scholarly journals The effect of visual uncertainty on implicit motor adaptation

2021 ◽  
Vol 125 (1) ◽  
pp. 12-22
Author(s):  
Jonathan S. Tsay ◽  
Guy Avraham ◽  
Hyosub E. Kim ◽  
Darius E. Parvin ◽  
Zixuan Wang ◽  
...  
Keyword(s):  
Motor Adaptation ◽  
Joint Effect ◽  
Sensorimotor Adaptation ◽  
Implicit Motor ◽  
Visuomotor Tasks ◽  
Feedback Method

Sensorimotor adaptation is influenced by both the size and variance of error information. In the present study, we varied visual uncertainty and error size in a factorial manner and evaluated their joint effect on adaptation, using a feedback method that avoids inherent limitations with standard visuomotor tasks. Uncertainty attenuated adaptation but only when the error was small. This striking interaction highlights a novel constraint for models of sensorimotor adaptation.

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.

Impaired Sensorimotor Adaption in Schizophrenia in Comparison to Age-Matched and Elderly Controls

2021 ◽  
pp. 1-14
Author(s):  
Claudia Cornelis ◽  
Livia J. De Picker ◽  
Violette Coppens ◽  
Anne Morsel ◽  
Maarten Timmers ◽  
...  
Keyword(s):  
Motor Adaptation ◽  
Strategy Use ◽  
Sensorimotor Adaptation ◽  
Healthy Controls ◽  
Reversal Task ◽  
Elderly Individuals ◽  
Gain Adaptation ◽  
Learning Tasks ◽  
Adaptation Task

<b><i>Background:</i></b> The “cognitive dysmetria hypothesis” of schizophrenia proposes a disrupted communication between the cerebellum and cerebral cortex, resulting in sensorimotor and cognitive symptoms. Sensorimotor adaptation relies strongly on the function of the cerebellum. <b><i>Objectives:</i></b> This study investigated whether sensorimotor adaptation is reduced in schizophrenia compared with age-matched and elderly healthy controls. <b><i>Methods:</i></b> Twenty-nine stably treated patients with schizophrenia, 30 age-matched, and 30 elderly controls were tested in three motor adaptation tasks in which visual movement feedback was unexpectedly altered. In the “rotation adaptation task” the perturbation consisted of a rotation (30° clockwise), in the “gain adaptation task” the extent of the movement feedback was reduced (by a factor of 0.7) and in the “vertical reversal task,” up- and downward pen movements were reversed by 180°. <b><i>Results:</i></b> Patients with schizophrenia adapted to the perturbations, but their movement times and errors were substantially larger than controls. Unexpectedly, the magnitude of adaptation was significantly smaller in schizophrenia than elderly participants. The impairment already occurred during the first adaptation trials, pointing to a decline in explicit strategy use. Additionally, post-adaptation aftereffects provided strong evidence for impaired implicit adaptation learning. Both negative and positive schizophrenia symptom severities were correlated with indices of the amount of adaptation and its aftereffects. <b><i>Conclusions:</i></b> Both explicit and implicit components of sensorimotor adaptation learning were reduced in patients with schizophrenia, adding to the evidence for a role of the cerebellum in the pathophysiology of schizophrenia. Elderly individuals outperformed schizophrenia patients in the adaptation learning tasks.

scholarly journals Relative sensitivity of explicit reaiming and implicit motor adaptation

2018 ◽  
Vol 120 (5) ◽  
pp. 2640-2648 ◽  
Author(s):  
Sarah A. Hutter ◽  
Jordan A. Taylor
Keyword(s):  
Motor Adaptation ◽  
Relative Sensitivity ◽  
Sensitivity Function ◽  
Prior Work ◽  
Visuomotor Rotation ◽  
Small Perturbations ◽  
Task Relevance ◽  
Error Magnitude ◽  
Implicit Motor ◽  
Visual Error

It has become increasingly clear that learning in visuomotor rotation tasks, which induce an angular mismatch between movements of the hand and visual feedback, largely results from the combined effort of two distinct processes: implicit motor adaptation and explicit reaiming. However, it remains unclear how these two processes work together to produce trial-by-trial learning. Previous work has found that implicit motor adaptation operates automatically, regardless of task relevance, and saturates for large errors. In contrast, little is known about the automaticity of explicit reaiming and its sensitivity to error magnitude. Here we sought to characterize the automaticity and sensitivity function of these two processes to determine how they work together to facilitate performance in a visuomotor rotation task. We found that implicit adaptation scales relative to the visual error but only for small perturbations—replicating prior work. In contrast, explicit reaiming scales linearly for all tested perturbation sizes. Furthermore, the consistency of the perturbation appears to diminish both implicit adaptation and explicit reaiming, but to different degrees. Whereas implicit adaptation always displayed a response to the error, explicit reaiming was only engaged when errors displayed a minimal degree of consistency. This comports with the idea that implicit adaptation is obligatory and less flexible, whereas explicit reaiming is volitional and flexible. NEW & NOTEWORTHY This paper provides the first psychometric sensitivity function for explicit reaiming. Additionally, we show that the sensitivities of both implicit adaptation and explicit reaiming are influenced by consistency of errors. The pattern of results across two experiments further supports the idea that implicit adaptation is largely inflexible, whereas explicit reaiming is flexible and can be suppressed when unnecessary.

scholarly journals Relative sensitivity of explicit re-aiming and implicit motor adaptation

2018 ◽  
Author(s):  
Sarah A. Hutter ◽  
Jordan A. Taylor
Keyword(s):  
Motor Adaptation ◽  
Relative Sensitivity ◽  
Sensitivity Function ◽  
Prior Work ◽  
Visuomotor Rotation ◽  
Small Perturbations ◽  
Error Magnitude ◽  
Implicit Motor ◽  
Task Relevancy ◽  
Visual Error

AbstractIt has become increasingly clear that learning in visuomotor rotation tasks, which induce an angular mismatch between movements of the hand and visual feedback, largely results from the combined effort of two distinct processes: implicit motor adaptation and explicit re-aiming. However, it remains unclear how these two processes work together to produce trial-by-trial learning. Previous work has found that implicit motor adaptation operates automatically, regardless of task relevancy, and saturates for large errors. In contrast, little is known about the automaticity of explicit re-aiming and its sensitivity to error magnitude. Here we sought to characterize the automaticity and sensitivity function of these two processes to determine how they work together to facilitate performance in a visuomotor rotation task. We found that implicit adaptation scales relative to the visual error, but only for small perturbations – replicating prior work. In contrast, explicit re-aiming scales linearly for all tested perturbation sizes. Furthermore, the consistency of the perturbation appears to diminish both implicit adaptation and explicit re-aiming, but to different degrees. Whereas implicit adaptation always displayed a response to the error, explicit re-aiming was only engaged when errors displayed a minimal degree of consistency. This comports with the idea that implicit adaptation is obligatory and less flexible, while explicit re-aiming is volitional and flexible.

scholarly journals Distinct Processing of Sensory Prediction Error and Task Error during Motor Learning

2021 ◽  
Author(s):  
Jonathan Tsay ◽  
Adrian Haith ◽  
Richard B Ivry ◽  
Hyosub E Kim
Keyword(s):  
Prediction Error ◽  
Sensory Feedback ◽  
Displacement Method ◽  
Visuomotor Learning ◽  
Primary Signal ◽  
Implicit Motor ◽  
Feedback Method ◽  
The Difference ◽  
Sensory Prediction ◽  
And Task

While sensory-prediction error (SPE), the difference between predicted and actual sensory feedback, is recognized as the primary signal that drives implicit motor recalibration, recent studies have shown that task error (TE), the difference between sensory feedback and the movement goal, also plays a modulatory role. To systematically examine how SPE and TE collectively shape implicit recalibration, we performed a series of visuomotor learning experiments, introducing perturbations that varied the size of TE using a popular target displacement method and the size of SPE using a clamped visual feedback method. In Experiments 1 & 2, we observed robust sign-dependent changes in hand angle in response to perturbations with both SPE and TE but failed to observe changes in hand angle in response to TE-only perturbations. Yet in Experiments 3 & 4, the magnitude of TE modulated implicit recalibration in the presence of a fixed SPE. Taken together, these results underscore that implicit recalibration is driven by both SPE and TE (Kim, Parvin, & Ivry, 2019), while specifying unappreciated interactions between these two error-based processes. First, TE only impacts implicit calibration when SPE is present. Second, transient changes occurring when the target is displaced to manipulate TE has an attenuating effect on implicit recalibration, perhaps due to attention being directed away from the sensory feedback.

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 Does somatosensory acuity influence the extent of internal model recalibration in young and older adults?

2020 ◽  
Author(s):  
Koenraad Vandevoorde ◽  
Jean-Jacques Orban de Xivry
Keyword(s):  
Older Adults ◽  
Sensory Integration ◽  
Prediction Error ◽  
Internal Model ◽  
Sensory Feedback ◽  
Motor Adaptation ◽  
Age Related ◽  
Somatosensory Information ◽  
Implicit Motor ◽  
Sensory Prediction

AbstractThe 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, automatic adjustment of movement, or internal model recalibration, remains intact and might even be increased with aging. Since somatosensory information appears to be required for internal model recalibration, it might well be that an age-related decline in somatosensory acuity is linked to the increase of internal model recalibration. One possible explanation for an increased internal model recalibration is that age-related somatosensory deficits could lead to altered sensory integration with an increased weighting of the visual sensory-prediction error. Another possibility is that reduced somatosensory acuity results in an increased reliance on predicted sensory feedback. Both these explanations led to our preregistered hypothesis: we expect a relation between the decline of somatosensation and the increased internal model recalibration with aging. However, we failed to support this hypothesis. Our results question the existence of reliability-based integration of visual and somatosensory signals during motor adaptation.New & NoteworthyIs somatosensory acuity linked to implicit motor adaptation? The latter is larger in old compared to younger people? In light of reliability-based sensory integration, we hypothesized that this larger implicit adaptation was linked to an age-related lower reliability of somatosensation. Over two experiments and 130 participants, we failed to find any evidence for this. We discuss alternative explanations for the increase in implicit adaptation with age and the validity of our somatosensory assessment.

Individual differences in proprioception predict the extent of implicit sensorimotor adaptation

2020 ◽  
Author(s):  
Jonathan S. Tsay ◽  
Hyosub E. Kim ◽  
Darius E. Parvin ◽  
Alissa R. Stover ◽  
Richard B. Ivry
Keyword(s):  
Individual Differences ◽  
Upper Bound ◽  
Critical Role ◽  
Motor Adaptation ◽  
Proprioceptive Feedback ◽  
Hand Position ◽  
Sensorimotor Adaptation ◽  
Proprioceptive Information ◽  
Visual Perturbation

ABSTRACTRecent studies have revealed an upper bound in motor adaptation, beyond which other learning systems may be recruited. The factors determining this upper bound are poorly understood. The multisensory integration hypothesis states that this limit arises from opposing responses to visual and proprioceptive feedback. As individuals adapt to a visual perturbation, they experience an increasing proprioceptive error in the opposite direction, and the upper bound is the point where these two error signals reach an equilibrium. Assuming that visual and proprioceptive feedback are weighted according to their variability, there should be a correlation between proprioceptive variability and the limits of adaptation. Alternatively, the proprioceptive realignment hypothesis states that the upper bound arises when the (biased) sensed hand position realigns with the target. When a visuo-proprioceptive discrepancy is introduced, the sensed hand position is biased towards the visual cursor and the adaptive system nullifies this discrepancy by driving the hand away from the target. This hypothesis predicts a correlation between the size of the proprioceptive shift and the upper bound of adaptation. We tested these two hypotheses by considering natural variation in proprioception and motor adaptation across individuals. We observed a modest, yet reliable correlation between the upper bound of adaptation with both proprioceptive measures (variability and shift). While these results do not favor one hypothesis over the other, they underscore the critical role of proprioception in sensorimotor adaptation, and moreover, motivate a novel perspective on how these proprioceptive constraints drive implicit changes in motor behavior.SIGNIFICANCE STATEMENTWhile the sensorimotor system uses sensory feedback to remain properly calibrated, this learning process is constrained, limited in the maximum degree of plasticity. The factors determining this limit remain elusive. Guided by two hypotheses concerning how visual and proprioceptive information are integrated, we show that individual differences in the upper bound of adaptation in response to a visual perturbation can be predicted by the bias and variability in proprioception. These results underscore the critical, but often neglected role of proprioception in human motor learning.

scholarly journals Motor Adaptation Impairment in Chronic Cannabis Users Assessed by a Visuomotor Rotation Task

2019 ◽  
Vol 8 (7) ◽  
pp. 1049 ◽  
Author(s):  
Ivan Herreros ◽  
Laia Miquel ◽  
Chrysanthi Blithikioti ◽  
Laura Nuño ◽  
Belen Rubio Ballester ◽  
...  
Keyword(s):  
Prolonged Exposure ◽  
Motor Adaptation ◽  
Brain Structures ◽  
Healthy Controls ◽  
Long Term Effects ◽  
Visuomotor Rotation ◽  
Important Player ◽  
The Central Nervous System ◽  
Implicit Motor ◽  
The Brain

Background—The cerebellum has been recently suggested as an important player in the addiction brain circuit. Cannabis is one of the most used drugs worldwide, and its long-term effects on the central nervous system are not fully understood. No valid clinical evaluations of cannabis impact on the brain are available today. The cerebellum is expected to be one of the brain structures that are highly affected by prolonged exposure to cannabis, due to its high density in endocannabinoid receptors. We aim to use a motor adaptation paradigm to indirectly assess cerebellar function in chronic cannabis users (CCUs). Methods—We used a visuomotor rotation (VMR) task that probes a putatively-cerebellar implicit motor adaptation process together with the learning and execution of an explicit aiming rule. We conducted a case-control study, recruiting 18 CCUs and 18 age-matched healthy controls. Our main measure was the angular aiming error. Results—Our results show that CCUs have impaired implicit motor adaptation, as they showed a smaller rate of adaptation compared with healthy controls (drift rate: 19.3 +/− 6.8° vs. 27.4 +/− 11.6°; t(26) = −2.1, p = 0.048, Cohen’s d = −0.8, 95% CI = (−1.7, −0.15)). Conclusions—We suggest that a visuomotor rotation task might be the first step towards developing a useful tool for the detection of alterations in implicit learning among cannabis users.

scholarly journals Savings in sensorimotor adaptation without an explicit strategy

2020 ◽  
Vol 123 (3) ◽  
pp. 1180-1192 ◽  
Author(s):  
Cong Yin ◽  
Kunlin Wei
Keyword(s):  
Motor Adaptation ◽  
Cognitive Strategy ◽  
Adaptation Strategy ◽  
Sensorimotor Adaptation ◽  
Supporting Evidence ◽  
Term Retention ◽  
Long Term Retention ◽  
Saving Effect ◽  
Implicit And Explicit

The hallmark of long-term retention of sensorimotor adaptation is a faster relearning when similar perturbations are encountered again. However, what processes underlie this saving effect is in debate. Though motor adaptation is traditionally viewed as a type of procedural learning, its savings has been recently shown to be solely based on a quick recall of explicit adaptation strategy. Here, we showed that adaptation to a novel error-invariant perturbation without an explicit strategy could enable subsequent savings. We further showed that adaptation to gradual perturbations could enable savings, which was supported by enhanced implicit learning. Our study provides supporting evidence that long-term retention of motor adaptation is possible without forming or recalling a cognitive strategy, and the interplay between implicit and explicit learning critically depends on the specifics of learning protocol and available sensory feedback. NEW & NOTEWORTHY Savings in motor learning sometimes refers to faster learning when one encounters the same perturbation again. Previous studies assert that forming a cognitive strategy for countering perturbations is necessary for savings. We used novel experimental techniques to prevent the formation of a cognitive strategy during initial adaptation and found that savings still existed during relearning. Our findings suggest that savings in sensorimotor adaptation do not exclusively depend on forming and recalling an explicit strategy.

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