Reexposure to a sensorimotor perturbation produces opposite effects on explicit and implicit learning processes

Tiny visual latencies can profoundly impair implicit sensorimotor learning

Short sub-100 ms visual feedback latencies are common in many types of human-computer interactions yet are known to markedly reduce performance in a wide variety of motor tasks from simple pointing to operating surgical robotics. It remains unclear, however, whether these latencies impair not only skilled motor performance but also the implicit sensorimotor learning that underlies its acquisition. Inspired by neurophysiological findings showing that cerebellar LTD and cortical LTP would both be disrupted by sub-100 ms latencies, we hypothesized that implicit sensorimotor learning may be particularly sensitive to these short latencies. Remarkably, we find that improving latency by just 60 ms, from 85 to 25 ms in continuous-feedback experiments, increases implicit learning by 50% and proportionally decreases explicit learning. This resulted in a dramatic reorganization of sensorimotor memory from a 45/55 to a 70/30 implicit/explicit ratio. This 70/30 ratio is more than double that observed in any previous study examining the effect of latency on sensorimotor learning, including a recent study which provided time-advanced visual feedback, suggesting that the low-latency continuous visual feedback we provided is critical for efficiently driving implicit learning. We go on to show that implicit sensorimotor learning is considerably more sensitive to latencies in the sub-100 ms range than to higher latencies, in line with the latency-specific neural plasticity that has been observed. This suggests a clear benefit for latency reduction in computer-based training that involves implicit sensorimotor learning and that across-study differences in computer-based experiments that have examined implicit sensorimotor learning might be explained by differences in unmeasured feedback latencies.

Visuomotor memory is not bound to visual motion

The motor system adapts its output in response to experienced errors to maintain effective movement in a dynamic environment. This learning is thought to utilize sensory prediction errors, the discrepancy between predicted and observed sensory feedback, to update internal models that map motor outputs to sensory states. However, it remains unclear what sensory information is relevant (e.g., the extent to which sensory predictions depend on visual feedback features). We explored this topic by measuring the transfer of visuomotor adaptation across two contexts where input movements created visual motion in opposite directions by either: (i) translating a cursor across a static environment or (ii) causing the environment to move towards a static cursor (272 participants: 94 male, 175 female). We hypothesized that this difference in visual feedback should engage distinct internal models, resulting in poor transfer of learning between contexts. Instead, we found nearly complete transfer of learning across contexts, with evidence that the motor memory was bound to the planned displacement of the hand rather than visual features of the task space. Our results suggest that internal model adaptation is not tied to the exact nature of the sensory feedback that results from movement. Instead, adaptation relies on representations of planned movements, allowing a common internal model to be employed across different visual contexts.Significance statement Human motor control requires constant calibration to remain effective in a dynamic environment. This adaptive process is thought to be driven by error-based learning in internal models that either predict the sensory consequences of a planned movement or output the required movement to realize a sensory goal. However, what sensory information is relevant is unclear. We probed whether internal model adaptation, in response to rotated visual feedback, transferred across two contexts where a common hand movement caused visual motion in opposite directions. We found near-complete transfer of learning across these two contexts, and that learning was tied to hand movements. These results indicate that internal models operate at a level abstracted from the exact nature of the visual feedback provided.

Auditory sequence learning with degraded input: children with cochlear implants ('nature effect') compared to children from low and high socio-economic backgrounds ('nurture effect')

Implicit sequence learning (SL) is crucial for language acquisition and has been studied in children with organic language deficits (e.g., specific language impairment). However, language delays are also seen in children with non-organic deficits, such as those with hearing loss or from low socioeconomic status (SES). While some children with cochlear implants (CI) develop strong language skills, variability in performance suggests that degraded auditory input (nature) may affect SL. Low SES children typically experience language delays due to environmental deprivation (nurture). The purpose of this study was to investigate nature versus nurture effects on auditory SL. A total of 100 participants were divided into normal hearing (NH) children, young adults, CI children from high-moderate SES, and NH children from low SES who were tested with two Serial Reaction Time (SRT) tasks with speech and environmental sounds, and with cognitive tests. Results showed SL for speech and nonspeech stimuli for all participants, suggesting that SL is resilient to degradation of auditory and language input and that SL is not specific to speech. Absolute reaction time (RT) (reflecting a combination of complex processes including SL) was found to be a sensitive measure for differentiating between groups and between types of stimuli. Specifically, normal hearing groups showed longer RT for speech compared to environmental stimuli, a prolongation that was not evident for the CI group, suggesting similar perceptual strategies applying for both sound types; and RT of Low SES children was the longest for speech stimuli compared to other groups of children, evidence of the negative impact of language deprivation on speech processing. Age was the largest contributing factor to the results (~ 50%) followed by cognitive abilities (~ 10%). Implications for intervention include speech-processing targeted programs, provided early in the critical periods of development for low SES children.

Sensorimotor Challenges in Minimally Invasive Surgery: A Theoretically-Oriented Review

OBJECTIVE

This review surveys the literature on sensorimotor challenges impacting performance in laparoscopic minimally invasive surgery (MIS).

BACKGROUND

Despite its well-known benefits for patients, achieving proficiency in MIS can be challenging for surgeons due to many factors including altered visual perspectives and fulcrum effects in instrument handling. Research on these and other sensorimotor challenges has been hindered by imprecise terminology and the lack of a unified theoretical framework to guide research questions in the field.

METHOD

We conducted a systematic survey of the MIS literature, focusing on studies investigating sensorimotor challenges affecting laparoscopic performance. To provide a common foundation for cross-study comparisons, we propose a standardized taxonomy that distinguishes between different experimental paradigms used in the literature. We then show how the computational motor learning perspective provides a unifying theoretical framework for the field that can facilitate progress and motivate future research along clearer, hypothesis-driven lines.

RESULTS

The survey identified diverse sensorimotor perturbations in MIS, which can be effectively categorized according to our proposed taxonomy. Studies investigating monitor-, camera-, and tool-based perturbations were systematically analyzed, elucidating their impact on surgical performance. We also show how the computational motor learning perspective provides deeper insights and potential strategies to mitigate challenges.

CONCLUSION

Sensorimotor challenges significantly impact MIS, necessitating a systematic, empirically informed approach. Our proposed taxonomy and theoretical framework shed light on the complexities involved, paving the way for more structured research and targeted training approaches to enhance surgical proficiency.

APPLICATION

Understanding the sensorimotor challenges inherent to MIS can guide the design of improved training curricula and inform the configuration of setups in the operating room to enhance surgeon performance and ultimately patient outcomes. This review offers key insights for surgeons, educators, and researchers in surgical performance and technology development.

Not fleeting but lasting: limited influence of aging on implicit adaptative motor learning and its short-term retention

In motor adaptation, learning is thought to rely on a combination of several processes. Two of these are implicit learning (incidental updating of the movement due to sensory prediction error) and explicit learning (intentional adjustment to reduce target error). The explicit component is thought to be fast adapting, whereas the implicit one is slow. The dynamic integration of such fast and slow components can lead to spontaneous recovery. That is, after prolonged adaptation of movement to a given perturbation, the learning is extinguished by presenting a perturbation in the opposite direction for a few trials. After such extinction, the learned adaptation can reappear in the absence of any further training, a phenomenon called spontaneous recovery. Trewartha et al. (Trewartha KM, Garcia A, Wolpert DM, Flanagan JR. J Neurosci 34: 13411-13421, 2014) found that older adults show less spontaneous recovery than their younger controls, indicating impairments in short-term retention of force-field adaptation. This disagrees with evidence suggesting that the implicit component and its retention do not decline with aging. To clarify this discrepancy, we performed a conceptual replication of that result. Twenty-eight healthy young and 20 healthy older adults learned to adapt to a forcefield perturbation in a paradigm known to elicit spontaneous recovery. Both groups adapted equally well to the perturbation. Implicit adaptation of the older subjects was indistinguishable from that of their younger counterparts. In addition, our conceptual replication failed to reproduce the result of Trewartha et al. (Trewartha KM, Garcia A, Wolpert DM, Flanagan JR. J Neurosci 34: 13411-13421, 2014) and found that the spontaneous recovery was also similar across groups. Our results reconcile previous studies by showing that both spontaneous recovery and implicit adaptation are unaffected by aging.NEW & NOTEWORTHY In this study, we tested whether aging influences the ability to learn to counteract a perturbation during reaching movements and to recall previously learned motor memories. In contrast to a previously published paper, we found that the ability of older participants to adapt to a perturbation and to recall motor memories remains unimpaired.

A neurocognitive pathway for engineering artificial touch

Artificial haptics has the potential to revolutionize the way we integrate physical and virtual technologies in our daily lives, with implications for teleoperation, motor skill acquisition, rehabilitation, gaming, interpersonal communication, and beyond. Here, we delve into the intricate interplay between the somatosensory system and engineered haptic inputs for perception and action. We critically examine the sensory feedback's fidelity and the cognitive demands of interfacing with these systems. We examine how artificial touch interfaces could be redesigned to better align with human sensory, motor, and cognitive systems, emphasizing the dynamic and context-dependent nature of sensory integration. We consider the various learning processes involved in adapting to artificial haptics, highlighting the need for interfaces that support both explicit and implicit learning mechanisms. We emphasize the need for technologies that are not only physiologically biomimetic but also behaviorally and cognitively congruent with the user, affording a range of alternative solutions to users' needs.

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.

Lateralization of acquisition and consolidation in direction but not amplitude of a motor skill task

Previous research suggests that the neural processes underlying specification of movement direction and amplitude are independently represented in the nervous system. However, our understanding of acquisition and consolidation processes in the direction and distance learning remains limited. We designed a virtual air hockey task, in which the puck direction is determined by the hand direction at impact, while the puck distance is determined by the amplitude of the velocity. In two versions of this task, participants were required to either specify the direction or the distance of the puck, while the alternate variable did not contribute to task success. Separate groups of right-handed participants were recruited for each task. Each participant was randomly assigned to one of two groups with a counter-balanced arm practice sequence (right to left, or left to right). We examined acquisition and, after 24 h, we examined two aspects of consolidation: 1) same hand performance to test the durability and 2) the opposite hand to test the effector-independent consolidation (interlimb transfer) of learning. The distance task showed symmetry between hands in the extent of acquisition as well as in both aspects of consolidation. In contrast, the direction task showed asymmetry in both acquisition and consolidation: the dominant right arm showed faster and greater acquisition and greater transfer from the opposite arm training. The asymmetric acquisition and consolidation processes shown in the direction task might be explained by lateralized control and mapping of direction, an interpretation consistent with previous findings on motor adaptation paradigms.

Neurophysiological evidence of sensory prediction errors driving speech sensorimotor adaptation

The human sensorimotor system has a remarkable ability to quickly and efficiently learn movements from sensory experience. A prominent example is sensorimotor adaptation, learning that characterizes the sensorimotor system's response to persistent sensory errors by adjusting future movements to compensate for those errors. Despite being essential for maintaining and fine-tuning motor control, mechanisms underlying sensorimotor adaptation remain unclear. A component of sensorimotor adaptation is implicit (i.e., the learner is unaware of the learning process) which has been suggested to result from sensory prediction errors-the discrepancies between predicted sensory consequences of motor commands and actual sensory feedback. However, to date no direct neurophysiological evidence that sensory prediction errors drive adaptation has been demonstrated. Here, we examined prediction errors via magnetoencephalography (MEG) imaging of the auditory cortex (n = 34) during sensorimotor adaptation of speech to altered auditory feedback, an entirely implicit adaptation task. Specifically, we measured how speaking-induced suppression (SIS)--a neural representation of auditory prediction errors--changed over the trials of the adaptation experiment. SIS refers to the suppression of auditory cortical response to speech onset (in particular, the M100 response) to self-produced speech when compared to the response to passive listening to identical playback of that speech. SIS was reduced (reflecting larger prediction errors) during the early learning phase compared to the initial unaltered feedback phase. Furthermore, reduction in SIS positively correlated with behavioral adaptation extents, suggesting that larger prediction errors were associated with more learning. In contrast, such a reduction in SIS was not found in a control experiment in which participants heard unaltered feedback and thus did not adapt. In addition, in some participants who reached a plateau in the late learning phase, SIS increased (reflecting smaller prediction errors), demonstrating that prediction errors were minimal when there was no further adaptation. Together, these findings provide the first neurophysiological evidence for the hypothesis that prediction errors drive human sensorimotor adaptation.

Attention defines the context for implicit sensorimotor adaptation

Movement errors are used to continuously recalibrate the sensorimotor map, a process known as sensorimotor adaptation. Here we examined how attention influences this automatic and obligatory learning process. Focusing first on spatial attention, we compared conditions in which the visual feedback that provided information about the movement outcome was either attended or unattended. Surprisingly, this manipulation had no effect on the rate of adaptation. We next used a dual-task methodology to examine the influence of attentional resources on adaptation. Here, again, we found no effect of attention, with the rate of adaptation similar under focused or divided attention conditions. Interestingly, we found that attention modulates adaptation in an indirect manner: Attended stimuli serve as cues that define the context for learning. The rate of adaptation was significantly attenuated when the attended stimulus changed from the end of one trial to the start of the next trial. In contrast, similar changes to unattended stimuli had no impact on adaptation. Together, these results suggest that visual attention defines the cues that establish the context for sensorimotor learning.

Fundamental processes in sensorimotor learning: Reasoning, refinement, and retrieval

Motor learning is often viewed as a unitary process that operates outside of conscious awareness. This perspective has led to the development of sophisticated models designed to elucidate the mechanisms of implicit sensorimotor learning. In this review, we argue for a broader perspective, emphasizing the contribution of explicit strategies to sensorimotor learning tasks. Furthermore, we propose a theoretical framework for motor learning that consists of three fundamental processes: reasoning, the process of understanding action-outcome relationships; refinement, the process of optimizing sensorimotor and cognitive parameters to achieve motor goals; and retrieval, the process of inferring the context and recalling a control policy. We anticipate that this '3R' framework for understanding how complex movements are learned will open exciting avenues for future research at the intersection between cognition and action.

"Leap before you look": Conditions that suppress explicit, knowledge-based learning during visuomotor adaptation

When learning a novel visuomotor mapping (e.g., mirror writing), accuracy can improve quickly through explicit, knowledge-based learning (e.g., aim left to go right), but after practice, implicit or procedural learning takes over, producing fast, natural movements. This procedural learning occurs automatically, whereas it has recently been found that knowledge-based learning can be suppressed by the gradual introduction of the novel mapping when participants must make fast movements and visuomotor perturbations are small (e.g., 30° rotations). We explored the range of task instructions, perturbation parameters, and feedback that preclude or encourage this suppression. Using a reaching task with a rotation between screen position and movement direction, we found that knowledge-based learning could be suppressed even for an extreme 90° rotation, but only if it was introduced gradually and only under instructions to move quickly. If the rotation was introduced abruptly or if instructions emphasized accuracy over speed, knowledge-based learning occurred. A second experiment indicated that knowledge-based learning always occurred in the absence of continuous motion feedback, evidenced by the time course of learning, the aftereffects of learning when the rotation was abruptly removed, and the outcome of formal model comparison between a dual-state (procedural and knowledge-based) versus a single-state (procedural only) learning model of the data. A third experiment replicated the findings and verified that the knowledge-based component of the dual-state model corresponded to explicit aiming, whereas the procedural component was slow to unlearn. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Differential Aging Effects on Implicit and Explicit Sensorimotor Learning

Deterioration in motor control is a hallmark of aging, significantly contributing to a decline in quality of life. More controversial is the question of whether and how aging impacts sensorimotor learning. We hypothesized that the inconsistent picture observed in the current literature can be attributed to at least two factors. First, aging studies tend to be underpowered. Second, the learning assays used in these experiments tend to reflect, to varying degrees, the operation of multiple learning processes, making it difficult to make inferences across studies. We took a two-pronged approach to address these issues. We first performed a meta-analysis of the sensorimotor adaptation literature focusing on outcome measures that provide estimates of explicit and implicit components of adaptation. We then conducted two well-powered experiments to re-examine the effect of aging on sensorimotor adaptation, using behavioral tasks designed to isolate explicit and implicit processes. Convergently, both approaches revealed a striking dissociation: Older individuals exhibited a marked impairment in their ability to discover an explicit strategy to counteract a visuomotor perturbation. However, they exhibited enhanced implicit recalibration. We hypothesize that the effect of aging on explicit learning reflects an age-related decline in reasoning and problem solving, and the effect of aging on implicit learning reflects age-related changes in multisensory integration. Taken together, these findings deepen our understanding of the impact of aging on sensorimotor learning.

Perceptual error based on Bayesian cue combination drives implicit motor adaptation

The sensorimotor system can recalibrate itself without our conscious awareness, a type of procedural learning whose computational mechanism remains undefined. Recent findings on implicit motor adaptation, such as over-learning from small perturbations and fast saturation for increasing perturbation size, challenge existing theories based on sensory errors. We argue that perceptual error, arising from the optimal combination of movement-related cues, is the primary driver of implicit adaptation. Central to our theory is the increasing sensory uncertainty of visual cues with increasing perturbations, which was validated through perceptual psychophysics (Experiment 1). Our theory predicts the learning dynamics of implicit adaptation across a spectrum of perturbation sizes on a trial-by-trial basis (Experiment 2). It explains proprioception changes and their relation to visual perturbation (Experiment 3). By modulating visual uncertainty in perturbation, we induced unique adaptation responses in line with our model predictions (Experiment 4). Overall, our perceptual error framework outperforms existing models based on sensory errors, suggesting that perceptual error in locating one's effector, supported by Bayesian cue integration, underpins the sensorimotor system's implicit adaptation.

Motor adaptation is reduced by symbolic compared to sensory feedback

Motor adaptation - the process of reducing motor errors through feedback and practice - is an essential feature of human competence, allowing us to move accurately in dynamic and novel environments. Adaptation typically results from sensory feedback, with most learning driven by visual and proprioceptive feedback that arises with the movement. In humans, motor adaptation can also be driven by symbolic feedback. In the present study, we examine how implicit and explicit components of motor adaptation are modulated by symbolic feedback. We conducted three reaching experiments involving over 400 human participants to compare sensory and symbolic feedback using a task in which both types of learning processes could be operative (Experiment 1) or tasks in which learning was expected to be limited to only an explicit process (Experiments 2 and 3). Adaptation with symbolic feedback was dominated by explicit strategy use, with minimal evidence of implicit recalibration. Even when matched in terms of information content, adaptation to rotational and mirror reversal perturbations was slower in response to symbolic feedback compared to sensory feedback. Our results suggest that the abstract and indirect nature of symbolic feedback disrupts strategic reasoning and/or refinement, deepening our understanding of how feedback type influences the mechanisms of sensorimotor learning.

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.

Implicit Adaptation Is Modulated by the Relevance of Feedback

Given that informative and relevant feedback in the real world is often intertwined with distracting and irrelevant feedback, we asked how the relevancy of visual feedback impacts implicit sensorimotor adaptation. To tackle this question, we presented multiple cursors as visual feedback in a center-out reaching task and varied the task relevance of these cursors. In other words, participants were instructed to hit a target with a specific task-relevant cursor, while ignoring the other cursors. In Experiment 1, we found that reach aftereffects were attenuated by the mere presence of distracting cursors, compared with reach aftereffects in response to a single task-relevant cursor. The degree of attenuation did not depend on the position of the distracting cursors. In Experiment 2, we examined the interaction between task relevance and attention. Participants were asked to adapt to a task-relevant cursor/target pair, while ignoring the task-irrelevant cursor/target pair. Critically, we jittered the location of the relevant and irrelevant target in an uncorrelated manner, allowing us to index attention via how well participants tracked the position of target. We found that participants who were better at tracking the task-relevant target/cursor pair showed greater aftereffects, and interestingly, the same correlation applied to the task-irrelevant target/cursor pair. Together, these results highlight a novel role of task relevancy on modulating implicit adaptation, perhaps by giving greater attention to informative sources of feedback, increasing the saliency of the sensory prediction error.

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.

Subtle Visual Latency Can Profoundly Impair Implicit Sensorimotor Learning

Short sub-100ms visual feedback latencies are common in many types of human-computer interactions yet are known to markedly reduce performance in a wide variety of motor tasks from simple pointing to operating surgical robotics. These latencies are also present in the computer-based experiments used to study the sensorimotor learning that underlies the acquisition of motor performance. Inspired by neurophysiological findings showing that cerebellar LTD and cortical LTP would both be disrupted by sub-100ms latencies, we hypothesized that implicit sensorimotor learning may be particularly sensitive to these short latencies. Remarkably, we find that improving latency by just 60ms, from 85 to 25ms in latency-optimized experiments, increases implicit learning by 50% and proportionally decreases explicit learning, resulting in a dramatic reorganization of sensorimotor memory. We go on to show that implicit sensorimotor learning is considerably more sensitive to latencies in the sub-100ms range than at higher latencies, in line with the latency-specific neural plasticity that has been observed. This suggests a clear benefit for latency reduction in computer-based training that involves implicit sensorimotor learning and that across-study differences in implicit motor learning might often be explained by disparities in feedback latency.

Perturbation Variability Does Not Influence Implicit Sensorimotor Adaptation

Implicit adaptation has been regarded as a rigid process that automatically operates in response to movement errors to keep the sensorimotor system precisely calibrated. This hypothesis has been challenged by recent evidence suggesting flexibility in this learning process. One compelling line of evidence comes from work suggesting that this form of learning is context-dependent, with the rate of learning modulated by error history. Specifically, learning was attenuated in the presence of perturbations exhibiting high variance compared to when the perturbation is fixed. However, these findings are confounded by the fact that the adaptation system corrects for errors of different magnitudes in a non-linear manner, with the adaptive response increasing in a proportional manner to small errors and saturating to large errors. Through simulations, we show that this non-linear motor correction function is sufficient to explain the effect of perturbation variance without referring to an experience-dependent change in error sensitivity. Moreover, by controlling the distribution of errors experienced during training, we provide empirical evidence showing that there is no measurable effect of perturbation variance on implicit adaptation. As such, we argue that the evidence to date remains consistent with the rigidity assumption.

Age-related changes in motor planning for prior intentions: a mouse tracking reach-to-click task

When we complete sequential movements with different intentions, we plan our movements and adjust ahead. Such a phenomenon is called anticipatory planning for prior intentions and is known to decline with age. In daily life activities, we often need to consider and plan for multiple demands in one movement sequence. However, previous studies only considered one dimension of prior intentions, either different types of onward actions or different precisions of fit or placement. Therefore, in this study, we investigated anticipatory planning for both extrinsic (movement direction) and intrinsic (fit precision) target-related properties in a computer-based movement task and analyzed the computer cursor movement kinematics of both young and older adults. We found that older people consider and adjust for different properties step-by-step, with movement direction being considered as a prior intention during reach movement and fit precision as a motor constraint during drop movement. The age-related changes in the completion of onward actions are constrained by one's general cognitive ability, sensorimotor performance and effective motor planning for prior intentions. Age-related decline in motor planning can manifest as counterproductive movement profiles, resulting in suboptimal performance of intended actions.

Advanced feedback enhances sensorimotor adaptation

It is widely recognized that sensorimotor adaptation is facilitated when feedback is provided throughout the movement compared with when it is provided at the end of the movement. However, the source of this advantage is unclear: continuous feedback is more ecological, dynamic, and available earlier than endpoint feedback. Here, we assess the relative merits of these factors using a method that allows us to manipulate feedback timing independent of actual hand position. By manipulating the onset time of "endpoint" feedback, we found that adaptation was modulated in a non-monotonic manner, with the peak of the function occurring in advance of the hand reaching the target. Moreover, at this optimal time, learning was of similar magnitude as that observed with continuous feedback. By varying movement duration, we demonstrate that this optimal time occurs at a relatively fixed time after movement onset, an interval we hypothesize corresponds to when the comparison of the sensory prediction and feedback generates the strongest error signal.

Large-scale citizen science reveals predictors of sensorimotor adaptation

Sensorimotor adaptation is essential for keeping our movements well calibrated in response to changes in the body and environment. For over a century, researchers have studied sensorimotor adaptation in laboratory settings that typically involve small sample sizes. While this approach has proved useful for characterizing different learning processes, laboratory studies are not well suited for exploring the myriad of factors that may modulate human performance. Here, using a citizen science website, we collected over 2,000 sessions of data on a visuomotor rotation task. This unique dataset has allowed us to replicate, reconcile and challenge classic findings in the learning and memory literature, as well as discover unappreciated demographic constraints associated with implicit and explicit processes that support sensorimotor adaptation. More generally, this study exemplifies how a large-scale exploratory approach can complement traditional hypothesis-driven laboratory research in advancing sensorimotor neuroscience.

Theoretical limits on the speed of learning inverse models explain the rate of adaptation in arm reaching tasks

An essential aspect of human motor learning is the formation of inverse models, which map desired actions to motor commands. Inverse models can be learned by adjusting parameters in neural circuits to minimize errors in the performance of motor tasks through gradient descent. However, the theory of gradient descent establishes limits on the learning speed. Specifically, the eigenvalues of the Hessian of the error surface around a minimum determine the maximum speed of learning in a task. Here, we use this theoretical framework to analyze the speed of learning in different inverse model learning architectures in a set of isometric arm-reaching tasks. We show theoretically that, in these tasks, the error surface and, thus the speed of learning, are determined by the shapes of the force manipulability ellipsoid of the arm and the distribution of targets in the task. In particular, rounder manipulability ellipsoids generate a rounder error surface, allowing for faster learning of the inverse model. Rounder target distributions have a similar effect. We tested these predictions experimentally in a quasi-isometric reaching task with a visuomotor transformation. The experimental results were consistent with our theoretical predictions. Furthermore, our analysis accounts for the speed of learning in previous experiments with incompatible and compatible virtual surgery tasks, and with visuomotor rotation tasks with different numbers of targets. By identifying aspects of a task that influence the speed of learning, our results provide theoretical principles for the design of motor tasks that allow for faster learning.

A Case Study of the Validity of Web-based Visuomotor Rotation Experiments

Web-based experiments are gaining momentum in motor learning research because of the desire to increase statistical power, decrease overhead for human participant experiments, and utilize a more demographically inclusive sample population. However, there is a vital need to understand the general feasibility and considerations necessary to shift tightly controlled human participant experiments to an online setting. We developed and deployed an online experimental platform modeled after established in-laboratory visuomotor rotation experiments to serve as a case study examining remotely collected data quality for an 80-min experiment. Current online motor learning experiments have thus far not exceeded 60 min, and current online crowdsourced studies have a median duration of approximately 10 min. Thus, the impact of a longer-duration, web-based experiment is unknown. We used our online platform to evaluate perturbation-driven motor adaptation behavior under three rotation sizes (±10°, ±35°, and ±65°) and two sensory uncertainty conditions. We hypothesized that our results would follow predictions by the relevance estimation hypothesis. Remote execution allowed us to double (n = 49) the typical participant population size from similar studies. Subsequently, we performed an in-depth examination of data quality by analyzing single-trial data quality, participant variability, and potential temporal effects across trials. Results replicated in-laboratory findings and provided insight on the effect of induced sensory uncertainty on the relevance estimation hypothesis. Our experiment also highlighted several specific challenges associated with online data collection including potentially smaller effect sizes, higher data variability, and lower recommended experiment duration thresholds. Overall, online paradigms present both opportunities and challenges for future motor learning research.

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.

Strategy-based motor learning decreases the post-movement β power

Motor learning depends on the joint contribution of several processes including cognitive strategies aiming at goal achievement and prediction error-driven implicit adaptation. Understanding this functional interplay and its clinical implications requires insight into the individual learning processes, including at a neural level. Here, we set out to examine the impact of learning a cognitive strategy, over and above implicit adaptation, on the oscillatory post-movement β rebound (PMBR), which typically decreases in power following (visuo)motor perturbations. Healthy participants performed reaching movements towards a target, with online visual feedback replacing the view of their moving hand. The feedback was sometimes rotated, either relative to their movements (visuomotor rotation) or invariant to their movements (and relative to the target; clamped feedback), always for two consecutive trials interspersed between non-rotated trials. In both conditions, the first trial with a rotation was unpredictable. On the second trial, the task was either to re-aim, and thereby compensate for the rotation experienced in the first trial (visuomotor rotation; Compensate condition), or to ignore the rotation and keep on aiming at the target (clamped feedback; Ignore condition). After-effects did not differ between conditions, indicating that the amount of implicit learning was similar, while large differences in movement direction in the second rotated trial between conditions indicated that participants successfully acquired re-aiming strategies. Importantly, PMBR power following the first rotated trial was modulated differently in the two conditions. Specifically, it decreased in both conditions, but this effect was larger when participants had to acquire a cognitive strategy and prepare to re-aim. Our results therefore suggest that the PMBR is modulated by cognitive demands of motor learning, possibly reflecting the evaluation of a behaviourally significant goal achievement error.

Implicit motor adaptation driven by intermittent and invariant errors

Our movements and movement outcomes are disturbed by environmental changes, leading to errors. During ongoing environmental changes, people should correct their movement using sensory feedback. However, when the changes are momentary, corrections based on sensory feedback are undesirable. Previous studies have suggested that implicit motor adaptation takes place despite the realization that the presented visual feedback should be ignored. Although these studies created experimental situations in which participants had to continuously ignore the presented visual feedback, in daily lives, people intermittently encounter opportunities to ignore sensory feedback. In this study, by intermittently presenting visual error clamp feedback, always offset from a target by 16° counterclockwise, regardless of the actual movement in a reaching experiment, we provided intermittent opportunities to ignore the visual feedback. We found that in the trials conducted immediately after presenting the visual error clamp feedback, reaching movements shifted in the direction opposite to the feedback, which is a hallmark of implicit motor adaptation. Moreover, the magnitude of the shift was significantly correlated with the rate of motor adaptation to gradual changes in the environment. Therefore, the results suggest that people unintentionally react to momentary environmental changes, which should be ignored. In addition, the sensitivity to momentary changes is greater in people who can quickly adapt to gradual environmental changes.

Daily artificial gravity is associated with greater neural efficiency during sensorimotor adaptation

Altered vestibular signaling and body unloading in microgravity results in sensory reweighting and adaptation. Microgravity effects are well-replicated in head-down tilt bed rest (HDBR). Artificial gravity (AG) is a potential countermeasure to mitigate the effects of microgravity on human physiology and performance. We examined the effectiveness of daily AG for mitigating brain and/or behavioral changes in 60 days of HDBR. One group received AG for 30 minutes daily (AG; n = 16) and a control group spent the same time in HDBR but received no AG (CTRL; n = 8). All participants performed a sensorimotor adaptation task five times during fMRI scanning: twice prior to HDBR, twice during HDBR, and once following HDBR. The AG group showed similar behavioral adaptation effects compared with the CTRLs. We identified decreased brain activation in the AG group from pre to late HDBR in the cerebellum for the task baseline portion and in the thalamus, calcarine, cuneus, premotor cortices, and superior frontal gyrus in the AG group during the early adaptation phase. The two groups also exhibited differential brain-behavior correlations. Together, these results suggest that AG may result in a reduced recruitment of brain activity for basic motor processes and sensorimotor adaptation. These effects may stem from the somatosensory and vestibular stimulation that occur with AG.

Whole-brain dynamics of human sensorimotor adaptation

Humans vary greatly in their motor learning abilities, yet little is known about the neural processes that underlie this variability. We identified distinct profiles of human sensorimotor adaptation that emerged across 2 days of learning, linking these profiles to the dynamics of whole-brain functional networks early on the first day when cognitive strategies toward sensorimotor adaptation are believed to be most prominent. During early learning, greater recruitment of a network of higher-order brain regions, involving prefrontal and anterior temporal cortex, was associated with faster learning. At the same time, greater integration of this "cognitive network" with a sensorimotor network was associated with slower learning, consistent with the notion that cognitive strategies toward adaptation operate in parallel with implicit learning processes of the sensorimotor system. On the second day, greater recruitment of a network that included the hippocampus was associated with faster learning, consistent with the notion that declarative memory systems are involved with fast relearning of sensorimotor mappings. Together, these findings provide novel evidence for the role of higher-order brain systems in driving variability in adaptation.

A double dissociation between savings and long-term memory in motor learning

Memories are easier to relearn than learn from scratch. This advantage, known as savings, has been widely assumed to result from the reemergence of stable long-term memories. In fact, the presence of savings has often been used as a marker for whether a memory has been consolidated. However, recent findings have demonstrated that motor learning rates can be systematically controlled, providing a mechanistic alternative to the reemergence of a stable long-term memory. Moreover, recent work has reported conflicting results about whether implicit contributions to savings in motor learning are present, absent, or inverted, suggesting a limited understanding of the underlying mechanisms. To elucidate these mechanisms, we investigate the relationship between savings and long-term memory by experimentally dissecting the underlying memories based on short-term (60-s) temporal persistence. Components of motor memory that are temporally-persistent at 60 s might go on to contribute to stable, consolidated long-term memory, whereas temporally-volatile components that have already decayed away by 60 s cannot. Surprisingly, we find that temporally-volatile implicit learning leads to savings, whereas temporally-persistent learning does not, but that temporally-persistent learning leads to long-term memory at 24 h, whereas temporally-volatile learning does not. This double dissociation between the mechanisms for savings and long-term memory formation challenges widespread assumptions about the connection between savings and memory consolidation. Moreover, we find that temporally-persistent implicit learning not only fails to contribute to savings, but also that it produces an opposite, anti-savings effect, and that the interplay between this temporally-persistent anti-savings and temporally-volatile savings provides an explanation for several seemingly conflicting recent reports about whether implicit contributions to savings are present, absent, or inverted. Finally, the learning curves we observed for the acquisition of temporally-volatile and temporally-persistent implicit memories demonstrate the coexistence of implicit memories with distinct time courses, challenging the assertion that models of context-based learning and estimation should supplant models of adaptive processes with different learning rates. Together, these findings provide new insight into the mechanisms for savings and long-term memory formation.

Low Vision Impairs Implicit Sensorimotor Adaptation in Response to Small Errors, But Not Large Errors

Successful goal-directed actions require constant fine-tuning of the motor system. This fine-tuning is thought to rely on an implicit adaptation process that is driven by sensory prediction errors (e.g., where you see your hand after reaching vs. where you expected it to be). Individuals with low vision experience challenges with visuomotor control, but whether low vision disrupts motor adaptation is unknown. To explore this question, we assessed individuals with low vision and matched controls with normal vision on a visuomotor task designed to isolate implicit adaptation. We found that low vision was associated with attenuated implicit adaptation only for small visual errors, but not for large visual errors. This result highlights important constraints underlying how low-fidelity visual information is processed by the sensorimotor system to enable successful implicit adaptation.

Signatures of contextual interference in implicit sensorimotor adaptation

Contextual interference refers to the phenomenon whereby a blocked practice schedule results in faster acquisition but poorer retention of new motor skills compared to a random practice schedule. While contextual interference has been observed under a broad range of tasks, it remains unclear if this effect generalizes to the implicit and automatic recalibration of an overlearned motor skill. To address this question, we compared blocked and random practice schedules in a visuomotor rotation task that isolates implicit adaptation. In experiment 1, we found robust signatures of contextual interference in implicit adaptation: compared to participants tested under a blocked training schedule, participants tested under a random training schedule exhibited a reduced rate of learning during the training phase but better retention during a subsequent no-feedback assessment phase. In experiment 2, we again observed an advantage in retention following random practice and showed that this result was not due to a change in context between the training and assessment phases (e.g. a blocked training schedule followed by a random assessment schedule). Taken together, these results indicate that contextual interference is not limited to the acquisition of new motor skills but also applies to the implicit adaptation of established motor skills.

Chronic cannabis use affects cerebellum dependent visuomotor adaptation

BACKGROUND

Cannabis is one of the most commonly used substances in the world. However, its effects on human cognition are not yet fully understood. Although the cerebellum has the highest density of cannabinoid receptor type 1 (CB1R) in the human brain, literature on how cannabis use affects cerebellar-dependent learning is sparse. This study examined the effect of chronic cannabis use on sensorimotor adaptation, a cerebellar-mediated task, which has been suggested to depend on endocannabinoid signaling.

METHODS

Chronic cannabis users (n = 27) with no psychiatric comorbidities and healthy, cannabis-naïve controls (n = 25) were evaluated using a visuomotor rotation task. Cannabis users were re-tested after 1 month of abstinence (n = 13) to assess whether initial differences in performance would persist after cessation of use.

RESULTS

Cannabis users showed lower adaptation rates compared to controls at the first time point. However, this difference in performance did not persist when participants were retested after one month of abstinence (n = 13). Healthy controls showed attenuated implicit learning in the late phase of the adaptation during re-exposure, which was not present in cannabis users. This explains the lack of between group differences in the second time point and suggests a potential alteration of synaptic plasticity required for cerebellar learning in cannabis users.

CONCLUSIONS

Overall, our results suggest that chronic cannabis users show alterations in sensorimotor adaptation, likely due to a saturation of the endocannabinoid system after chronic cannabis use.

Implicit sensorimotor adaptation is preserved in Parkinson's disease

Our ability to enact successful goal-directed actions involves multiple learning processes. Among these processes, implicit motor adaptation ensures that the sensorimotor system remains finely tuned in response to changes in the body and environment. Whether Parkinson's disease impacts implicit motor adaptation remains a contentious area of research: whereas multiple reports show impaired performance in this population, many others show intact performance. While there is a range of methodological differences across studies, one critical issue is that performance in many of the studies may reflect a combination of implicit adaptation and strategic re-aiming. Here, we revisited this controversy using a visuomotor task designed to isolate implicit adaptation. In two experiments, we found that adaptation in response to a wide range of visual perturbations was similar in Parkinson's disease and matched control participants. Moreover, in a meta-analysis of previously published and unpublished work, we found that the mean effect size contrasting Parkinson's disease and controls across 16 experiments involving over 200 participants was not significant. Together, these analyses indicate that implicit adaptation is preserved in Parkinson's disease, offering a fresh perspective on the role of the basal ganglia in sensorimotor learning.

Contextual effects in sensorimotor adaptation adhere to associative learning rules

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

Motor learning without movement

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

Dissociable use-dependent processes for volitional goal-directed reaching

Repetition of specific movement biases subsequent actions towards the practiced movement, a phenomenon known as use-dependent learning (UDL). Recent experiments that impose strict constraints on planning time have revealed two sources of use-dependent biases, one arising from dynamic changes occurring during motor planning and another reflecting a stable shift in motor execution. Here, we used a distributional analysis to examine the contribution of these biases in reaching. To create the conditions for UDL, the target appeared at a designated 'frequent' location on most trials, and at one of six 'rare' locations on other trials. Strikingly, the heading angles were bimodally distributed, with peaks at both frequent and rare target locations. Despite having no constraints on planning time, participants exhibited a robust bias towards the frequent target when movements were self-initiated quickly, the signature of a planning bias; notably, the peak near the rare target was shifted in the frequently practiced direction, the signature of an execution bias. Furthermore, these execution biases were not only replicated in a delayed-response task but were also insensitive to reward. Taken together, these results extend our understanding of how volitional movements are influenced by recent experience.

Sensorimotor Learning in Response to Errors in Task Performance

The human sensorimotor system is sensitive to both limb-related prediction errors and task-related performance errors. Prediction error signals are believed to drive implicit refinements to motor plans. However, an understanding of the mechanisms that performance errors stimulate has remained unclear largely because their effects have not been probed in isolation from prediction errors. Diverging from past work, we induced performance errors independent of prediction errors by shifting the location of a reach target but keeping the intended and actual kinematic consequences of the motion matched. Our first two experiments revealed that rather than implicit learning, motor adjustments in response to performance errors reflect the use of deliberative, volitional strategies. Our third experiment revealed a potential dissociation of performance-error-driven strategies based on error size. Specifically, behavioral changes following large errors were consistent with goal-directed or model-based control, known to be supported by connections between prefrontal cortex and associative striatum. In contrast, motor changes following smaller performance errors carried signatures of model-free stimulus-response learning, of the kind underpinned by pathways between motor cortical areas and sensorimotor striatum. Across all experiments, we also found remarkably faster re-learning, advocating that such "savings" is associated with retrieval of previously learned strategic error compensation and may not require a history of exposure to limb-related errors.

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.

Revisiting the Role of the Medial Temporal Lobe in Motor Learning

Classic taxonomies of memory distinguish explicit and implicit memory systems, placing motor skills squarely in the latter branch. This assertion is in part a consequence of foundational discoveries showing significant motor learning in amnesics. Those findings suggest that declarative memory processes in the medial temporal lobe (MTL) do not contribute to motor learning. Here, we revisit this issue, testing an individual (L. S. J.) with severe MTL damage on four motor learning tasks and comparing her performance to age-matched controls. Consistent with previous findings in amnesics, we observed that L. S. J. could improve motor performance despite having significantly impaired declarative memory. However, she tended to perform poorly relative to age-matched controls, with deficits apparently related to flexible action selection. Further supporting an action selection deficit, L. S. J. fully failed to learn a task that required the acquisition of arbitrary action-outcome associations. We thus propose a modest revision to the classic taxonomic model: Although MTL-dependent memory processes are not necessary for some motor learning to occur, they play a significant role in the acquisition, implementation, and retrieval of action selection strategies. These findings have implications for our understanding of the neural correlates of motor learning, the psychological mechanisms of skill, and the theory of multiple memory systems.

Long-Term Motor Learning in the "Wild" With High Volume Video Game Data

Motor learning occurs over long periods of practice during which motor acuity, the ability to execute actions more accurately, precisely, and in less time, improves. Laboratory-based studies of motor learning are typically limited to a small number of participants and a time frame of minutes to several hours per participant. There is a need to assess the generalizability of theories and findings from lab-based motor learning studies on larger samples and time scales. In addition, laboratory-based studies of motor learning use relatively simple motor tasks which participants are unlikely to be intrinsically motivated to learn, limiting the interpretation of their findings in more ecologically valid settings ("in the wild"). We studied the acquisition and longitudinal refinement of a complex sensorimotor skill embodied in a first-person shooter video game scenario, with a large sample size (N = 7174, 682,564 repeats of the 60 s game) over a period of months. Participants voluntarily practiced the gaming scenario for up to several hours per day up to 100 days. We found improvement in performance accuracy (quantified as hit rate) was modest over time but motor acuity (quantified as hits per second) improved considerably, with 40-60% retention from 1 day to the next. We observed steady improvements in motor acuity across multiple days of video game practice, unlike most motor learning tasks studied in the lab that hit a performance ceiling rather quickly. Learning rate was a non-linear function of baseline performance level, amount of daily practice, and to a lesser extent, number of days between practice sessions. In addition, we found that the benefit of additional practice on any given day was non-monotonic; the greatest improvements in motor acuity were evident with about an hour of practice and 90% of the learning benefit was achieved by practicing 30 min per day. Taken together, these results provide a proof-of-concept in studying motor skill acquisition outside the confines of the traditional laboratory, in the presence of unmeasured confounds, and provide new insights into how a complex motor skill is acquired in an ecologically valid setting and refined across much longer time scales than typically explored.

Individual Differences in Sensorimotor Adaptation Are Conserved Over Time and Across Force-Field Tasks

Sensorimotor adaptation enables the nervous system to modify actions for different conditions and environments. Many studies have investigated factors that influence adaptation at the group level. There is growing recognition that individuals vary in their ability to adapt motor skills and that a better understanding of individual differences in adaptation may inform how motor skills are taught and rehabilitated. Here we examined individual differences in the adaptation of upper-limb reaching movements. We quantified the extent to which participants adapted their movements to a velocity-dependent force field during an initial session, at 24 h, and again 1-week later. Participants (n = 28) displayed savings, which was expressed as greater initial adaptation when re-exposed to the force field. Individual differences in adaptation across various stages of the experiment displayed weak-strong reliability, such that individuals who adapted to a greater extent in the initial session tended to do so when re-exposed to the force field. Our second experiment investigated if individual differences in adaptation are also present when participants adapt to different force fields or a force field and visuomotor rotation. Separate groups of participants adapted to position- and velocity-dependent force fields (Experiment 2a; n = 20) or a velocity-dependent force field and visuomotor rotation in a single session (Experiment 2b; n = 20). Participants who adapted to a greater extent to velocity-dependent forces tended to show a greater extent of adaptation when exposed to position-dependent forces. In contrast, correlations were weak between various stages of adaptation to the force-field and visuomotor rotation. Collectively, our study reveals individual differences in adaptation that are reliable across repeated exposure to the same force field and present when adapting to different force fields.

Younger and Late Middle-Aged Adults Exhibit Different Patterns of Cognitive-Motor Interference During Locomotor Adaptation, With No Disruption of Savings

It has been proposed that motor adaptation and subsequent savings (or faster relearning) of an adapted movement pattern are mediated by cognitive processes. Here, we evaluated the pattern of cognitive-motor interference that emerges when young and late middle-aged adults perform an executive working memory task during locomotor adaptation. We also asked if this interferes with savings of a newly learned walking pattern, as has been suggested by a study of reaching adaptation. We studied split-belt treadmill adaptation and savings in young (21 ± 2 y/o) and late middle-aged (56 ± 6 y/o) adults with or without a secondary 2-back task during adaptation. We found that young adults showed similar performance on the 2-back task during baseline and adaptation, suggesting no effect of the dual-task on cognitive performance; however, dual-tasking interfered with adaptation over the first few steps. Conversely, dual-tasking caused a decrement in cognitive performance in late middle-aged adults with no effect on adaptation. To determine if this effect was specific to adaptation, we also evaluated dual-task interference in late middle-aged adults that dual-tasked while walking in a complex environment that did not induce motor adaptation. This group exhibited less cognitive-motor interference than late middle-aged adults who dual-tasked during adaptation. Savings was unaffected by dual-tasking in both young and late middle-aged adults, which may indicate different underlying mechanisms for savings of reaching and walking. Collectively, our findings reveal an age-dependent effect of cognitive-motor interference during dual-task locomotor adaptation and no effect of dual-tasking on savings, regardless of age. Young adults maintain cognitive performance and show a mild decrement in locomotor adaptation, while late middle-aged adults adapt locomotion at the expense of cognitive performance.

Implicit adaptation to mirror reversal is in the correct coordinate system but the wrong direction

Learning in visuomotor adaptation tasks is the result of both explicit and implicit processes. Explicit processes, operationalized as reaiming an intended movement to a new goal, account for a significant proportion of learning. However, implicit processes, operationalized as error-dependent learning that gives rise to aftereffects, appear to be highly constrained. The limitations of implicit learning are highlighted in the mirror-reversal task, where implicit corrections act in opposition to performance. This is surprising given the mirror-reversal task has been viewed as emblematic of implicit learning. One potential issue not being considered in these studies is that both explicit and implicit processes were allowed to operate concurrently, which may interact, potentially in opposition. Therefore, we sought to further characterize implicit learning in a mirror-reversal task with a clamp design to isolate implicit learning from explicit strategies. We confirmed that implicit adaptation is in the wrong direction for mirror reversal and operates as if the perturbation were a rotation and only showed a moderate attenuation after 3 days of training. This result raised the question of whether implicit adaptation blindly operates as though perturbations were a rotation. In a separate experiment, which directly compared a mirror reversal and a rotation, we found that implicit adaptation operates in a proper coordinate system for different perturbations: adaptation to a mirror reversal and rotational perturbation is more consistent with Cartesian and polar coordinate systems, respectively. It remains an open question why implicit process would be flexible to the coordinate system of a perturbation but continue to be directed inappropriately.NEW & NOTEWORTHY Recent studies have found that implicit learning may operate inappropriately in some motor tasks, requiring explicit strategies to improve performance. However, this inappropriate adaptation could be attributable to competitive interactions between explicit and implicit processes. After isolating implicit processes, we found that implicit adaptation remained in the wrong direction for a mirror reversal, acting as if it were a rotation. Interestingly, however, the implicit system is sensitive to a particular coordinate system, treating mirror reversal and rotation differently.

Perception and control: individual difference in the sense of agency is associated with learnability in sensorimotor adaptation

Adaptive motor learning refers to the ability to adjust to novel disturbances in the environment as a way of minimizing sensorimotor errors. It is known that such processes show large individual differences and are linked to multiple perceptual and cognitive processes. On the other hand, the sense of agency refers to the subjective feeling of control during voluntary motor control. Is the sense of agency just a by-product of the control outcome, or is it actually important for motor control and learning? To answer this question, this study takes an approach based on individual differences to investigate the relationship between the sense of agency and learnability in sensorimotor adaptation. Specifically, we use an adaptive motor learning task to measure individual differences in the efficiency of motor learning. Regarding the sense of agency, we measure the perceptual sensitivity of detecting an increase or a decrease in control when the actual level of control gradually increases or decreases, respectively. The results of structure equation modelling reveal a significant influence of perceptual sensitivity to increased control on motor learning efficiency. On the other hand, the link between perceptual sensitivity to decreased control and motor learning is nonsignificant. The results show that the sense of agency in detecting increased control is associated with the actual ability of sensorimotor adaptation: people who are more sensitive in detecting their control in the environment can also more quickly adjust their behaviors to novel disturbances to acquire better control, compared to people who have a less sensitive sense of agency. Finally, the results also reveal that the processes of increasing control and decreasing control may be partially independent.

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.

Implicit Visuomotor Adaptation Remains Limited after Several Days of Training

Learning in sensorimotor adaptation tasks has been viewed as an implicit learning phenomenon. The implicit process affords recalibration of existing motor skills so that the system can adjust to changes in the body or environment without relearning from scratch. However, recent findings suggest that the implicit process is heavily constrained, calling into question its utility in motor learning and the theoretical framework of sensorimotor adaptation paradigms. These inferences have been based mainly on results from single bouts of training, where explicit compensation strategies, such as explicitly re-aiming the intended movement direction, contribute a significant proportion of adaptive learning. It is possible, however, that the implicit process supersedes explicit compensation strategies over repeated practice sessions. We tested this by dissociating the contributions of explicit re-aiming strategies and the implicit process in human participants over five consecutive days of training. Despite a substantially longer duration of training, the implicit process still plateaued at a value far short of complete learning and, as has been observed in previous studies, was inappropriate for a mirror-reversal task. Notably, we find significant between subject differences that call into question traditional interpretation of these group-level results.