Books by Jordan A Taylor
Papers by Jordan A Taylor
Visuomotor adaptation has been thought to be an implicit process that results when a sensory-pred... more 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.
Traditionally, motor learning has been studied as an implicit learning process, one in which move... more 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.
Human motor learning is useful if it generalizes beyond the trained task. Here, we introduce a ne... more 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.
Sensorimotor adaptation tasks have been used to characterize processes responsible for calibratin... more 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.
When a person fails to obtain an expected reward from an object in the environment, they face a c... more 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 tracta-ble solution to the credit assignment problem. decision-making | reinforcement learning | sensory prediction error | reward prediction error | cerebellum W hen a diner reaches across the table and knocks over her coffee, the absence of anticipated reward should be attributed to a failure of coordination rather than diminish her love of coffee. Although this attribution is intuitive, current models of decision-making lack a mechanistic explanation for this seemingly simple computation. We set out to ask if, and how, selection processes in decision-making incorporate information specific to action execution and thus solve the credit assignment problem that arises when an expected reward is not obtained because of a failure in motor execution. Humans are highly capable of tracking the value of stimuli, varying their behavior on the basis of reinforcement history (1, 2), and exhibiting sensitivity to intrinsic motor noise when reward outcomes depend on movement accuracy (3–5). In real-world behavior, the underlying cause of unrewarded events is often ambiguous: A lost point in tennis could occur because the player made a poor choice about where to hit the ball or failed to properly execute the stroke. However, in laboratory studies of reinforcement learning, the underlying cause of unrewarded events is typically unambiguous, either solely dependent on properties of the stimulus or on motor noise. Thus, it remains unclear how people assign credit to either extrinsic or intrinsic causes during reward learning. We hypothesized that, during reinforcement learning, sensorimotor error signals could indicate when negative outcomes should be attributed to failures of the motor system. To test this idea, we developed a task in which outcomes could be assigned to properties of the environment or intrinsic motor error. We find that the presence of signals associated with movement errors has a marked effect on choice behavior, and does so in a way consistent with the operation of an implicit learning mechanism that modulates credit assignment. This process appears to be impaired in individuals with cerebellar degeneration, consistent with a computational model in which movement errors modulate reinforcement learning. Results Participants performed a two-armed " bandit task " (ref. 1, Fig. 1A), seeking to maximize points that were later exchanged for money. For all participants, the outcome of each trial was predetermined by two functions: One function defined if a target yielded a reward for that trial (" hit " or " miss "), and the other specified the magnitude of reward on hit trials (Fig. 1B). The expected value was equivalent for the two targets on all trials; however, risk, defined in terms of hit probability, was not. Under such conditions, people tend to be risk-averse (2, 6). We manipulated three variables: The manner in which participants made their choices, the feedback on " miss trials, " and the instructions. In experiment 1, participants were assigned to one of three conditions (n = 20/group). In the Standard condition, choices were indicated by pressing one of two keys, the typical response method in bandit tasks (1, 2). Points were only earned on hit trials Significance Thorndike's Law of Effect states that when an action leads to a desirable outcome, that action is likely to be repeated. However , when an action is not rewarded, the brain must solve a credit assignment problem: Was the lack of reward attributable to a bad decision or poor action execution? In a series of experiments , we find that salient motor error signals modulate biases in a simple decision-making task. This effect is independent of the participant's sense of control, suggesting that the error information impacts behavior in an implicit and automatic manner. We describe computational models of reinforcement learning in which execution error signals influence , or gate, the updating of value representations, providing a novel solution to the credit assignment problem.
Poh E, Carroll TJ, Taylor JA. Effect of coordinate frame compatibility on the transfer of implici... more Poh E, Carroll TJ, Taylor JA. Effect of coordinate frame compatibility on the transfer of implicit and explicit learning across limbs..—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 partici-pants' 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. interlimb transfer; visuomotor learning; explicit learning; implicit learning NEW & NOTEWORTHY Visuomotor learning in one limb often confers benefits in performance with the other limb, a phenomenon known as interlimb transfer. In this study, we demonstrate for the first time that transfer of learning across limbs can be dissociated into explicit and implicit components and that the extent to which these distinct components of learning transfer to the opposite limb is constrained by the alignment of the learned compensation in joint-based and ex-trinsic coordinates.
Stark-Inbar A, Raza M, Taylor JA, Ivry RB. Individual differences in implicit motor learning: tas... more Stark-Inbar A, Raza M, Taylor JA, Ivry RB. Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning..—In standard taxono-mies, 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.
■ Sensorimotor adaptation occurs when there is a discrepancy between the expected and actual sens... more ■ 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. ■
—Generalization is a fundamental aspect of behavior , allowing for the transfer of knowledge from... more —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. NEW & NOTEWORTHY 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.
Bond KM, Taylor JA. Flexible explicit but rigid implicit learning in a visuomotor adaptation task... more Bond KM, Taylor JA. Flexible explicit but rigid implicit learning in a visuomotor adaptation task. 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. explicit learning; implicit learning; visuomotor rotation; motor adaptation ; motor learning
A popular model of human sensorimotor learning suggests that a fast process and a slow process wo... more 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.
We often interact with multiple objects at once, such as when balancing food and beverages on a d... more 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.
—In sensorimo-tor adaptation tasks, feedback delays can cause significant reductions in the rate ... more —In sensorimo-tor 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 .
The pattern of generalization following motor learning can provide a probe on the neural mechanis... more 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.
There has been renewed interest in the role of strategies in sensorimotor learning. The combinati... more 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.
Current trends in …, Jan 1, 2009
The anatomical connections of the parvocellular red nucleus (RNp) have led to the suggestion that... more 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.
Attention is seemingly required to learn a novel motor skill, however, as learning progresses the... more Attention is seemingly required to learn a novel motor skill, however, as learning progresses the motor task can be performed without attention. By using dual-task paradigms, several studies have found impairments in motor learning when attention is divided early in training (Nissen and Bullemer, 1987; Redding et al., 1992; Lang and Bastian, 2002). A recent experiment suggests that when attention is divided during a movement error, the incremental transformation of previous error into adaptation on the subsequent movement is impaired (Taylor and Thoroughman, 2007). While this study aimed to determine how attention fundamentally interacts with motor learning, the study focused only on the trialby-trial adaptation of unlearnable and unpredictable forces. Everyday motor learning develops motor memories and most motor learning studies focus on memory formation; therefore, we set out to determine how attention functionally contributes to the learning of new but repeatable and predictable forces.
Experimental brain …, Jan 1, 2011
We investigated the cause(s) of two effects associated with involuntary attention in the spatial ... more 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 ). 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.
Uploads
Books by Jordan A Taylor
Papers by Jordan A Taylor