Reduction in learning rates associated with anterograde interference results from interactions between different timescales in motor adaptation

Sleep Consolidation Potentiates Sensorimotor Adaptation

Contrary to its well-established role in declarative learning, the impact of sleep on motor memory consolidation remains a subject of debate. Current literature suggests that while motor skill learning benefits from sleep, consolidation of sensorimotor adaptation (SMA) depends solely on the passage of time. This has led to the proposal that SMA may be an exception to other types of memories. Here, we addressed this ongoing controversy in humans through three comprehensive experiments using the visuomotor adaptation paradigm (N = 290, 150 females). In Experiment 1, we investigated the impact of sleep on memory retention when the temporal gap between training and sleep was not controlled. In line with the previous literature, we found that memory consolidates with the passage of time. In Experiment 2, we used an anterograde interference protocol to determine the time window during which SMA memory is most fragile and, thus, potentially most sensitive to sleep intervention. Our results show that memory is most vulnerable during the initial hour post-training. Building on this insight, in Experiment 3, we investigated the impact of sleep when it coincided with the critical first hour of memory consolidation. This manipulation unveiled a benefit of sleep (30% memory enhancement) alongside an increase in spindle density and spindle-SO coupling during NREM sleep, two well-established neural markers of sleep consolidation. Our findings reconcile seemingly conflicting perspectives on the active role of sleep in motor learning and point to common mechanisms at the basis of memory formation.

Interference underlies attenuation upon relearning in sensorimotor adaptation

Savings refers to the gain in performance upon relearning a task. In sensorimotor adaptation, savings is tested by having participants adapt to perturbed feedback and, following a washout block during which the system resets to baseline, presenting the same perturbation again. While savings has been observed with these tasks, we have shown that the contribution from implicit sensorimotor adaptation, a process that uses sensory prediction errors to recalibrate the sensorimotor map, is actually attenuated upon relearning (Avraham et al., 2021). In the present study, we test the hypothesis that this attenuation is due to interference arising from the washout block, and more generally, from experience with a different relationship between the movement and the feedback. In standard adaptation studies, removing the perturbation at the start of the washout block results in a salient error signal in the opposite direction to that observed during learning. As a starting point, we replicated the finding that implicit adaptation is attenuated following a washout period in which the feedback now signals a salient opposite error. When we eliminated visual feedback during washout, implicit adaptation was no longer attenuated upon relearning, consistent with the interference hypothesis. Next, we eliminated the salient error during washout by gradually decreasing the perturbation, creating a scenario in which the perceived errors fell within the range associated with motor noise. Nonetheless, attenuation was still prominent. Inspired by this observation, we tested participants with an extended experience with veridical feedback during an initial baseline phase and found that this was sufficient to cause robust attenuation of implicit adaptation during the first exposure to the perturbation. This effect was context-specific: It did not generalize to movements that were not associated with the interfering feedback. Taken together, these results show that the implicit sensorimotor adaptation system is highly sensitive to memory interference from a recent experience with a discrepant action-outcome contingency.

Repeated context-specific actions disrupt feedforward adjustments in motor commands in younger and older adults

The flexibility of the motor system to adjust a planned action before or during the execution of the movement in response to sensory information is critical for preventing errors in motor control. As individuals age, this function declines, leading to an increased incidence of motor errors. Although sensory processing and cognitive decline are known contributors to this impairment, here, we test the hypothesis that repetition of context-specific planned actions interferes with the adjustment of feedforward motor commands. Younger and older participants were instructed to grasp and lift a T-shaped object with a concealed, off-sided center of mass and minimize its roll through anticipatory force control, relying predominantly on predictive model-driven planning (i.e., sensorimotor memories) developed through repeated lifts. We selectively manipulate the number of trial repeats with the center of mass on one side before switching it to the other side of the T-shaped object. The results showed that increasing the number of repetitions improved performance in manipulating an object with a given center of mass but led to increased errors when the object's center of mass was switched. This deleterious effect of repetition on feedforward motor adjustment was observed in younger and older adults. Critically, we show these effects on an internal model-driven motor planning task that relies predominantly on sensorimotor memory, with no differences in sensory inputs from the repetition manipulation. The findings indicate that feedforward motor adjustments are hampered by repetitive stereotyped planning and execution of motor behavior.NEW & NOTEWORTHY Adjusting planned actions in response to sensory stimuli degrades with age contributing to increased incidence of errors ranging from clumsy spills to catastrophic falls. Multiple factors likely contribute to age-related motor inflexibility, including sensory- and cognition-supporting system declines. Here, we present compelling evidence for repetition to disrupt feedforward adjusting of motor commands in younger and older adults, which suggests increases in stereotypy as a deleterious potentiator of motor control errors.

A cerebellar population coding model for sensorimotor learning

The cerebellum is crucial for sensorimotor adaptation, using error information to keep the sensorimotor system well-calibrated. Here we introduce a population-coding model to explain how cerebellar-dependent learning is modulated by contextual variation. The model consists of a two-layer network, designed to capture activity in both the cerebellar cortex and deep cerebellar nuclei. A core feature of the model is that within each layer, the processing units are tuned to both movement direction and the direction of movement error. The model captures a large range of contextual effects including interference from prior learning and the influence of error uncertainty and volatility. While these effects have traditionally been taken to indicate meta learning or context-dependent memory within the adaptation system, our results show that they are emergent properties that arise from the population dynamics within the cerebellum. Our results provide a novel framework to understand how the nervous system responds to variable environments.

A software tool for at-home measurement of sensorimotor adaptation

Sensorimotor adaptation is traditionally studied in well-controlled laboratory settings with specialized equipment. However, recent public health concerns such as the COVID-19 pandemic, as well as a desire to recruit a more diverse study population, have led the motor control community to consider at-home study designs. At-home motor control experiments are still rare because of the requirement to write software that can be easily used by anyone on any platform. To this end, we developed software that runs locally on a personal computer. The software provides audiovisual instructions and measures the ability of the subject to control the cursor in the context of visuomotor perturbations. We tested the software on a group of at-home participants and asked whether the adaptation principles inferred from in-lab measurements were reproducible in the at-home setting. For example, we manipulated the perturbations to test whether there were changes in adaptation rates (savings and interference), whether adaptation was associated with multiple timescales of memory (spontaneous recovery), and whether we could selectively suppress subconscious learning (delayed feedback, perturbation variability) or explicit strategies (limited reaction time). We found remarkable similarity between in-lab and at-home behaviors across these experimental conditions. Thus, we developed a software tool that can be used by research teams with little or no programming experience to study mechanisms of adaptation in an at-home setting.

The influence of learning history on anterograde interference

Classically interpreted as a competition between opposite memories (A vs B), anterograde interference (AI) also emerges in the absence of competing memories (A vs A), suggesting that mechanisms other than those involved in memory competition contribute to AI. To investigate this, we tested the hypothesis that extending motor practice would enhance a first memory, but come at the cost of reduced learning capabilities when subsequently exposed to a second learning session of the same task. Based on converging biological evidence, AI was expected to depend upon the degree of extended practice of the initial exposure. During a first Session, four conditions were carried out where participants (n = 24) adapted to a gradually introduced -20° visual deviation while the extent of the initial exposure was manipulated by varying the duration or type of the performance asymptote. Specifically, the performance asymptote at -20° was either Short (40 trials), Moderate (160 trials), Long (320 trials), or absent due to continuously changing perturbations around the mean of -20° (Jagged; 160 trials). After a 2-min interval, participants re-adapted to the same (-20°) visual deviation, which was meant to probe the effect of extended practice in the first Session on the learning capabilities of a second identical memory (A vs A). The results first confirmed that the duration of exposure in the first Session enhanced immediate aftereffects in the Moderate, Long, and Jagged conditions as compared to the Short condition, suggesting that extended practice enhanced retention of the first memory. When comparing the second Session to the first one, results revealed a different pattern of re-adaptation depending on the duration of initial exposure: in the Short condition, there was evidence for facilitated re-adaptation and similar aftereffects. However, in the Moderate, Long and Jagged conditions, re-adaptation was similar and aftereffects were impaired, suggestive of AI. This suggests that extended practice initially enhances memory formation, but comes at the cost of reduced subsequent learning capabilities. One possibility is that AI occurs because extended practice induces the emergence of network-specific homeostatic constraints, which limit subsequent neuroplastic and learning capabilities in the same neural network.

Paving the Way for Memory Enhancement: Development and Examination of a Neurofeedback System Targeting the Medial Temporal Lobe

Neurofeedback (NF) shows promise in enhancing memory, but its application to the medial temporal lobe (MTL) still needs to be studied. Therefore, we aimed to develop an NF system for the memory function of the MTL and examine neural activity changes and memory task score changes through NF training. We created a memory NF system using intracranial electrodes to acquire and visualise the neural activity of the MTL during memory encoding. Twenty trials of a tug-of-war game per session were employed for NF and designed to control neural activity bidirectionally (Up/Down condition). NF training was conducted with three patients with drug-resistant epilepsy, and we observed an increasing difference in NF signal between conditions (Up-Down) as NF training progressed. Similarities and negative correlation tendencies between the transition of neural activity and the transition of memory function were also observed. Our findings demonstrate NF's potential to modulate MTL activity and memory encoding. Future research needs further improvements to the NF system to validate its effects on memory functions. Nonetheless, this study represents a crucial step in understanding NF's application to memory and provides valuable insights into developing more efficient memory enhancement strategies.

Evidence that anterograde learning interference depends on the stage of learning of the interferer: blocked versus interleaved training

Training on one task (task A) can disrupt learning on a subsequently trained task (task B), illustrating anterograde learning interference. We asked whether the induction of anterograde learning interference depends on the learning stage that task A has reached when the training on task B begins. To do so, we drew on previous observations in perceptual learning in which completing all training on one task before beginning training on another task (blocked training) yielded markedly different learning outcomes than alternating training between the same two tasks for the same total number of trials (interleaved training). Those blocked versus interleaved contrasts suggest that there is a transition between two differentially vulnerable learning stages that is related to the number of consecutive training trials on each task, with interleaved training presumably tapping acquisition, and blocked training tapping consolidation. Here, we used the blocked versus interleaved paradigm in auditory perceptual learning in a case in which blocked training generated anterograde-but not its converse, retrograde-learning interference (A→B, not B←A). We report that anterograde learning interference of training on task A (interaural time difference discrimination) on learning on task B (interaural level difference discrimination) occurred with blocked training and diminished with interleaved training, with faster rates of interleaving leading to less interference. This pattern held for across-day, within-session, and offline learning. Thus, anterograde learning interference only occurred when the number of consecutive training trials on task A surpassed some critical value, consistent with other recent evidence that anterograde learning interference only arises when learning on task A has entered the consolidation stage.

Distinct adaptation processes underlie multidigit force coordination for dexterous manipulation

The human sensorimotor system can adapt to various changes in the environmental dynamics by updating motor commands to improve performance after repeated exposure to the same task. However, the characteristics and mechanisms of the adaptation process remain unknown for dexterous manipulation, a unique motor task in which the body physically interacts with the environment with multiple effectors, i.e., digits, in parallel. We addressed this gap by using robotic manipulanda to investigate the changes in the digit force coordination following mechanical perturbation of an object held by tripod grasps. As the participants gradually adapted to lifting the object under perturbations, we quantified two components of digit force coordination. One is the direction-specific manipulation moment that directly counteracts the perturbation, whereas the other one is the direction-independent internal moment that supports the stability and stiffness of the grasp. We found that trial-to-trial improvement of task performance was associated with increased manipulation moment and a gradual decrease of the internal moment. These two moments were characterized by different rates of adaptation. We also examined how these two force coordination components respond to changes in perturbation directions. Importantly, we found that the manipulation moment was sensitive to the extent of repetitive exposure to the previous context that has an opposite perturbation direction, whereas the internal moment did not. However, the internal moment was sensitive to whether the postchange perturbation direction was previously experienced. Our results reveal, for the first time, that two distinct processes underlie the adaptation of multidigit force coordination for dexterous manipulation.NEW & NOTEWORTHY Changes in digit force coordination in multidigit object manipulation were quantified with a novel experimental design in which human participants adapted to mechanical perturbations applied to the object. Our results show that the adaptation of digit force coordination can be characterized by two distinct components that operate at different timescales. We further show that these two components respond to changes in perturbation direction differently.

Contextual inference in learning and memory

Context is widely regarded as a major determinant of learning and memory across numerous domains, including classical and instrumental conditioning, episodic memory, economic decision-making, and motor learning. However, studies across these domains remain disconnected due to the lack of a unifying framework formalizing the concept of context and its role in learning. Here, we develop a unified vernacular allowing direct comparisons between different domains of contextual learning. This leads to a Bayesian model positing that context is unobserved and needs to be inferred. Contextual inference then controls the creation, expression, and updating of memories. This theoretical approach reveals two distinct components that underlie adaptation, proper and apparent learning, respectively referring to the creation and updating of memories versus time-varying adjustments in their expression. We review a number of extensions of the basic Bayesian model that allow it to account for increasingly complex forms of contextual learning.

Selective modulation of cortical population dynamics during neuroprosthetic skill learning

Brain-machine interfaces (BMIs) provide a framework for studying how cortical population dynamics evolve over learning in a task in which the mapping between neural activity and behavior is precisely defined. Learning to control a BMI is associated with the emergence of coordinated neural dynamics in populations of neurons whose activity serves as direct input to the BMI decoder (direct subpopulation). While previous work shows differential modification of firing rate modulation in this population relative to a population whose activity was not directly input to the BMI decoder (indirect subpopulation), little is known about how learning-related changes in cortical population dynamics within these groups compare.To investigate this, we monitored both direct and indirect subpopulations as two macaque monkeys learned to control a BMI. We found that while the combined population increased coordinated neural dynamics, this increase in coordination was primarily driven by changes in the direct subpopulation. These findings suggest that motor cortex refines cortical dynamics by increasing neural variance throughout the entire population during learning, with a more pronounced coordination of firing activity in subpopulations that are causally linked to behavior.

Statistical determinants of visuomotor adaptation along different dimensions during naturalistic 3D reaches

Neurorehabilitation in patients suffering from motor deficits relies on relearning or re-adapting motor skills. Yet our understanding of motor learning is based mostly on results from one or two-dimensional experimental paradigms with highly confined movements. Since everyday movements are conducted in three-dimensional space, it is important to further our understanding about the effect that gravitational forces or perceptual anisotropy might or might not have on motor learning along all different dimensions relative to the body. Here we test how well existing concepts of motor learning generalize to movements in 3D. We ask how a subject’s variability in movement planning and sensory perception influences motor adaptation along three different body axes. To extract variability and relate it to adaptation rate, we employed a novel hierarchical two-state space model using Bayesian modeling via Hamiltonian Monte Carlo procedures. Our results show that differences in adaptation rate occur between the coronal, sagittal and horizontal planes and can be explained by the Kalman gain, i.e., a statistically optimal solution integrating planning and sensory information weighted by the inverse of their variability. This indicates that optimal integration theory for error correction holds for 3D movements and explains adaptation rate variation between movements in different planes.

Competition between parallel sensorimotor learning systems

Sensorimotor learning is supported by at least two parallel systems: a strategic process that benefits from explicit knowledge and an implicit process that adapts subconsciously. How do these systems interact? Does one system's contributions suppress the other, or do they operate independently? Here, we illustrate that during reaching, implicit and explicit systems both learn from visual target errors. This shared error leads to competition such that an increase in the explicit system's response siphons away resources that are needed for implicit adaptation, thus reducing its learning. As a result, steady-state implicit learning can vary across experimental conditions, due to changes in strategy. Furthermore, strategies can mask changes in implicit learning properties, such as its error sensitivity. These ideas, however, become more complex in conditions where subjects adapt using multiple visual landmarks, a situation which introduces learning from sensory prediction errors in addition to target errors. These two types of implicit errors can oppose each other, leading to another type of competition. Thus, during sensorimotor adaptation, implicit and explicit learning systems compete for a common resource: error.

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.

Contextual inference underlies the learning of sensorimotor repertoires

ASBTRACT

Humans spend a lifetime learning, storing and refining a repertoire of motor memories. For example, through experience, we become proficient at manipulating a large range of objects with distinct dynamical properties. However, it is unknown what principle underlies how our continuous stream of sensorimotor experience is segmented into separate memories and how we adapt and use this growing repertoire. Here we develop a theory of motor learning based on the key principle that memory creation, updating and expression are all controlled by a single computation-contextual inference. Our theory reveals that adaptation can arise both by creating and updating memories (proper learning) and by changing how existing memories are differentially expressed (apparent learning). This insight enables us to account for key features of motor learning that had no unified explanation: spontaneous recovery¹, savings², anterograde interference³, how environmental consistency affects learning rate^4,5 and the distinction between explicit and implicit learning⁶. Critically, our theory also predicts new phenomena-evoked recovery and context-dependent single-trial learning-which we confirm experimentally. These results suggest that contextual inference, rather than classical single-context mechanisms^1,4,7-9, is the key principle underlying how a diverse set of experiences is reflected in our motor behaviour.

Direction-Specific Iterative Tuning of Motor Commands With Local Generalization During Randomized Reaching Practice Across Movement Directions

During motor learning, people often practice reaching in variety of movement directions in a randomized sequence. Such training has been shown to enhance retention and transfer capability of the acquired skill compared to the blocked repetition of the same movement direction. The learning system must accommodate such randomized order either by having a memory for each movement direction, or by being able to generalize what was learned in one movement direction to the controls of nearby directions. While our preliminary study used a comprehensive dataset from visuomotor learning experiments and evaluated the first-order model candidates that considered the memory of error and generalization across movement directions, here we expanded our list of candidate models that considered the higher-order effects and error-dependent learning rates. We also employed cross-validation to select the leading models. We found that the first-order model with a constant learning rate was the best at predicting learning curves. This model revealed an interaction between the learning and forgetting processes using the direction-specific memory of error. As expected, learning effects were observed at the practiced movement direction on a given trial. Forgetting effects (error increasing) were observed at the unpracticed movement directions with learning effects from generalization from the practiced movement direction. Our study provides insights that guide optimal training using the machine-learning algorithms in areas such as sports coaching, neurorehabilitation, and human-machine interactions.

An implicit memory of errors limits human sensorimotor adaptation

During extended motor adaptation, learning appears to saturate despite persistence of residual errors. This adaptation limit is not fixed but varies with perturbation variance; when variance is high, residual errors become larger. These changes in total adaptation could relate to either implicit or explicit learning systems. Here, we found that when adaptation relied solely on the explicit system, residual errors disappeared and learning was unaltered by perturbation variability. In contrast, when learning depended entirely, or in part, on implicit learning, residual errors reappeared. Total implicit adaptation decreased in the high-variance environment due to changes in error sensitivity, not in forgetting. These observations suggest a model in which the implicit system becomes more sensitive to errors when they occur in a consistent direction. Thus, residual errors in motor adaptation are at least in part caused by an implicit learning system that modulates its error sensitivity in response to the consistency of past errors.

Acoustic stimulation increases implicit adaptation in sensorimotor adaptation

Sensorimotor adaptation is an important part of our ability to perform novel motor tasks (i.e., learning of motor skills). Efforts to improve adaptation in healthy and clinical patients using non-invasive brain stimulation methods have been hindered by inter-individual and intra-individual variability in brain susceptibility to stimulation. Here, we explore unpredictable loud acoustic stimulation as an alternative method of modulating brain excitability to improve sensorimotor adaptation. In two experiments, participants moved a cursor towards targets, and adapted to a 30º rotation of cursor feedback, either with or without unpredictable acoustic stimulation. Acoustic stimulation improved initial adaptation to sensory prediction errors in Study 1, and improved overnight retention of adaptation in Study 2. Unpredictable loud acoustic stimulation might thus be a potent method of modulating sensorimotor adaptation in healthy adults.

Null effects of levodopa on reward- and error-based motor adaptation, savings, and anterograde interference

Dopamine signaling is thought to mediate reward-based learning. We tested for a role of dopamine in motor adaptation by administering the dopamine precursor levodopa to healthy participants in two experiments involving reaching movements. Levodopa has been shown to impair reward-based learning in cognitive tasks. Thus, we hypothesized that levodopa would selectively impair aspects of motor adaptation that depend on the reinforcement of rewarding actions. In the first experiment, participants performed two separate tasks in which adaptation was driven either by visual error-based feedback of the hand position or binary reward feedback. We used EEG to measure event-related potentials evoked by task feedback. We hypothesized that levodopa would specifically diminish adaptation and the neural responses to feedback in the reward learning task. However, levodopa did not affect motor adaptation in either task nor did it diminish event-related potentials elicited by reward outcomes. In the second experiment, participants learned to compensate for mechanical force field perturbations applied to the hand during reaching. Previous exposure to a particular force field can result in savings during subsequent adaptation to the same force field or interference during adaptation to an opposite force field. We hypothesized that levodopa would diminish savings and anterograde interference, as previous work suggests that these phenomena result from a reinforcement learning process. However, we found no reliable effects of levodopa. These results suggest that reward-based motor adaptation, savings, and interference may not depend on the same dopaminergic mechanisms that have been shown to be disrupted by levodopa during various cognitive tasks.NEW & NOTEWORTHY Motor adaptation relies on multiple processes including reinforcement of successful actions. Cognitive reinforcement learning is impaired by levodopa-induced disruption of dopamine function. We administered levodopa to healthy adults who participated in multiple motor adaptation tasks. We found no effects of levodopa on any component of motor adaptation. This suggests that motor adaptation may not depend on the same dopaminergic mechanisms as cognitive forms or reinforcement learning that have been shown to be impaired by levodopa.

Learning the same motor task twice impairs its retention in a time- and dose-dependent manner

Anterograde interference emerges when two differing tasks are learned in close temporal proximity, an effect repeatedly attributed to a competition between differing task memories. However, recent development alternatively suggests that initial learning may trigger a refractory period that occludes neuroplasticity and impairs subsequent learning, consequently mediating interference independently of memory competition. Accordingly, this study tested the hypothesis that interference can emerge when the same motor task is being learned twice, that is when competition between memories is prevented. In a first experiment, the inter-session interval (ISI) between two identical motor learning sessions was manipulated to be 2 min, 1 h or 24 h. Results revealed that retention of the second session was impaired as compared to the first one when the ISI was 2 min but not when it was 1 h or 24 h, indicating a time-dependent process. Results from a second experiment replicated those of the first one and revealed that adding a third motor learning session with a 2 min ISI further impaired retention, indicating a dose-dependent process. Results from a third experiment revealed that the retention impairments did not take place when a learning session was preceded by simple rehearsal of the motor task without concurrent learning, thus ruling out fatigue and confirming that retention is impaired specifically when preceded by a learning session. Altogether, the present results suggest that competing memories is not the sole mechanism mediating anterograde interference and introduce the possibility that a time- and dose-dependent refractory period-independent of fatigue-also contributes to its emergence. One possibility is that learning transiently perturbs the homeostasis of learning-related neuronal substrates. Introducing additional learning when homeostasis is still perturbed may not only impair performance improvements, but also memory formation.

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.

Improving the repeatability of two-rate model parameter estimations by using autoencoder networks

The adaptive changes elicited in visuomotor adaptation experiments are usually well explained at group level by two-rate models (Smith et al., 2006), but parameters fitted to individuals show considerable variance. Data cleaning can mitigate this problem, but the assumption of smoothness can be problematic due to fast adaptive changes with discontinuous derivatives. In this paper, we collected time-series data from an experimental paradigm involving repeated training and investigated the effect of various cleaning methods, including an autoencoder network (AE), on the parameter estimation. We compared changes in the fitted parameters across different methods and across training repetitions. The results suggest that AE performed best overall, without introducing an underestimation bias on b_f like moving average or piecewise polynomials, and that it reduced the within-subject variance overall and especially that of the fast retention rate a_f by >50%.

The Origins of Anterograde Interference in Visuomotor Adaptation

Anterograde interference refers to the negative impact of prior learning on the propensity for future learning. There is currently no consensus on whether this phenomenon is transient or long lasting, with studies pointing to an effect in the time scale of hours to days. These inconsistencies might be caused by the method employed to quantify performance, which often confounds changes in learning rate and retention. Here, we aimed to unveil the time course of anterograde interference by tracking its impact on visuomotor adaptation at different intervals throughout a 24-h period. Our empirical and model-based approaches allowed us to measure the capacity for new learning separately from the influence of a previous memory. In agreement with previous reports, we found that prior learning persistently impaired the initial level of performance upon revisiting the task. However, despite this strong initial bias, learning capacity was impaired only when conflicting information was learned up to 1 h apart, recovering thereafter with passage of time. These findings suggest that when adapting to conflicting perturbations, impairments in performance are driven by two distinct mechanisms: a long-lasting bias that acts as a prior and hinders initial performance and a short-lasting anterograde interference that originates from a reduction in error sensitivity.

Dissociating effects of error size, training duration, and amount of adaptation on the ability to retain motor memories

Extensive computational and neurobiological work has focused on how the training schedule, i.e., the duration and rate at which an environmental disturbance is presented, shapes the formation of motor memories. If long-lasting benefits are to be derived from motor training, however, retention of the performance improvements gained during practice is essential. Thus a better understanding of mechanisms that promote retention could lead to the design of more effective training procedures. The few studies that have investigated how retention depends on the training schedule have suggested that the gradual exposure of a perturbation leads to improved retention of motor memory compared with an abrupt exposure. However, several of these previous studies showed small effects, and although some controlled the training duration and others the level of learning, none have controlled both. In the present study we disambiguated both of these effects from exposure rate by systematically varying the duration of training, type of trained dynamics, and exposure rate for these dynamics in human force-field adaptation. After controlling for both training duration and the amount of learning, we found essentially identical retention when comparing gradual and abrupt training for two different types of force-field dynamics. By contrast, we found that retention was markedly higher for long-duration compared with short-duration training for both types of dynamics. These results demonstrate that the duration of training has a far greater effect on the retention of motor memory than the exposure rate during training. We show that a multirate learning model provides a computational mechanism for these findings.NEW & NOTEWORTHY Previous studies have suggested that a gradual, incremental introduction of a novel environment is helpful for improving retention. However, we used experimental and computational approaches to demonstrate that previously reported improvements in retention associated with gradual introductions fail to persist when other factors, including the duration of training and the degree of initial learning, are accounted for.

Post-training TMS abolishes performance improvement and releases future learning from interference

The period immediately after the offset of visual training is thought to be critical for memory consolidation. Nevertheless, we still lack direct evidence for the causal role of this period to perceptual learning of either previously or subsequently trained material. To address these issues, we had human subjects complete two consecutive trainings with different tasks (detecting different Gabor orientations). We applied continuous theta burst stimulation (cTBS) to either the visual cortex or a control site (vertex) immediately after the offset of the first training. In the vertex cTBS condition, subjects showed improvement on the first task but not on the second task, suggesting the presence of anterograde interference. Critically, cTBS to the visual cortex abolished the performance improvement on the first task and released the second training from the anterograde interference. These results provide causal evidence for a role of the immediate post-training period in the consolidation of perceptual learning.

The 24-h savings of adaptation to novel movement dynamics initially reflects the recall of previous performance

Humans rapidly adapt reaching movements in response to perturbations (e.g., manipulations of movement dynamics or visual feedback). Following a break, when reexposed to the same perturbation, subjects demonstrate savings, a faster learning rate compared with the time course of initial training. Although this has been well studied, there are open questions on the extent early savings reflects the rapid recall of previous performance. To address this question, we examined how the properties of initial training (duration and final adaptive state) influence initial single-trial adaptation to force-field perturbations when training sessions were separated by 24 h. There were two main groups that were distinct based on the presence or absence of a washout period at the end of day 1 (with washout vs. without washout). We also varied the training duration on day 1 (15, 30, 90, or 160 training trials), resulting in 8 subgroups of subjects. We show that single-trial adaptation on day 2 scaled with training duration, even for similar asymptotic levels of learning on day 1 of training. Interestingly, the temporal force profile following the first perturbation on day 2 matched that at the end of day 1 for the longest training duration group that did not complete the washout. This correspondence persisted but was significantly lower for shorter training durations and the washout subject groups. Collectively, the results suggest that the adaptation observed very early in reexposure results from the rapid recall of the previously learned motor recalibration but is highly dependent on the initial training duration and final adaptive state.NEW & NOTEWORTHY The extent initial readaptation reflects the recall of previous motor performance is largely unknown. We examined early single-trial force-field adaptation on the second day of training and distinguished initial retention from recall. We found that the single-trial adaptation following the 24-h break matched that at the end of the first day, but this recall was modified by the training duration and final level of learning on the first day of training.

No effects of cerebellar transcranial direct current stimulation on force field and visuomotor reach adaptation in young and healthy subjects

Previous studies have shown that cerebellar transcranial direct current stimulation (tDCS) leads to faster adaptation of arm reaching movements to visuomotor rotation and force field perturbations in healthy subjects. The first aim of the present study was to confirm a stimulation-dependent effect on motor adaptation. Second, we investigated whether tDCS effects differ depending on onset, that is, before or at the beginning of the adaptation phase. A total of 120 healthy and right-handed subjects (60 women, mean age 23.2 ± SD 2.7 yr, range 18-31 yr) were tested. Subjects moved a cursor with a manipulandum to one of eight targets presented on a vertically orientated screen. Three baseline blocks were followed by one adaptation block and three washout blocks. Sixty subjects did a force field adaptation task (FF), and 60 subjects did a visuomotor adaptation task (VM). Equal numbers of subjects received anodal, cathodal, or sham cerebellar tDCS beginning either in the third baseline block or at the start of the adaptation block. In FF and VM, tDCS and the onset of tDCS did not show a significant effect on motor adaptation (all P values >0.05). We were unable to support previous findings of modulatory cerebellar tDCS effects in reaching adaptation tasks in healthy subjects. Prior to possible application in patients with cerebellar disease, future experiments are needed to determine which tDCS and task parameters lead to robust tDCS effects. NEW & NOTEWORTHY Transcranial direct current stimulation (tDCS) is a promising tool to improve motor learning. We investigated whether cerebellar tDCS improves motor learning in force field and visuomotor tasks in healthy subjects and what influence the onset of stimulation has. We did not find stimulation effects of tDCS or an effect of onset of stimulation. A reevaluation of cerebellar tDCS in healthy subjects and at the end of the clinical potential in cerebellar patients is demanded.

Decreased Temporal Sensorimotor Adaptation Due to Perturbation-Induced Measurement Noise

In daily life, we often need to make accurate and precise movements. However, our movements do not always end up as intended. When we are consistently too late to catch a ball for example, we need to update the predictions of the temporal consequences of our motor commands. These predictions can be improved when the brain evaluates sensory error signals. This is thought to be an optimal process, in which the relative reliabilities of the error signal and the prediction determine how much of an error is updated. Perturbation paradigms are used to identify how the brain learns from errors. Temporal perturbations (delays) between sensory signals impede the multisensory integration of these signals. Adaptation to these perturbations is often incomplete. We propose that the lack of adaptation is caused by an increased measurement noise that accompanies the temporal perturbation. We use a modification of the standard Kalman filter that allows for increases in measurement uncertainty with larger delays, and verify this model with a timing task on a screen. Participants were instructed to press a button when a ball reached a vertical line. Temporal feedback was given visually (unisensory consequence) or visually and auditory (multisensory consequence). The consequence of their button press was delayed incrementally with one ms per trial. Participants learned from their errors and started pressing the button earlier, but did not adapt fully. We found that our model, a Kalman filter with non-stationary measurement variance, could account for this pattern. Measurement variance increased less for the multisensory than the unisensory condition. In addition, we simulated our model's output for other perturbation paradigms and found that it could also account for fast de-adaptation. Our paper highlights the importance of evaluating changes in measurement noise when interpreting the results motor learning tasks that include perturbation paradigms.

Corticospinal correlates of fast and slow adaptive processes in motor learning

Recent computational theories and behavioral observations suggest that motor learning is supported by multiple adaptation processes, operating on different timescales, but direct neural evidence is lacking. We tested this hypothesis by applying transcranial magnetic stimulation over motor cortex in 16 human subjects during a validated reach adaptation task. Motor-evoked potentials (MEPs) and cortical silent periods (CSPs) were recorded from the biceps brachii to assess modulations of corticospinal excitability as indices for corticospinal plasticity. Guided by a two-state adaptation model, we show that the MEP reflects an adaptive process that learns quickly but has poor retention, while the CSP correlates with a process that responds more slowly but retains information well. These results provide a physiological link between models of motor learning and distinct changes in corticospinal excitability. Our findings support the relationship between corticospinal gain modulations and the adaptive processes in motor learning. NEW & NOTEWORTHY Computational theories and behavioral observations suggest that motor learning is supported by multiple adaptation processes, but direct neural evidence is lacking. We tested this hypothesis by applying transcranial magnetic stimulation over human motor cortex during a reach adaptation task. Guided by a two-state adaptation model, we show that the motor-evoked potential reflects a process that adapts and decays quickly, whereas the cortical silent period reflects slow adaptation and decay.

The influence of awareness on explicit and implicit contributions to visuomotor adaptation over time

Explicit (strategic) and implicit (unconscious) processes play a role in visuomotor adaptation (Bond and Taylor, J Neurophysiol 113:3836-3849, https://doi.org/10.1152/jn.00009.2015 , 2015; Werner et al., PLoS ONE 10:1-18, https://doi.org/10.1371/journal.pone.0123321 , 2015). We investigated the contributions of explicit and implicit processes to visuomotor adaptation when awareness was manipulated directly vs. indirectly, and asked how these contributions changed over time. Participants were assigned to a Strategy or No-Strategy group. Those in the Strategy group were made aware of the visuomotor distortion directly. Participants were further subdivided into groups to train with a large (60°), medium (40°) or small (20°) visuomotor distortion, providing the potential for awareness to develop indirectly. Participants reached with their respective distorted cursor, followed by a series of no-cursor reaches to assess the contributions of explicit and implicit processes to visuomotor adaptation after every 30 reach training trials. Within the no-cursor reaching trials, participants reached (1) with any strategies they had gained during training (explicit + implicit processes), and (2) as accurately to the target as possible (implicit processes). Results showed that implicit contributions were greatest in the No-Strategy group, took time to develop, and were transient, as partial decay was seen following a 5-min rest. As well, implicit contributions were similar (i.e., plateaued), regardless of the rotation size participants trained with. In contrast, explicit contributions were greatest in the Strategy group, increased with rotation size, and remained consistent over time. Taken together, results reveal that there are notable differences in the stability of explicit and implicit processes and their potential to contribute to visuomotor adaptation depending on if awareness is provided directly.

Long-term retention of proprioceptive recalibration

Sensorimotor changes are well documented following reaches with altered visual feedback of the hand. Specifically, reaches are adapted and proprioceptive estimates of felt hand position shifted in the direction of the visual feedback experienced. While research has examined one's ability to retain reach adaptation, limited attention has been given to the retention of proprioceptive recalibration. This experiment examined retention of proprioceptive recalibration in the form of recall and savings (i.e., faster proprioceptive recalibration on subsequent testing days) over an extended period of time (i.e., four days). As well, we looked to determine the benefits of additional training on short-term retention (i.e., one day) of proprioceptive recalibration. Twenty-four participants trained to reach to a visual target while seeing a cursor that was rotated 30° clockwise relative to their hand on an initial day of testing. Half of the participants then completed additional reach training trials on 4 subsequent testing days (Training group), whereas the second half of participants did not complete additional training until Day 5 (Non-Training group). Participants provided estimates of their felt hand position on all 5 testing days to establish retention of proprioceptive recalibration. Results revealed that proprioceptive recalibration was recalled 24 h after initial training across all participants. Recall of proprioceptive recalibration was not observed on subsequent testing days for the Non-Training group, while recall of proprioceptive recalibration was retained at a similar level across all subsequent testing days for the Training group. Retention of proprioceptive recalibration in the form of savings was observed on Day 5 in the Non-Training group. These results reveal that short-term recall of proprioceptive recalibration does not benefit from additional training. Moreover, the different time scales (i.e., retention in the form of recall seen only at 24 h after initial training versus savings observed 4 days after initial training in the Non-Training group), suggest that distinct processes may underlie recall and savings of proprioceptive recalibration.

Rapid visuomotor feedback gains are tuned to the task dynamics

Here, we test whether rapid visuomotor feedback responses are selectively tuned to the task dynamics. The responses do not exhibit gain scaling, but they do vary with the level and stability of task dynamics. Moreover, these feedback gains are independently tuned to perturbations to the left and right, depending on these dynamics. Our results demonstrate that the sensorimotor control system regulates the feedback gain as part of the adaptation process, tuning them appropriately to the environment.

Adaptation to novel dynamics requires learning a motor memory, or a new pattern of predictive feedforward motor commands. Recently, we demonstrated the upregulation of rapid visuomotor feedback gains early in curl force field learning, which decrease once a predictive motor memory is learned. However, even after learning is complete, these feedback gains are higher than those observed in the null field trials. Interestingly, these upregulated feedback gains in the curl field were not observed in a constant force field. Therefore, we suggest that adaptation also involves selectively tuning the feedback sensitivity of the sensorimotor control system to the environment. Here, we test this hypothesis by measuring the rapid visuomotor feedback gains after subjects adapt to a variety of novel dynamics generated by a robotic manipulandum in three experiments. To probe the feedback gains, we measured the magnitude of the motor response to rapid shifts in the visual location of the hand during reaching. While the feedback gain magnitude remained similar over a larger than a fourfold increase in constant background load, the feedback gains scaled with increasing lateral resistance and increasing instability. The third experiment demonstrated that the feedback gains could also be independently tuned to perturbations to the left and right, depending on the lateral resistance, demonstrating the fractionation of feedback gains to environmental dynamics. Our results show that the sensorimotor control system regulates the gain of the feedback system as part of the adaptation process to novel dynamics, appropriately tuning them to the environment.

NEW & NOTEWORTHY Here, we test whether rapid visuomotor feedback responses are selectively tuned to the task dynamics. The responses do not exhibit gain scaling, but they do vary with the level and stability of task dynamics. Moreover, these feedback gains are independently tuned to perturbations to the left and right, depending on these dynamics. Our results demonstrate that the sensorimotor control system regulates the feedback gain as part of the adaptation process, tuning them appropriately to the environment.

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.

Consecutive learning of opposing unimanual motor tasks using the right arm followed by the left arm causes intermanual interference

Intermanual transfer (motor memory generalization across arms) and motor memory interference (impairment of retest performance in consecutive motor learning) are well-investigated motor learning phenomena. However, the interplay of these phenomena remains elusive, i.e., whether intermanual interference occurs when two unimanual tasks are consecutively learned using different arms. Here, we examine intermanual interference when subjects consecutively adapt their right and left arm movements to novel dynamics. We considered two force field tasks A and B which were of the same structure but mirrored orientation (B = -A). The first test group (ABA-group) consecutively learned task A using their right arm and task B using their left arm before being retested for task A with their right arm. Another test group (AAA-group) learned only task A in the same right-left-right arm schedule. Control subjects learned task A using their right arm without intermediate left arm learning. All groups were able to adapt their right arm movements to force field A and both test groups showed significant intermanual transfer of this initial learning to the contralateral left arm of 21.9% (ABA-group) and 27.6% (AAA-group). Consecutively, both test groups adapted their left arm movements to force field B (ABA-group) or force field A (AAA-group). For the ABA-group, left arm learning caused significant intermanual interference of the initially learned right arm task (68.3% performance decrease). The performance decrease of the AAA-group (10.2%) did not differ from controls (15.5%). These findings suggest that motor control and learning of right and left arm movements involve partly similar neural networks or underlie a vital interhemispheric connectivity. Moreover, our results suggest a preferred internal task representation in extrinsic Cartesian-based coordinates rather than in intrinsic joint-based coordinates because interference was absent when learning was performed in extrinsically equivalent fashion (AAA-group) but interference occurred when learning was performed in intrinsically equivalent fashion (ABA-group).

Decoded fMRI neurofeedback can induce bidirectional confidence changes within single participants

Neurofeedback studies using real-time functional magnetic resonance imaging (rt-fMRI) have recently incorporated the multi-voxel pattern decoding approach, allowing for fMRI to serve as a tool to manipulate fine-grained neural activity embedded in voxel patterns. Because of its tremendous potential for clinical applications, certain questions regarding decoded neurofeedback (DecNef) must be addressed. Specifically, can the same participants learn to induce neural patterns in opposite directions in different sessions? If so, how does previous learning affect subsequent induction effectiveness? These questions are critical because neurofeedback effects can last for months, but the short- to mid-term dynamics of such effects are unknown. Here we employed a within-subjects design, where participants underwent two DecNef training sessions to induce behavioural changes of opposing directionality (up or down regulation of perceptual confidence in a visual discrimination task), with the order of training counterbalanced across participants. Behavioral results indicated that the manipulation was strongly influenced by the order and the directionality of neurofeedback training. We applied nonlinear mathematical modeling to parametrize four main consequences of DecNef: main effect of change in confidence, strength of down-regulation of confidence relative to up-regulation, maintenance of learning effects, and anterograde learning interference. Modeling results revealed that DecNef successfully induced bidirectional confidence changes in different sessions within single participants. Furthermore, the effect of up- compared to down-regulation was more prominent, and confidence changes (regardless of the direction) were largely preserved even after a week-long interval. Lastly, the effect of the second session was markedly diminished as compared to the effect of the first session, indicating strong anterograde learning interference. These results are interpreted in the framework of reinforcement learning and provide important implications for its application to basic neuroscience, to occupational and sports training, and to therapy.

Savings for visuomotor adaptation require prior history of error, not prior repetition of successful actions

When we move, perturbations to our body or the environment can elicit discrepancies between predicted and actual outcomes. We readily adapt movements to compensate for such discrepancies, and the retention of this learning is evident as savings, or faster readaptation to a previously encountered perturbation. The mechanistic processes contributing to savings, or even the necessary conditions for savings, are not fully understood. One theory suggests that savings requires increased sensitivity to previously experienced errors: when perturbations evoke a sequence of correlated errors, we increase our sensitivity to the errors experienced, which subsequently improves error correction (Herzfeld et al. 2014). An alternative theory suggests that a memory of actions is necessary for savings: when an action becomes associated with successful target acquisition through repetition, that action is more rapidly retrieved at subsequent learning (Huang et al. 2011). In the present study, to better understand the necessary conditions for savings, we tested how savings is affected by prior experience of similar errors and prior repetition of the action required to eliminate errors using a factorial design. Prior experience of errors induced by a visuomotor rotation in the savings block was either prevented at initial learning by gradually removing an oppositely signed perturbation or enforced by abruptly removing the perturbation. Prior repetition of the action required to eliminate errors in the savings block was either deprived or enforced by manipulating target location in preceding trials. The data suggest that prior experience of errors is both necessary and sufficient for savings, whereas prior repetition of a successful action is neither necessary nor sufficient for savings.

Forces That Supplement Visuomotor Learning: A "Sensory Crossover" Experiment

Previous studies on reaching movements have shown that people can adapt to either visuomotor (e.g., prism glasses) or mechanical distortions (e.g., force fields) through repetitive practice. Recent work has shown that adaptation to one type of distortion might have implications on learning the other type, suggesting that neural resources are common to both kinematic and kinetic adaptation. This study investigated whether training with a novel force field might benefit the learning of a visual distortion-specifically, when forces were designed to produce aftereffects that aligned with the ideal trajectory for a visual rotation. Participants training with these forces (Force Group) were tested on a visual rotation. After training with this novel field, we found that participants had surprisingly good performance in the visual rotation condition, comparable to a group that trained on the visual rotation directly. A third group tested the rate of learning with intermittent catch trials, where we zeroed the forces and switched to the visual rotation, and found a significantly faster learning rate than the group that trained directly on the visual rotation. Interestingly, these abilities continued to significantly improve one day later, whereas the direct training showed no such effect. All participants were able to generalize what they learned to unpracticed movement directions. We speculate that when forces are used in training, haptic feedback can have a substantial influence on learning a task that heavily relies on visual feedback. Such methods can impact any situation where one might add robotic forces to the training process.

Flexible Control of Safety Margins for Action Based on Environmental Variability

To reduce the risk of slip, grip force (GF) control includes a safety margin above the force level ordinarily sufficient for the expected load force (LF) dynamics. The current view is that this safety margin is based on the expected LF dynamics, amounting to a static safety factor like that often used in engineering design. More efficient control could be achieved, however, if the motor system reduces the safety margin when LF variability is low and increases it when this variability is high. Here we show that this is indeed the case by demonstrating that the human motor system sizes the GF safety margin in proportion to an internal estimate of LF variability to maintain a fixed statistical confidence against slip. In contrast to current models of GF control that neglect the variability of LF dynamics, we demonstrate that GF is threefold more sensitive to the SD than the expected value of LF dynamics, in line with the maintenance of a 3-sigma confidence level. We then show that a computational model of GF control that includes a variability-driven safety margin predicts highly asymmetric GF adaptation between increases versus decreases in load. We find clear experimental evidence for this asymmetry and show that it explains previously reported differences in how rapidly GFs and manipulatory forces adapt. This model further predicts bizarre nonmonotonic shapes for GF learning curves, which are faithfully borne out in our experimental data. Our findings establish a new role for environmental variability in the control of action.

Learning to expect the unexpected: rapid updating in primate cerebellum during voluntary self-motion

There is considerable evidence that the cerebellum has a vital role in motor learning by constructing an estimate of the sensory consequences of movement. Theory suggests that this estimate is compared with the actual feedback to compute the sensory prediction error. However, direct proof for the existence of this comparison is lacking. We carried out a trial-by-trial analysis of cerebellar neurons during the execution and adaptation of voluntary head movements and found that neuronal sensitivities dynamically tracked the comparison of predictive and feedback signals. When the relationship between the motor command and resultant movement was altered, neurons robustly responded to sensory input as if the movement was externally generated. Neuronal sensitivities then declined with the same time course as the concurrent behavioral learning. These findings demonstrate the output of an elegant computation in which rapid updating of an internal model enables the motor system to learn to expect unexpected sensory inputs.

The Decay of Motor Memories Is Independent of Context Change Detection

When the error signals that guide human motor learning are withheld following training, recently-learned motor memories systematically regress toward untrained performance. It has previously been hypothesized that this regression results from an intrinsic volatility in these memories, resulting in an inevitable decay in the absence of ongoing error signals. However, a recently-proposed alternative posits that even recently-acquired motor memories are intrinsically stable, decaying only if a change in context is detected. This new theory, the context-dependent decay hypothesis, makes two key predictions: (1) after error signals are withheld, decay onset should be systematically delayed until the context change is detected; and (2) manipulations that impair detection by masking context changes should result in prolonged delays in decay onset and reduced decay amplitude at any given time. Here we examine the decay of motor adaptation following the learning of novel environmental dynamics in order to carefully evaluate this hypothesis. To account for potential issues in previous work that supported the context-dependent decay hypothesis, we measured decay using a balanced and baseline-referenced experimental design that allowed for direct comparisons between analogous masked and unmasked context changes. Using both an unbiased variant of the previous decay onset analysis and a novel highly-powered group-level version of this analysis, we found no evidence for systematically delayed decay onset nor for the masked context change affecting decay amplitude or its onset time. We further show how previous estimates of decay onset latency can be substantially biased in the presence of noise, and even more so with correlated noise, explaining the discrepancy between the previous results and our findings. Our results suggest that the decay of motor memories is an intrinsic feature of error-based learning that does not depend on context change detection.

Suppose you are asked to shoot free throws with a basketball. If you’re an unskilled shooter, you may at first miss in a consistent way for consecutive shots—perhaps a bit to the right—but you will soon learn to correct that error. However, an often-repeated finding is that if error information is withheld, such as if you close your eyes just after releasing the ball, performance will regress toward baseline. One explanation is that newly-formed motor memories are intrinsically volatile, decaying away if there is no continued performance feedback. However, recent work proposed an alternative mechanism: that newly-formed motor memories are intrinsically stable, but people change their behavior upon detecting a context change. This hypothesis predicts decay will occur only after the change is detected, leading to delayed decay if the context change is purposefully masked in an experiment. We show that previous estimates of decay onset delay, which provided support for the context-dependent decay hypothesis, were systematically biased and that decay instead begins immediately, without delay, even when context changes are effectively masked, in stark contrast to the 40+ trial delays previously reported. Thus, we show that recent memories decay independently of context change detection, suggesting that they are indeed intrinsically volatile.

Prospective errors determine motor learning

Diverse features of motor learning have been reported by numerous studies, but no single theoretical framework concurrently accounts for these features. Here, we propose a model for motor learning to explain these features in a unified way by extending a motor primitive framework. The model assumes that the recruitment pattern of motor primitives is determined by the predicted movement error of an upcoming movement (prospective error). To validate this idea, we perform a behavioural experiment to examine the model’s novel prediction: after experiencing an environment in which the movement error is more easily predictable, subsequent motor learning should become faster. The experimental results support our prediction, suggesting that the prospective error might be encoded in the motor primitives. Furthermore, we demonstrate that this model has a strong explanatory power to reproduce a wide variety of motor-learning-related phenomena that have been separately explained by different computational models.

Motor learning is characterized by diverse cognitive processes, which lack a unified theoretical framework. Here, Takiyama et al. present a model demonstrating that motor learning is determined by prospective errors, which they test in a specially designed visuomotor adaptation task.

Retention and interference of learned dexterous manipulation: interaction between multiple sensorimotor processes

An object can be used in multiple contexts, each requiring different hand actions. How the central nervous system builds and maintains memory of such dexterous manipulations remains unclear. We conducted experiments in which human subjects had to learn and recall manipulations performed in two contexts, A and B. Both contexts involved lifting the same L-shaped object whose geometry cued its asymmetrical mass distribution. Correct performance required producing a torque on the vertical handle at object lift onset to prevent it from tilting. The torque direction depended on the context, i.e., object orientation, which was changed by 180° object rotation about a vertical axis. With an A1B1A2 context switching paradigm, subjects learned A1 in the first block of eight trials as indicated by a torque approaching the required one. However, subjects made large errors in anticipating the required torque when switching to B1 immediately after A1 (negative transfer), as well as when they had to recall A1 when switching to A2 after learning B through another block of eight lifts (retrieval interference). Classic sensorimotor learning theories attribute such interferences to multi-rate, multi-state error-driven updates of internal models. However, by systematically changing the interblock break duration and within-block number of trials, our results suggest an alternative explanation underlying interference and retention of dexterous manipulation. Specifically, we identified and quantified through a novel computational model the nonlinear interaction between two sensorimotor mechanisms: a short-lived, context-independent, use-dependent sensorimotor memory and a context-sensitive, error-based learning process.

Fast but fleeting: adaptive motor learning processes associated with aging and cognitive decline

Motor learning has been shown to depend on multiple interacting learning processes. For example, learning to adapt when moving grasped objects with novel dynamics involves a fast process that adapts and decays quickly-and that has been linked to explicit memory-and a slower process that adapts and decays more gradually. Each process is characterized by a learning rate that controls how strongly motor memory is updated based on experienced errors and a retention factor determining the movement-to-movement decay in motor memory. Here we examined whether fast and slow motor learning processes involved in learning novel dynamics differ between younger and older adults. In addition, we investigated how age-related decline in explicit memory performance influences learning and retention parameters. Although the groups adapted equally well, they did so with markedly different underlying processes. Whereas the groups had similar fast processes, they had different slow processes. Specifically, the older adults exhibited decreased retention in their slow process compared with younger adults. Within the older group, who exhibited considerable variation in explicit memory performance, we found that poor explicit memory was associated with reduced retention in the fast process, as well as the slow process. These findings suggest that explicit memory resources are a determining factor in impairments in the both the fast and slow processes for motor learning but that aging effects on the slow process are independent of explicit memory declines.

Interference from mere thinking: mental rehearsal temporarily disrupts recall of motor memory

Interference between successively learned tasks is widely investigated to study motor memory. However, how simultaneously learned motor memories interact with each other has been rarely studied despite its prevalence in daily life. Assuming that motor memory shares common neural mechanisms with declarative memory system, we made unintuitive predictions that mental rehearsal, as opposed to further practice, of one motor memory will temporarily impair the recall of another simultaneously learned memory. Subjects simultaneously learned two sensorimotor tasks, i.e., visuomotor rotation and gain. They retrieved one memory by either practice or mental rehearsal and then had their memory evaluated. We found that mental rehearsal, instead of execution, impaired the recall of unretrieved memory. This impairment was content-independent, i.e., retrieving either gain or rotation impaired the other memory. Hence, conscious recollection of one motor memory interferes with the recall of another memory. This is analogous to retrieval-induced forgetting in declarative memory, suggesting a common neural process across memory systems. Our findings indicate that motor imagery is sufficient to induce interference between motor memories. Mental rehearsal, currently widely regarded as beneficial for motor performance, negatively affects memory recall when it is exercised for a subset of memorized items.

An evaluation of the effectiveness of PROMPT therapy in improving speech production accuracy in six children with cerebral palsy

This study evaluates perceptual changes in speech production accuracy in six children (3-11 years) with moderate-to-severe speech impairment associated with cerebral palsy before, during, and after participation in a motor-speech intervention program (Prompts for Restructuring Oral Muscular Phonetic Targets). An A1BCA2 single subject research design was implemented. Subsequent to the baseline phase (phase A1), phase B targeted each participant's first intervention priority on the PROMPT motor-speech hierarchy. Phase C then targeted one level higher. Weekly speech probes were administered, containing trained and untrained words at the two levels of intervention, plus an additional level that served as a control goal. The speech probes were analysed for motor-speech-movement-parameters and perceptual accuracy. Analysis of the speech probe data showed all participants recorded a statistically significant change. Between phases A1-B and B-C 6/6 and 4/6 participants, respectively, recorded a statistically significant increase in performance level on the motor speech movement patterns targeted during the training of that intervention. The preliminary data presented in this study make a contribution to providing evidence that supports the use of a treatment approach aligned with dynamic systems theory to improve the motor-speech movement patterns and speech production accuracy in children with cerebral palsy.

Dynamic neural correlates of motor error monitoring and adaptation during trial-to-trial learning

A basic EEG feature upon voluntary movements in healthy human subjects is a β (13-30 Hz) band desynchronization followed by a postmovement event-related synchronization (ERS) over contralateral sensorimotor cortex. The functional implications of these changes remain unclear. We hypothesized that, because β ERS follows movement, it may reflect the degree of error in that movement, and the salience of that error to the task at hand. As such, the signal might underpin trial-to-trial modifications of the internal model that informs future movements. To test this hypothesis, EEG was recorded in healthy subjects while they moved a joystick-controlled cursor to visual targets on a computer screen, with different rotational perturbations applied between the joystick and cursor. We observed consistently lower β ERS in trials with large error, even when other possible motor confounds, such as reaction time, movement duration, and path length, were controlled, regardless of whether the perturbation was random or constant. There was a negative trial-to-trial correlation between the size of the absolute initial angular error and the amplitude of the β ERS, and this negative correlation was enhanced when other contextual information about the behavioral salience of the angular error, namely, the bias and variance of errors in previous trials, was additionally considered. These same features also had an impact on the behavioral performance. The findings suggest that the β ERS reflects neural processes that evaluate motor error and do so in the context of the prior history of errors.