direction in the task space. The contribution of the primitives to the motor output is determined by both top-down contextual information and bottom-up error information. We implement this model for a task in which subjects learn to manipulate a dynamic object whose orientation can vary. In the model, visual information regarding the context (the orientation of the object) allows the appropriate primitives to be engaged. This top-down module selection is implemented by a Gaussian function tuned for the visual orientation of the object. Second, each module's contribution adapts across trials in proportion to its ability to decrease the current kinematic error. Specifically, adaptation is implemented by cosine tuning of primitives to the current direction of the error, which we show to be theoretically optimal for reducing error. This error-tuned model makes two novel predictions. First, interference should occur between alternating dynamics only when the kinematic errors associated with each oppose one another. In contrast, dynamics which lead to orthogonal errors should not interfere. Second, kinematic errors alone should be sufficient to engage the appropriate modules, even in the absence of contextual information normally provided by vision. We confirm both these predictions experimentally and show that the model can also account for data from previous experiments. Our results suggest that two interacting processes account for module selection during sensorimotor control and learning.

Research in motor learning has focused on how we acquire new motor memories for novel situations. However, in many real world motor tasks, the challenge is to select appropriate memories for a given context. In such tasks, we are guided by two key types of information. First, contextual information from vision (for example) is available before we perform the task. Second, movement errors are available as we begin to perform the task. Here we present a model that provides a mechanism by which these two processes operate in parallel to enable us to tune and adapt our motor commands. We show that a model consisting of multiple simple modules, each of which can correct errors in a single direction only, can account for learning in multidimensional tasks. The model makes predictions about which tasks should interfere and how experience of errors alone without any contextual information can drive learning. We confirm these predictions in a series of experiments. The model provides a new framework for understanding the interaction between task context and error feedback during sensorimotor control and learning.

The Importance of Planning in Motor Learning

The addition of differentiating follow-through motions can facilitate simultaneous learning of multiple motor skills that would otherwise interfere with each other. In this issue of Neuron, Sheahan and colleagues (2016) demonstrate that it is the preparation, not execution, of different follow-through movements that separates motor memories and reduces interference.

Active lead-in variability affects motor memory formation and slows motor learning

Rapid learning can be critical to ensure elite performance in a changing world or to recover basic movement after neural injuries. Recently it was shown that the variability of follow-through movements affects the rate of motor memory formation. Here we investigate if lead-in movement has a similar effect on learning rate. We hypothesized that both modality and variability of lead-in movement would play critical roles, with simulations suggesting that only changes in active lead-in variability would exhibit slower learning. We tested this experimentally using a two-movement paradigm, with either visual or active initial lead-in movements preceeding a second movement performed in a force field. As predicted, increasing active lead-in variability reduced the rate of motor adaptation, whereas changes in visual lead-in variability had little effect. This demonstrates that distinct neural tuning activity is induced by different lead-in modalities, subsequently influencing the access to, and switching between, distinct motor memories.

Memory Reactivation Enables Long-Term Prevention of Interference

The ability of the human brain to successively learn or perform two competing tasks constitutes a major challenge in daily function. Indeed, exposing the brain to two different competing memories within a short temporal offset can induce interference, resulting in deteriorated performance in at least one of the learned memories [1-4]. Although previous studies have investigated online interference and its effects on performance [5-13], whether the human brain can enable long-term prevention of future interference is unknown. To address this question, we utilized the memory reactivation-reconsolidation framework [2, 12] stemming from studies at the synaptic level [14-17], according to which reactivation of a memory enables its update. In a set of experiments, using the motor sequence learning task [18] we report that a unique pairing of reactivating the original memory (right hand) in synchrony with novel memory trials (left hand) prevented future interference between the two memories. Strikingly, these effects were long-term and observed a month following reactivation. Further experiments showed that preventing future interference was not due to practice per se, but rather specifically depended on a limited time window induced by reactivation of the original memory. These results suggest a mechanism according to which memory reactivation enables long-term prevention of interference, possibly by creating an updated memory trace integrating original and novel memories during the reconsolidation time window. The opportunity to induce a long-term preventive effect on memories may enable the utilization of strategies optimizing normal human learning, as well as recovery following neurological insults.

Motor Planning, Not Execution, Separates Motor Memories

Recent theories of limb control emphasize motor cortex as a dynamical system, with planning setting the initial neural state, and execution arising from the self-limiting evolution of the intrinsic neural dynamics. Therefore, movements that share an initial trajectory but then diverge might have different neural states during the execution of the identical initial trajectories. We hypothesized that motor adaptation maps neural states to changes in motor command. This predicts that two opposing perturbations, which interfere when experienced over the same movement, could be learned if each is associated with a different plan even if not executed. We show that planning, but not executing, different follow-through movements allow opposing perturbations to be learned simultaneously over the same movement. However, no learning occurs if different follow throughs are executed, but not planned prior to movement initiation. Our results suggest neural, rather than physical states, are the critical factor associated with motor adaptation.

Tagging motor memories with transcranial direct current stimulation allows later artificially-controlled retrieval

We demonstrate that human motor memories can be artificially tagged and later retrieved by noninvasive transcranial direct current stimulation (tDCS). Participants learned to adapt reaching movements to two conflicting dynamical environments that were each associated with a different tDCS polarity (anodal or cathodal tDCS) on the sensorimotor cortex. That is, we sought to determine whether divergent background activity levels within the sensorimotor cortex (anodal: higher activity; cathodal: lower activity) give rise to distinct motor memories. After a training session, application of each tDCS polarity automatically resulted in the retrieval of the motor memory corresponding to that polarity. These results reveal that artificial modulation of neural activity in the sensorimotor cortex through tDCS can act as a context for the formation and recollection of motor memories.

DOI:http://dx.doi.org/10.7554/eLife.15378.001

Memory is strongly affected by the context in which a particular memory is formed and remembered. For example, visiting a familiar place can often trigger memories associated or “tagged” with that place. Such tagging also exists for memories related to movement: for instance, distinct motor memories for a limb movement are formed depending on whether the other limb is stationary or moving. However, little is known about how the tagging of such motor memories takes place.

Nozaki et al. have now used a technique known as transcranial direct current stimulation to generate artificial “tags” for motor memories. In the experiments, volunteers tried to move a robotic arm towards a goal while the robot pushed their hand off-course. Sometimes the robot pushed the participant’s hand to the left, and sometimes to the right. This makes the task difficult to learn, even when the cue for the direction is provided, as the motor memories that are made to counteract each push overwrite each other.

Nozaki et al. used transcranial stimulation to alter the background electrical activity in the sensorimotor regions of the participants’ brains as they performed the robotic arm task. Artificially generating a different pattern of background brain electrical activity for each push direction caused the motor memories associated with leftward and rightward pushes to be tagged differently. Once this association had been learnt, applying the artificial brain stimulation pattern associated with one of the pushes resulted in the participants unconsciously compensating for a push in that direction, even when it was not there.

Overall, the results presented by Nozaki et al. suggest that the background electrical activity seen in the brain can influence how a motor memory is created and later recalled. A future challenge is to investigate whether this technique could be used to help athletes improve their performance or to treat people with movement disorders. Further experiments are also needed to test whether the same approach can influence the formation and recollection of other kinds of memories, such as those related to fear.

DOI:http://dx.doi.org/10.7554/eLife.15378.002

Improving a Bimanual Motor Skill Through Unimanual Training

When we learn a bimanual motor skill (e.g., rowing a boat), we often break it down into unimanual practices (e.g., a rowing drill with the left or right arm). Such unimanual practice is thought to be useful for learning bimanual motor skills efficiently because the learner can concentrate on learning to perform a simpler component. However, it is not so straightforward to assume that unimanual training (UT) improves bimanual performance. We have previously demonstrated that motor memories for reaching movements consist of three different parts: unimanual-specific, bimanual-specific, and overlapping parts. According to this scheme, UT appears to be less effective, as its training effect is only partially transferred to the same limb for bimanual movement. In the present study, counter-intuitively, we demonstrate that, even after the bimanual skill is almost fully learned by means of bimanual training (BT), additional UT could further improve bimanual skill. We hypothesized that this effect occurs because UT increases the memory content in the overlapping part, which might contribute to an increase in the memory for bimanual movement. To test this hypothesis, we examined whether the UT performed after sufficient BT could improve the bimanual performance. Participants practiced performing bimanual reaching movements (BM) in the presence of a novel force-field imposed only on their left arm. As an index for the motor performance, we used the error-clamp method (i.e., after-effect of the left arm) to evaluate the force output to compensate for the force-field during the reaching movement. After sufficient BT, the training effect reached a plateau. However, UT performed subsequently improved the bimanual performance significantly. In contrast, when the same amount of BT was continued, the bimanual performance remained unchanged, highlighting the beneficial effect of UT on bimanual performance. Considering memory structure, we also expected that BT could improve unimanual performance, which was confirmed by another experiment. These results provide a new interpretation of why UT was useful for improving a bimanual skill, and propose a practical strategy for enhancing performance by performing training in various contexts.

Adaptive tuning functions arise from visual observation of past movement

Visual observation of movement plays a key role in action. For example, tennis players have little time to react to the ball, but still need to prepare the appropriate stroke. Therefore, it might be useful to use visual information about the ball trajectory to recall a specific motor memory. Past visual observation of movement (as well as passive and active arm movement) affects the learning and recall of motor memories. Moreover, when passive or active, these past contextual movements exhibit generalization (or tuning) across movement directions. Here we extend this work, examining whether visual motion also exhibits similar generalization across movement directions and whether such generalization functions can explain patterns of interference. Both the adaptation movement and contextual movement exhibited generalization beyond the training direction, with the visual contextual motion exhibiting much broader tuning. A second experiment demonstrated that this pattern was consistent with the results of an interference experiment where opposing force fields were associated with two separate visual movements. Overall, our study shows that visual contextual motion exhibits much broader (and shallower) tuning functions than previously seen for either passive or active movements, demonstrating that the tuning characteristics of past motion are highly dependent on their sensory modality.

Computations underlying sensorimotor learning

The study of sensorimotor learning has a long history. With the advent of innovative techniques for studying learning at the behavioral and computational levels new insights have been gained in recent years into how the sensorimotor system acquires, retains, represents, retrieves and forgets sensorimotor tasks. In this review we highlight recent advances in the field of sensorimotor learning from a computational perspective. We focus on studies in which computational models are used to elucidate basic mechanisms underlying adaptation and skill acquisition in human behavior.

Neural Tuning Functions Underlie Both Generalization and Interference

In sports, the role of backswing is considered critical for generating a good shot, even though it plays no direct role in hitting the ball. We recently demonstrated the scientific basis of this phenomenon by showing that immediate past movement affects the learning and recall of motor memories. This effect occurred regardless of whether the past contextual movement was performed actively, passively, or shown visually. In force field studies, it has been shown that motor memories generalize locally and that the level of compensation decays as a function of movement angle away from the trained movement. Here we examine if the contextual effect of past movement exhibits similar patterns of generalization and whether it can explain behavior seen in interference studies. Using a single force-field learning task, the directional tuning curves of both the prior contextual movement and the subsequent force field adaptive movements were measured. The adaptation movement direction showed strong directional tuning, decaying to zero by 90° relative to the training direction. The contextual movement direction exhibited a similar directional tuning, although the effect was always above 60%. We then investigated the directional tuning of the passive contextual movement using interference tasks, where the contextual movements that uniquely specified the force field direction were separated by ±15° or ±45°. Both groups showed a pronounced tuning effect, which could be well explained by the directional tuning functions for single force fields. Our results show that contextual effect of past movement influences predictive force compensation, even when adaptation does not require contextual information. However, when such past movement contextual information is crucial to the task, such as in an interference study, it plays a strong role in motor memory learning and recall. This work demonstrates that similar tuning responses underlie both generalization of movement direction during dynamic learning and contextual movements in both single force field and interference tasks.

Computations in Sensorimotor Learning

Our cognitive abilities can only be expressed on the world through our actions. Here we review the computations underlying the way that the sensorimotor system converts both low-level sensory signals and high-level decisions into action, focusing on the behavioral evidence for the theoretical frameworks. We review recent work that determines how motor memories underlying sensorimotor learning are activated and protected from interference, the role of Bayesian decision theory in sensorimotor control including sources of suboptimality, the role of risk sensitivity in guiding action, and how rapid motor responses may underlie the robustness of the motor system to the vagaries of the world.

Motor neuroscience: changing the future and remembering the past

A new study shows that two skills that would otherwise interfere can be learned if each has a unique following action, and that a single skill is learned more quickly if the goal of the subsequent action is consistent across trials.