scholarly journals Task Errors Do Not Induce Implicit Sensorimotor Learning

2020 ◽  
Author(s):  
Anushka Oza ◽  
Adarsh Kumar ◽  
Pratik K. Mutha
Keyword(s):  
Implicit Learning ◽  
Prediction Error ◽  
Cognitive Process ◽  
Target Location ◽  
Prediction Errors ◽  
Verbal Instruction ◽  
Reaching Task ◽  
Task Success ◽  
Task Goals ◽  
Sensory Prediction

ABSTRACTHumans implicitly adjust their movements when challenged with perturbations that induce sensory prediction errors. Recent work suggests that failure to accomplish task goals could function as a gain on this prediction-error-driven adaptation or could independently trigger additional implicit mechanisms to bring about greater net learning. We aimed to distinguish between these possibilities using a reaching task wherein prediction errors were fixed at zero, but task success was modulated via changes in target location and size. We first observed that task failure caused changes in hand angle that showed classic signatures of implicit learning. Surprisingly however, these adjustments were eliminated when participants were explicitly instructed to ignore task errors. These results fail to support the idea that task errors independently induce implicit learning, and instead endorse the view that they provide a distinct signal to an intentional cognitive process that is responsive to verbal instruction.

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 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.

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 Event-related potentials reflect prediction errors and pop-out during comprehension of degraded speech

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Leah Banellis ◽  
Rodika Sokoliuk ◽  
Conor J Wild ◽  
Howard Bowman ◽  
Damian Cruse
Keyword(s):  
Prediction Error ◽  
Event Related Potentials ◽  
Event Related Potential ◽  
Prediction Errors ◽  
Top Down ◽  
Degraded Speech ◽  
Related Potentials ◽  
Task Goals ◽  
Post Hoc

Abstract Comprehension of degraded speech requires higher-order expectations informed by prior knowledge. Accurate top-down expectations of incoming degraded speech cause a subjective semantic ‘pop-out’ or conscious breakthrough experience. Indeed, the same stimulus can be perceived as meaningless when no expectations are made in advance. We investigated the event-related potential (ERP) correlates of these top-down expectations, their error signals and the subjective pop-out experience in healthy participants. We manipulated expectations in a word-pair priming degraded (noise-vocoded) speech task and investigated the role of top-down expectation with a between-groups attention manipulation. Consistent with the role of expectations in comprehension, repetition priming significantly enhanced perceptual intelligibility of the noise-vocoded degraded targets for attentive participants. An early ERP was larger for mismatched (i.e. unexpected) targets than matched targets, indicative of an initial error signal not reliant on top-down expectations. Subsequently, a P3a-like ERP was larger to matched targets than mismatched targets only for attending participants—i.e. a pop-out effect—while a later ERP was larger for mismatched targets and did not significantly interact with attention. Rather than relying on complex post hoc interactions between prediction error and precision to explain this apredictive pattern, we consider our data to be consistent with prediction error minimization accounts for early stages of processing followed by Global Neuronal Workspace-like breakthrough and processing in service of task goals.

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.

scholarly journals Dopamine neuron ensembles signal the content of sensory prediction errors

2019 ◽  
Author(s):  
Thomas A. Stalnaker ◽  
James D. Howard ◽  
Yuji K. Takahashi ◽  
Samuel J. Gershman ◽  
Thorsten Kahnt ◽  
...  
Keyword(s):  
Neural Activity ◽  
Prediction Error ◽  
Sensory Information ◽  
Dopamine Neurons ◽  
Prediction Errors ◽  
Bold Response ◽  
Dopamine System ◽  
Sensory Event ◽  
Specific Teaching ◽  
Sensory Prediction

AbstractDopamine neurons respond to errors in predicting value-neutral sensory information. These data, combined with causal evidence that dopamine transients support sensory-based associative learning, suggest that the dopamine system signals a multidimensional prediction error. Yet such complexity is not evident in individual neuron or average neural activity. How then do downstream areas know what to learn in response to these signals? One possibility is that information about content is contained in the pattern of firing across many dopamine neurons. Consistent with this, here we show that the pattern of firing across a small group of dopamine neurons recorded in rats signals the identity of a mis-predicted sensory event. Further, this same information is reflected in the BOLD response elicited by sensory prediction errors in human midbrain. These data provide evidence that ensembles of dopamine neurons provide highly specific teaching signals, opening new possibilities for how this system might contribute to learning.

scholarly journals Rethinking dopamine as generalized prediction error

2017 ◽  
Author(s):  
Matthew P.H. Gardner ◽  
Geoffrey Schoenbaum ◽  
Samuel J. Gershman
Keyword(s):  
Reinforcement Learning ◽  
Prediction Error ◽  
Dopamine Neurons ◽  
Prediction Errors ◽  
Model Free ◽  
Reward Prediction ◽  
Midbrain Dopamine ◽  
Sensory Prediction ◽  
Lines Of Evidence ◽  
Midbrain Dopamine Neurons

AbstractMidbrain dopamine neurons are commonly thought to report a reward prediction error, as hypothesized by reinforcement learning theory. While this theory has been highly successful, several lines of evidence suggest that dopamine activity also encodes sensory prediction errors unrelated to reward. Here we develop a new theory of dopamine function that embraces a broader conceptualization of prediction errors. By signaling errors in both sensory and reward predictions, dopamine supports a form of reinforcement learning that lies between model-based and model-free algorithms. This account remains consistent with current canon regarding the correspondence between dopamine transients and reward prediction errors, while also accounting for new data suggesting a role for these signals in phenomena such as sensory preconditioning and identity unblocking, which ostensibly draw upon knowledge beyond reward predictions.

scholarly journals Altered Dynamics of Cortical Beta-Oscillations during Motor Learning in Cerebellar Ataxia

2020 ◽  
Author(s):  
Jana Klimpke ◽  
Dorothea Henkel ◽  
Hans-Jochen Heinze ◽  
Max-Philipp Stenner
Keyword(s):  
Motor Learning ◽  
Implicit Learning ◽  
Cerebellar Ataxia ◽  
Prediction Error ◽  
Cognitive Strategies ◽  
Strategy Use ◽  
Healthy Controls ◽  
Healthy Individuals ◽  
Beta Oscillations ◽  
Sensory Prediction

AbstractCerebellar ataxia is associated with an implicit motor learning dysfunction, specifically, a miscalibration of internal models relating motor commands to state changes of the body. Explicit cognitive strategies could compensate for deficits in implicit calibration. Surprisingly, however, patients with cerebellar ataxia use insufficient strategies compared to healthy controls. We report a candidate physiological phenomenon of disrupted strategy use in cerebellar ataxia, reflected in an interaction of implicit and explicit learning effects on cortical beta oscillations. We recorded electroencephalography in patients with cerebellar ataxia (n=18), age-matched healthy controls (n=19), and young, healthy individuals (n=34) during a visuomotor rotation paradigm in which an aiming strategy was either explicitly instructed, or had to be discovered through learning. In young, healthy individuals, learning a strategy, but not implicit learning from sensory prediction error alone, decreased the post-movement beta rebound. Disrupted learning from sensory prediction error in patients, on the other hand, unmasked effects of explicit and implicit control that are normally balanced. Specifically, the post-movement beta rebound increased during strategy use when implicit learning was disrupted, i.e., in patients, but not controls. We conclude that a network disturbance due to cerebellar degeneration surfaces in imbalanced cortical beta oscillations normally involved in strategy learning.

scholarly journals Rethinking dopamine as generalized prediction error

2018 ◽  
Vol 285 (1891) ◽  
pp. 20181645 ◽  
Author(s):  
Matthew P. H. Gardner ◽  
Geoffrey Schoenbaum ◽  
Samuel J. Gershman
Keyword(s):  
Reinforcement Learning ◽  
Prediction Error ◽  
Dopamine Neurons ◽  
Prediction Errors ◽  
Model Free ◽  
Reward Prediction ◽  
Midbrain Dopamine ◽  
Sensory Prediction ◽  
Lines Of Evidence ◽  
Midbrain Dopamine Neurons

Midbrain dopamine neurons are commonly thought to report a reward prediction error (RPE), as hypothesized by reinforcement learning (RL) theory. While this theory has been highly successful, several lines of evidence suggest that dopamine activity also encodes sensory prediction errors unrelated to reward. Here, we develop a new theory of dopamine function that embraces a broader conceptualization of prediction errors. By signalling errors in both sensory and reward predictions, dopamine supports a form of RL that lies between model-based and model-free algorithms. This account remains consistent with current canon regarding the correspondence between dopamine transients and RPEs, while also accounting for new data suggesting a role for these signals in phenomena such as sensory preconditioning and identity unblocking, which ostensibly draw upon knowledge beyond reward predictions.

scholarly journals Dopamine neuron ensembles signal the content of sensory prediction errors

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Thomas A Stalnaker ◽  
James D Howard ◽  
Yuji K Takahashi ◽  
Samuel J Gershman ◽  
Thorsten Kahnt ◽  
...  
Keyword(s):  
Associative Learning ◽  
Prediction Error ◽  
Sensory Information ◽  
Dopamine Neurons ◽  
Prediction Errors ◽  
Bold Response ◽  
Dopamine System ◽  
Sensory Event ◽  
Specific Teaching ◽  
Sensory Prediction

Dopamine neurons respond to errors in predicting value-neutral sensory information. These data, combined with causal evidence that dopamine transients support sensory-based associative learning, suggest that the dopamine system signals a multidimensional prediction error. Yet such complexity is not evident in the activity of individual neurons or population averages. How then do downstream areas know what to learn in response to these signals? One possibility is that information about content is contained in the pattern of firing across many dopamine neurons. Consistent with this, here we show that the pattern of firing across a small group of dopamine neurons recorded in rats signals the identity of a mis-predicted sensory event. Further, this same information is reflected in the BOLD response elicited by sensory prediction errors in human midbrain. These data provide evidence that ensembles of dopamine neurons provide highly specific teaching signals, opening new possibilities for how this system might contribute to learning.

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