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 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 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.

Cluster analysis and subgrouping to investigate inter-individual variability to non-invasive brain stimulation: a systematic review

2018 ◽  
Vol 29 (6) ◽  
pp. 675-697 ◽  
Author(s):  
Michael Pellegrini ◽  
Maryam Zoghi ◽  
Shapour Jaberzadeh
Keyword(s):  
Systematic Review ◽  
Cluster Analysis ◽  
Brain Stimulation ◽  
Individual Variability ◽  
Response Patterns ◽  
Contributing Factors ◽  
Cluster Analyses ◽  
Analysis Techniques ◽  
Non Invasive ◽  
Statistical Cluster

Abstract Cluster analysis and other subgrouping techniques have risen in popularity in recent years in non-invasive brain stimulation research in the attempt to investigate the issue of inter-individual variability – the issue of why some individuals respond, as traditionally expected, to non-invasive brain stimulation protocols and others do not. Cluster analysis and subgrouping techniques have been used to categorise individuals, based on their response patterns, as responder or non-responders. There is, however, a lack of consensus and consistency on the most appropriate technique to use. This systematic review aimed to provide a systematic summary of the cluster analysis and subgrouping techniques used to date and suggest recommendations moving forward. Twenty studies were included that utilised subgrouping techniques, while seven of these additionally utilised cluster analysis techniques. The results of this systematic review appear to indicate that statistical cluster analysis techniques are effective in identifying subgroups of individuals based on response patterns to non-invasive brain stimulation. This systematic review also reports a lack of consensus amongst researchers on the most effective subgrouping technique and the criteria used to determine whether an individual is categorised as a responder or a non-responder. This systematic review provides a step-by-step guide to carrying out statistical cluster analyses and subgrouping techniques to provide a framework for analysis when developing further insights into the contributing factors of inter-individual variability in response to non-invasive brain stimulation.

scholarly journals Mini-review: The Role of the Cerebellum in Visuomotor Adaptation

2021 ◽  
Author(s):  
Elinor Tzvi ◽  
Sebastian Loens ◽  
Opher Donchin
Keyword(s):  
Premotor Cortex ◽  
Motor Program ◽  
Visuomotor Adaptation ◽  
Prediction Errors ◽  
Visuomotor Rotation ◽  
Non Invasive ◽  
Behavioral Studies ◽  
Sensory Prediction ◽  
The Brain

AbstractThe incredible capability of the brain to quickly alter performance in response to ever-changing environment is rooted in the process of adaptation. The core aspect of adaptation is to fit an existing motor program to altered conditions. Adaptation to a visuomotor rotation or an external force has been well established as tools to study the mechanisms underlying sensorimotor adaptation. In this mini-review, we summarize recent findings from the field of visuomotor adaptation. We focus on the idea that the cerebellum plays a central role in the process of visuomotor adaptation and that interactions with cortical structures, in particular, the premotor cortex and the parietal cortex, may be crucial for this process. To this end, we cover a range of methodologies used in the literature that link cerebellar functions and visuomotor adaptation; behavioral studies in cerebellar lesion patients, neuroimaging and non-invasive stimulation approaches. The mini-review is organized as follows: first, we provide evidence that sensory prediction errors (SPE) in visuomotor adaptation rely on the cerebellum based on behavioral studies in cerebellar patients. Second, we summarize structural and functional imaging studies that provide insight into spatial localization as well as visuomotor adaptation dynamics in the cerebellum. Third, we discuss premotor — cerebellar interactions and how these may underlie visuomotor adaptation. And finally, we provide evidence from transcranial direct current and magnetic stimulation studies that link cerebellar activity, beyond correlational relationships, to visuomotor adaptation .

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 Non-Invasive Brain Stimulation: Augmenting the Training and Performance Potential in Esports Players

2020 ◽  
Vol 10 (7) ◽  
pp. 454
Author(s):  
Wei Zhuang ◽  
Keyi Yin ◽  
Yahua Zi ◽  
Yu Liu
Keyword(s):  
Motor Skills ◽  
Brain Stimulation ◽  
Cognitive Abilities ◽  
Ethical Issues ◽  
Fine Motor ◽  
Performance Potential ◽  
Non Invasive ◽  
Effective Training ◽  
And Performance ◽  
Technical Safety

During the last two decades, esports, a highly competitive sporting activity, has gained increasing popularity. Both performance and competition in esports require players to have fine motor skills and physical and cognitive abilities in controlling and manipulating digital activities in a virtual environment. While strategies for building and improving skills and abilities are crucial for successful gaming performance, few effective training approaches exist in the fast-growing area of competitive esports. In this paper, we describe a non-invasive brain stimulation (NIBS) approach and highlight the relevance and potential areas for research while being cognizant of various technical, safety, and ethical issues related to NIBS when applied to esports.

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.

Inter-individual Variability in Response to Non-invasive Brain Stimulation Paradigms

2014 ◽  
Vol 7 (3) ◽  
pp. 372-380 ◽  
Author(s):  
Virginia López-Alonso ◽  
Binith Cheeran ◽  
Dan Río-Rodríguez ◽  
Miguel Fernández-del-Olmo
Keyword(s):  
Brain Stimulation ◽  
Individual Variability ◽  
Non Invasive
Sign in / Sign up

Export Citation Format

Share Document