Implicit motor learning within three trials

Attenuation of implicit motor learning with consecutive exposure to visual errors

Visual errors induced by movement drive implicit corrections of that movement. When similar errors are experienced consecutively, does sensitivity to the error remain consistent each time? This study aimed to investigate the modulation of implicit error sensitivity through continuous exposure to the same errors. In the reaching task using visual error-clamp feedback, participants were presented with the same error in direction and magnitude for four consecutive trials. We found that implicit error sensitivity decreased after exposure to the second error. These results indicate that when visual errors occur consecutively, the sensorimotor system exhibits different responses, even for identical errors. The continuity of errors may be a factor that modulates error sensitivity.

Imprecise perception of hand position during early motor adaptation

Localizing one's body parts is important for movement control and motor learning. Recent studies have shown that the precision with which people localize their hand places constraints on motor adaptation. Although these studies have assumed that hand localization remains equally precise across learning, we show that precision decreases rapidly during early motor learning. In three experiments, healthy young participants (n = 92) repeatedly adapted to a 45° visuomotor rotation for a cycle of two to four reaches, followed by a cycle of two to four reaches with veridical feedback. Participants either used an aiming strategy that fully compensated for the rotation (experiment 1), or always aimed directly at the target, so that adaptation was implicit (experiment 2). We omitted visual feedback for the last reach of each cycle, after which participants localized their unseen hand. We observed an increase in the variability of angular localization errors when subjects used a strategy to counter the visuomotor rotation (experiment 1). This decrease in precision was less pronounced in the absence of reaiming (experiment 2), and when subjects knew that they would have to localize their hand on the upcoming trial, and could thus focus on hand position (experiment 3). We propose that strategic reaiming decreases the precision of perceived hand position, possibly due to attention to vision rather than proprioception. We discuss how these dynamics in precision during early motor learning could impact on motor control and shape the interplay between implicit and strategy-based motor adaptation.NEW & NOTEWORTHY Recent studies indicate that the precision with which people localize their hand limits implicit visuomotor learning. We found that localization precision is not static, but decreases early during learning. This decrease is pronounced when people apply a reaiming strategy to compensate for a visuomotor perturbation and is partly resistant to allocation of attention to the hand. We propose that these dynamics in position sense during learning may influence how implicit and strategy-based motor adaption interact.

Minimal impact of proprioceptive loss on implicit sensorimotor adaptation and perceived movement outcome

Implicit sensorimotor adaptation keeps our movements well-calibrated amid changes in the body and environment. We have recently postulated that implicit adaptation is driven by a perceptual error: the difference between the desired and perceived movement outcome. According to this perceptual re-alignment model, implicit adaptation ceases when the perceived movement outcome - a multimodal percept determined by a prior belief conveying the intended action, the motor command, and feedback from proprioception and vision - is aligned with the desired movement outcome. Here, we examined the role of proprioception in implicit motor adaptation and perceived movement outcome by examining individuals who lack proprioception. We used a modified visuomotor rotation task designed to isolate implicit adaptation and probe perceived outcome throughout the experiment. Surprisingly, implicit adaptation and perceived outcome were minimally impacted by deafferentation, posing a challenge to the perceptual re-alignment model of implicit adaptation.

Action does not drive visual biases in peri-tool space

Observers experience visual biases in the area around handheld tools. These biases may occur when active use leads an observer to incorporate a tool into the body schema. However, the visual salience of a handheld tool may instead create an attentional prioritization that is not reliant on body-based representations. We investigated these competing explanations of near-tool visual biases in two experiments during which participants performed a target detection task. Targets could appear near or far from a tool positioned next to a display. In Experiment 1, participants showed facilitation in detecting targets that appeared near a simple handheld rake tool regardless of whether they first used the rake to retrieve objects, but participants who only viewed the tool without holding it were no faster to detect targets appearing near the rake than targets that appeared on the opposite side of the display. In a second experiment, participants who held a novel magnetic tool again showed a near-tool bias even when they refrained from using the tool. Taken together, these results suggest active use is unnecessary, but visual salience is not sufficient, to introduce visual biases in peri-tool space.

Contribution of implicit memory to adaptation of movement extent during reaching against unpredictable spring-like loads: insensitivity to intentional suppression of kinematic performance

We examined the extent to which intentionally underperforming a goal-directed reaching task impacts how memories of recent performance contribute to sensorimotor adaptation. Healthy human subjects performed computerized cognition testing and an assessment of sensorimotor adaptation, wherein they grasped the handle of a horizontal planar robot while making goal-directed out-and-back reaching movements. The robot exerted forces that resisted hand motion with a spring-like load that changed unpredictably between movements. The robotic test assessed how implicit and explicit memories of sensorimotor performance contribute to the compensation for the unpredictable changes in the hand-held load. After each movement, subjects were to recall and report how far the hand moved on the previous trial (peak extent of the out-and-back movement). Subjects performed the tests under two counter-balanced conditions: one where they performed with their best effort, and one where they intentionally sabotaged (i.e., suppressed) kinematic performance. Results from the computerized cognition tests confirmed that subjects understood and complied with task instructions. When suppressing performance during the robotic assessment, subjects demonstrated marked changes in reach precision, time to capture the target, and reaction time. We fit a set of limited memory models to the data to identify how subjects used implicit and explicit memories of recent performance to compensate for the changing loads. In both sessions, subjects used implicit, but not explicit, memories from the most recent trial to adapt reaches to unpredictable spring-like loads. Subjects did not "give up" on large errors, nor did they discount small errors deemed "good enough". Although subjects clearly suppressed kinematic performance (response timing, movement variability, and self-reporting of reach error), the relative contributions of sensorimotor memories to trial-by-trial variations in task performance did not differ significantly between the two testing conditions. We conclude that intentional performance suppression had minimal impact on how implicit sensorimotor memories contribute to adaptation of unpredictable mechanical loads applied to the hand.

Sensory prediction error drives subconscious motor learning outside of the laboratory

Sensorimotor adaptation is supported by at least two parallel learning systems: an intentionally controlled explicit strategy and an involuntary implicit learning system. Past work focused on constrained reaches or finger movements in laboratory environments has shown subconscious learning systems to be driven in part by sensory prediction error (SPE), i.e., the mismatch between the realized and expected outcome of an action. We designed a ball rolling task to explore whether SPEs can drive implicit motor adaptation during complex whole body movements that impart physical motion on external objects. After applying a visual shift, participants rapidly adapted their rolling angles to reduce the error between the ball and the target. We removed all visual feedback and told participants to aim their throw directly toward the primary target, revealing an unintentional 5.06° implicit adjustment to reach angles that decayed over time. To determine whether this implicit adaptation was driven by SPE, we gave participants a second aiming target that would "solve" the visual shift, as in the study by Mazzoni and Krakauer (Mazzoni P, Krakauer JW. J Neurosci 26: 3642-3645, 2006). Remarkably, after rapidly reducing ball-rolling error to zero (due to enhancements in strategic aiming), the additional aiming target caused rolling angles to deviate beyond the primary target by 3.15°. This involuntary overcompensation, which worsened task performance, is a hallmark of SPE-driven implicit learning. These results show that SPE-driven implicit processes, previously observed within simplified finger or planar reaching movements, actively contribute to motor adaptation in more complex naturalistic skill-based tasks.NEW & NOTEWORTHY Implicit and explicit learning systems have been detected using simple, constrained movements inside the laboratory. How these systems impact movements during complex whole body, skill-based tasks has not been established. Here, we demonstrate that sensory prediction errors significantly impact how a person updates their movements, replicating findings from the laboratory in an unconstrained ball-rolling task. This real-world validation is an important step toward explaining how subconscious learning helps humans execute common motor skills in dynamic environments.

Reinforcement learning establishes a minimal metacognitive process to monitor and control motor learning performance

Humans and animals develop learning-to-learn strategies throughout their lives to accelerate learning. One theory suggests that this is achieved by a metacognitive process of controlling and monitoring learning. Although such learning-to-learn is also observed in motor learning, the metacognitive aspect of learning regulation has not been considered in classical theories of motor learning. Here, we formulated a minimal mechanism of this process as reinforcement learning of motor learning properties, which regulates a policy for memory update in response to sensory prediction error while monitoring its performance. This theory was confirmed in human motor learning experiments, in which the subjective sense of learning-outcome association determined the direction of up- and down-regulation of both learning speed and memory retention. Thus, it provides a simple, unifying account for variations in learning speeds, where the reinforcement learning mechanism monitors and controls the motor learning process.

A reliable and efficient adaptive Bayesian method to assess static lower limb position sense

BACKGROUND

Lower limb proprioception is critical for maintaining stability during gait and may impact how individuals modify their movements in response to changes in the environment and body state, a process termed "sensorimotor adaptation". However, the connection between lower limb proprioception and sensorimotor adaptation during human gait has not been established. We suspect this gap is due in part to the lack of reliable, efficient methods to assess global lower limb proprioception in an ecologically valid context.

NEW METHOD

We assessed static lower limb proprioception using an alternative forced choice task, administered twice to determine test-retest reliability. Participants stood on a dual-belt treadmill which passively moved one limb to stimulus locations selected by a Bayesian adaptive algorithm. At the stimulus locations, participants judged relative foot positions and the algorithm estimated the point of subjective equality (PSE) and the uncertainty of lower limb proprioception.

RESULTS

Using the Bland-Altman method, combined with Bayesian statistics, we found that both the PSE and uncertainty estimates had good reliability.

COMPARISON WITH EXISTING METHOD(S)

Current methods assessing static lower limb proprioception do so within a single joint, in non-weight bearing positions, and rely heavily on memory. One exception assessed static lower limb proprioception in standing but did not measure reliability and contained confounds impacting participants' judgments, which we experimentally controlled here.

CONCLUSIONS

This efficient and reliable method assessing lower limb proprioception will aid future mechanistic understanding of locomotor adaptation and serve as a useful tool for basic and clinical researchers studying balance and falls.

Changes in body perception following virtual object manipulation are accompanied by changes of the internal reference scale

Changes in body perception often arise when observers are confronted with related yet discrepant multisensory signals. Some of these effects are interpreted as outcomes of sensory integration of various signals, whereas related biases are ascribed to learning-dependent recalibration of coding individual signals. The present study explored whether the same sensorimotor experience entails changes in body perception that are indicative of multisensory integration and those that indicate recalibration. Participants enclosed visual objects by a pair of visual cursors controlled by finger movements. Then either they judged their perceived finger posture (indicating multisensory integration) or they produced a certain finger posture (indicating recalibration). An experimental variation of the size of the visual object resulted in systematic and opposite biases of the perceived and produced finger distances. This pattern of results is consistent with the assumption that multisensory integration and recalibration had a common origin in the task we used.

A reliable and efficient adaptive Bayesian method to assess static lower limb position sense

Background

Lower limb proprioception is critical for maintaining stability during gait and may impact how individuals modify their movements in response to changes in the environment and body state, a process termed "sensorimotor adaptation". However, the connection between lower limb proprioception and sensorimotor adaptation during human gait has not been established. We suspect this gap is due in part to the lack of reliable, efficient methods to assess global lower limb proprioception in an ecologically valid context.

New Method

We assessed static lower limb proprioception using an alternative forced choice task, administered twice to determine test-retest reliability. Participants stood on a dual-belt treadmill which passively moved one limb to stimulus locations selected by a Bayesian adaptive algorithm. At the stimulus locations, participants judged relative foot positions and the algorithm estimated the point of subjective equality (PSE) and the uncertainty of lower limb proprioception.

Results

Using the Bland-Altman method, combined with Bayesian statistics, we found that both the PSE and uncertainty estimates had good reliability.

Comparison with Existing Methods

Current methods assessing static lower limb proprioception do so within a single joint, in non-weight bearing positions, and rely heavily on memory. One exception assessed static lower limb proprioception in standing but did not measure reliability and contained confounds impacting participants' judgments, which we experimentally controlled here.

Conclusions

This efficient and reliable method assessing lower limb proprioception will aid future mechanistic understanding of locomotor adaptation and serve as a useful tool for basic and clinical researchers studying balance and falls.

Adapting to visuomotor rotations in stepped increments increases implicit motor learning

Human motor adaptation relies on both explicit conscious strategies and implicit unconscious updating of internal models to correct motor errors. Implicit adaptation is powerful, requiring less preparation time before executing adapted movements, but recent work suggests it is limited to some absolute magnitude regardless of the size of a visuomotor perturbation when the perturbation is introduced abruptly. It is commonly assumed that gradually introducing a perturbation should lead to improved implicit learning beyond this limit, but outcomes are conflicting. We tested whether introducing a perturbation in two distinct gradual methods can overcome the apparent limit and explain past conflicting findings. We found that gradually introducing a perturbation in a stepped manner, where participants were given time to adapt to each partial step before being introduced to a larger partial step, led to ~ 80% higher implicit aftereffects of learning, but introducing it in a ramped manner, where participants adapted larger rotations on each subsequent reach, did not. Our results clearly show that gradual introduction of a perturbation can lead to substantially larger implicit adaptation, as well as identify the type of introduction that is necessary to do so.

Error Size Shape Relationships between Motor Variability and Implicit Motor Adaptation

Previous studies have demonstrated the effects of motor variability on motor adaptation. However, their findings have been inconsistent, suggesting that various factors affect the relationship between motor variability and adaptation. This study focused on the size of errors driving motor adaptation as one of the factors and examined the relationship between different error sizes. Thirty-one healthy young adults participated in a visuomotor task in which they made fast-reaching movements toward a target. Motor variability was measured in the baseline phase when a veridical feedback cursor was presented. In the adaptation phase, the feedback cursor was sometimes not reflected in the hand position and deviated from the target by 0°, 3°, 6°, or 12° counterclockwise or clockwise (i.e., error-clamp feedback). Movements during trials following trials with error-clamp feedback were measured to quantify implicit adaptation. Implicit adaptation was driven by errors presented through error-clamp feedback. Moreover, motor variability significantly correlated with implicit adaptation driven by a 12° error. The results suggested that motor variability accelerates implicit adaptation when a larger error occurs. As such a trend was not observed when smaller errors occurred, the relationship between motor variability and motor adaptation might have been affected by the error size driving implicit adaptation.

Short-term effects of visuomotor discrepancies on multisensory integration, proprioceptive recalibration, and motor adaptation

Information about the position of our hand is provided by multisensory signals that are often not perfectly aligned. Discrepancies between the seen and felt hand position or its movement trajectory engage the processes of 1) multisensory integration, 2) sensory recalibration, and 3) motor adaptation, which adjust perception and behavioral responses to apparently discrepant signals. To foster our understanding of the coemergence of these three processes, we probed their short-term dependence on multisensory discrepancies in a visuomotor task that has served as a model for multisensory perception and motor control previously. We found that the well-established integration of discrepant visual and proprioceptive signals is tied to the immediate discrepancy and independent of the outcome of the integration of discrepant signals in immediately preceding trials. However, the strength of integration was context dependent, being stronger in an experiment featuring stimuli that covered a smaller range of visuomotor discrepancies (±15°) compared with one covering a larger range (±30°). Both sensory recalibration and motor adaptation for nonrepeated movement directions were absent after two bimodal trials with same or opposite visuomotor discrepancies. Hence our results suggest that short-term sensory recalibration and motor adaptation are not an obligatory consequence of the integration of preceding discrepant multisensory signals.NEW & NOTEWORTHY The functional relation between multisensory integration and recalibration remains debated. We here refute the notion that they coemerge in an obligatory manner and support the hypothesis that they serve distinct goals of perception.

An emergent temporal basis set robustly supports cerebellar time-series learning

The cerebellum is considered a "learning machine" essential for time interval estimation underlying motor coordination and other behaviors. Theoretical work has proposed that the cerebellum's input recipient structure, the granule cell layer (GCL), performs pattern separation of inputs that facilitates learning in Purkinje cells (P-cells). However, the relationship between input reformatting and learning has remained debated, with roles emphasized for pattern separation features from sparsification to decorrelation. We took a novel approach by training a minimalist model of the cerebellar cortex to learn complex time-series data from time-varying inputs, typical during movements. The model robustly produced temporal basis sets from these inputs, and the resultant GCL output supported better learning of temporally complex target functions than mossy fibers alone. Learning was optimized at intermediate threshold levels, supporting relatively dense granule cell activity, yet the key statistical features in GCL population activity that drove learning differed from those seen previously for classification tasks. These findings advance testable hypotheses for mechanisms of temporal basis set formation and predict that moderately dense population activity optimizes learning.NEW & NOTEWORTHY During movement, mossy fiber inputs to the cerebellum relay time-varying information with strong intrinsic relationships to ongoing movement. Are such mossy fibers signals sufficient to support Purkinje signals and learning? In a model, we show how the GCL greatly improves Purkinje learning of complex, temporally dynamic signals relative to mossy fibers alone. Learning-optimized GCL population activity was moderately dense, which retained intrinsic input variance while also performing pattern separation.

Memory decay and generalization following distinct motor learning mechanisms

Motor skill learning is considered to arise out of contributions from multiple learning mechanisms, including error-based learning (EBL), use-dependent learning (UDL), and reinforcement learning (RL). These learning mechanisms exhibit dissociable roles and engage different neural circuits during skill acquisition. However, it remains largely unknown how a newly formed motor memory acquired through each learning mechanism decays over time and whether distinct learning mechanisms produce different generalization patterns. Here, we used variants of reaching paradigms that dissociated these learning mechanisms to examine the time course of memory decay following each learning and the generalization patterns of each learning. We found that motor memories acquired through these learning mechanisms decayed as a function of time. Notably, 15 min, 6 h, and 24 h after acquisition, the memory of EBL decayed much greater than that of RL. The memory acquired through UDL faded away within a few minutes. Motor memories formed through EBL and RL for given movement directions generalized to untrained movement directions, with the generalization of EBL being greater than that of RL. In contrast, motor memory of UDL could not generalize to untrained movement directions. These results suggest that distinct learning mechanisms exhibit different patterns of memory decay and generalization.NEW & NOTEWORTHY Motor skill learning is likely to involve error-based learning, use-dependent plasticity, and operant reinforcement. Here, we showed that these dissociable learning mechanisms exhibited distinct patterns of memory decay and generalization. With a better understanding of the characteristics of these learning mechanisms, it becomes possible to regulate each learning process separately to improve neurological rehabilitation.

Reduced feedback barely slows down proprioceptive recalibration

Introducing altered visual feedback of the hand produces quick adaptation of reaching movements. Our lab has shown that the associated shifts in estimates of the felt position of the hand saturate within a few training trials. The current study investigates whether the rapid changes in felt hand position that occur during classic visuomotor adaptation are diminished or slowed when training feedback is reduced. We reduced feedback by either providing visual feedback only at the end of the reach (terminal feedback) or constraining hand movements to reduce motor adaptation-related error signals such as sensory prediction errors and task errors (exposure). We measured changes as participants completed reaches with a 30° rotation, a -30° rotation, and clamped visual feedback, with these two "impoverished" training conditions, along with classic visuomotor adaptation training, while continuously estimating their felt hand position. Training with terminal feedback slightly reduced the initial rate of change in overall adaptation. However, the rate of change in hand localization, as well as the asymptote of hand localization shifts in both the terminal feedback group and the exposure training group was not noticeably different from those in the classic training group. Taken together, shifts in felt hand position are rapid and robust responses to sensory mismatches and are at best slightly modulated when feedback is reduced. This suggests that given the speed and invariance to the quality of feedback of proprioceptive recalibration, it could immediately contribute to all kinds of reach adaptation.NEW & NOTEWORTHY Reaching to targets with altered visual feedback about hand position leads to adaptation of movements as well as shifts in estimates of felt hand position. Felt hand position can shift in as little as one trial, and here we show that there is no noticeable reduction in speed when the feedback about movements is impoverished, indicating the robustness of the process of recalibrating felt hand position.

Humans Can Track But Fail to Predict Accelerating Objects

Objects in our visual environment often move unpredictably and can suddenly speed up or slow down. The ability to account for acceleration when interacting with moving objects can be critical for survival. Here, we investigate how human observers track an accelerating target with their eyes and predict its time of reappearance after a temporal occlusion by making an interceptive hand movement. Before occlusion, observers smoothly tracked the accelerating target with their eyes. At the time of occlusion, observers made a predictive saccade to the location where they subsequently intercepted the target with a quick pointing movement. We tested how observers integrated target motion information by comparing three alternative models that describe time-to-contact (TTC) based on the (1) final target velocity sample before occlusion, (2) average target velocity before occlusion, or (3) final target velocity and the rate of target acceleration. We show that observers were able to accurately track the accelerating target with visually-guided smooth pursuit eye movements. However, the timing of the predictive saccade and manual interception revealed inability to act on target acceleration when predicting TTC. Instead, interception timing was best described by the final velocity model that relies on extrapolating the last available target velocity sample before occlusion. Moreover, predictive saccades and manual interception showed similar insensitivity to target acceleration and were correlated on a trial-by-trial basis. These findings provide compelling evidence for the failure of integrating target acceleration into predictive models of target motion that drive both interceptive eye and hand movements.

Individual sensorimotor adaptation characteristics are independent across orofacial speech movements and limb reaching movements

Sensorimotor adaptation is critical for human motor control but shows considerable interindividual variability. Efforts are underway to identify factors accounting for individual differences in specific adaptation tasks. However, a fundamental question has remained unaddressed: Is an individual's capability for adaptation effector system specific or does it reflect a generalized adaptation ability? We therefore tested the same participants in analogous adaptation paradigms focusing on distinct sensorimotor systems: speaking with perturbed auditory feedback and reaching with perturbed visual feedback. Each task was completed once with the perturbation introduced gradually (ramped up over 60 trials) and, on a different day, once with the perturbation introduced suddenly. Consistent with studies of each system separately, visuomotor reach adaptation was more complete than auditory-motor speech adaptation (80% vs. 29% of the perturbation). Adaptation was not significantly correlated between the speech and reach tasks. Moreover, considered within tasks, 1) adaptation extent was correlated between the gradual and sudden conditions for reaching but not for speaking, 2) adaptation extent was correlated with additional measures of performance (e.g., trial duration, within-trial corrections) only for reaching and not for speaking, and 3) fitting individual participant adaptation profiles with exponential rather than linear functions offered a larger benefit [lower root mean square error (RMSE)] for the reach task than for the speech task. Combined, results suggest that the ability for sensorimotor adaptation relies on neural plasticity mechanisms that are effector system specific rather than generalized. This finding has important implications for ongoing efforts seeking to identify cognitive, behavioral, and neurochemical predictors of individual sensorimotor adaptation.NEW & NOTEWORTHY This study provides the first detailed demonstration that individual sensorimotor adaptation characteristics are independent across articulatory speech movements and limb reaching movements. Thus, individual sensorimotor learning abilities are effector system specific rather than generalized. Findings regarding one effector system do not necessarily apply to other systems, different underlying mechanisms may be involved, and implications for clinical rehabilitation or performance training also cannot be generalized.

A single exposure to altered auditory feedback causes observable sensorimotor adaptation in speech

Sensory errors induce two types of behavioral changes: rapid compensation within a movement and longer-term adaptation of subsequent movements. Although adaptation is hypothesized to occur whenever a sensory error is perceived (including after a single exposure to altered feedback), adaptation of articulatory movements in speech has only been observed after repeated exposure to auditory perturbations, questioning both current theories of speech sensorimotor adaptation and the universality of more general theories of adaptation. We measured single-exposure or ‘one-shot’ learning in a large dataset in which participants were exposed to intermittent, unpredictable perturbations of their speech acoustics. On unperturbed trials immediately following these perturbed trials, participants adjusted their speech to oppose the preceding shift, demonstrating that learning occurs even after a single exposure to auditory error. These results provide critical support for current theories of sensorimotor adaptation in speech and align speech more closely with learning in other motor domains.

Are tools truly incorporated as an extension of the body representation?: Assessing the evidence for tool embodiment

The predominant view on human tool-use suggests that an action-oriented body representation, the body schema, is altered to fit the tool being wielded, a phenomenon termed tool embodiment. While observations of perceptual change after tool-use purport to support this hypothesis, several issues undermine their validity in this context, discussed at length in this critical review. The primary measures used as indicators of tool embodiment each face unique challenges to their construct validity. Further, the perceptual changes taken as indicating extension of the body representation only appear to account for a fraction of the tool's size in any given experiment, and do not demonstrate the covariance with tool length that the embodiment hypothesis would predict. The expression of tool embodiment also appears limited to a narrow range of tool-use tasks, as deviations from a simple reaching paradigm can mollify or eliminate embodiment effects altogether. The shortcomings identified here generate important avenues for future research. Until the source of the kinematic and perceptual effects that have substantiated tool embodiment is disambiguated, the hypothesis that the body representation changes to fit tools during tool-use should not be favored over other possibilities such as the formation of separable internal tool models, which seem to offer a more complete account of human tool-use behaviors. Indeed, studies of motor learning have observed analogous perceptual changes as aftereffects to adaptation despite the absence of handheld tool-use, offering a compelling alternative explanation, though more work is needed to confirm this possibility.

Understanding implicit sensorimotor adaptation as a process of proprioceptive re-alignment

Multiple learning processes contribute to successful goal-directed actions in the face of changing physiological states, biomechanical constraints, and environmental contexts. Amongst these processes, implicit sensorimotor adaptation is of primary importance, ensuring that movements remain well-calibrated and accurate. A large body of work on reaching movements has emphasized how adaptation centers on an iterative process designed to minimize visual errors. The role of proprioception has been largely neglected, thought to play a passive role in which proprioception is affected by the visual error but does not directly contribute to adaptation. Here, we present an alternative to this visuo-centric framework, outlining a model in which implicit adaptation acts to minimize a proprioceptive error, the distance between the perceived hand position and its intended goal. This proprioceptive re-alignment model (PReMo) is consistent with many phenomena that have previously been interpreted in terms of learning from visual errors, and offers a parsimonious account of numerous unexplained phenomena. Cognizant that the evidence for PReMo rests on correlational studies, we highlight core predictions to be tested in future experiments, as well as note potential challenges for a proprioceptive-based perspective on implicit adaptation.

What triggers explicit awareness in implicit sequence learning? Implications from theories of consciousness

This article aims to continue the debate on how explicit, conscious knowledge can arise in an implicit learning situation. We review hitherto existing theoretical views and evaluate their compatibility with two current, successful scientific concepts of consciousness: The Global Workspace Theory and Higher-Order Thought Theories. In this context, we introduce the Unexpected Event Hypothesis (Frensch et al., Attention and implicit learning, John Benjamins Publishing Company, 2003) in an elaborated form and discuss its advantage in explaining the emergence of conscious knowledge in an implicit learning situation.

Sensitivity to error during visuomotor adaptation is similarly modulated by abrupt, gradual and random perturbation schedules

It has been suggested that sensorimotor adaptation involves at least two processes (i.e., fast and slow) that differ in retention and error sensitivity. Previous work has shown that repeated exposure to an abrupt force field perturbation results in greater error sensitivity for both the fast and slow processes. While this implies that the faster relearning is associated with increased error sensitivity, it remains unclear what aspects of prior experience modulate error sensitivity. In the present study, we manipulated the initial training using different perturbation schedules, thought to differentially affect fast and slow learning processes based on error magnitude, and then observed what effect prior learning had on subsequent adaptation. During initial training of a visuomotor rotation task, we exposed three groups of participants to either an abrupt, a gradual, or a random perturbation schedule. During a testing session, all three groups were subsequently exposed to an abrupt perturbation schedule. Comparing the two sessions of the control group who experienced repetition of the same perturbation, we found an increased error sensitivity for both processes. We found that the error sensitivity was increased for both the fast and slow processes, with no reliable changes in the retention, for both the gradual and structural learning groups when compared to the first session of the control group. We discuss the findings in the context of how fast and slow learning processes respond to a history of errors.

Individual differences in proprioception predict the extent of implicit sensorimotor adaptation

Recent studies have revealed an upper bound in motor adaptation, beyond which other learning systems may be recruited. The factors determining this upper bound are poorly understood. The multisensory integration hypothesis states that this limit arises from opposing responses to visual and proprioceptive feedback. As individuals adapt to a visual perturbation, they experience an increasing proprioceptive error in the opposite direction, and the upper bound is the point where these two error signals reach an equilibrium. Assuming that visual and proprioceptive feedback are weighted according to their variability, there should be a correlation between proprioceptive variability and the limits of adaptation. Alternatively, the proprioceptive realignment hypothesis states that the upper bound arises when the (visually biased) sensed hand position realigns with the expected sensed position (target). When a visuo-proprioceptive discrepancy is introduced, the sensed hand position is biased toward the visual cursor, and the adaptive system counteracts this discrepancy by driving the hand away from the target. This hypothesis predicts a correlation between the size of the proprioceptive shift and the upper bound of adaptation. We tested these two hypotheses by considering natural variation in proprioception and motor adaptation across individuals. We observed a modest, yet reliable correlation between the upper bound of adaptation with both proprioceptive measures (variability and shift). Although the results do not clearly favor one hypothesis over the other, they underscore the critical role of proprioception in sensorimotor adaptation.NEW & NOTEWORTHY Although the sensorimotor system uses sensory feedback to remain calibrated, this learning process is constrained, limited by the maximum degree of plasticity. The factors determining this limit remain elusive. Guided by two hypotheses, we show that individual differences in the upper bound of adaptation in response to a visual perturbation can be predicted by the bias and variability in proprioception. These results underscore the critical, but often neglected role of proprioception in human motor learning.