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

Relationship between overall right pre-frontal cortex activity and learning and retention of a visuomotor adaptation task: A continuous analysis

Learning a visuomotor adaptation task (VMA) is typically assessed by describing the behavioral changes during adaption (early-fast and late-slow phases) and retention (consolidation) tests. Few studies have concurrently examined behavioral and brain activity during this type of learning and therefore their time-dependent dynamics is unknown. It has been proposed that two distinct strategies can be used during such learning: a model-free and a model-based, which distinctively involved explicit and implicit learning strategies. It has also been proposed that prefrontal cortex (PFC) is more implicated when explicit processes are more relevant as it was observed in the early adaptation (Taylor & Ivry, 2014; Wolpe et al., 2020). Additionally, an explicit model-based strategy has been inferred when prefrontal (PFC) activity increases. Therefore, the study's aims were: (1) to examine the continuous temporal dynamics of behavior and right PFC activity during adaptation and retention of a VMA, and (2) to infer the implication of explicit processes during the learning of a VMA derived from right PFC activity. Eighteen young adults (24.22 ± 3.12 years) took part in this study. Continuous measures of the performance (the initial directional error, IDE, and the root mean square error, RMSE) of a rotational visuomotor adaptation task during an adaptation (AD) and two retention sets at 1 h (RT1) and 24 h (RT24) were collected. Concurrently, measures of the right PFC activity (relative changes of the oxyhemoglobin concentration, [ΔO2Hb]) were registered via a three-channel functional near-infrared spectroscopy device. General linear mixed models were run to explore differences across adaptation and retentions. Also, cross-correlations between performance (IDE and RMSE) and PFC activity were conducted to observe their relation during sets. The main results indicated that (1) initial fast behavioral improvement (decrease of IDE and RMSE) did not occur simultaneously with the largest increase of the [ΔO2Hb] in the PFC during the AD, and (2) there was similar performance in the RT1 and RT24 but possibly involving the PFC differently. While in both retentions the errors improved after the first trials, in RT1, the [ΔO2Hb] decreased from the very beginning, whereas the PFC activity initially increased in RT24. Our observations would suggest that various cooperating learning strategies, including model-free (i.e., exploratory) and model-based explicit (i.e., strategy) and implicit (i.e., sensory prediction errors), are coordinated in different timings to cooperate during the sensorimotor adaptation and consolidation processes. Furthermore, the involvement of these strategies during the retention may depend on the time elapsed from the end of the adaptation to the re-introduction of the task.

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.

Linking Motor Working Memory to Explicit and Implicit Motor Learning

While explicit and implicit motor learning have been widely studied, the extent to which working memory for recent movements - motor working memory (MWM) - contributes to these processes remains unclear. Previous research suggests that visuospatial working memory may facilitate explicit motor learning but is either uninvolved in or detrimental to implicit learning. Here, we ask if and how these findings extend to non-visual MWM. Based on recent work pointing to separate effector-independent and effector-specific MWM codes, we hypothesized that: (1) explicit motor learning processes would correlate with effector-independent MWM, and (2) implicit motor learning processes would correlate with effector-specific MWM. To test these hypotheses, human participants completed both a MWM task and a visuomotor adaptation task. Our results revealed significant correlations between the quality of effector-independent MWM and the degree of explicit motor learning, extending previous findings on visuospatial working memory. Additionally, we present evidence supporting our second hypothesis, that effector-specific MWM correlates with implicit motor learning.

Probing sensorimotor memory through the human speech-audiomotor system

Our knowledge of human sensorimotor learning and memory is predominantly based on the visuospatial workspace and limb movements. Humans also have a remarkable ability to produce and perceive speech sounds. We asked whether the human speech-auditory system could serve as a model to characterize the retention of sensorimotor memory in a workspace that is functionally independent of the visuospatial one. Using adaptation to altered auditory feedback, we investigated the durability of a newly acquired speech-acoustical memory (8- and 24-h delay), its sensitivity to the manner of acquisition (abrupt vs. gradual perturbation), and factors affecting memory retrieval. We observed extensive retention of learning (∼70%) but found no evidence for offline gains. The speech-acoustical memory was insensitive to the manner of its acquisition. To assess factors affecting memory retrieval, tests were first done in the absence of auditory feedback (with masking noise). Under these conditions, it appeared there was no memory for prior learning as if after an overnight delay, speakers had returned to their habitual speech production modes. However, when speech was reintroduced, resulting in speech error feedback, speakers returned immediately to their fully adapted state. This rapid switch shows that the two modes of speech production (adapted and habitual) can coexist in parallel in sensorimotor memory. The findings demonstrate extensive persistence of speech-acoustical memory and reveal context-specific memory retrieval processes in speech-motor learning. We conclude that the human speech-auditory system can be used to characterize sensorimotor memory in a workspace that is distinct from the visuospatial workspace.NEW & NOTEWORTHY There is extensive retention of speech-motor learning. Two parallel modes exist in speech motor memory, one with access to everyday habitual speech and the other with access to newly learned speech-acoustical maps. The availability of speech error feedback triggers a switch between these two modes. Properties of sensorimotor memory in the human speech-auditory system are behaviorally similar to, but functionally independent of, their visuospatial counterparts.

Women show enhanced proprioceptive target estimation through visual-proprioceptive conflict resolution

To form a unified and coherent perception of the organism's state and its relationship with the surrounding environment, the nervous system combines information from various sensory modalities through multisensory integration processes. Occasionally, data from two or more sensory channels may provide conflicting information. This is particularly evident in experiments using the mirror-guided drawing task and the mirror-box illusion, where there is conflict between positional estimates guided by vision and proprioception. This study combined two experimental protocols (the mirror-box and the mirror-guided drawing tasks) to examine whether the learned resolution of visuo-proprioceptive conflicts in the mirror-guided drawing task would improve proprioceptive target estimation of men and women during the mirror-box test. Our results confirm previous findings of visual reaching bias produced by the mirror-box illusion and show that this effect is progressively reduced by improvement in the mirror drawing task performance. However, this was only observed in women. We discuss these findings in the context of possible gender differences in multisensory integration processes as well as in embodiment.

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

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

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.

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.

Reward actively engages both implicit and explicit components in dual force field adaptation

Motor learning occurs through multiple mechanisms, including unsupervised, supervised (error based), and reinforcement (reward based) learning. Although studies have shown that reward leads to an overall better motor adaptation, the specific processes by which reward influences adaptation are still unclear. Here, we examine how the presence of reward affects dual adaptation to novel dynamics and distinguish its influence on implicit and explicit learning. Participants adapted to two opposing force fields in an adaptation/deadaptation/error-clamp paradigm, where five levels of reward (a score and a digital face) were provided as participants reduced their lateral error. Both reward and control (no reward provided) groups simultaneously adapted to both opposing force fields, exhibiting a similar final level of adaptation, which was primarily implicit. Triple-rate models fit to the adaptation process found higher learning rates in the fast and slow processes and a slightly increased fast retention rate for the reward group. Whereas differences in the slow learning rate were only driven by implicit learning, the large difference in the fast learning rate was mainly explicit. Overall, we confirm previous work showing that reward increases learning rates, extending this to dual-adaptation experiments and demonstrating that reward influences both implicit and explicit adaptation. Specifically, we show that reward acts primarily explicitly on the fast learning rate and implicitly on the slow learning rates.NEW & NOTEWORTHY Here we show that rewarding participants' performance during dual force field adaptation primarily affects the initial rate of learning and the early timescales of adaptation, with little effect on the final adaptation level. However, reward affects both explicit and implicit components of adaptation. Whereas the learning rate of the slow process is increased implicitly, the fast learning and retention rates are increased through both implicit components and the use of explicit strategies.

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.

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

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

Significance Statement

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

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.

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.

Dissociable Codes in Motor Working Memory

Working memory has been comprehensively studied in sensory domains, like vision, but little attention has been paid to how motor information (e.g., kinematics of recent movements) is maintained and manipulated in working memory. "Motor working memory" (MWM) is important for short-term behavioral control and skill learning. Here, we employed tasks that required participants to encode and recall reaching movements over short timescales. We conducted three experiments (N = 65 undergraduates) to examine MWM under varying cognitive loads, delays, and degrees of interference. The results support a model of MWM that includes an abstract code that flexibly transfers across effectors, and an effector-specific code vulnerable to interfering movements, even when interfering movements are irrelevant to the task. Neither code was disrupted by increasing visuospatial working memory load. These results echo distinctions between representational formats in other domains, suggesting that MWM shares a basic computational structure with other working memory subsystems.

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.