A shared resource between declarative memory and motor memory

EEG subject-dependent neurofeedback training selectively impairs declarative memories consolidation process

The process of stabilization and storage of memories, known as consolidation, can be modulated by different interventions. Research has shown that self-regulation of brain activity through Neurofeedback (NFB) during the consolidation phase significantly impacts memory stabilization. While some studies have successfully modulated the consolidation phase using traditional EEG-based Neurofeedback (NFB) that focuses on general parameters, such as training a specific frequency band at particular electrodes, they often overlook the unique and complex neurodynamics that underlie each memory content in different individuals, potentially limiting the selective modulation of memories. The main objective of this study is to investigate the effects of a Subject-Dependent NFB (SD-NFB), based on individual models created from the brain activity of each participant, on long-term declarative memories. Participants underwent an experimental protocol involving three sessions. In the first session, they learned images of faces and houses while their brain activity was recorded. This EEG data was used to create individualized models to identify brain patterns related to learning these images. Participants were then divided into three groups, with one group receiving SD-NFB to enhance brain activity linked to faces, another to houses, and a CONTROL sham group that did not receive SD-NFB. Memory performance was evaluated 24 h and seven days later using an 'old-new' recognition task, where participants distinguished between 'old' and 'new' images. The results showed that memory contents (faces or houses) whose brain patterns were trained via SD-NFB scored lower in recognition compared to untrained contents, as evidenced 24 h and seven days post-training. In summary, this study demonstrates that SD-NFB can selectively impact the consolidation of specific declarative memories. This technique could hold significant implications for clinical applications, potentially aiding in the modulation of declarative memory strength in neuropsychiatric disorders where memories are pathologically exacerbated.

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.

Early-Stage Alzheimer's Disease Affects Fast But Not Slow Adaptive Processes in Motor Learning

Alzheimer's disease (AD) is characterized by an initial decline in declarative memory, while nondeclarative memory processing remains relatively intact. Error-based motor adaptation is traditionally seen as a form of nondeclarative memory, but recent findings suggest that it involves both fast, declarative, and slow, nondeclarative adaptive processes. If the declarative memory system shares resources with the fast process in motor adaptation, it can be hypothesized that the fast, but not the slow, process is disturbed in AD patients. To test this, we studied 20 early-stage AD patients and 21 age-matched controls of both sexes using a reach adaptation paradigm that relies on spontaneous recovery after sequential exposure to opposing force fields. Adaptation was measured using error clamps and expressed as an adaptation index (AI). Although patients with AD showed slightly lower adaptation to the force field than the controls, both groups demonstrated effects of spontaneous recovery. The time course of the AI was fitted by a hierarchical Bayesian two-state model in which each dynamic state is characterized by a retention and learning rate. Compared to controls, the retention rate of the fast process was the only parameter that was significantly different (lower) in the AD patients, confirming that the memory of the declarative, fast process is disturbed by AD. The slow adaptive process was virtually unaffected. Since the slow process learns only weakly from an error, our results provide neurocomputational evidence for the clinical practice of errorless learning of everyday tasks in people with dementia.

Reinforcement Learning during Locomotion

When learning a new motor skill, people often must use trial and error to discover which movement is best. In the reinforcement learning framework, this concept is known as exploration and has been linked to increased movement variability in motor tasks. For locomotor tasks, however, increased variability decreases upright stability. As such, exploration during gait may jeopardize balance and safety, making reinforcement learning less effective. Therefore, we set out to determine if humans could acquire and retain a novel locomotor pattern using reinforcement learning alone. Young healthy male and female participants walked on a treadmill and were provided with binary reward feedback (indicated by a green checkmark on the screen) that was tied to a fixed monetary bonus, to learn a novel stepping pattern. We also recruited a comparison group who walked with the same novel stepping pattern but did so by correcting for target error, induced by providing real-time veridical visual feedback of steps and a target. In two experiments, we compared learning, motor variability, and two forms of motor memories between the groups. We found that individuals in the binary reward group did, in fact, acquire the new walking pattern by exploring (increasing motor variability). Additionally, while reinforcement learning did not increase implicit motor memories, it resulted in more accurate explicit motor memories compared with the target error group. Overall, these results demonstrate that humans can acquire new walking patterns with reinforcement learning and retain much of the learning over 24 h.

Comparison of online, offline, and hybrid hypotheses of motor sequence learning using a quantitative model that incorporate reactive inhibition

Two hypotheses have been advanced for when motor sequence learning occurs: offline between bouts of practice or online concurrently with practice. A third possibility is that learning occurs both online and offline. A complication for differentiating between those hypotheses is a process known as reactive inhibition, whereby performance worsens over consecutively executed sequences, but dissipates during breaks. We advance a new quantitative modeling framework that incorporates reactive inhibition and in which the three learning accounts can be implemented. Our results show that reactive inhibition plays a far larger role in performance than is appreciated in the literature. Across four groups of participants in which break times and correct sequences per trial were varied, the best overall fits were provided by a hybrid model. The version of the offline model that does not account for reactive inhibition, which is widely assumed in the literature, had the worst fits. We discuss implications for extant hypotheses and directions for future research.

Neural representations for multi-context visuomotor adaptation and the impact of common representation on multi-task performance: a multivariate decoding approach

The human brain's remarkable motor adaptability stems from the formation of context representations and the use of a common context representation (e.g., an invariant task structure across task contexts) derived from structural learning. However, direct evaluation of context representations and structural learning in sensorimotor tasks remains limited. This study aimed to rigorously distinguish neural representations of visual, movement, and context levels crucial for multi-context visuomotor adaptation and investigate the association between representation commonality across task contexts and adaptation performance using multivariate decoding analysis with fMRI data. Here, we focused on three distinct task contexts, two of which share a rotation structure (i.e., visuomotor rotation contexts with -90° and +90° rotations, in which the mouse cursor's movement was rotated 90 degrees counterclockwise and clockwise relative to the hand-movement direction, respectively) and the remaining one does not (i.e., mirror-reversal context where the horizontal movement of the computer mouse was inverted). This study found that visual representations (i.e., visual direction) were decoded in the occipital area, while movement representations (i.e., hand-movement direction) were decoded across various visuomotor-related regions. These findings are consistent with prior research and the widely recognized roles of those areas. Task-context representations (i.e., either -90° rotation, +90° rotation, or mirror-reversal) were also distinguishable in various brain regions. Notably, these regions largely overlapped with those encoding visual and movement representations. This overlap suggests a potential intricate dependency of encoding visual and movement directions on the context information. Moreover, we discovered that higher task performance is associated with task-context representation commonality, as evidenced by negative correlations between task performance and task-context-decoding accuracy in various brain regions, potentially supporting structural learning. Importantly, despite limited similarities between tasks (e.g., rotation and mirror-reversal contexts), such association was still observed, suggesting an efficient mechanism in the brain that extracts commonalities from different task contexts (such as visuomotor rotations or mirror-reversal) at multiple structural levels, from high-level abstractions to lower-level details. In summary, while illuminating the intricate interplay between visuomotor processing and context information, our study highlights the efficiency of learning mechanisms, thereby paving the way for future exploration of the brain's versatile motor ability.

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

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

The Computational and Neural Bases of Context-Dependent Learning

Flexible behavior requires the creation, updating, and expression of memories to depend on context. While the neural underpinnings of each of these processes have been intensively studied, recent advances in computational modeling revealed a key challenge in context-dependent learning that had been largely ignored previously: Under naturalistic conditions, context is typically uncertain, necessitating contextual inference. We review a theoretical approach to formalizing context-dependent learning in the face of contextual uncertainty and the core computations it requires. We show how this approach begins to organize a large body of disparate experimental observations, from multiple levels of brain organization (including circuits, systems, and behavior) and multiple brain regions (most prominently the prefrontal cortex, the hippocampus, and motor cortices), into a coherent framework. We argue that contextual inference may also be key to understanding continual learning in the brain. This theory-driven perspective places contextual inference as a core component of learning.

Distinct frequencies balance segregation with interaction between different memory types within a prefrontal circuit

Once formed, the fate of memory is uncertain. Subsequent offline interactions between even different memory types (actions versus words) modify retention.^1,2,3,4,5,6 These interactions may occur due to different oscillations functionally linking together different memory types within a circuit.^{7,8,9,10,11,12,13} With memory processing driving the circuit, it may become less susceptible to external influences.¹⁴ We tested this prediction by perturbing the human brain with single pulses of transcranial magnetic stimulation (TMS) and simultaneously measuring the brain activity changes with electroencephalography (EEG^15,16,17). Stimulation was applied over brain areas that contribute to memory processing (dorsolateral prefrontal cortex, DLPFC; primary motor cortex, M1) at baseline and offline, after memory formation, when memory interactions are known to occur.^1,4,6,10,18 The EEG response decreased offline (compared with baseline) within the alpha/beta frequency bands when stimulation was applied to the DLPFC, but not to M1. This decrease exclusively followed memory tasks that interact, revealing that it was due specifically to the interaction, not task performance. It remained even when the order of the memory tasks was changed and so was present, regardless of how the memory interaction was produced. Finally, the decrease within alpha power (but not beta) was correlated with impairment in motor memory, whereas the decrease in beta power (but not alpha) was correlated with impairment in word-list memory. Thus, different memory types are linked to different frequency bands within a DLPFC circuit, and the power of these bands shapes the balance between interaction and segregation between these memories.

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.

Sleep does not influence schema-facilitated motor memory consolidation

STUDY OBJECTIVES

Novel information is rapidly learned when it is compatible with previous knowledge. This "schema" effect, initially described for declarative memories, was recently extended to the motor memory domain. Importantly, this beneficial effect was only observed 24 hours-but not immediately-following motor schema acquisition. Given the established role of sleep in memory consolidation, we hypothesized that sleep following the initial learning of a schema is necessary for the subsequent rapid integration of novel motor information.

METHODS

Two experiments were conducted to investigate the effect of diurnal and nocturnal sleep on schema-mediated motor sequence memory consolidation. In Experiment 1, participants first learned an 8-element motor sequence through repeated practice (Session 1). They were then afforded a 90-minute nap opportunity (N = 25) or remained awake (N = 25) before learning a second motor sequence (Session 2) which was highly compatible with that learned prior to the sleep/wake interval. Experiment 2 was similar; however, Sessions 1 and 2 were separated by a 12-hour interval that included nocturnal sleep (N = 28) or only wakefulness (N = 29).

RESULTS

For both experiments, we found no group differences in motor sequence performance (reaction time and accuracy) following the sleep/wake interval. Furthermore, in Experiment 1, we found no correlation between sleep features (non-REM sleep duration, spindle and slow wave activity) and post-sleep behavioral performance.

CONCLUSIONS

The results of this research suggest that integration of novel motor information into a cognitive-motor schema does not specifically benefit from post-learning sleep.

Enhanced cognitive performance after multiple adaptations to visuomotor transformations

Several studies reported that adaptation to a visuomotor transformation correlates with the performance in cognitive performance tests. However, it is unclear whether there is a causal relationship between sensorimotor adaptation and cognitive performance. The present study examined whether repeated adaptations to double steps and rotated feedback increase cognitive performance assessed by neuropsychological tests in a pre-post design. The participants of the intervention group adapted in 24 sessions their hand movements to visuomotor transformations with increasing size. Pre-post changes were significantly larger in the intervention group than in a control group without training. This result suggests a causal relationship between sensorimotor adaptation training and cognitive performance.

Effects of virtual body-representation on motor skill learning

Motor learning is often hindered or facilitated by visual information from one's body and its movement. However, it is unclear whether visual representation of the body itself facilitates motor learning. Thus, we tested the effects of virtual body-representation on motor learning through a virtual reality rotary pursuit task. In the task, visual feedback on participants' movements was identical, but virtual body-representation differed by dividing the experimental conditions into three conditions: non-avatar, non-hand avatar, and hand-shaped avatar. We measured the differences in the rate of motor learning, body-ownership, and sense of agency in the three conditions. Although there were no differences in body-ownership and sense of agency between the conditions, the hand-shaped avatar condition was significantly superior to the other conditions in the rate of learning. These findings suggest that visually recognizing one's body shape facilitates motor learning.

Human Variation in Error-Based and Reinforcement Motor Learning Is Associated With Entorhinal Volume

Error-based and reward-based processes are critical for motor learning and are thought to be mediated via distinct neural pathways. However, recent behavioral work in humans suggests that both learning processes can be bolstered by the use of cognitive strategies, which may mediate individual differences in motor learning ability. It has been speculated that medial temporal lobe regions, which have been shown to support motor sequence learning, also support the use of cognitive strategies in error-based and reinforcement motor learning. However, direct evidence in support of this idea remains sparse. Here we first show that better overall learning during error-based visuomotor adaptation is associated with better overall learning during the reward-based shaping of reaching movements. Given the cognitive contribution to learning in both of these tasks, these results support the notion that strategic processes, associated with better performance, drive intersubject variation in both error-based and reinforcement motor learning. Furthermore, we show that entorhinal cortex volume is larger in better learning individuals-characterized across both motor learning tasks-compared with their poorer learning counterparts. These results suggest that individual differences in learning performance during error and reinforcement learning are related to neuroanatomical differences in entorhinal cortex.

The Effects of Post-Learning Alcohol Ingestion on Human Motor Memory Consolidation

The neurochemical mechanisms underlying motor memory consolidation remain largely unknown. Based on converging work showing that ethyl alcohol retrogradely enhances declarative memory consolidation, this work tested the hypothesis that post‐learning alcohol ingestion would enhance motor memory consolidation. In a within‐subject and fully counterbalanced design, participants (n = 24; 12M; 12F) adapted to a gradually introduced visual deviation and ingested, immediately after adaptation, a placebo (PBO), a medium (MED) or high (HIGH) dose of alcohol. The alcohol doses were bodyweight‐ and gender‐controlled to yield peak breath alcohol concentrations of 0.00% in the PBO, ~0.05% in the MED and ~0.095% in the HIGH condition. Retention was evaluated 24 h later through reach aftereffects when participants were sober. The results revealed that retention levels were neither significantly nor meaningfully different in both the MED and HIGH conditions as compared to PBO (all absolute Cohen's d_z values < ~0.2; small to negligible effects), indicating that post‐learning alcohol ingestion did not alter motor memory consolidation. Given alcohol's known pharmacological GABAergic agonist and NMDA antagonist properties, one possibility is that these neurochemical mechanisms do not decisively contribute to motor memory consolidation. As converging work demonstrated alcohol's retrograde enhancement of declarative memory, the present results suggest that distinct neurochemical mechanisms underlie declarative and motor memory consolidation. Elucidating the neurochemical mechanisms underlying the consolidation of different memory systems may yield insights into the effects of over‐the‐counter drugs on everyday learning and memory but also inform the development of pharmacological interventions seeking to alter human memory consolidation.

Neural excursions from manifold structure explain patterns of learning during human sensorimotor adaptation

Humans vary greatly in their motor learning abilities, yet little is known about the neural mechanisms that underlie this variability. Recent neuroimaging and electrophysiological studies demonstrate that large-scale neural dynamics inhabit a low-dimensional subspace or manifold, and that learning is constrained by this intrinsic manifold architecture. Here, we asked, using functional MRI, whether subject-level differences in neural excursion from manifold structure can explain differences in learning across participants. We had subjects perform a sensorimotor adaptation task in the MRI scanner on 2 consecutive days, allowing us to assess their learning performance across days, as well as continuously measure brain activity. We find that the overall neural excursion from manifold activity in both cognitive and sensorimotor brain networks is associated with differences in subjects' patterns of learning and relearning across days. These findings suggest that off-manifold activity provides an index of the relative engagement of different neural systems during learning, and that subject differences in patterns of learning and relearning are related to reconfiguration processes occurring in cognitive and sensorimotor networks.

Age-related enhancement in visuomotor learning by a dual-task

Many daily activities require performance of multiple tasks integrating cognitive and motor processes. While the fact that both processes go through deterioration and changes with aging has been generally accepted, not much is known about how aging interacts with stages of motor skill acquisition under a cognitively demanding situation. To address this question, we combined a visuomotor adaptation task with a secondary cognitive task. We made two primary findings beyond the expected age-related performance deterioration. First, while young adults showed classical dual-task cost in the early motor learning phase dominated by explicit processes, older adults instead strikingly displayed enhanced performance in the later stage, dominated by implicit processes. For older adults, the secondary task may have facilitated a shift to their relatively intact implicit learning processes that reduced reliance on their already-deficient explicit processes during visuomotor adaptation. Second, we demonstrated that consistently performing the secondary task in learning and re-learning phases can operate as an internal task-context and facilitate visuomotor memory retrieval later regardless of age groups. Therefore, our study demonstrated age-related similarities and differences in integrating concurrent cognitive load with motor skill acquisition which, may in turn, contributes to the understanding of a shift in balance across multiple systems.

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.

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

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

Contextual inference underlies the learning of sensorimotor repertoires

ASBTRACT

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

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

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

Contributions of implicit and explicit memories to sensorimotor adaptation of movement extent during goal-directed reaching

We examined how implicit and explicit memories contribute to sensorimotor adaptation of movement extent during goal-directed reaching. Twenty subjects grasped the handle of a horizontal planar robot that rendered spring-like resistance to movement. Subjects made rapid “out-and-back” reaches to capture a remembered visual target at the point of maximal reach extent. The robot’s resistance changed unpredictably between reaches, inducing target capture errors that subjects attempted to correct from one trial to the next. Each subject performed over 400 goal-directed reaching trials. Some trials were performed without concurrent visual cursor feedback of hand motion. Some trials required self-assessment of performance between trials, whereby subjects reported peak reach extent on the most recent trial. This was done by either moving a cursor on a horizontal display (visual self-assessment), or by moving the robot’s handle back to the recalled location (proprioceptive self-assessment). Control condition trials performed either without or with concurrent visual cursor feedback of hand motion did not require self-assessments. We used step-wise linear regression analyses to quantify the extent to which prior reach errors and explicit memories of reach extent contribute to subsequent reach performance. Consistent with prior reports, providing concurrent visual feedback of hand motion increased reach accuracy and reduced the impact of past performance errors on future performance, relative to the corresponding no-vision control condition. By contrast, we found no impact of interposed self-assessment on subsequent reach performance or on how prior target capture errors influence subsequent reach performance. Self-assessments were biased toward the remembered target location and they spanned a compressed range of values relative to actual reach extents, demonstrating that declarative memories of reach performance systematically differed from actual performances. We found that multilinear regression could best account for observed data variability when the regression model included only implicit memories of prior reach performance; including explicit memories (self-assessments) in the model did not improve its predictive accuracy. We conclude therefore that explicit memories of prior reach performance do not contribute to implicit sensorimotor adaptation of movement extent during goal-directed reaching under conditions of environmental uncertainty.

Hierarchical motor adaptations negotiate failures during force field learning

Humans have the amazing ability to learn the dynamics of the body and environment to develop motor skills. Traditional motor studies using arm reaching paradigms have viewed this ability as the process of ‘internal model adaptation’. However, the behaviors have not been fully explored in the case when reaches fail to attain the intended target. Here we examined human reaching under two force fields types; one that induces failures (i.e., target errors), and the other that does not. Our results show the presence of a distinct failure-driven adaptation process that enables quick task success after failures, and before completion of internal model adaptation, but that can result in persistent changes to the undisturbed trajectory. These behaviors can be explained by considering a hierarchical interaction between internal model adaptation and the failure-driven adaptation of reach direction. Our findings suggest that movement failure is negotiated using hierarchical motor adaptations by humans.

How do we improve actions after a movement failure? Although negotiating movement failures is obviously crucial, previous motor-control studies have predominantly examined human movement adaptations in the absence of failures, and it remains unclear how failures affect subsequent movement adaptations. Here we examined this issue by developing a novel force field adaptation task where the hand movement during an arm reaching is perturbed by novel forces that induce a large target error, that is a failure. Our experimental observation and computational modeling show that, in addition to the popular ‘internal model learning’ process of motor adaptations, humans also utilize a ‘failure-negotiating’ process, that enables them to quickly improve movements in the presence of failure, even at the expense of increased arm trajectory deflections, which are subsequently reduced gradually with training after the achievement of the task success. Our results suggest that a hierarchical interaction between these two processes is a key for humans to negotiate movement failures.

Acquisition and consolidation processes following motor imagery practice

It well-known that mental training improves skill performance. Here, we evaluated skill acquisition and consolidation after physical or motor imagery practice, by means of an arm pointing task requiring speed-accuracy trade-off. In the main experiment, we showed a significant enhancement of skill after both practices (72 training trials), with a better acquisition after physical practice. Interestingly, we found a positive impact of the passage of time (+ 6 h post training) on skill consolidation for the motor imagery training only, without any effect of sleep (+ 24 h post training) for none of the interventions. In a control experiment, we matched the gain in skill learning after physical training (new group) with that obtained after motor imagery training (main experiment) to evaluate skill consolidation after the same amount of learning. Skill performance in this control group deteriorated with the passage of time and sleep. In another control experiment, we increased the number of imagined trials (n = 100, new group) to compare the acquisition and consolidation processes of this group with that observed in the motor imagery group of the main experiment. We did not find significant differences between the two groups. These findings suggest that physical and motor imagery practice drive skill learning through different acquisition and consolidation processes.

The effect of visual uncertainty on implicit motor adaptation

Sensorimotor adaptation is influenced by both the size and variance of error information. In the present study, we varied visual uncertainty and error size in a factorial manner and evaluated their joint effect on adaptation, using a feedback method that avoids inherent limitations with standard visuomotor tasks. Uncertainty attenuated adaptation, but only when the error was small. This striking interaction highlights a novel constraint for models of sensorimotor adaptation. Sensorimotor adaptation is driven by sensory prediction errors, the difference between the predicted and actual feedback. When the position of the feedback is made uncertain, motor adaptation is attenuated. This effect, in the context of optimal sensory integration models, has been attributed to the motor system discounting noisy feedback and thus reducing the learning rate. In its simplest form, optimal integration predicts that uncertainty would result in reduced learning for all error sizes. However, these predictions remain untested since manipulations of error size in standard visuomotor tasks introduce confounds in the degree to which performance is influenced by other learning processes such as strategy use. Here, we used a novel visuomotor task that isolates the contribution of implicit adaptation, independent of error size. In two experiments, we varied feedback uncertainty and error size in a factorial manner. At odds with the basic predictions derived from the optimal integration theory, the results show that uncertainty attenuated learning only when the error size was small but had no effect when the error size was large. We discuss possible mechanisms that may account for this interaction, considering how uncertainty may interact with the relevance assigned to the error signal or how the output of the adaptation system in terms of recalibrating the sensorimotor map may be modified by uncertainty.NEW & NOTEWORTHY Sensorimotor adaptation is influenced by both the size and variance of error information. In the present study, we varied visual uncertainty and error size in a factorial manner and evaluated their joint effect on adaptation, using a feedback method that avoids inherent limitations with standard visuomotor tasks. Uncertainty attenuated adaptation but only when the error was small. This striking interaction highlights a novel constraint for models of sensorimotor adaptation.

Use of explicit processes during a visually guided locomotor learning task predicts 24-h retention after stroke

Implicit and explicit processes can occur within a single locomotor learning task. The combination of these learning processes may impact how individuals acquire/retain the task. Because these learning processes rely on distinct neural pathways, neurological conditions may selectively impact the processes that occur, thus, impacting learning and retention. Thus, our purpose was to examine the contribution of implicit and explicit processes during a visually guided walking task and characterize the relationship between explicit processes and performance/retention in stroke survivors and age-matched healthy adults. Twenty chronic stroke survivors and twenty healthy adults participated in a 2-day treadmill study. Day 1 included baseline, acquisition1, catch, acquisition2, and immediate retention phases, and day 2 included 24-h retention. During acquisition phases, subjects learned to take a longer step with one leg through distorted visual feedback. During catch and retention phases, visual feedback was removed and subjects were instructed to walk normally (catch) or how they walked during the acquisition phases (retention). Change in step length from baseline to catch represented implicit processes. Change in step length from catch to the end of acquisition2 represented explicit processes. A mixed ANOVA found no difference in the type of learning between groups (P = 0.74). There was a significant relationship between explicit processes and 24-h retention in stroke survivors (r = 0.47, P = 0.04) but not in healthy adults (r = 0.34, P = 0.15). These results suggest that stroke may not affect the underlying learning mechanisms used during locomotor learning, but that these mechanisms impact how well stroke survivors retain the new walking pattern.NEW & NOTEWORTHY This study found that stroke survivors used implicit and explicit processes similar to age-matched healthy adults during a visually guided locomotion learning task. The amount of explicit processes was related to how well stroke survivors retained the new walking pattern but not to how well they performed during the task. This work illustrates the importance of understanding the underlying learning mechanisms to maximize retention of a newly learned motor behavior.

Can sex influence the neurocognition of language? Evidence from Parkinson's disease

Parkinson's disease (PD), which involves basal ganglia degeneration, affects language as well as motor function. However, which aspects of language are impaired in PD and under what circumstances remains unclear. We examined whether lexical and grammatical aspects of language are differentially affected in PD, and whether this dissociation is moderated by sex as well as the degree of basal ganglia degeneration. Our predictions were based on the declarative/procedural model of language. The model posits that grammatical composition, including in regular inflection, depends importantly on left basal ganglia procedural memory circuits, whereas irregular and other lexicalized forms are memorized in declarative memory. Since females tend to show declarative memory advantages as compared to males, the model further posits that females should tend to rely on this system for regulars, which can be stored as lexicalized chunks. We tested non-demented male and female PD patients and healthy control participants on the intensively studied paradigm of English regular and irregular past-tense production. Mixed-effects regression revealed PD deficits only at regular inflection, only in male patients. The degree of left basal ganglia degeneration, as reflected by right-side hypokinesia, predicted only regular inflection, and only in male patients. Left-side hypokinesia did not show this pattern. Past-tense frequency effects suggested that the female patients retrieved regular as well as irregular past-tense forms from declarative memory, whereas the males retrieved only irregulars. Sensitivity analyses showed that the pattern of findings was robust. The results, which are consistent with the declarative/procedural model, suggest a grammatical deficit in PD due to left basal ganglia degeneration, with a relative sparing of lexical retrieval. Female patients appear to compensate for this deficit by relying on chunks stored in declarative memory. More generally, the study elucidates the neurocognition of inflectional morphology and provides evidence that sex can influence how language is computed in the mind and brain.

Procedural Sequence Learning in Attention Deficit Hyperactivity Disorder: A Meta-Analysis

Previous literature proposes that the motor deficits in Attention Deficit Hyperactivity Disorder (ADHD) may be attributed to impairments of the procedural memory network, a long-term memory system involved in sensorimotor and cognitive skill development. A handful of studies have explored procedural sequence learning in ADHD, but findings have been inconsistent. A meta-analysis was conducted to begin to establish whether procedural sequence learning deficits exist in ADHD. The results of seven studies comprising 213 participants with ADHD and 257 participants with typical development (TD) generated an average standardized mean difference of 0.02 (CI95 -0.35, 0.39) that was not significant. Heterogeneity was significant across studies and could be partially attributed to the age of participants. We argue that procedural sequence learning appears to be preserved in ADHD and discuss potential explanations for and against this finding.

Opposing force fields induce direction-specific sensorimotor adaptation but a non-specific perceptual shift consistent with a contraction of peripersonal space representation

Most of our daily interactions with objects occur in the space immediately surrounding the body, i.e. the peripersonal space. The peripersonal space is characterized by multisensory processing of objects which are coded in terms of potential actions, specifying for instance whether objects are within reach or not. Our recent work suggested a link between exposure to a new force field, which changed the effector dynamics, and the representation of peripersonal space. To better understand the interplay between the plasticity of the motor system and peripersonal space representation, the present study examined whether changing the direction of the force field specifically modified the perception of action boundaries. Participants seated at the centre of an experimental platform estimated visual targets' reachability before and after adapting upper-limb reaching movements to the Coriolis force generated by either clockwise or counter clockwise rotation of the platform (120°/s). Opposite spatial after-effects were observed, showing that force-field adaptation depends on the direction of the rotation. In contrast, perceived action boundaries shifted leftward following exposure to the new force field, regardless of the direction of the rotation. Overall, these findings support the idea that abrupt exposure to a new force field results in a direction-specific updating of the central sensorimotor representations underlying the control of arm movements. Abrupt exposure to a new force field also results in a nonspecific shift in the perception of action boundaries, which is consistent with a contraction of the peripersonal space. Such effect, which does not appear to be related to state anxiety, could be related to the protective role of the peripersonal space in response to the uncertainty of the sensorimotor system induced by the abrupt modification of the environment.

The effect of age on visuomotor learning processes

Knowing where our limbs are in space is essential for moving and for adapting movements to various changes in our environments and bodies. The ability to adapt movements declines with age, and age-related cognitive decline can explain a decreased ability to adopt and deploy explicit, cognitive strategies in motor learning. Age-related sensory decline could also lead to a reduced fidelity of sensory position signals and error signals, each of which can affect implicit motor adaptation. Here we investigate two estimates of limb position; one based on proprioception, the other on predicted sensory consequences of movements. Each is considered a measure of an implicit adaptation process and may be affected by both age and cognitive strategies. Both older (n = 38) and younger (n = 42) adults adapted to a 30° visuomotor rotation in a centre-out reaching task. We make an explicit, cognitive strategy available to half of participants in each age group with a detailed instruction. After training, we first quantify the explicit learning elicited by instruction. Instructed older adults initially use the provided strategy slightly less than younger adults but show a similar ability to evoke it after training. This indicates that cognitive explanations for age-related decline in motor learning are limited. In contrast, training induced much larger shifts of state estimates of hand location in older adults compared to younger adults. This is not modulated by strategy instructions, and appears driven by recalibrated proprioception, which is almost twice as large in older adults, while predictions might not be updated in older adults. This means that in healthy aging, some implicit processes may be compensating for other changes to maintain motor capabilities, while others also show age-related decline (data: https://osf.io/qzhmy).

A Proposed Postural Control Theory Synthesizing Optimal Feedback Control Theory, Postural Motor Learning, and Cerebellar Supervision Learning

Multiple theories regarding motor learning and postural control development aim to explain how the central nervous system (CNS) acquires, adjusts, and learns postural behaviors. However, few theories of postural motor development and learning propose possible neurophysiologic correlates to support their assumptions. Evidence from behavioral and computational models support the cerebellum's role in supervising motor learning through the production of forward internal models, corrected by sensory prediction errors. Optimal Feedback Control Theory (OFCT) states that the CNS learns new behaviors by minimizing the cost of multi-joint movements that attain a task goal. By synthesizing principles of the OFCT, postural sway characteristics, and cerebellar anatomy and its internal models, we propose an integrated learning model in which cerebellar supervision of postural control is governed by movement cost functions.

Bidirectional competitive interactions between motor memory and declarative memory during interleaved learning

Distinct motor and declarative memory systems are widely thought to compete during memory consolidation and retrieval, yet the nature of their interactions during learning is less clear. Recent studies have suggested motor learning not only depend on implicit motor memory system supporting gradual tuning of responses by feedback but also depend on explicit declarative memory system. However, this competition has been identified when both systems are engaged in learning the same material (motor information), and so competition might be emphasized. We tested whether such competition also occurs when learning involved separate motor memory and declarative information presented distinctly but yet in close temporal proximity. We measured behavioral and brain-activity correlates of motor-declarative competition during learning using a novel task with interleaved motor-adaptation and declarative-learning demands. Despite unrelated motor versus declarative information and temporal segregation, motor learning interfered with declarative learning and declarative learning interfered with motor learning. This reciprocal competition was tightly coupled to corresponding reductions of fMRI activity in motor versus declarative learning systems. These findings suggest that distinct motor and declarative learning systems compete even when they are engaged by system-specific demands in close temporal proximity during memory formation.

Assessing explicit strategies in force field adaptation

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

A general theory of consciousness I: Consciousness and adaptation

This paper examines how cognitive processes in living beings become conscious. Consciousness is often assumed to be a human quality only. While the basis of this paper is that consciousness is as much present in animals as it is in humans, the human form is shown to be fundamentally different. Animal consciousness expresses itself in sensory images, while human consciousness is largely verbal. Because spoken language is not an individual quality - thoughts are shared with others via communication - consciousness in humans is complex and difficult to understand. The theory proposed postulates that consciousness is an inseparable part of the body's adaptation mechanism. In adaptation to a new environmental disturbance, the outcome of the neural cognitive process - a possible solution to the problem posed by the disturbance - is transformed into a sensory image. Sensory images are essentially conscious as they are the way living creatures experience new environmental information. Through the conversion of neural cognitive activity - thoughts - about the state of the outside world into the way that world is experienced through the senses, the thoughts gain the reality that sensory images have. The translation of thoughts into sensory images makes them real and understandable which is experienced as consciousness. The theory proposed in this paper is corroborated by functional block diagrams of the processes involved in the complex regulated mechanism of adaptation and consciousness during an environmental disturbance. All functions in this mechanism and their interrelations are discussed in detail.

Domain-Specific Working Memory, But Not Dopamine-Related Genetic Variability, Shapes Reward-Based Motor Learning

The addition of rewarding feedback to motor learning tasks has been shown to increase the retention of learning, spurring interest in its possible utility for rehabilitation. However, motor tasks using rewarding feedback have repeatedly been shown to lead to great interindividual variability in performance. Understanding the causes of such variability is vital for maximizing the potential benefits of reward-based motor learning. Thus, using a large human cohort of both sexes (n = 241), we examined whether spatial (SWM), verbal, and mental rotation (RWM) working memory capacity and dopamine-related genetic profiles were associated with performance in two reward-based motor tasks. The first task assessed the participant's ability to follow a slowly shifting reward region based on hit/miss (binary) feedback. The second task investigated the participant's capacity to preserve performance with binary feedback after adapting to the rotation with full visual feedback. Our results demonstrate that higher SWM is associated with greater success and an enhanced capacity to reproduce a successful motor action, measured as change in reach angle following reward. In contrast, higher RWM was predictive of an increased propensity to express an explicit strategy when required to make large reach angle adjustments. Therefore, SWM and RWM were reliable, but dissociable, predictors of success during reward-based motor learning. Change in reach direction following failure was also a strong predictor of success rate, although we observed no consistent relationship with working memory. Surprisingly, no dopamine-related genotypes predicted performance. Therefore, working memory capacity plays a pivotal role in determining individual ability in reward-based motor learning.SIGNIFICANCE STATEMENT Reward-based motor learning tasks have repeatedly been shown to lead to idiosyncratic behaviors that cause varying degrees of task success. Yet, the factors determining an individual's capacity to use reward-based feedback are unclear. Here, we assessed a wide range of possible candidate predictors, and demonstrate that domain-specific working memory plays an essential role in determining individual capacity to use reward-based feedback. Surprisingly, genetic variations in dopamine availability were not found to play a role. This is in stark contrast with seminal work in the reinforcement and decision-making literature, which show strong and replicated effects of the same dopaminergic genes in decision-making. Therefore, our results provide novel insights into reward-based motor learning, highlighting a key role for domain-specific working memory capacity.

Reciprocal intralimb transfer of skilled isometric force production

Motor control theories propose that the same motor plans can be employed by different effectors (e.g., the hand and arm). Skills learned with one effector can therefore "transfer" to others, which has potential applications in clinical situations. However, evidence from adaptation suggests this effect is not reciprocal; learning can be generalized from proximal to distal effectors (e.g., arm to hand), but not from distal to proximal effectors (e.g., hand to arm). We propose that skill learning may not follow the same pattern, because it relies on multiple learning processes beyond error detection and correction. Participants learned a skill task involving the production of isometric forces. We assessed their ability to perform the task with the hand and arm. One group then trained to perform the task using only their hand, whereas a second group trained using only their arm. In a final assessment, we found that participants who trained with either effector improved their skill in performing the task with both their hand and arm. There was no change in a control group that did not train between assessments, indicating that gains were related to the training, not the multiple assessments. These results indicate that in contrast to adaptation, motor skills can generalize from both proximal to distal effectors and from distal to proximal effectors. We propose this is due to differences in the processes underlying skill acquisition as compared with adaptation. NEW & NOTEWORTHY Prior research indicates that motor learning transfers from proximal to distal effectors, but not vice versa. However, this work focused on adapting existing behavior; we questioned whether different results would occur during learning of new motor skills. We found that the benefits of training on a skill task with either the hand or arm transferred across both effectors. This highlights important differences between adaptation and skill learning, and may allow therapeutic benefits for patients with impairments in specific effectors.

Advanced spatial knowledge of target location eliminates age-related differences in early sensorimotor learning

Motor learning has been shown to decline in healthy aging, particularly in the early stages of acquisition. There is now ample evidence that motor learning relies on multiple interacting learning processes that operate on different timescales, but the specific cognitive mechanisms that contribute to motor learning remain unclear. Working memory resources appear to be particularly important during the early stages of motor learning, and declines in early motor learning have been associated with working memory performance in older adults. We examined whether age differences in the early stages of motor learning could be reduced or eliminated by reducing the spatial working memory demands during a force-field adaptation task. Groups of younger and older adults made center-out reaching movements to spatial targets either in a repeating four-element sequence, or in a random order. Participants also performed a battery of cognitive tests to further investigate the potential involvement of associative memory, spatial working memory, and procedural learning mechanisms in the early stage of motor learning. Although all groups adapted their movements equally well by the end of the learning phase, older adults only adapted as quickly as younger adults in the sequence condition, with the older adults in the random group exhibiting slower learning in the earliest stage of motor learning. Across all participants, early motor learning performance was correlated with recognition memory performance on an associative memory test. Within the younger random group, who were able to adapt as quickly as the sequence groups, early motor learning performance was also correlated with performance on a test of procedural learning. These findings suggest that age differences in early stages of motor learning can be eliminated if the spatial working memory demands involved in a motor learning task are limited. Moreover, the results suggest that multiple cognitive resources may be utilized during the early stage of learning, and younger adults may be more flexible than older adults in the recruitment of additional cognitive resources to support learning when spatial working memory demands are high.

Time-dependent motor memory representations in prefrontal cortex

How memories evolve over time is fundamental for understanding memory. Hippocampus-dependent episodic memories are generally assumed to undergo a time-dependent neural reorganization involving an increased reliance on neocortical areas. Yet, whether other forms of memory undergo a similar reorganization over time remains unclear. Here, we examined whether the neural underpinnings of motor sequence memories change over time. Participants were trained on a motor sequence learning task. Either 1d or 28d later, they performed a retention test for this task in the fMRI scanner. Sequence-specific motor memory was observed both 1d and 28d after initial training. Bayesian second-level fMRI analyses suggested a higher probability for task activity in the middle frontal gyrus and frontal pole 28d compared to 1d after initial motor learning. Searchlight representational similarity analysis indicated that areas in middle and superior frontal cortex were more involved in differentiating between multivariate activity patterns for old motor sequence memories and newly learned motor sequences in the 28d-group compared to the 1d-group. This increased involvement of lateral frontal areas during the task after 28 days was not paralleled by a decrease in those areas that were involved in performing the motor sequence retention task after 1d. These novel findings provide insights into how memories beyond the hippocampus evolve over time.

Cerebellum, Predictions and Errors

Making predictions and validating the predictions against actual sensory information is thought to be one of the most fundamental functions of the nervous system. A growing body of evidence shows that the neural mechanisms controlling behavior, both in motor and non-motor domains, rely on prediction errors, the discrepancy between predicted and actual information. The cerebellum has been viewed as a key component of the motor system providing predictions about upcoming movements and receiving feedback about motor errors. Consequentially, studies of cerebellar function have focused on the motor domain with less consideration for the wider context in which movements are generated. However, motor learning experiments show that cognition makes important contributions to motor adaptation that involves the cerebellum. One of the more successful theoretical frameworks for understanding motor control and cerebellar function is the forward internal model which states that the cerebellum predicts the sensory consequences of the motor commands and is involved in computing sensory prediction errors by comparing the predictions to the sensory feedback. The forward internal model was applied and tested mainly for effector movements, raising the question whether cerebellar encoding of behavior reflects task performance measures associated with cognitive involvement. Electrophysiological studies based on pseudo-random tracking in monkeys show that the discharge of Purkinje cell, the sole output neurons of the cerebellar cortex, encodes predictive and feedback signals not only of the effector kinematics but also of task performance. The implications are that the cerebellum implements both effector and task performance forward models and the latter are consistent with the cognitive contributions observed during motor learning. The implications of these findings include insights into recent psychophysical observations on moving with reduced feedback and motor learning. The findings also support the cerebellum's place in hierarchical generative models that work in concert to refine predictions about behavior and the world. Therefore, cerebellar representations bridge motor and non-motor domains and provide a better understanding of cerebellar function within the functional architecture of the brain.

Contextual interference enhances motor learning through increased resting brain connectivity during memory consolidation

Increasing contextual interference (CI) during practice benefits learning, making it a desirable difficulty. For example, interleaved practice (IP) of motor sequences is generally more difficult than repetitive practice (RP) during practice but leads to better learning. Here we investigated whether CI in practice modulated resting-state functional connectivity during consolidation. 26 healthy adults (11 men/15 women, age = 23.3 ± 1.3 years) practiced two sets of three sequences in an IP or RP condition over 2 days, followed by a retention test on Day 5 to evaluate learning. On each practice day, functional magnetic resonance imaging (fMRI) data were acquired during practice and also in a resting state immediately after practice. The resting-state fMRI data were processed using independent component analysis (ICA) followed by functional connectivity analysis, showing that IP on Day 1 led to greater resting connectivity than RP between the left premotor cortex and left dorsolateral prefrontal cortex (DLPFC), bilateral posterior cingulate cortices, and bilateral inferior parietal lobules. Moreover, greater resting connectivity after IP than RP on Day 1, between the left premotor cortex and the hippocampus, amygdala, putamen, and thalamus on the right, and the cerebellum, was associated with better learning following IP. Mediation analysis further showed that the association between enhanced resting premotor-hippocampal connectivity on Day 1 and better retention performance following IP was mediated by greater task-related functional activation during IP on Day 2. Our findings suggest that the benefit of CI to motor learning is likely through enhanced resting premotor connectivity during the early phase of consolidation.

Contribution of explicit processes to reinforcement-based motor learning

Despite increasing interest in the role of reward in motor learning, the underlying mechanisms remain ill defined. In particular, the contribution of explicit processes to reward-based motor learning is unclear. To address this, we examined subjects' ( n = 30) ability to learn to compensate for a gradually introduced 25° visuomotor rotation with only reward-based feedback (binary success/failure). Only two-thirds of subjects ( n = 20) were successful at the maximum angle. The remaining subjects initially followed the rotation but after a variable number of trials began to reach at an insufficiently large angle and subsequently returned to near-baseline performance ( n = 10). Furthermore, those who were successful accomplished this via a large explicit component, evidenced by a reduction in reach angle when they were asked to remove any strategy they employed. However, both groups displayed a small degree of remaining retention even after the removal of this explicit component. All subjects made greater and more variable changes in reach angle after incorrect (unrewarded) trials. However, subjects who failed to learn showed decreased sensitivity to errors, even in the initial period in which they followed the rotation, a pattern previously found in parkinsonian patients. In a second experiment, the addition of a secondary mental rotation task completely abolished learning ( n = 10), while a control group replicated the results of the first experiment ( n = 10). These results emphasize a pivotal role of explicit processes during reinforcement-based motor learning, and the susceptibility of this form of learning to disruption has important implications for its potential therapeutic benefits. NEW & NOTEWORTHY We demonstrate that learning a visuomotor rotation with only reward-based feedback is principally accomplished via the development of a large explicit component. Furthermore, this form of learning is susceptible to disruption with a secondary task. The results suggest that future experiments utilizing reward-based feedback should aim to dissect the roles of implicit and explicit reinforcement learning systems. Therapeutic motor learning approaches based on reward should be aware of the sensitivity to disruption.

Estimating the implicit component of visuomotor rotation learning by constraining movement preparation time

When sensory feedback is perturbed, accurate movement is restored by a combination of implicit processes and deliberate reaiming to strategically compensate for errors. Here, we directly compare two methods used previously to dissociate implicit from explicit learning on a trial-by-trial basis: 1) asking participants to report the direction that they aim their movements, and contrasting this with the directions of the target and the movement that they actually produce, and 2) manipulating movement preparation time. By instructing participants to reaim without a sensory perturbation, we show that reaiming is possible even with the shortest possible preparation times, particularly when targets are narrowly distributed. Nonetheless, reaiming is effortful and comes at the cost of increased variability, so we tested whether constraining preparation time is sufficient to suppress strategic reaiming during adaptation to visuomotor rotation with a broad target distribution. The rate and extent of error reduction under preparation time constraints were similar to estimates of implicit learning obtained from self-report without time pressure, suggesting that participants chose not to apply a reaiming strategy to correct visual errors under time pressure. Surprisingly, participants who reported aiming directions showed less implicit learning according to an alternative measure, obtained during trials performed without visual feedback. This suggests that the process of reporting can affect the extent or persistence of implicit learning. The data extend existing evidence that restricting preparation time can suppress explicit reaiming and provide an estimate of implicit visuomotor rotation learning that does not require participants to report their aiming directions.NEW & NOTEWORTHY During sensorimotor adaptation, implicit error-driven learning can be isolated from explicit strategy-driven reaiming by subtracting self-reported aiming directions from movement directions, or by restricting movement preparation time. Here, we compared the two methods. Restricting preparation times did not eliminate reaiming but was sufficient to suppress reaiming during adaptation with widely distributed targets. The self-report method produced a discrepancy in implicit learning estimated by subtracting aiming directions and implicit learning measured in no-feedback trials.

Interference Conditions of the Reconsolidation Process in Humans: The Role of Valence and Different Memory Systems

Following the presentation of a reminder, consolidated memories become reactivated followed by a process of re-stabilization, which is referred to as reconsolidation. The most common behavioral tool used to reveal this process is interference produced by new learning shortly after memory reactivation. Memory interference is defined as a decrease in memory retrieval, the effect is generated when new information impairs an acquired memory. In general, the target memory and the interference task used are the same. Here we investigated how different memory systems and/or their valence could produce memory reconsolidation interference. We showed that a reactivated neutral declarative memory could be interfered by new learning of a different neutral declarative memory. Then, we revealed that an aversive implicit memory could be interfered by the presentation of a reminder followed by a threatening social event. Finally, we showed that the reconsolidation of a neutral declarative memory is unaffected by the acquisition of an aversive implicit memory and conversely, this memory remains intact when the neutral declarative memory is used as interference. These results suggest that the interference of memory reconsolidation is effective when two task rely on the same memory system or both evoke negative valence.

Motor skill learning and offline-changes in TGA patients with acute hippocampal CA1 lesions

Learning and the formation of memory are reflected in various memory systems in the human brain such as the hippocampus based declarative memory system and the striatum-cortex based system involved in motor sequence learning. It is a matter of debate how both memory systems interact in humans during learning and consolidation and how this interaction is influenced by sleep. We studied the effect of an acute dysfunction of hippocampal CA1 neurons on the acquisition (on-line condition) and off-line changes of a motor skill in patients with a transient global amnesia (TGA). Sixteen patients (68 ± 4.4 yrs) were studied in the acute phase and during follow-up using a declarative and procedural test, and were compared to controls. Acute TGA patients displayed profound deficits in all declarative memory functions. During the acute amnestic phase, patients were able to acquire the motor skill task reflected by increasing finger tapping speed across the on-line condition, albeit to a lesser degree than during follow-up or compared to controls. Retrieval two days later indicated a greater off-line gain in motor speed in patients than controls. Moreover, this gain in motor skill performance was negatively correlated to the declarative learning deficit. Our results suggest a differential interaction between procedural and declarative memory systems during acquisition and consolidation of motor sequences in older humans. During acquisition, hippocampal dysfunction attenuates fast learning and thus unmasks the slow and rigid learning curve of striatum-based procedural learning. The stronger gains in the post-consolidation condition in motor skill in CA1 lesioned patients indicate a facilitated consolidation process probably occurring during sleep, and suggest a competitive interaction between the memory systems. These findings might be a reflection of network reorganization and plasticity in older humans and in the presence of CA1 hippocampal pathology.

The stuff that motor chunks are made of: Spatial instead of motor representations?

In order to determine how participants represent practiced, discrete keying sequences in the discrete sequence production task, we had 24 participants practice two six-key sequences on the basis of two pre-learned six-digit numbers. These sequences were carried out by fingers of the left (L) and right (R) hand with between-hand transitions always occurring between the second and third, and the fifth and sixth responses. This yielded the so-called LLRRRL and RRLLLR sequences. Early and late in practice, the keypad used for the right hand was briefly relocated from the front of the participants to 90° at their right side. The results indicate that after 600 practice trials, executing a keying sequence relies heavily on a spatial cross-hand representation in a trunk- or head-based reference frame that after about only 15 trials is fully adjusted to the changed hand location. The hand location effect was not found with the last sequence element. This is attributed to the application of explicit knowledge. The between-hand transitions appeared to induce initial segmentation in some of the participants, but this did not consolidate into a concatenation point of successive motor chunks.