Poh, Eugene, et al.Generalization of motor learning in psychological space”. bioRxiv (Submitted). Web. pohetal2021.pdf
Avraham, Guy, et al.Contextual effects in motor adaptation adhere to associative learning rules”. bioRxiv (Submitted). Web. avrahametal2021b.pdf
McDougle, Samuel D., et al.Revisiting the role of the medial temporal lobe in motor learning”. Journal of Cognitive Neuroscience 34.3 (2022): , 34, 3, 532-549. Web.Abstract

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 founda- tional discoveries showing significant motor learning in amne- sics. 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 com- paring 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.

Mushtaq, Faisal, et al.Distinct Neural Signatures of Outcome Monitoring After Selection and Execution Errors”. Journal of Cognitive Neuroscience 34.5 (2022): , 34, 5, 748-765. Web.Abstract
Losing a point in tennis could result from poor shot selection or faulty stroke execution. To explore how the brain responds to these different types of errors, we examined feedback-locked EEG activity while participants completed a modified version of a standard three-armed bandit probabilistic reward task. Our task framed unrewarded outcomes as the result of either errors of selection or errors of execution. We examined whether amplitude of a medial frontal negativity (the feedback-related negativity [FRN]) was sensitive to the different forms of error attribution. Consistent with previous reports, selection errors elicited a large FRN relative to rewards, and amplitude of this signal correlated with behavioral adjustment after these errors. A different pattern was observed in response to execution errors. These outcomes produced a larger FRN, a frontocentral attenuation in activity preceding this component, and a subsequent enhanced error positivity in parietal sites. Notably, the only correlations with behavioral adjustment were with the early frontocentral attenuation and amplitude of the parietal signal; FRN differences between execution errors and rewarded trials did not correlate with subsequent changes in behavior. Our findings highlight distinct neural correlates of selection and execution error processing, providing insight into how the brain responds to the different classes of error that determine future action.
McDougle, Samuel D., et al.Continuous manipulation of mental representations is compromised in cerebellar degeneration”. Brain awac072 (2022). Web.Abstract
We introduce a novel perspective on how the cerebellum might contribute to cognition, hypothesizing that this structure supports dynamic transformations of mental representations. In support of this hypothesis, we report a series of neuropsychological experiments comparing the performance of individuals with degenerative cerebellar disorders (CD) on tasks that either entail continuous, movement-like mental operations or more discrete mental operations. In the domain of visual cognition, the CD group exhibited an impaired rate of mental rotation, an operation hypothesized to require the continuous manipulation of a visual representation. In contrast, the CD group showed a normal processing rate when scanning items in visual working memory, an operation hypothesized to require the maintenance and retrieval of remembered items. In the domain of mathematical cognition, the CD group was impaired at single-digit addition, an operation hypothesized to primarily require iterative manipulations along a mental number-line; this group was not impaired on arithmetic tasks linked to memory retrieval (e.g., single-digit multiplication). These results, obtained in tasks from two disparate domains, point to a potential constraint on the contribution of the cerebellum to cognitive tasks. Paralleling its role in motor control, the cerebellum may be essential for coordinating dynamic, movement-like transformations in a mental workspace.
Wang, Tianhe, and Jordan A. Taylor. “Implicit adaptation to mirror reversal is in the correct coordinate system but the wrong direction”. J Neurophysiol 126.5 (2021): , 126, 5, 1478-1489. Web.Abstract

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

NEW & NOTEWORTHY Recent studies have found that implicit learning may operate inappropriately in some motor tasks, requiring explicit strategies to improve performance. However, this inappropriate adaptation could be attributable to competitive interactions between explicit and implicit processes. After isolating implicit processes, we found that implicit adaptation remained in the wrong direction for a mirror reversal, acting as if it were a rotation. Interestingly, however, the implicit system is sensitive to a particular coordinate system, treating mirror reversal and rotation differently.

coordinate system; implicit adaptation; mirror reversal; motor learning; sensorimotor adaptation

Forano, Marion, et al.Direct and indirect cues can enable dual adaptation, but through different learning processes”. J Neurophysiol 126.5 (2021): , 126, 5, 1490-1506. Web.Abstract

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.

dual-adaptation; explicit strategies; implicit adaptation; force field adaptation; motor learning

Campagnoli, Carlo, Fulvio Domini, and Jordan A. Taylor. “Taking aim at the perceptual side of motor learning: Exploring how explicit and implicit learning encode perceptual error information through depth vision”. J Neurophysiol 126.2 (2021): , 126, 2, 413-426. Web.Abstract

Motor learning in visuomotor adaptation tasks results from both explicit and implicit processes, each responding differently to an error signal. Although the motor output side of these processes has been extensively studied, the visual input side is relatively unknown. We investigated if and how depth perception affects the computation of error information by explicit and implicit motor learning. Two groups of participants made reaching movements to bring a virtual cursor to a target in the frontoparallel plane. The Delayed group was allowed to reaim and their feedback was delayed to emphasize explicit learning, whereas the camped group received task-irrelevant clamped cursor feedback and continued to aim straight at the target to emphasize implicit adapta- tion. Both groups played this game in a highly detailed virtual environment (depth condition), leveraging a cover task of playing darts in a virtual tavern, and in an empty environment (no-depth condition). The delayed group showed an increase in error sen- sitivity under depth relative to no-depth. In contrast, the clamped group adapted to the same degree under both conditions. The movement kinematics of the delayed participants also changed under the depth condition, consistent with the target appearing more distant, unlike the Clamped group. A comparison of the delayed behavioral data with a perceptual task from the same indi- viduals showed that the greater reaiming in the depth condition was consistent with an increase in the scaling of the error dis- tance and size. These findings suggest that explicit and implicit learning processes may rely on different sources of perceptual information.

Wilterson, Sarah A., and Jordan A. Taylor. “Implicit visuomotor adaptation remains limited after several days of training”. eNeuro (2021). Web.Abstract

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

Cesanek, Evan, Jordan A. Taylor, and Fulvio Domini. “Persistent grasping errors produce depth cue reweighting in perception”. Vision Research 178 (2021). Web.Abstract

When a grasped object is larger or smaller than expected, haptic feedback automatically recalibrates motor planning. Intriguingly, haptic feedback can also affect 3D shape perception through a process called depth cue reweighting. Although signatures of cue reweighting also appear in motor behavior, it is unclear whether this motor reweighting is the result of upstream perceptual reweighting, or a separate process. We propose that perceptual reweighting is directly related to motor control; in particular, that it is caused by persistent, sys- tematic movement errors that cannot be resolved by motor recalibration alone. In Experiment 1, we inversely varied texture and stereo cues to create a set of depth-metamer objects: when texture speci ed a deep object, stereo speci ed a shallow object, and vice versa, such that all objects appeared equally deep. The stereo-texture pairings that produced this perceptual metamerism were determined for each participant in a matching task (Pre- test). Next, participants repeatedly grasped these depth metamers, receiving haptic feedback that was positively correlated with one cue and negatively correlated with the other, resulting in persistent movement errors. Finally, participants repeated the perceptual matching task (Post-test). In the condition where haptic feedback reinforced the texture cue, perceptual changes were correlated with changes in grasping performance across individuals, demonstrating a link between perceptual reweighting and improved motor control. Experiment 2 showed that cue reweighting does not occur when movement errors are rapidly corrected by standard motor adaptation. These ndings suggest a mutual dependency between perception and action, with perception directly guiding action, and actions producing error signals that drive motor and perceptual learning.

Schween, Raphael, et al.Assessing explicit strategies in force field adaptation”. J Neurophysiol 123.4 (2020): , 123, 4, 1552-1565. Web.Abstract
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.
Cesanek, Evan, Jordan A. Taylor, and Fulvio Domini. “Sensorimotor adaptation and cue reweighing compensate for distorted 3D shape information, accounting for paradoxical perception-action dissociations”. J Neurophysiol 123.4 (2020): , 123, 4, 1407-1419. Web.Abstract
Visually guided movements can show surprising accuracy even when the perceived three-dimensional (3D) shape of the target is distorted. One explanation of this paradox is that an evolutionarily specialized “vision-for-action” system provides accurate shape estimates by relying selectively on stereo information and ignoring less reliable sources of shape information like texture and shading. However, the key support for this hypothesis has come from studies that analyze average behavior across many visuomotor interactions where available sensory feedback reinforces stereo information. The present study, which carefully accounts for the effects of feedback, shows that visuomotor interactions with slanted surfaces are actually planned using the same cue-combination function as slant perception and that apparent dissociations can arise due to two distinct supervised learning processes: sensorimotor adaptation and cue reweighting. In two experiments, we show that when a distorted slant cue biases perception (e.g., surfaces appear flattened by a fixed amount), sensorimotor adaptation rapidly adjusts the planned grip orientation to compensate for this constant error. However, when the distorted slant cue is unreliable, leading to variable errors across a set of objects (i.e., some slants are overestimated, others underestimated), then relative cue weights are gradually adjusted to reduce the misleading effect of the unreliable cue, consistent with previous perceptual studies of cue reweighting. The speed and flexibility of these two forms of learning provide an alternative explanation of why perception and action are sometimes found to be dissociated in experiments where some 3D shape cues are consistent with sensory feedback while others are faulty.
Taylor, Jordan A, and Samuel D McDougle. “Visuomotor Adaptation Tasks as a Window into the Interplay between Explicit and Implicit Cognitive Processes”. Cognitive Neurosciences VI. MIT Press, 2020. 549-558. Print.
Schween, Raphael, et al.How different effectors and action effects modulate the formation of separate motor memories”. Scientific Reports 9 (2019): , 9, 17040. Web.Abstract
Humans can operate a variety of modern tools, which are often associated with diferent visuomotor transformations. Studies investigating this ability have shown that separate motor memories can be acquired implicitly when diferent sensorimotor transformations are associated with distinct (intended) postures or explicitly when abstract contextual cues are leveraged by aiming strategies. It still remains unclear how diferent transformations are remembered implicitly when postures are similar. We investigated whether features of planning to manipulate a visual tool, such as its visual identity or the environmental efect intended by its use (i.e. action efect) would enable implicit learning of opposing visuomotor rotations. Results show that neither contextual cue led to distinct implicit motor memories, but that cues only afected implicit adaptation indirectly through generalization around explicit strategies. In contrast, a control experiment where participants practiced opposing transformations with diferent hands did result in contextualized afterefects difering between hands across generalization targets. It appears that diferent (intended) body states are necessary for separate afterefects to emerge, suggesting that the role of sensory prediction error-based adaptation may be limited to the recalibration of a body model, whereas establishing separate tool models may proceed along a diferent route.
Wong, Aaron L, et al.Can patients with cerebellar disease switch learning mechanisms to reduce their adaptation deficits?”. Brain 142.3 (2019): , 142, 3, 662-673. Web.Abstract
Systematic perturbations in motor adaptation tasks are primarily countered by learning from sensory-prediction errors, with secondary contributions from other learning processes. Despite the availability of these additional processes, particularly the use of explicit re-aiming to counteract observed target errors, patients with cerebellar degeneration are surprisingly unable to compensate for their sensory-prediction error deficits by spontaneously switching to another learning mechanism. We hypothesized that if the nature of the task was changed-by allowing vision of the hand, which eliminates sensory-prediction errors-patients could be induced to preferentially adopt aiming strategies to solve visuomotor rotations. To test this, we first developed a novel visuomotor rotation paradigm that provides participants with vision of their hand in addition to the cursor, effectively setting the sensory-prediction error signal to zero. We demonstrated in younger healthy control subjects that this promotes a switch to strategic re-aiming based on target errors. We then showed that with vision of the hand, patients with cerebellar degeneration could also switch to an aiming strategy in response to visuomotor rotations, performing similarly to age-matched participants (older controls). Moreover, patients could retrieve their learned aiming solution after vision of the hand was removed (although they could not improve beyond what they retrieved), and retain it for at least 1 year. Both patients and older controls, however, exhibited impaired overall adaptation performance compared to younger healthy controls (age 18-33 years), likely due to age-related reductions in spatial and working memory. Patients also failed to generalize, i.e. they were unable to adopt analogous aiming strategies in response to novel rotations. Hence, there appears to be an inescapable obligatory dependence on sensory-prediction error-based learning-even when this system is impaired in patients with cerebellar disease. The persistence of sensory-prediction error-based learning effectively suppresses a switch to target error-based learning, which perhaps explains the unexpectedly poor performance by patients with cerebellar degeneration in visuomotor adaptation tasks.
McDougle, Samuel D, and Jordan A Taylor. “Dissociable cognitive strategies for sensorimotor learning”. Nat Commun 10.1 (2019): , 10, 1, 40. Web.Abstract
Computations underlying cognitive strategies in human motor learning are poorly understood. Here we investigate such strategies in a common sensorimotor transformation task. We show that strategies assume two forms, likely reflecting distinct working memory representations: discrete caching of stimulus-response contingencies, and time-consuming parametric computations. Reaction times and errors suggest that both strategies are employed during learning, and trade off based on task complexity. Experiments using pressured preparation time further support dissociable strategies: In response caching, time pressure elicits multi-modal distributions of movements; during parametric computations, time pressure elicits a shifting distribution of movements between visual targets and distal goals, consistent with analog re-computing of a movement plan. A generalization experiment reveals that discrete and parametric strategies produce, respectively, more localized or more global transfer effects. These results describe how qualitatively distinct cognitive representations are leveraged for motor learning and produce downstream consequences for behavioral flexibility.
Poh, Eugene, and Jordan A Taylor. “Generalization via superposition: combined effects of mixed reference frame representations for explicit and implicit learning in a visuomotor adaptation task”. J Neurophysiol 121.5 (2019): , 121, 5, 1953-1966. Web.Abstract
Studies on generalization of learned visuomotor perturbations have generally focused on whether learning is coded in extrinsic or intrinsic reference frames. This dichotomy, however, is challenged by recent findings showing that learning is represented in a mixed reference frame. Overlooked in this framework is how learning appears to consist of multiple processes, such as explicit reaiming and implicit motor adaptation. Therefore, the proposed mixed representation may simply reflect the superposition of explicit and implicit generalization functions, each represented in different reference frames. Here we characterized the individual generalization functions of explicit and implicit learning in relative isolation to determine whether their combination could predict the overall generalization function when both processes are in operation. We modified the form of feedback in a visuomotor rotation task in an attempt to isolate explicit and implicit learning and tested generalization across new limb postures to dissociate the extrinsic/intrinsic representations. We found that the amplitude of explicit generalization was reduced with postural change and was only marginally shifted, resembling an extrinsic representation. In contrast, implicit generalization maintained its amplitude but was significantly shifted, resembling a mixed representation. A linear combination of individual explicit and implicit generalization functions accounted for nearly 85% of the variance associated with the generalization function in a typical visuomotor rotation task, where both processes are in operation. This suggests that each form of learning results from a mixed representation with distinct extrinsic and intrinsic contributions and the combination of these features shapes the generalization pattern observed at novel limb postures. Generalization following learning in visuomotor adaptation tasks can reflect how the brain represents what it learns. In this study, we isolated explicit and implicit forms of learning and showed that they are derived from a mixed reference frame representation with distinct extrinsic and intrinsic contributions. Furthermore, we showed that the overall generalization pattern at novel workspaces is due to the superposition of independent generalization effects developed by explicit and implicit learning processes.
McDougle, Samuel D, et al.Neural Signatures of Prediction Errors in a Decision-Making Task Are Modulated by Action Execution Failures”. Curr Biol 29.10 (2019): , 29, 10, 1606-1613.e5. Web.Abstract
Decisions must be implemented through actions, and actions are prone to error. As such, when an expected outcome is not obtained, an individual should be sensitive to not only whether the choice itself was suboptimal but also whether the action required to indicate that choice was executed successfully. The intelligent assignment of credit to action execution versus action selection has clear ecological utility for the learner. To explore this, we used a modified version of a classic reinforcement learning task in which feedback indicated whether negative prediction errors were, or were not, associated with execution errors. Using fMRI, we asked if prediction error computations in the human striatum, a key substrate in reinforcement learning and decision making, are modulated when a failure in action execution results in the negative outcome. Participants were more tolerant of non-rewarded outcomes when these resulted from execution errors versus when execution was successful, but reward was withheld. Consistent with this behavior, a model-driven analysis of neural activity revealed an attenuation of the signal associated with negative reward prediction errors in the striatum following execution failures. These results converge with other lines of evidence suggesting that prediction errors in the mesostriatal dopamine system integrate high-level information during the evaluation of instantaneous reward outcomes.
Parvin, Darius E, et al.Credit Assignment in a Motor Decision Making Task Is Influenced by Agency and Not Sensory Prediction Errors”. J Neurosci 38.19 (2018): , 38, 19, 4521-4530. Web.Abstract
Failures to obtain reward can occur from errors in action selection or action execution. Recently, we observed marked differences in choice behavior when the failure to obtain a reward was attributed to errors in action execution compared with errors in action selection (McDougle et al., 2016). Specifically, participants appeared to solve this credit assignment problem by discounting outcomes in which the absence of reward was attributed to errors in action execution. Building on recent evidence indicating relatively direct communication between the cerebellum and basal ganglia, we hypothesized that cerebellar-dependent sensory prediction errors (SPEs), a signal indicating execution failure, could attenuate value updating within a basal ganglia-dependent reinforcement learning system. Here we compared the SPE hypothesis to an alternative, "top-down" hypothesis in which changes in choice behavior reflect participants' sense of agency. In two experiments with male and female human participants, we manipulated the strength of SPEs, along with the participants' sense of agency in the second experiment. The results showed that, whereas the strength of SPE had no effect on choice behavior, participants were much more likely to discount the absence of rewards under conditions in which they believed the reward outcome depended on their ability to produce accurate movements. These results provide strong evidence that SPEs do not directly influence reinforcement learning. Instead, a participant's sense of agency appears to play a significant role in modulating choice behavior when unexpected outcomes can arise from errors in action execution. When learning from the outcome of actions, the brain faces a credit assignment problem: Failures of reward can be attributed to poor choice selection or poor action execution. Here, we test a specific hypothesis that execution errors are implicitly signaled by cerebellar-based sensory prediction errors. We evaluate this hypothesis and compare it with a more "top-down" hypothesis in which the modulation of choice behavior from execution errors reflects participants' sense of agency. We find that sensory prediction errors have no significant effect on reinforcement learning. Instead, instructions influencing participants' belief of causal outcomes appear to be the main factor influencing their choice behavior.
Butcher, Peter A, and Jordan A Taylor. “Decomposition of a sensory prediction error signal for visuomotor adaptation”. J Exp Psychol Hum Percept Perform 44.2 (2018): , 44, 2, 176-194. Web.Abstract
To accomplish effective motor control, the brain contains an internal forward model that predicts the expected sensory consequence of a motor command. When this prediction is inaccurate, a sensory prediction error is produced which adapts the forward model to make more accurate predictions of future movements. Other types of errors, such as task performance errors or reward, play less of a role in adapting a forward model. This raises the following question: What unique information is conveyed by the sensory prediction error that results in forward model adaptation? sensory prediction errors typically contain both the magnitude and direction of the error, but it is unclear if both components are necessary for adaptation or a single component is sufficient. In this article, we address this by having participants learn to counter a visuomotor rotation, which induces an angular mismatch between movements of the hand and visual feedback. We manipulated the information content of the visual feedback, in the form of a line, which accurately represented only the magnitude (distance), direction, or both magnitude and direction, of the virtual cursor relative to the target. We demonstrate that sensorimotor adaptation does not occur, or is minimal, when feedback is limited to information about the magnitude of an error. In contrast, sensorimotor adaptation is present when feedback is limited only to the direction of an error or when it contains combined direction and magnitude information. This result stands in contrast to current computational models of cerebellar-based sensorimotor adaptation that use error magnitude to drive adaptation. (PsycINFO Database Record
Cesanek, Evan, et al.Does visuomotor adaptation contribute to illusion-resistant grasping?”. Psychon Bull Rev 25.2 (2018): , 25, 2, 827-845. Web.Abstract
Do illusory distortions of perceived object size influence how wide the hand is opened during a grasping movement? Many studies on this question have reported illusion-resistant grasping, but this finding has been contradicted by other studies showing that grasping movements and perceptual judgments are equally susceptible. One largely unexplored explanation for these contradictions is that illusion effects on grasping can be reduced with repeated movements. Using a visuomotor adaptation paradigm, we investigated whether an adaptation model could predict the time course of Ponzo illusion effects on grasping. Participants performed a series of trials in which they viewed a thin wooden target, manually reported an estimate of the target's length, then reached to grasp the target. Manual size estimates (MSEs) were clearly biased by the illusion, but maximum grip apertures (MGAs) of grasping movements were consistently accurate. Illusion-resistant MGAs were observed immediately upon presentation of the illusion, so there was no decrement in susceptibility for the adaptation model to explain. To determine whether online corrections based on visual feedback could have produced illusion-resistant MGAs, we performed an exploratory post hoc analysis of movement trajectories. Early portions of the illusion effect profile evolved as if they were biased by the illusion to the same magnitude as the perceptual responses (MSEs), but this bias was attenuated prior to the MGA. Overall, this preregistered study demonstrated that visuomotor adaptation of grasping is not the primary source of illusion resistance in closed-loop grasping.
Schween, Raphael, Jordan A Taylor, and Mathias Hegele. “Plan-based generalization shapes local implicit adaptation to opposing visuomotor transformations”. J Neurophysiol 120.6 (2018): , 120, 6, 2775-2787. Web.Abstract
The human ability to use different tools demonstrates our capability of forming and maintaining multiple, context-specific motor memories. Experimentally, this has been investigated in dual adaptation, where participants adjust their reaching movements to opposing visuomotor transformations. Adaptation in these paradigms occurs by distinct processes, such as strategies for each transformation or the implicit acquisition of distinct visuomotor mappings. Although distinct, transformation-dependent aftereffects have been interpreted as support for the latter, they could reflect adaptation of a single visuomotor map, which is locally adjusted in different regions of the workspace. Indeed, recent studies suggest that explicit aiming strategies direct where in the workspace implicit adaptation occurs, thus potentially serving as a cue to enable dual adaptation. Disentangling these possibilities is critical to understanding how humans acquire and maintain motor memories for different skills and tools. We therefore investigated generalization of explicit and implicit adaptation to untrained movement directions after participants practiced two opposing cursor rotations, which were associated with the visual display being presented in the left or right half of the screen. Whereas participants learned to compensate for opposing rotations by explicit strategies specific to this visual workspace cue, aftereffects were not cue sensitive. Instead, aftereffects displayed bimodal generalization patterns that appeared to reflect locally limited learning of both transformations. By varying target arrangements and instructions, we show that these patterns are consistent with implicit adaptation that generalizes locally around movement plans associated with opposing visuomotor transformations. Our findings show that strategies can shape implicit adaptation in a complex manner. NEW & NOTEWORTHY Visuomotor dual adaptation experiments have identified contextual cues that enable learning of separate visuomotor mappings, but the underlying representations of learning are unclear. We report that visual workspace separation as a contextual cue enables the compensation of opposing cursor rotations by a combination of explicit and implicit processes: Learners developed context-dependent explicit aiming strategies, whereas an implicit visuomotor map represented dual adaptation independent from arbitrary context cues by local adaptation around the explicit movement plan.
Hutter, Sarah A, and Jordan A Taylor. “Relative sensitivity of explicit reaiming and implicit motor adaptation”. J Neurophysiol 120.5 (2018): , 120, 5, 2640-2648. Web.Abstract
It has become increasingly clear that learning in visuomotor rotation tasks, which induce an angular mismatch between movements of the hand and visual feedback, largely results from the combined effort of two distinct processes: implicit motor adaptation and explicit reaiming. However, it remains unclear how these two processes work together to produce trial-by-trial learning. Previous work has found that implicit motor adaptation operates automatically, regardless of task relevance, and saturates for large errors. In contrast, little is known about the automaticity of explicit reaiming and its sensitivity to error magnitude. Here we sought to characterize the automaticity and sensitivity function of these two processes to determine how they work together to facilitate performance in a visuomotor rotation task. We found that implicit adaptation scales relative to the visual error but only for small perturbations-replicating prior work. In contrast, explicit reaiming scales linearly for all tested perturbation sizes. Furthermore, the consistency of the perturbation appears to diminish both implicit adaptation and explicit reaiming, but to different degrees. Whereas implicit adaptation always displayed a response to the error, explicit reaiming was only engaged when errors displayed a minimal degree of consistency. This comports with the idea that implicit adaptation is obligatory and less flexible, whereas explicit reaiming is volitional and flexible. NEW & NOTEWORTHY This paper provides the first psychometric sensitivity function for explicit reaiming. Additionally, we show that the sensitivities of both implicit adaptation and explicit reaiming are influenced by consistency of errors. The pattern of results across two experiments further supports the idea that implicit adaptation is largely inflexible, whereas explicit reaiming is flexible and can be suppressed when unnecessary.
Liew, Sook-Lei, et al.Variable Neural Contributions to Explicit and Implicit Learning During Visuomotor Adaptation”. Front Neurosci 12 (2018): , 12, 610. Web.Abstract
We routinely make fine motor adjustments to maintain optimal motor performance. These adaptations have been attributed to both implicit, error-based mechanisms, and explicit, strategy-based mechanisms. However, little is known about the neural basis of implicit vs. explicit learning. Here, we aimed to use anodal transcranial direct current stimulation (tDCS) to probe the relationship between different brain regions and learning mechanisms during a visuomotor adaptation task in humans. We hypothesized that anodal tDCS over the cerebellum (CB) should increase implicit learning while anodal tDCS over the dorsolateral prefrontal cortex (dlPFC), a region associated with higher-level cognition, should facilitate explicit learning. Using a horizontal visuomotor adaptation task that measures explicit/implicit contributions to learning (Taylor et al., 2014), we found that dlPFC stimulation significantly improved performance compared to the other groups, and weakly increased explicit learning. However, CB stimulation had no effects on either target error or implicit learning. Previous work showed variable CB stimulation effects only on a vertical visuomotor adaptation task (Jalali et al., 2017), so in Experiment 2, we conducted the same study using a vertical context to see if we could find effects of CB stimulation. We found only weak effects of CB stimulation on target error and implicit learning, and now the dlPFC effect did not replicate. To resolve this discrepancy, in Experiment 3, we examined the effect of context (vertical vs. horizontal) on implicit and explicit contributions and found that individuals performed significantly worse and used greater implicit learning in the vertical screen condition compared to the horizontal screen condition. Across all experiments, however, there was high inter-individual variability, with strong influences of a few individuals, suggesting that these effects are not consistent across individuals. Overall, this work provides preliminary support for the idea that different neural regions can be engaged to improve visuomotor adaptation, but shows that each region's effects are highly context-dependent and not clearly dissociable from one another. This holds implications especially in neurorehabilitation, where an intact neural region could be engaged to potentially compensate if another region is impaired. Future work should examine factors influencing interindividual variability during these processes.
Butcher, Peter A, et al.The cerebellum does more than sensory prediction error-based learning in sensorimotor adaptation tasks”. J Neurophysiol 118.3 (2017): , 118, 3, 1622-1636. Web.Abstract
Individuals with damage to the cerebellum perform poorly in sensorimotor adaptation paradigms. This deficit has been attributed to impairment in sensory prediction error-based updating of an internal forward model, a form of implicit learning. These individuals can, however, successfully counter a perturbation when instructed with an explicit aiming strategy. This successful use of an instructed aiming strategy presents a paradox: In adaptation tasks, why do individuals with cerebellar damage not come up with an aiming solution on their own to compensate for their implicit learning deficit? To explore this question, we employed a variant of a visuomotor rotation task in which, before executing a movement on each trial, the participants verbally reported their intended aiming location. Compared with healthy control participants, participants with spinocerebellar ataxia displayed impairments in both implicit learning and aiming. This was observed when the visuomotor rotation was introduced abruptly () or gradually (). This dual deficit does not appear to be related to the increased movement variance associated with ataxia: Healthy undergraduates showed little change in implicit learning or aiming when their movement feedback was artificially manipulated to produce similar levels of variability (). Taken together the results indicate that a consequence of cerebellar dysfunction is not only impaired sensory prediction error-based learning but also a difficulty in developing and/or maintaining an aiming solution in response to a visuomotor perturbation. We suggest that this dual deficit can be explained by the cerebellum forming part of a network that learns and maintains action-outcome associations across trials. Individuals with cerebellar pathology are impaired in sensorimotor adaptation. This deficit has been attributed to an impairment in error-based learning, specifically, from a deficit in using sensory prediction errors to update an internal model. Here we show that these individuals also have difficulty in discovering an aiming solution to overcome their adaptation deficit, suggesting a new role for the cerebellum in sensorimotor adaptation tasks.
Morehead, Ryan J, et al.Characteristics of Implicit Sensorimotor Adaptation Revealed by Task-irrelevant Clamped Feedback”. J Cogn Neurosci 29.6 (2017): , 29, 6, 1061-1074. Web.Abstract
Sensorimotor adaptation occurs when there is a discrepancy between the expected and actual sensory consequences of a movement. This learning can be precisely measured, but its source has been hard to pin down because standard adaptation tasks introduce two potential learning signals: task performance errors and sensory prediction errors. Here we employed a new method that induces sensory prediction errors without task performance errors. This method combines the use of clamped visual feedback that is angularly offset from the target and independent of the direction of motion, along with instructions to ignore this feedback while reaching to targets. Despite these instructions, participants unknowingly showed robust adaptation of their movements. This adaptation was similar to that observed with standard methods, showing sign dependence, local generalization, and cerebellar dependency. Surprisingly, adaptation rate and magnitude were invariant across a large range of offsets. Collectively, our results challenge current models of adaptation and demonstrate that behavior observed in many studies of adaptation reflect the composite effects of task performance and sensory prediction errors.
McDougle, Samuel D, Krista M Bond, and Jordan A Taylor. “Implications of plan-based generalization in sensorimotor adaptation”. J Neurophysiol 118.1 (2017): , 118, 1, 383-393. Web.Abstract
Generalization is a fundamental aspect of behavior, allowing for the transfer of knowledge from one context to another. The details of this transfer are thought to reveal how the brain represents what it learns. Generalization has been a central focus in studies of sensorimotor adaptation, and its pattern has been well characterized: Learning of new dynamic and kinematic transformations in one region of space tapers off in a Gaussian-like fashion to neighboring untrained regions, echoing tuned population codes in the brain. In contrast to common allusions to generalization in cognitive science, generalization in visually guided reaching is usually framed as a passive consequence of neural tuning functions rather than a cognitive feature of learning. While previous research has presumed that maximum generalization occurs at the instructed task goal or the actual movement direction, recent work suggests that maximum generalization may occur at the location of an explicitly accessible movement plan. Here we provide further support for plan-based generalization, formalize this theory in an updated model of adaptation, and test several unexpected implications of the model. First, we employ a generalization paradigm to parameterize the generalization function and ascertain its maximum point. We then apply the derived generalization function to our model and successfully simulate and fit the time course of implicit adaptation across three behavioral experiments. We find that dynamics predicted by plan-based generalization are borne out in the data, are contrary to what traditional models predict, and lead to surprising implications for the behavioral, computational, and neural characteristics of sensorimotor adaptation. The pattern of generalization is thought to reveal how the motor system represents learned actions. Recent work has made the intriguing suggestion that maximum generalization in sensorimotor adaptation tasks occurs at the location of the learned movement plan. Here we support this interpretation, develop a novel model of motor adaptation that incorporates plan-based generalization, and use the model to successfully predict surprising dynamics in the time course of adaptation across several conditions.
Stark-Inbar, Alit, et al.Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning”. J Neurophysiol 117.1 (2017): , 117, 1, 412-428. Web.Abstract
In standard taxonomies, motor skills are typically treated as representative of implicit or procedural memory. We examined two emblematic tasks of implicit motor learning, sensorimotor adaptation and sequence learning, asking whether individual differences in learning are correlated between these tasks, as well as how individual differences within each task are related to different performance variables. As a prerequisite, it was essential to establish the reliability of learning measures for each task. Participants were tested twice on a visuomotor adaptation task and on a sequence learning task, either the serial reaction time task or the alternating reaction time task. Learning was evident in all tasks at the group level and reliable at the individual level in visuomotor adaptation and the alternating reaction time task but not in the serial reaction time task. Performance variability was predictive of learning in both domains, yet the relationship was in the opposite direction for adaptation and sequence learning. For the former, faster learning was associated with lower variability, consistent with models of sensorimotor adaptation in which learning rates are sensitive to noise. For the latter, greater learning was associated with higher variability and slower reaction times, factors that may facilitate the spread of activation required to form predictive, sequential associations. Interestingly, learning measures of the different tasks were not correlated. Together, these results oppose a shared process for implicit learning in sensorimotor adaptation and sequence learning and provide insight into the factors that account for individual differences in learning within each task domain. NEW & NOTEWORTHY: We investigated individual differences in the ability to implicitly learn motor skills. As a prerequisite, we assessed whether individual differences were reliable across test sessions. We found that two commonly used tasks of implicit learning, visuomotor adaptation and the alternating serial reaction time task, exhibited good test-retest reliability in measures of learning and performance. However, the learning measures did not correlate between the two tasks, arguing against a shared process for implicit motor learning.
Bond, Krista M, and Jordan A Taylor. “Structural Learning in a Visuomotor Adaptation Task Is Explicitly Accessible”. eNeuro 44 (2017). Web.Abstract
Structural learning is a phenomenon characterized by faster learning in a new situation that shares features of previously experienced situations. One prominent example within the sensorimotor domain is that human participants are faster to counter a novel rotation following experience with a set of variable visuomotor rotations. This form of learning is thought to occur implicitly through the updating of an internal forward model, which predicts the sensory consequences of motor commands. However, recent work has shown that much of rotation learning occurs through an explicitly accessible process, such as movement re-aiming. We sought to determine if structural learning in a visuomotor rotation task is purely implicit (e.g., driven by an internal model) or explicitly accessible (i.e., re-aiming). We found that participants exhibited structural learning: following training with a variable set of rotations, they more quickly learned a novel rotation. This benefit was entirely conferred by the explicit re-aiming of movements. Implicit learning offered little to no contribution. Next, we investigated the specificity of this learning benefit by exposing participants to a novel perturbation drawn from a statistical structure either congruent or incongruent with their prior experience. We found that participants who experienced congruent training and test phase structure (i.e., rotations to rotation) learned more quickly than participants exposed to incongruent training and test phase structure (i.e., gains to rotation) and a control group. These results suggest that structural learning in a visuomotor rotation task is specific to previously experienced statistical structure and expressed via explicit re-aiming of movements.
McDougle, Samuel D, et al.Credit assignment in movement-dependent reinforcement learning”. Proc Natl Acad Sci U S A 113.24 (2016): , 113, 24, 6797-802. Web.Abstract
When a person fails to obtain an expected reward from an object in the environment, they face a credit assignment problem: Did the absence of reward reflect an extrinsic property of the environment or an intrinsic error in motor execution? To explore this problem, we modified a popular decision-making task used in studies of reinforcement learning, the two-armed bandit task. We compared a version in which choices were indicated by key presses, the standard response in such tasks, to a version in which the choices were indicated by reaching movements, which affords execution failures. In the key press condition, participants exhibited a strong risk aversion bias; strikingly, this bias reversed in the reaching condition. This result can be explained by a reinforcement model wherein movement errors influence decision-making, either by gating reward prediction errors or by modifying an implicit representation of motor competence. Two further experiments support the gating hypothesis. First, we used a condition in which we provided visual cues indicative of movement errors but informed the participants that trial outcomes were independent of their actual movements. The main result was replicated, indicating that the gating process is independent of participants' explicit sense of control. Second, individuals with cerebellar degeneration failed to modulate their behavior between the key press and reach conditions, providing converging evidence of an implicit influence of movement error signals on reinforcement learning. These results provide a mechanistically tractable solution to the credit assignment problem.
Brudner, Samuel N, et al.Delayed feedback during sensorimotor learning selectively disrupts adaptation but not strategy use”. J Neurophysiol 115.3 (2016): , 115, 3, 1499-511. Web.Abstract
In sensorimotor adaptation tasks, feedback delays can cause significant reductions in the rate of learning. This constraint is puzzling given that many skilled behaviors have inherently long delays (e.g., hitting a golf ball). One difference in these task domains is that adaptation is primarily driven by error-based feedback, whereas skilled performance may also rely to a large extent on outcome-based feedback. This difference suggests that error- and outcome-based feedback may engage different learning processes, and these processes may be associated with different temporal constraints. We tested this hypothesis in a visuomotor adaptation task. Error feedback was indicated by the terminal position of a cursor, while outcome feedback was indicated by points. In separate groups of participants, the two feedback signals were presented immediately at the end of the movement, after a delay, or with just the error feedback delayed. Participants learned to counter the rotation in a similar manner regardless of feedback delay. However, the aftereffect, an indicator of implicit motor adaptation, was attenuated with delayed error feedback, consistent with the hypothesis that a different learning process supports performance under delay. We tested this by employing a task that dissociates the contribution of explicit strategies and implicit adaptation. We find that explicit aiming strategies contribute to the majority of the learning curve, regardless of delay; however, implicit learning, measured over the course of learning and by aftereffects, was significantly attenuated with delayed error-based feedback. These experiments offer new insight into the temporal constraints associated with different motor learning processes.
Poh, Eugene, Timothy J Carroll, and Jordan A Taylor. “Effect of coordinate frame compatibility on the transfer of implicit and explicit learning across limbs”. J Neurophysiol 116.3 (2016): , 116, 3, 1239-49. Web.Abstract
Insights into the neural representation of motor learning can be obtained by investigating how learning transfers to novel task conditions. We recently demonstrated that visuomotor rotation learning transferred strongly between left and right limbs when the task was performed in a sagittal workspace, which afforded a consistent remapping for the two limbs in both extrinsic and joint-based coordinates. In contrast, transfer was absent when performed in horizontal workspace, where the extrinsically defined perturbation required conflicting joint-based remapping for the left and right limbs. Because visuomotor learning is thought to be supported by both implicit and explicit forms of learning, however, it is unclear to what extent these distinct forms of learning contribute to interlimb transfer. In this study, we assessed the degree to which interlimb transfer, following visuomotor rotation training, reflects explicit vs. implicit learning by obtaining verbal reports of participants' aiming direction before each movement. We also determined the extent to which these distinct components of learning are constrained by the compatibility of coordinate systems by comparing transfer between groups of participants who reached to targets arranged in the horizontal and sagittal planes. Both sagittal and horizontal conditions displayed complete transfer of explicit learning to the untrained limb. In contrast, transfer of implicit learning was incomplete, but the sagittal condition showed greater transfer than the horizontal condition. These findings suggest that explicit strategies developed with one limb can be fully implemented in the opposite limb, whereas implicit transfer depends on the degree to which new sensorimotor maps are spatially compatible for the two limbs.
Fan, Judith E, Nicholas B Turk-Browne, and Jordan A Taylor. “Error-driven learning in statistical summary perception”. J Exp Psychol Hum Percept Perform 42.2 (2016): , 42, 2, 266-80. Web.Abstract
We often interact with multiple objects at once, such as when balancing food and beverages on a dining tray. The success of these interactions relies upon representing not only individual objects, but also statistical summary features of the group (e.g., center-of-mass). Although previous research has established that humans can readily and accurately extract such statistical summary features, how this ability is acquired and refined through experience currently remains unaddressed. Here we ask if training and task feedback can improve summary perception. During training, participants practiced estimating the centroid (i.e., average location) of an array of objects on a touchscreen display. Before and after training, they completed a transfer test requiring perceptual discrimination of the centroid. Across 4 experiments, we manipulated the information in task feedback and how participants interacted with the objects during training. We found that vector error feedback, which conveys error both in terms of distance and direction, was the only form of feedback that improved perceptual discrimination of the centroid on the transfer test. Moreover, this form of feedback was effective only when coupled with reaching movements toward the visual objects. Taken together, these findings suggest that sensory-prediction error-signaling the mismatch between expected and actual consequences of an action-may play a previously unrecognized role in tuning perceptual representations. (PsycINFO Database Record
McDougle, Samuel D, Richard B Ivry, and Jordan A Taylor. “Taking Aim at the Cognitive Side of Learning in Sensorimotor Adaptation Tasks”. Trends Cogn Sci 20.7 (2016): , 20, 7, 535-544. Web.Abstract
Sensorimotor adaptation tasks have been used to characterize processes responsible for calibrating the mapping between desired outcomes and motor commands. Research has focused on how this form of error-based learning takes place in an implicit and automatic manner. However, recent work has revealed the operation of multiple learning processes, even in this simple form of learning. This review focuses on the contribution of cognitive strategies and heuristics to sensorimotor learning, and how these processes enable humans to rapidly explore and evaluate novel solutions to enable flexible, goal-oriented behavior. This new work points to limitations in current computational models, and how these must be updated to describe the conjoint impact of multiple processes in sensorimotor learning.
Day, Kevin A, et al.Visuomotor Learning Generalizes Around the Intended Movement”. eNeuro 32 (2016). Web.Abstract
Human motor learning is useful if it generalizes beyond the trained task. Here, we introduce a new idea about how human visuomotor learning generalizes. We show that learned reaching movements generalize around where a person intends to move (i.e., aiming direction) as opposed to where they actually move. We used a visual rotation paradigm that allowed us to disentangle whether generalization is centered on where people aim to move, where they actually move, or where visual feedback indicates they moved. Participants reached to a visual target with their arm occluded from view. The cursor feedback was rotated relative to the position of their unseen hand to induce learning. Participants verbally reported their aiming direction, reached, and then were shown the outcome. We periodically introduced single catch trials with no feedback to measure learning. Results showed that learning was maximal at the participants' aiming location, and not at the actual hand position or where the cursor was displayed. This demonstrates that visuomotor learning generalizes around where we intend to move rather than where we actually move, and thus introduces a new role for cognitive processes beyond simply reducing movement error.
McDougle, Samuel D, Krista M Bond, and Jordan A Taylor. “Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning”. J Neurosci 35.26 (2015): , 35, 26, 9568-79. Web.Abstract
A popular model of human sensorimotor learning suggests that a fast process and a slow process work in parallel to produce the canonical learning curve (Smith et al., 2006). Recent evidence supports the subdivision of sensorimotor learning into explicit and implicit processes that simultaneously subserve task performance (Taylor et al., 2014). We set out to test whether these two accounts of learning processes are homologous. Using a recently developed method to assay explicit and implicit learning directly in a sensorimotor task, along with a computational modeling analysis, we show that the fast process closely resembles explicit learning and the slow process approximates implicit learning. In addition, we provide evidence for a subdivision of the slow/implicit process into distinct manifestations of motor memory. We conclude that the two-state model of motor learning is a close approximation of sensorimotor learning, but it is unable to describe adequately the various implicit learning operations that forge the learning curve. Our results suggest that a wider net be cast in the search for the putative psychological mechanisms and neural substrates underlying the multiplicity of processes involved in motor learning.
Bond, Krista M, and Jordan A Taylor. “Flexible explicit but rigid implicit learning in a visuomotor adaptation task”. J Neurophysiol 113.10 (2015): , 113, 10, 3836-49. Web.Abstract
There is mounting evidence for the idea that performance in a visuomotor rotation task can be supported by both implicit and explicit forms of learning. The implicit component of learning has been well characterized in previous experiments and is thought to arise from the adaptation of an internal model driven by sensorimotor prediction errors. However, the role of explicit learning is less clear, and previous investigations aimed at characterizing the explicit component have relied on indirect measures such as dual-task manipulations, posttests, and descriptive computational models. To address this problem, we developed a new method for directly assaying explicit learning by having participants verbally report their intended aiming direction on each trial. While our previous research employing this method has demonstrated the possibility of measuring explicit learning over the course of training, it was only tested over a limited scope of manipulations common to visuomotor rotation tasks. In the present study, we sought to better characterize explicit and implicit learning over a wider range of task conditions. We tested how explicit and implicit learning change as a function of the specific visual landmarks used to probe explicit learning, the number of training targets, and the size of the rotation. We found that explicit learning was remarkably flexible, responding appropriately to task demands. In contrast, implicit learning was strikingly rigid, with each task condition producing a similar degree of implicit learning. These results suggest that explicit learning is a fundamental component of motor learning and has been overlooked or conflated in previous visuomotor tasks.
Taylor, Jordan A, and Richard B Ivry. “Cerebellar and prefrontal cortex contributions to adaptation, strategies, and reinforcement learning”. Prog Brain Res 210 (2014): , 210, 217-53. Web.Abstract
Traditionally, motor learning has been studied as an implicit learning process, one in which movement errors are used to improve performance in a continuous, gradual manner. The cerebellum figures prominently in this literature given well-established ideas about the role of this system in error-based learning and the production of automatized skills. Recent developments have brought into focus the relevance of multiple learning mechanisms for sensorimotor learning. These include processes involving repetition, reinforcement learning, and strategy utilization. We examine these developments, considering their implications for understanding cerebellar function and how this structure interacts with other neural systems to support motor learning. Converging lines of evidence from behavioral, computational, and neuropsychological studies suggest a fundamental distinction between processes that use error information to improve action execution or action selection. While the cerebellum is clearly linked to the former, its role in the latter remains an open question.
Taylor, Jordan A, John W Krakauer, and Richard B Ivry. “Explicit and implicit contributions to learning in a sensorimotor adaptation task”. J Neurosci 34.8 (2014): , 34, 8, 3023-32. Web.Abstract
Visuomotor adaptation has been thought to be an implicit process that results when a sensory-prediction error signal is used to update a forward model. A striking feature of human competence is the ability to receive verbal instructions and employ strategies to solve tasks; such explicit processes could be used during visuomotor adaptation. Here, we used a novel task design that allowed us to obtain continuous verbal reports of aiming direction while participants learned a visuomotor rotation. We had two main hypotheses: the contribution of explicit learning would be modulated by instruction and the contribution of implicit learning would be modulated by the form of error feedback. By directly assaying aiming direction, we could identify the time course of the explicit component and, via subtraction, isolate the implicit component of learning. There were marked differences in the time courses of explicit and implicit contributions to learning. Explicit learning, driven by target error, was achieved by initially large then smaller explorations of aiming direction biased toward the correct solution. In contrast, implicit learning, driven by a sensory-prediction error, was slow and monotonic. Continuous error feedback reduced the amplitude of explicit learning and increased the contribution of implicit learning. The presence of instruction slightly increased the rate of initial learning and only had a subtle effect on implicit learning. We conclude that visuomotor adaptation, even in the absence of instruction, results from the interplay between explicit learning driven by target error and implicit learning of a forward model driven by prediction error.
Taylor, Jordan A, and Richard B Ivry. “Context-dependent generalization”. Front Hum Neurosci 7 (2013): , 7, 171. Web.Abstract
The pattern of generalization following motor learning can provide a probe on the neural mechanisms underlying learning. For example, the breadth of generalization to untrained regions of space after visuomotor adaptation to targets in a restricted region of space has been attributed to the directional tuning properties of neurons in the motor system. Building on this idea, the effect of different types of perturbations on generalization (e.g., rotation vs. visual translation) have been attributed to the selection of differentially tuned populations. Overlooked in this discussion is consideration of how the context of the training environment may constrain generalization. Here, we explore the role of context by having participants learn a visuomotor rotation or a translational shift in two different contexts, one in which the array of targets were presented in a circular arrangement and the other in which they were presented in a rectilinear arrangement. The perturbation and environments were either consistent (e.g., rotation with circular arrangement) or inconsistent (e.g., rotation with rectilinear arrangement). The pattern of generalization across the workspace was much more dependent on the context of the environment than on the perturbation, with broad generalization for the rectilinear arrangement for both types of perturbations. Moreover, the generalization pattern for this context was evident, even when the perturbation was introduced in a gradual manner, precluding the use of an explicit strategy. We describe how current models of generalization might be modified to incorporate these results, building on the idea that context provides a strong bias for how the motor system infers the nature of the visuomotor perturbation and, in turn, how this information influences the pattern of generalization.
Taylor, Jordan A, Laura L Hieber, and Richard B Ivry. “Feedback-dependent generalization”. J Neurophysiol 109.1 (2013): , 109, 1, 202-15. Web.Abstract
Generalization provides a window into the representational changes that occur during motor learning. Neural network models have been integral in revealing how the neural representation constrains the extent of generalization. Specifically, two key features are thought to define the pattern of generalization. First, generalization is constrained by the properties of the underlying neural units; with directionally tuned units, the extent of generalization is limited by the width of the tuning functions. Second, error signals are used to update a sensorimotor map to align the desired and actual output, with a gradient-descent learning rule ensuring that the error produces changes in those units responsible for the error. In prior studies, task-specific effects in generalization have been attributed to differences in neural tuning functions. Here we ask whether differences in generalization functions may arise from task-specific error signals. We systematically varied visual error information in a visuomotor adaptation task and found that this manipulation led to qualitative differences in generalization. A neural network model suggests that these differences are the result of error feedback processing operating on a homogeneous and invariant set of tuning functions. Consistent with novel predictions derived from the model, increasing the number of training directions led to specific distortions of the generalization function. Taken together, the behavioral and modeling results offer a parsimonious account of generalization that is based on the utilization of feedback information to update a sensorimotor map with stable tuning functions.
Fan, Judith E, Nicholas B Turk-Browne, and Jordan A Taylor. “Feedback-driven tuning of statistical summary representations”. Vis cogn 21.6 (2013): , 21, 6, 685-689. Web. fanetal2013.pdf
Taylor, Jordan A, and Richard B Ivry. “The role of strategies in motor learning”. Ann N Y Acad Sci 1251 (2012): , 1251, 1-12. Web.Abstract
There has been renewed interest in the role of strategies in sensorimotor learning. The combination of new behavioral methods and computational methods has begun to unravel the interaction between processes related to strategic control and processes related to motor adaptation. These processes may operate on very different error signals. Strategy learning is sensitive to goal-based performance error. In contrast, adaptation is sensitive to prediction errors between the desired and actual consequences of a planned movement. The former guides what the desired movement should be, whereas the latter guides how to implement the desired movement. Whereas traditional approaches have favored serial models in which an initial strategy-based phase gives way to more automatized forms of control, it now seems that strategic and adaptive processes operate with considerable independence throughout learning, although the relative weight given the two processes will shift with changes in performance. As such, skill acquisition involves the synergistic engagement of strategic and adaptive processes.
Norris, Scott A, et al.Cerebellar inactivation impairs memory of learned prism gaze-reach calibrations”. J Neurophysiol 105.5 (2011): , 105, 5, 2248-59. Web.Abstract
Three monkeys performed a visually guided reach-touch task with and without laterally displacing prisms. The prisms offset the normally aligned gaze/reach and subsequent touch. Naive monkeys showed adaptation, such that on repeated prism trials the gaze-reach angle widened and touches hit nearer the target. On the first subsequent no-prism trial the monkeys exhibited an aftereffect, such that the widened gaze-reach angle persisted and touches missed the target in the direction opposite that of initial prism-induced error. After 20-30 days of training, monkeys showed long-term learning and storage of the prism gaze-reach calibration: they switched between prism and no-prism and touched the target on the first trials without adaptation or aftereffect. Injections of lidocaine into posterolateral cerebellar cortex or muscimol or lidocaine into dentate nucleus temporarily inactivated these structures. Immediately after injections into cortex or dentate, reaches were displaced in the direction of prism-displaced gaze, but no-prism reaches were relatively unimpaired. There was little or no adaptation on the day of injection. On days after injection, there was no adaptation and both prism and no-prism reaches were horizontally, and often vertically, displaced. A single permanent lesion (kainic acid) in the lateral dentate nucleus of one monkey immediately impaired only the learned prism gaze-reach calibration and in subsequent days disrupted both learning and performance. This effect persisted for the 18 days of observation, with little or no adaptation.
Prinzmetal, William, et al.Contingent capture and inhibition of return: a comparison of mechanisms”. Exp Brain Res 214.1 (2011): , 214, 1, 47-60. Web.Abstract
We investigated the cause(s) of two effects associated with involuntary attention in the spatial cueing task: contingent capture and inhibition of return (IOR). Previously, we found that there were two mechanisms of involuntary attention in this task: (1) a (serial) search mechanism that predicts a larger cueing effect in reaction time with more display locations and (2) a decision (threshold) mechanism that predicts a smaller cueing effect with more display locations (Prinzmetal et al. 2010). In the present study, contingent capture and IOR had completely different patterns of results when we manipulated the number of display locations and the presence of distractors. Contingent capture was best described by a search model, whereas the inhibition of return was best described by a decision model. Furthermore, we fit a linear ballistic accumulator model to the results and IOR was accounted for by a change of threshold, whereas the results from contingent capture experiments could not be fit with a change of threshold and were better fit by a search model.
Morehead, Ryan J, Peter A Butcher, and Jordan A Taylor. “Does fast learning depend on declarative mechanisms?”. J Neurosci 31.14 (2011): , 31, 14, 5184-5. Web. moreheadetal2011.pdf
Stoloff, Rebecca H, et al.Effect of reinforcement history on hand choice in an unconstrained reaching task”. Front Neurosci 5 (2011): , 5, 41. Web.Abstract
Choosing which hand to use for an action is one of the most frequent decisions people make in everyday behavior. We developed a simple reaching task in which we vary the lateral position of a target and the participant is free to reach to it with either the right or left hand. While people exhibit a strong preference to use the hand ipsilateral to the target, there is a region of uncertainty within which hand choice varies across trials. We manipulated the reinforcement rates for the two hands, either by increasing the likelihood that a reach with the non-dominant hand would successfully intersect the target or decreasing the likelihood that a reach with the dominant hand would be successful. While participants had minimal awareness of these manipulations, we observed an increase in the use of the non-dominant hand for targets presented in the region of uncertainty. We modeled the shift in hand use using a Q-learning model of reinforcement learning. The results provided a good fit of the data and indicate that the effects of increasing and decreasing the rate of positive reinforcement are additive. These experiments emphasize the role of decision processes for effector selection, and may point to a novel approach for physical rehabilitation based on intrinsic reinforcement.
Taylor, Jordan A, and Richard B Ivry. “Flexible cognitive strategies during motor learning”. PLoS Comput Biol 73 (2011): , 7, 3, e1001096. Web.Abstract
Visuomotor rotation tasks have proven to be a powerful tool to study adaptation of the motor system. While adaptation in such tasks is seemingly automatic and incremental, participants may gain knowledge of the perturbation and invoke a compensatory strategy. When provided with an explicit strategy to counteract a rotation, participants are initially very accurate, even without on-line feedback. Surprisingly, with further testing, the angle of their reaching movements drifts in the direction of the strategy, producing an increase in endpoint errors. This drift is attributed to the gradual adaptation of an internal model that operates independently from the strategy, even at the cost of task accuracy. Here we identify constraints that influence this process, allowing us to explore models of the interaction between strategic and implicit changes during visuomotor adaptation. When the adaptation phase was extended, participants eventually modified their strategy to offset the rise in endpoint errors. Moreover, when we removed visual markers that provided external landmarks to support a strategy, the degree of drift was sharply attenuated. These effects are accounted for by a setpoint state-space model in which a strategy is flexibly adjusted to offset performance errors arising from the implicit adaptation of an internal model. More generally, these results suggest that strategic processes may operate in many studies of visuomotor adaptation, with participants arriving at a synergy between a strategic plan and the effects of sensorimotor adaptation.
Taylor, Jordan A, Greg J Wojaczynski, and Richard B Ivry. “Trial-by-trial analysis of intermanual transfer during visuomotor adaptation”. J Neurophysiol 106.6 (2011): , 106, 6, 3157-72. Web.Abstract
Studies of intermanual transfer have been used to probe representations formed during skill acquisition. We employ a new method that provides a continuous assay of intermanual transfer, intermixing right- and left-hand trials while limiting visual feedback to right-hand movements. We manipulated the degree of awareness of the visuomotor rotation, introducing a 22.5° perturbation in either an abrupt single step or gradually in ∼1° increments every 10 trials. Intermanual transfer was observed with the direction of left-hand movements shifting in the opposite direction of the rotation over the course of training. The transfer on left-hand trials was less than that observed in the right hand. Moreover, the magnitude of transfer was larger in our mixed-limb design compared with the standard blocked design in which transfer is only probed at the end of training. Transfer was similar in the abrupt and gradual groups, suggesting that awareness of the perturbation has little effect on intermanual transfer. In a final experiment, participants were provided with a strategy to offset an abrupt rotation, a method that has been shown to increase error over the course of training due to the operation of sensorimotor adaptation. This deterioration was also observed on left-hand probe trials, providing further support that awareness has little effect on intermanual transfer. These results indicate that intermanual transfer is not dependent on the implementation of cognitively assisted strategies that participants might adopt when they become aware that the visuomotor mapping has been perturbed. Rather, the results indicate that the information available to processes involved in adaptation entails some degree of effector independence.
Taylor, Jordan A, Nola M Klemfuss, and Richard B Ivry. “An explicit strategy prevails when the cerebellum fails to compute movement errors”. Cerebellum 94 (2010): , 9, 4, 580-6. Web.Abstract
In sensorimotor adaptation, explicit cognitive strategies are thought to be unnecessary because the motor system implicitly corrects performance throughout training. This seemingly automatic process involves computing an error between the planned movement and actual feedback of the movement. When explicitly provided with an effective strategy to overcome an experimentally induced visual perturbation, people are immediately successful and regain good task performance. However, as training continues, their accuracy gets worse over time. This counterintuitive result has been attributed to the independence of implicit motor processes and explicit cognitive strategies. The cerebellum has been hypothesized to be critical for the computation of the motor error signals that are necessary for implicit adaptation. We explored this hypothesis by testing patients with cerebellar degeneration on a motor learning task that puts the explicit and implicit systems in conflict. Given this, we predicted that the patients would be better than controls in maintaining an effective strategy assuming strategic and adaptive processes are functionally and neurally independent. Consistent with this prediction, the patients were easily able to implement an explicit cognitive strategy and showed minimal interference from undesirable motor adaptation throughout training. These results further reveal the critical role of the cerebellum in an implicit adaptive process based on movement errors and suggest an asymmetrical interaction of implicit and explicit processes.
Reid, EK, et al.Is the parvocellular red nucleus involved in cerebellar motor learning?”. Curr Trends Neurol 3 (2009): , 3, 15-22. Print.Abstract
The anatomical connections of the parvocellular red nucleus (RNp) have led to the suggestion that it might participate along with the cerebellum in modifying old and developing new programs for the control of complex, compound, coordinated movements of multiple body parts. RNp projects to and excites the inferior olivary nuclear neurons, which send climbing fibers to excite neurons in contralateral cerebellar cortex and nuclei. RNp receives excitatory inputs from ipsilateral cerebral cortex (onto distal dendrites) and from contralateral cerebellar nuclei (onto proximal dendrites). We here further develop a hypothesis as to mechanism, and offer preliminary evidence from RNp inactivation studies in awake, trained macaques during modification of their gaze-reach calibration while wearing wedge prism spectacles.
Wang, Xun, et al.Kv11.1 channel subunit composition includes MinK and varies developmentally in mouse cardiac muscle”. Dev Dyn 237.9 (2008): , 237, 9, 2430-7. Web.Abstract
The Kv11.1 (also ERG1) K(+) channel underlies cardiac I(Kr), a current that contributes to repolarization in mammalian heart. In mice, I(Kr) current density decreases with development and studies suggest that changes in the structure and/or properties of the heteromultimeric I(Kr)/Kv11.1 channel are responsible. Here, using immunohistochemistry, we report that total Kv11.1 alpha subunit protein is more abundant in neonatal heart and is distributed throughout both adult and neonatal ventricles with greater abundance in epicardia. Immunoblots reveal that the alpha subunit alternative splice variant, Kv11.1a, is more abundant in adult heart while the Kv11.1b variant is more abundant in neonatal heart. Additionally, MinK channel subunit protein is shown to co-assemble with Kv11.1 protein and is more abundant in neonatal heart. In summary, Kv11.1/I(Kr) channel composition varies developmentally and the higher I(Kr) current density in neonatal heart is likely attributable to higher abundance of Kv11.1/I(Kr) channels, more specifically, the Kv11.1b splice variant.
Taylor, Jordan A, and Kurt A Thoroughman. “Motor adaptation scaled by the difficulty of a secondary cognitive task”. PLoS One 36 (2008): , 3, 6, e2485. Web.Abstract
BACKGROUND: Motor learning requires evaluating performance in previous movements and modifying future movements. The executive system, generally involved in planning and decision-making, could monitor and modify behavior in response to changes in task difficulty or performance. Here we aim to identify the quantitative cognitive contribution to responsive and adaptive control to identify possible overlap between cognitive and motor processes. METHODOLOGY/PRINCIPAL FINDINGS: We developed a dual-task experiment that varied the trial-by-trial difficulty of a secondary cognitive task while participants performed a motor adaptation task. Subjects performed a difficulty-graded semantic categorization task while making reaching movements that were occasionally subjected to force perturbations. We find that motor adaptation was specifically impaired on the most difficult to categorize trials. CONCLUSIONS/SIGNIFICANCE: We suggest that the degree of decision-level difficulty of a particular categorization differentially burdens the executive system and subsequently results in a proportional degradation of adaptation. Our results suggest a specific quantitative contribution of executive control in motor adaptation.
Taylor, Jordan A, and Kurt A Thoroughman. “Divided attention impairs human motor adaptation but not feedback control”. J Neurophysiol 98.1 (2007): , 98, 1, 317-26. Web.Abstract
When humans experience externally induced errors in a movement, the motor system's feedback control compensates for those errors within the movement. The motor system's predictive control then uses information about those errors to inform future movements. The role of attention in these two distinct motor processes is unclear. Previous experiments have revealed a role for attention in motor learning over the course of many movements; however, these experimental paradigms do not determine how attention influences within-movement feedback control versus across-movement adaptation. Here we develop a dual-task paradigm, consisting of movement and audio tasks, which can differentiate and expose attention's role in these two processes of motor control. Over the course of several days, subjects performed horizontal reaching movements, with and without the audio task; movements were occasionally subjected to transient force perturbations. On movements with a force perturbation, subjects compensated for the force-induced movement errors, and on movements immediately after the force perturbation subjects exhibited adaptation. On every movement trial, subjects performed a two-tone frequency-discrimination task. The temporal specificity of the frequency-discrimination task allowed us to divide attention within and across movements. We find that divided attention did not impair the within-movement feedback control of the arm, but did reduce subsequent movement adaptation. We suggest that the secondary task interfered with the encoding and transformation of errors into changes in predictive control.
Thoroughman, Kurt A, Michael S Fine, and Jordan A Taylor. “Trial-by-trial motor adaptation: a window into elemental neural computation”. Prog Brain Res 165 (2007): , 165, 373-82. Web.Abstract
How does the brain compute? To address this question, mathematical modelers, neurophysiologists, and psychophysicists have sought behaviors that provide evidence of specific neural computations. Human motor behavior consists of several such computations [Shadmehr, R., Wise, S.P. (2005). MIT Press: Cambridge, MA], such as the transformation of a sensory input to a motor output. The motor system is also capable of learning new transformations to produce novel outputs; humans have the remarkable ability to alter their motor output to adapt to changes in their own bodies and the environment [Wolpert, D.M., Ghahramani, Z. (2000). Nat. Neurosci., 3: 1212-1217]. These changes can be long term, through growth and changing body proportions, or short term, through changes in the external environment. Here we focus on trial-by-trial adaptation, the transformation of individually sensed movements into incremental updates of adaptive control. These investigations have the promise of revealing important basic principles of motor control and ultimately guiding a new understanding of the neuronal correlates of motor behaviors.
Thoroughman, Kurt A, and Jordan A Taylor. “Rapid reshaping of human motor generalization”. J Neurosci 25.39 (2005): , 25, 39, 8948-53. Web.Abstract
People routinely learn how to manipulate new tools or make new movements. This learning requires the transformation of sensed movement error into updates of predictive neural control. Here, we demonstrate that the richness of motor training determines not only what we learn but how we learn. Human subjects made reaching movements while holding a robotic arm whose perturbing forces changed directions at the same rate, twice as fast, or four times as fast as the direction of movement, therefore exposing subjects to environments of increasing complexity across movement space. Subjects learned all three environments and learned the low- and medium-complexity environments equally well. We found that subjects lessened their movement-by-movement adaptation and narrowed the spatial extent of generalization to match the environmental complexity. This result demonstrated that people can rapidly reshape the transformation of sense into motor prediction to best learn a new movement task. We then modeled this adaptation using a neural network and found that, to mimic human behavior, the modeled neuronal tuning of movement space needed to narrow and reduce gain with increased environmental complexity. Prominent theories of neural computation have hypothesized that neuronal tuning of space, which determines generalization, should remained fixed during learning so that a combination of neuronal outputs can underlie adaptation simply and flexibly. Here, we challenge those theories with evidence that the neuronal tuning of movement space changed within minutes of training.
Taylor, Jordan, et al.Optimization of ectopic gene expression in skeletal muscle through DNA transfer by electroporation”. BMC Biotechnol 4 (2004): , 4, 11. Web.Abstract
BACKGROUND: Electroporation (EP) is a widely used non-viral gene transfer method. We have attempted to develop an exact protocol to maximize DNA expression while minimizing tissue damage following EP of skeletal muscle in vivo. Specifically, we investigated the effects of varying injection techniques, electrode surface geometry, and plasmid mediums. RESULTS: We found that as the amount of damage increased in skeletal muscle in response to EP, the level of beta-galactosidase (beta-gal) expression drastically decreased and that there was no evidence of beta-gal expression in damaged fibers. Two specific types of electrodes yielded the greatest amount of expression. We also discovered that DNA uptake in skeletal muscle following intra-arterial injection of DNA was significantly enhanced by EP. Finally, we found that DMSO and LipoFECTAMINE, common enhancers of DNA electroporation in vitro, had no positive effect on DNA electroporation in vivo. CONCLUSIONS: When injecting DNA intramuscularly, a flat plate electrode without any plasmid enhancers is the best method to achieve high levels of gene expression.