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 Task errors drive memories that improve sensorimotor adaptation

2019 ◽  
Author(s):  
Li-Ann Leow ◽  
Welber Marinovic ◽  
Aymar de Rugy ◽  
Timothy J Carroll
Keyword(s):  
Sensory Feedback ◽  
Target Location ◽  
Adaptive Behaviour ◽  
Hand Position ◽  
Sensorimotor Adaptation ◽  
Prediction Errors ◽  
Preparation Time ◽  
Position Feedback ◽  
History Of ◽  
Sensory Prediction

AbstractTraditional views on how humans adapt movements to perturbations of sensory feedback emphasize a fundamental role for automatic, implicit correction of sensory prediction errors. However, it is now clear that adaptive behaviour also involves deliberate, strategic movement corrections. Such strategic processes have recently been argued to underlie the latent retention of sensorimotor adaptation, evident in improved adaptation to previously encountered perturbations; a phenomenon termed “savings”. It remains unclear, however, whether savings results from prior experience of sensory prediction errors, task errors, or both. Here, we used perturbations of target locations and hand position feedback during reaching to dissociate the contributions of task and sensory prediction errors to latent sensorimotor memory. We show that prior learning to correct for task errors is required to improve adaptation to rotated hand position feedback, whereas a history of sensory prediction errors is neither sufficient nor obligatory for savings. A history of correcting for task errors, induced by experimentally perturbing the target location instead of perturbing sensory feedback of movement, improved adaptation to visuomotor perturbations that were never before encountered. Limiting movement preparation time further showed that this learning consists of two distinct components: 1) a strategic component that is flexible enough to facilitate corrective responses in the opposite direction, but that requires substantial preparation time, and 2) a set of inflexible, cached, stimulus-response associations between targets and reach directions, that can be expressed under time-pressure when similar task conditions are experienced. The results emphasise that adaptive responses to sensorimotor perturbations take multiple forms.

Does proprioceptive acuity influence the extent of implicit sensorimotor adaptation in young and older adults?

2021 ◽  
Author(s):  
Koenraad Vandevoorde ◽  
Jean-Jacques Orban de Xivry
Keyword(s):  
Older Adults ◽  
Sensory Integration ◽  
Prediction Error ◽  
Motor Adaptation ◽  
Sensorimotor Adaptation ◽  
Proprioceptive Information ◽  
Age Related ◽  
Sensory Prediction

The ability to adjust movements to changes in the environment declines with aging. This age-related decline is caused by the decline of explicit adjustments. However, implicit adaptation remains intact and might even be increased with aging. Since proprioceptive information has been linked to implicit adaptation, it might well be that an age-related decline in proprioceptive acuity might be linked to the performance of older adults in implicit adaptation tasks. Indeed, age-related proprioceptive deficits could lead to altered sensory integration with an increased weighting of the visual sensory-prediction error. Another possibility is that reduced proprioceptive acuity results in an increased reliance on predicted sensory consequences of the movement. Both these explanations led to our preregistered hypothesis: we expected a relation between the decline of proprioception and the amount of implicit adaptation across ages. However, we failed to support this hypothesis. Our results question the existence of reliability-based integration of visual and proprioceptive signals during motor adaptation.

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 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 Time course of changes in the long latency feedback response parallels the fast process of short term motor adaptation

2020 ◽  
Author(s):  
Susan K. Coltman ◽  
Paul L. Gribble
Keyword(s):  
Force Field ◽  
Time Course ◽  
Motor Adaptation ◽  
Feedback Controller ◽  
Feedback Systems ◽  
Fast Process ◽  
Early Stages ◽  
Long Latency ◽  
Stages Of Learning ◽  
Stretch Response

AbstractAdapting to novel dynamics involves modifying both feedforward and feedback control. We investigated whether the motor system alters feedback responses during adaptation to a novel force field in a manner similar to adjustments in feedforward control. We simultaneously tracked the time course of both feedforward and feedback systems via independent probes during a force field adaptation task. Participants (n=35) grasped the handle of a robotic manipulandum and performed reaches to a visual target while the hand and arm were occluded. We introduced an abrupt counter-clockwise velocity-dependent force field during a block of reaching trials. We measured movement kinematics and shoulder and elbow muscle activity with surface EMG electrodes. We tracked the feedback stretch response throughout the task. Using force channel trials we measured overall learning, which was later decomposed into a fast and slow process. We found that the long-latency feedback response (LLFR) was upregulated in the early stages of learning and was correlated with the fast component of feedforward adaptation. The change in feedback response was specific to the long-latency epoch (50-100 ms after muscle stretch) and was observed only in the triceps muscle, which was the muscle required to counter the force field during adaptation. The similarity in time course for the LLFR and the estimated time course of the fast process suggests both are supported by common neural circuits. While some propose that the fast process reflects an explicit strategy, we argue instead that it may be a proxy for the feedback controller.New & NoteworthyWe investigated whether changes in the feedback stretch response were related to the proposed fast and slow processes of motor adaptation. We found that the long latency component of the feedback stretch response was upregulated in the early stages of learning, and the time course was correlated with the fast process. While some propose that the fast process reflects an explicit strategy, we argue instead that it may be a proxy for the feedback controller.

scholarly journals The cerebellum does more than sensory-prediction-error-based learning in sensorimotor adaptation tasks

2017 ◽  
Author(s):  
Peter A. Butcher ◽  
Richard B. Ivry ◽  
Sheng-Han Kuo ◽  
David Rydz ◽  
John W. Krakauer ◽  
...  
Keyword(s):  
Implicit Learning ◽  
Prediction Error ◽  
Internal Model ◽  
Sensorimotor Adaptation ◽  
Prediction Errors ◽  
Cerebellar Dysfunction ◽  
Visuomotor Rotation ◽  
Cerebellar Damage ◽  
Internal Forward Model ◽  
Sensory Prediction

AbstractIndividuals 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 don’t individuals with cerebellar damage 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, prior to executing a movement on each trial, the participants verbally reported their intended aiming location. Compared to healthy controls, participants with spinocerebellar ataxia (SCA) displayed impairments in both implicit learning and aiming. This was observed when the visuomotor rotation was introduced abruptly (Exp. 1) or gradually (Exp. 2). 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 (Exp. 3). 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.New and noteworthyIndividuals 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.

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 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 The cerebellum does more than sensory prediction error-based learning in sensorimotor adaptation tasks

2017 ◽  
Vol 118 (3) ◽  
pp. 1622-1636 ◽  
Author(s):  
Peter A. Butcher ◽  
Richard B. Ivry ◽  
Sheng-Han Kuo ◽  
David Rydz ◽  
John W. Krakauer ◽  
...  
Keyword(s):  
Implicit Learning ◽  
Prediction Error ◽  
Sensorimotor Adaptation ◽  
Prediction Errors ◽  
Cerebellar Dysfunction ◽  
Visuomotor Rotation ◽  
Cerebellar Damage ◽  
Internal Forward Model ◽  
Healthy Control ◽  
Sensory Prediction

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 ( experiment 1) or gradually ( experiment 2). 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 ( experiment 3). 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. NEW & NOTEWORTHY 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.

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