scholarly journals A Synthesis of the Many Errors and Learning Processes of Visuomotor Adaptation

2021 ◽  
Author(s):  
J. Ryan Morehead ◽  
Jean-Jacques Orban de Xivry
Keyword(s):  
Task Performance ◽  
Visuomotor Adaptation ◽  
Learning Processes ◽  
Skill Learning ◽  
Sensorimotor Adaptation ◽  
Prediction Errors ◽  
Control Measurement ◽  
Performance Error ◽  
Nuanced Understanding ◽  
Sensory Prediction

Visuomotor adaptation has one of the oldest experimental histories in psychology and neuroscience, yet its precise nature has always been a topic of debate. Here we offer a survey and synthesis of recent work on visuomotor adaptation that we hope will prove illuminating for this ongoing dialogue. We discuss three types of error signals that drive learning in adaptation tasks: task performance error, sensory prediction-error, and a binary target hitting error. Each of these errors has been shown to drive distinct learning processes. Namely, both target hitting errors and putative sensory prediction-errors drive an implicit change in visuomotor maps, while task performance error drives learning of explicit strategy use and non-motor decision-making. Each of these learning processes contributes to the overall learning that takes place in visuomotor adaptation tasks, and although the learning processes and error signals are independent, they interact in a complex manner. We outline many task contexts where the operation of these processes is counter-intuitive and offer general guidelines for their control, measurement and interpretation. We believe this new framework unifies several disparate threads of research in sensorimotor adaptation that often seem in conflict. We conclude by explaining how this more nuanced understanding of errors and learning processes could lend itself to the analysis of other types of sensorimotor adaptation, of motor skill learning, of the neural processing underlying sensorimotor adaptation in humans, of animal models and of brain computer interfaces.

scholarly journals Practice induces a qualitative change in the memory representation for visuomotor learning

2019 ◽  
Vol 122 (3) ◽  
pp. 1050-1059 ◽  
Author(s):  
David M. Huberdeau ◽  
John W. Krakauer ◽  
Adrian M. Haith
Keyword(s):  
Qualitative Change ◽  
Visuomotor Adaptation ◽  
Skill Learning ◽  
Memory Representation ◽  
Prediction Errors ◽  
Visuomotor Rotation ◽  
Repeated Practice ◽  
Target Locations ◽  
Sensory Prediction ◽  
Automatic Action

Adaptation of our movements to changes in the environment is known to be supported by multiple learning processes that operate in parallel. One is an implicit recalibration process driven by sensory-prediction errors; the other process counters the perturbation through more deliberate compensation. Prior experience is known to enable adaptation to occur more rapidly, a phenomenon known as “savings,” but exactly how experience alters each underlying learning process remains unclear. We measured the relative contributions of implicit recalibration and deliberate compensation to savings across 2 days of practice adapting to a visuomotor rotation. The rate of implicit recalibration showed no improvement with repeated practice. Instead, practice led to deliberate compensation being expressed even when preparation time was very limited. This qualitative change is consistent with the proposal that practice establishes a cached association linking target locations to appropriate motor output, facilitating a transition from deliberate to automatic action selection. NEW & NOTEWORTHY Recent research has shown that savings for visuomotor adaptation is attributable to retrieval of intentional, strategic compensation. This does not seem consistent with the implicit nature of memory for motor skills and calls into question the validity of visuomotor adaptation of reaching movements as a model for motor skill learning. Our findings suggest a solution: that additional practice adapting to a visuomotor perturbation leads to the caching of the initially explicit strategy for countering it.

scholarly journals Characteristics of Implicit Sensorimotor Adaptation Revealed by Task-irrelevant Clamped Feedback

2017 ◽  
Vol 29 (6) ◽  
pp. 1061-1074 ◽  
Author(s):  
J. Ryan Morehead ◽  
Jordan A. Taylor ◽  
Darius E. Parvin ◽  
Richard B. Ivry
Keyword(s):  
Task Performance ◽  
Visual Feedback ◽  
Large Range ◽  
New Method ◽  
Sensorimotor Adaptation ◽  
Prediction Errors ◽  
Standard Methods ◽  
Performance Errors ◽  
Task Irrelevant ◽  
Sensory Prediction

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.

scholarly journals Can patients with cerebellar disease switch learning mechanisms to reduce their adaptation deficits?

Brain ◽  
2019 ◽  
Vol 142 (3) ◽  
pp. 662-673 ◽  
Author(s):  
Aaron L Wong ◽  
Cherie L Marvel ◽  
Jordan A Taylor ◽  
John W Krakauer
Keyword(s):  
Prediction Error ◽  
Poor Performance ◽  
Visuomotor Adaptation ◽  
Cerebellar Degeneration ◽  
Prediction Errors ◽  
Cerebellar Disease ◽  
Learning Mechanisms ◽  
Visuomotor Rotation ◽  
Age Related ◽  
Sensory Prediction

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.

scholarly journals Task errors contribute to implicit remapping in sensorimotor adaptation

2018 ◽  
Author(s):  
Li-Ann Leow ◽  
Welber Marinovic ◽  
Aymar de Rugy ◽  
Timothy J Carroll
Keyword(s):  
Sensory Feedback ◽  
Hand Position ◽  
Sensorimotor Adaptation ◽  
Prediction Errors ◽  
Reward Prediction ◽  
Strategic Processes ◽  
The Relationship ◽  
Sensory Prediction ◽  
Or Task

AbstractPerturbations of sensory feedback evoke sensory prediction errors (discrepancies between predicted and actual sensory outcomes of movements), and reward prediction errors (discrepancies between predicted rewards and actual rewards). Sensory prediction errors result in obligatory remapping of the relationship between motor commands and predicted sensory outcomes. The role of reward prediction errors in sensorimotor adaptation is less clear. When moving towards a target, we expect to obtain the reward of hitting the target, and so we experience a reward prediction error if the perturbation causes us to miss it. These discrepancies between desired task outcomes and actual task outcomes, or “task errors”, are thought to drive the use of strategic processes to restore success, although their role is not fully understood. Here, we investigated the role of task errors in sensorimotor adaptation: during target-reaching, we either removed task errors by moving the target mid-movement to align with cursor feedback of hand position, or enforced task error by moving the target away from the cursor feedback of hand position. Removing task errors not only reduced the rate and extent of adaptation during exposure to the perturbation, but also reduced the amount of post-adaptation implicit remapping. Hence, task errors contribute to implicit remapping resulting from sensory prediction errors. This suggests that the system which implicitly acquires new sensorimotor maps via exposure to sensory prediction errors is also sensitive to reward prediction errors.

scholarly journals The perils of learning to move while speaking: One-sided interference between speech and visuomotor adaptation

2019 ◽  
Author(s):  
Daniel Robert Lametti ◽  
Marcus Quek ◽  
Calum Prescott ◽  
John-Stuart Brittain ◽  
Kate E Watkins
Keyword(s):  
Learning Process ◽  
Visuomotor Adaptation ◽  
Learning Processes ◽  
Hand Movements ◽  
Sensorimotor Adaptation ◽  
Explicit Learning ◽  
Automatic Learning ◽  
Implicit Processes ◽  
Adaptive Processes ◽  
Speech Feedback

Our understanding of the adaptive processes that shape sensorimotor behaviour is largely derived from studying isolated movements. Studies of visuomotor adaptation, in which participants adapt cursor movements to rotations of the cursor’s screen position, have led to prominent theories of motor control. In response to changes in visual feedback of movements, explicit (cognitive) and implicit (automatic) learning processes adapt movements to counter errors. However, movements rarely occur in isolation. The extent to which explicit and implicit processes drive sensorimotor adaptation when multiple movements occur simultaneously, as in the real world, remains unclear. Here, we address this problem in the context of speech and hand movements. Participants spoke in-time with rapid, hand-driven cursor movements. Using real-time auditory alterations of speech feedback, and visual rotations of the cursor’s screen position, we induced sensorimotor adaptation in one or both movements simultaneously. Across three experiments (n = 184), we demonstrate that visuomotor adaptation is markedly impaired by simultaneous speech adaptation, and the impairment is specific to the explicit learning process. In contrast, visuomotor adaptation had no impact on speech adaptation. The results demonstrate that the explicit learning process in visuomotor adaptation is sensitive to movements in other motor domains. They suggest that speech adaptation may lack an explicit learning process.

scholarly journals Acoustic stimulation increases implicit adaptation in sensorimotor adaptation

2020 ◽  
Author(s):  
Li-Ann Leow ◽  
James R. Tresilian ◽  
Aya Uchida ◽  
Dirk Koester ◽  
Tamara Spingler ◽  
...  
Keyword(s):  
Motor Skills ◽  
Brain Stimulation ◽  
Acoustic Stimulation ◽  
Individual Variability ◽  
Healthy Adults ◽  
Sensorimotor Adaptation ◽  
Prediction Errors ◽  
Motor Tasks ◽  
Non Invasive ◽  
Sensory Prediction

AbstractSensorimotor adaptation is an important part of our ability to perform novel motor tasks (i.e., learning of motor skills). Efforts to improve adaptation in healthy and clinical patients using non-invasive brain stimulation methods have been hindered by interindividual and intra-individual variability in brain susceptibility to stimulation. Here, we explore unpredictable loud acoustic stimulation as an alternative method of modulating brain excitability to improve sensorimotor adaptation. In two experiments, participants moved a cursor towards targets, and adapted to a 30° rotation of cursor feedback, either with or without unpredictable acoustic stimulation. Acoustic stimulation improved initial adaptation to sensory prediction errors in Study 1, and improved overnight retention of adaptation in Study 2. Unpredictable loud acoustic stimulation might thus be a potent method of modulating sensorimotor adaptation in healthy adults.

scholarly journals Reduced transfer of visuomotor adaptation is associated with aberrant sense of agency in Schizophrenia

2018 ◽  
Author(s):  
Sonia Bansal ◽  
Karthik G Murthy ◽  
Justin Fitzgerald ◽  
Barbara L. Schwartz ◽  
Wilsaan M. Joiner
Keyword(s):  
Negative Symptoms ◽  
Motor Behavior ◽  
Visuomotor Adaptation ◽  
Sense Of Agency ◽  
Common Source ◽  
Prediction Errors ◽  
Movement Trajectories ◽  
Action Awareness ◽  
Before And After ◽  
Sensory Prediction

ABSTRACTOne deficit associated with schizophrenia (SZ) is the reduced ability to distinguish sensations resulting from self-caused actions from those due to external sources. This reduced sense of agency (SoA, awareness of ownership over self-generated actions) is hypothesized to result from a diminished utilization of internal monitoring signals of self-movement (i.e., efferent copy) which subsequently impairs forming and utilizing sensory prediction errors (differences between the predicted and actual sensory consequences resulting from movement). Here, we investigated the connections between clinical SZ symptoms and motor adaptation, a process that uses sensory prediction errors to update motor output. Schizophrenia patients (SZP, N=30) and non-psychiatric healthy control subjects (HC, N=31) adapted to altered movement visual feedback, and then applied the motor recalibration to untested contexts (i.e., the spatial generalization to untrained targets). Although adaptation was similar for SZP and controls, the extent of generalization was significantly less for SZP; movement trajectories made by patients to the furthest untrained target (135°) before and after adaptation were largely indistinguishable. Interestingly, deficits in the generalization were correlated to positive symptoms of psychosis (e.g., hallucinations), but not negative symptoms. Generalization was also associated with subjective measures of SoA across both SZP and HC, emphasizing the major role action awareness plays in motor behavior, and suggesting that tendencies to misattribute agency, even in HC, manifest in abnormal motor performance. We discuss the possible link of these findings to cerebellar circuit abnormalities that may be a common source for deficits in the utilization of sensory prediction errors and aberrant SoA.

scholarly journals Both fast and slow learning processes contribute to savings following sensorimotor adaptation

2019 ◽  
Vol 121 (4) ◽  
pp. 1575-1583 ◽  
Author(s):  
Susan K. Coltman ◽  
Joshua G. A. Cashaback ◽  
Paul L. Gribble
Keyword(s):  
Force Field ◽  
Motor Adaptation ◽  
Retention Rates ◽  
Sensorimotor Adaptation ◽  
Prediction Errors ◽  
Fast Process ◽  
Learning Rates ◽  
History Of ◽  
Underlying Mechanisms ◽  
Sensory Prediction

Recent work suggests that the rate of learning in sensorimotor adaptation is likely not fixed, but rather can change based on previous experience. One example is savings, a commonly observed phenomenon whereby the relearning of a motor skill is faster than the initial learning. Sensorimotor adaptation is thought to be driven by sensory prediction errors, which are the result of a mismatch between predicted and actual sensory consequences. It has been proposed that during motor adaptation the generation of sensory prediction errors engages two processes (fast and slow) that differ in learning and retention rates. We tested the idea that a history of errors would influence both the fast and slow processes during savings. Participants were asked to perform the same force field adaptation task twice in succession. We found that adaptation to the force field a second time led to increases in estimated learning rates for both fast and slow processes. While it has been proposed that savings is explained by an increase in learning rate for the fast process, here we observed that the slow process also contributes to savings. Our work suggests that fast and slow adaptation processes are both responsive to a history of error and both contribute to savings. NEW & NOTEWORTHY We studied the underlying mechanisms of savings during motor adaptation. Using a two-state model to represent fast and slow processes that contribute to motor adaptation, we found that a history of error modulates performance in both processes. While previous research has attributed savings to only changes in the fast process, we demonstrated that an increase in both processes is needed to account for the measured behavioral data.

scholarly journals Can patients with cerebellar disease switch learning mechanisms to reduce their adaptation deficits?

2018 ◽  
Author(s):  
Aaron L. Wong ◽  
Cherie L. Marvel ◽  
Jordan A. Taylor ◽  
John W. Krakauer
Keyword(s):  
Spinocerebellar Ataxia ◽  
Prediction Error ◽  
Visuomotor Adaptation ◽  
Cerebellar Degeneration ◽  
Prediction Errors ◽  
Healthy Controls ◽  
Learning Mechanisms ◽  
Visuomotor Rotation ◽  
Age Related ◽  
Sensory Prediction

ABSTRACTSystematic 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 controls that this promotes a switch to strategic re-aiming based on target errors. We then showed that with vision of the hand, patients with spinocerebellar ataxia 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, and retain it for at least one year. Both patients and older controls, however, exhibited impaired overall adaptation performance compared to younger healthy controls (age, 18-33), likely due to age-related reductions in spatial and working memory. Moreover, patients failed to generalize, i.e., they were unable to adopt analogous aiming strategies in response to novel rotations, nor could they further improve their performance without vision of the hand. 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 degeneration. 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 spinocerebellar ataxia in visuomotor adaptation tasks.

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