Visuomotor Rotation Research Articles

A systematic review of observational practice for adaptation of reaching movements

Observational practice is discussed as a substitute for physical practice for motor learning and adaptation. We systematically reviewed the literature on observational practice in reaching and aiming tasks. Our objectives were to identify (i) performance differences between observational and physical practice; (ii) factors that contribute to adaptation following observational practice; and (iii) the neural correlates of observational practice. We found 18 studies, all investigated adaptation of reaching in visuomotor rotations or force-field perturbations. Results of the studies showed that observational practice led to adaptation in both, visuomotor rotation and force-field paradigms (d = −2.16 as compared to no practice). However, direct effects were considerably smaller as compared to physical practice (d = 4.38) and aftereffects were absent, suggesting that observational practice informed inverse, but not forward modes. Contrarily, neurophysiological evidence in this review showed that observational and physical practice involved similar brain regions.

The P3 event-related potential increases when humans learn a strategy for motor adaptation.

Human motor learning involves cognitive strategies in addition to implicit adaptation. Differences in systems-level neurophysiology between strategy-based and implicit learning remain poorly understood. We asked how the P3 event-related potential, an electroencephalography signal known to increase during early motor learning, relates to strategy-based learning and implicit adaptation. We re-analysed data from two experiments, in which participants (n = 64) reached towards a visual target, with online visual feedback replacing vision of their moving hand. We induced learning by rotating the visual feedback. In the first experiment, feedback rotations were turned on during pairs of two consecutive trials, interspersed between non-rotated trials. In one condition, feedback was rotated relative to the actual movement, allowing participants to develop a re-aiming strategy on the second trial of each pair, while it was rotated relative to the target in the other condition, rendering re-aiming futile. P3 amplitude increased in the first rotated trial in both conditions, but this increase was more pronounced in the re-aiming condition. In the second experiment, a constant visuomotor rotation was turned on for many consecutive trials. We instructed one group beforehand how to re-aim successfully, while the other group had to develop a strategy by themselves. P3 amplitude increased during early adaptation only in the latter group. These findings collectively suggest that in the context of motor learning, the P3 ERP is associated with a need to develop, or adjust, a cognitive strategy.

Task-relevant visual feedback uncertainty attenuates visuomotor adaptation.

Motor adaptation is attenuated when sensory feedback about the movement is uncertain. Although this was initially shown for small visual errors, attenuation seems not to hold when visual errors are larger and the contributions of implicit adaptation are isolated with the error-clamp method, which makes visual feedback task-irrelevant. Here we ask whether adaptation to a similarly large perturbation is attenuated when task-relevant visual feedback is uncertain. In a first experiment, we tested participants on a 30° movement-contingent visuomotor rotation under both low (cursor) and high (cloud of moving dots) visual feedback uncertainty. In line with optimal integration, we found that the early increase in adaptation and final extent of adaptation were reduced with high feedback uncertainty. In a second experiment, we included several blocks of no-feedback trials during the perturbation block to quantify the contribution of implicit adaptation. Results showed that implicit adaptation was smaller with high compared to low feedback uncertainty throughout the perturbation block. The estimated contribution of explicit adaptation was overall small, particularly for high feedback uncertainty. Our results demonstrate an influence of task-relevant visual feedback, and the resulting target errors, on implicit adaptation. We show that our motor system is sensitive to the feedback it receives even for larger error sizes and accordingly adjusts its learning properties when our ability to achieve the task goal is affected.NEW & NOTEWORTHY Motor adaptation is linked to the estimation of our actions. Whereas uncertainty of task-irrelevant visual feedback appears not to influence implicit adaptation for errors beyond a certain size, here we tested whether this is still the case for task-relevant feedback. We show that implicit adaptation is attenuated when task-relevant visual feedback is uncertain, suggesting a dependency on the assessment of not just sensory prediction errors but also target errors.

Minimal impact of chronic proprioceptive loss on implicit sensorimotor adaptation and perceived movement outcome.

Implicit sensorimotor adaptation keeps our movements well calibrated amid changes in the body and environment. We have recently postulated that implicit adaptation is driven by a perceptual error: the difference between the desired and perceived movement outcome. According to this perceptual realignment model, implicit adaptation ceases when the perceived movement outcome-a multimodal percept determined by a prior belief conveying the intended action, the motor command, and feedback from proprioception and vision-is aligned with the desired movement outcome. Here, we examined the role of proprioception in implicit motor adaptation and perceived movement outcome by examining individuals who experience deafferentation (i.e., individuals with impaired proprioception and touch). We used a modified visuomotor rotation task designed to isolate implicit adaptation and probe perceived movement outcomes throughout the experiment. Surprisingly, both implicit adaptation and perceived movement outcome were minimally impacted by chronic deafferentation, posing a challenge to the perceptual realignment model of implicit adaptation.NEW & NOTEWORTHY We tested six individuals with chronic somatosensory deafferentation on a novel task that isolates implicit sensorimotor adaptation and probes perceived movement outcome. Strikingly, both implicit motor adaptation and perceptual movement outcome were not significantly impacted by chronic deafferentation, posing a challenge for theoretical models of adaptation that involve proprioception.

Structural Learning Benefits in a Visuomotor Adaptation Task Generalize to a Contralateral Effector

Structural learning is characterized by facilitated adaptation following training on a set of sensory perturbations all belonging to the same structure (e.g., ‘visuomotor rotations’). This generalization of learning is a core feature of the motor system and is often studied in the context of interlimb transfer. However, such transfer has only been demonstrated when participants learn to counter a specific perturbation in the sensory feedback of their movements; we determined whether structural learning in one limb generalized to the contralateral limb. We trained 13 participants to counter random visual feedback rotations between +/-90 degrees with the right hand and subsequently tested the left hand on a fixed rotation. The structural training group showed faster adaptation in the left hand in both feedforward and feedback components of reaching compared to 13 participants who trained with veridical reaching, with lower initial reaching error, and straighter, faster, and smoother movements than in the control group. The transfer was ephemeral – benefits were confined to roughly the first 20 trials. The results demonstrate that the motor system can extract invariant properties of seemingly random environments in one limb, and that this information can be accessed by the contralateral limb.

Imprecise perception of hand position during early motor adaptation.

Localizing one's body parts is important for movement control and motor learning. Recent studies have shown that the precision with which people localize their hand places constraints on motor adaptation. Although these studies have assumed that hand localization remains equally precise across learning, we show that precision decreases rapidly during early motor learning. In three experiments, healthy young participants (n = 92) repeatedly adapted to a 45° visuomotor rotation for a cycle of two to four reaches, followed by a cycle of two to four reaches with veridical feedback. Participants either used an aiming strategy that fully compensated for the rotation (experiment 1), or always aimed directly at the target, so that adaptation was implicit (experiment 2). We omitted visual feedback for the last reach of each cycle, after which participants localized their unseen hand. We observed an increase in the variability of angular localization errors when subjects used a strategy to counter the visuomotor rotation (experiment 1). This decrease in precision was less pronounced in the absence of reaiming (experiment 2), and when subjects knew that they would have to localize their hand on the upcoming trial, and could thus focus on hand position (experiment 3). We propose that strategic reaiming decreases the precision of perceived hand position, possibly due to attention to vision rather than proprioception. We discuss how these dynamics in precision during early motor learning could impact on motor control and shape the interplay between implicit and strategy-based motor adaptation.NEW & NOTEWORTHY Recent studies indicate that the precision with which people localize their hand limits implicit visuomotor learning. We found that localization precision is not static, but decreases early during learning. This decrease is pronounced when people apply a reaiming strategy to compensate for a visuomotor perturbation and is partly resistant to allocation of attention to the hand. We propose that these dynamics in position sense during learning may influence how implicit and strategy-based motor adaption interact.

Spatio-temporal modulation of cortical activity during motor deadaptation depends on the feedback of task-related error

Motor adaptations are responsible for recalibrating actions and facilitating the achievement of goals in a constantly changing environment. Once consolidated, the decay of motor adaptation is a process affected by available sensory information during deadaptation. However, the cortical response to task error feedback during the deadaptation phase has received little attention. Here, we explored changes in brain cortical responses due to feedback of task-related error during deadaptation. Twelve healthy volunteers were recruited for the study. Right hand movement and EEG were recorded during repetitive trials of a hand reaching movement. A visuomotor rotation of 30° was introduced to induce motor adaptation. Volunteers participated in two experimental sessions organized in baseline, adaptation, and deadaptation blocks. In the deadaptation block, the visuomotor rotation was removed, and visual feedback was only provided in one session. Performance was quantified using angle end-point error, averaged speed, and movement onset time. A non-parametric spatiotemporal cluster-level permutation test was used to analyze the EEG recordings. During deadaptation, participants experienced a greater error reduction when feedback of the cursor was provided. The EEG responses showed larger activity in the left centro-frontal parietal areas during the deadaptation block when participants received feedback, as opposed to when they did not receive feedback. Centrally distributed clusters were found for the adaptation and deadaptation blocks in the absence of visual feedback. The results suggest that visual feedback of the task-related error activates cortical areas related to performance monitoring, depending on the accessible sensory information.

A lateralized motor network in order to understand adaptation to visuomotor rotation

Objective. The functional asymmetry between the two brain hemispheres in language and spatial processing is well documented. However, a description of difference in control between the two hemispheres in motor function is not well established. Our primary objective in this study was to examine the distribution of control in the motor hierarchy and its variation across hemispheres. Approach. We developed a computation model termed the bilateral control network and implemented the same in a neural network framework to be used to replicate certain experimental results. The network consists of a simple arm model capable of making movements in 2D space and a motor hierarchy with separate elements coding target location, estimated position of arm, direction, and distance to be moved by the arm, and the motor command sent to the arm. The main assumption made here is the division of direction and distance coding between the two hemispheres with distance coded in the non-dominant and direction coded in the dominant hemisphere. Main results. With this assumption, the network was able to show main results observed in visuomotor adaptation studies. Importantly it showed decrease in error exhibited by the untrained arm while the other arm underwent training compared to the corresponding naïve arm’s performance—transfer of motor learning from trained to the untrained arm. It also showed how this varied depending on the performance variable used—with distance as the measure, the non-dominant arm showed transfer and with direction, dominant arm showed transfer. Significance. Our results indicate the possibility of shared control between the two hemispheres. If indeed found true, this result could have major significance in motor rehabilitation as treatment strategies will need to be designed in order to account for this and can no longer be confined to the arm contralateral to the affected hemisphere.

Distinct learning, retention, and generalization patterns in de novo learning versus motor adaptation

People correct for movement errors when acquiring new motor skills (de novo learning) or adapting well-known movements (motor adaptation). While de novo learning establishes new control policies, adaptation modifies existing ones, and previous work have distinguished behavioral and underlying brain mechanisms for each motor learning type. However, it is still unclear whether learning in each type interferes with the other. In study 1, we use a within-subjects design where participants train with both 30° visuomotor rotation and mirror reversal perturbations, to compare adaptation and de novo learning respectively. We find no perturbation order effects, and find no evidence for differences in learning rates and asymptotes for both perturbations. Explicit instructions also provide an advantage during early learning in both perturbations. However, mirror reversal learning shows larger inter-participant variability and slower movement initiation. Furthermore, we only observe reach aftereffects following rotation training. In study 2, we incorporate the mirror reversal in a browser-based task, to investigate under-studied de novo learning mechanisms like retention and generalization. Learning persists across three or more days, substantially transfers to the untrained hand, and to targets on both sides of the mirror axis. Our results extend insights for distinguishing motor skill acquisition from adapting well-known movements.

Prediction error in implicit adaptation during visually- and memory-guided reaching tasks

Human movements are adjusted by motor adaptation in order to maintain their accuracy. There are two systems in motor adaptation, referred to as explicit or implicit adaptation. It has been suggested that the implicit adaptation is based on the prediction error and has been used in a number of motor adaptation studies. This study aimed to examine the effect of visual memory on prediction error in implicit visuomotor adaptation by comparing visually- and memory-guided reaching tasks. The visually-guided task is thought to be implicit learning based on prediction error, whereas the memory-guided task requires more cognitive processes. We observed the adaptation to visuomotor rotation feedback that is gradually rotated. We found that the adaptation and retention rates were higher in the visually-guided task than in the memory-guided task. Furthermore, the delta-band power obtained by electroencephalography (EEG) in the visually-guided task was increased immediately following the visual feedback, which indicates that the prediction error was larger in the visually-guided task. Our results show that the visuomotor adaptation is enhanced in the visually-guided task because the prediction error, which contributes update of the internal model, was more reliable than in the memory-guided task. Therefore, we suggest that the processing of the prediction error is affected by the task-type, which in turn affects the rate of the visuomotor adaptation.

Large-scale citizen science reveals predictors of sensorimotor adaptation.

Sensorimotor adaptation is essential for keeping our movements well calibrated in response to changes in the body and environment. For over a century, researchers have studied sensorimotor adaptation in laboratory settings that typically involve small sample sizes. While this approach has proved useful for characterizing different learning processes, laboratory studies are not well suited for exploring the myriad of factors that may modulate human performance. Here, using a citizen science website, we collected over 2,000 sessions of data on a visuomotor rotation task. This unique dataset has allowed us to replicate, reconcile and challenge classic findings in the learning and memory literature, as well as discover unappreciated demographic constraints associated with implicit and explicit processes that support sensorimotor adaptation. More generally, this study exemplifies how a large-scale exploratory approach can complement traditional hypothesis-driven laboratory research in advancing sensorimotor neuroscience.

Visuomotor adaptation across the lifespan.

Being able to adapt our movements to changing circumstances allows people to maintain performance across a wide range of tasks throughout life, but it is unclear whether visuomotor learning abilities are fully developed in young children and, if so, whether they remain stable in the elderly. There is limited evidence of changes in motor adaptation ability throughout life, and the findings are inconsistent. Therefore, our goal was to compare visuomotor learning abilities throughout the lifespan. We used a shorter, gamified experimental task and collected data from participants in 5 age groups. Young children (M = 7 years), older children (M = 11 years), young adults (M = 20 years), adults (M = 40 years) and older adults (M = 67 years) adapted to a 45° visuomotor rotation in a centre-out reaching task. Across measures of rate of adaptation, extent of learning, rate of unlearning, generalization, and savings, we found that all groups performed similarly. That is, at least for short bouts of gamified learning, children and older adults perform just as well as young adults.

A Case Study of the Validity of Web-based Visuomotor Rotation Experiments.

Web-based experiments are gaining momentum in motor learning research because of the desire to increase statistical power, decrease overhead for human participant experiments, and utilize a more demographically inclusive sample population. However, there is a vital need to understand the general feasibility and considerations necessary to shift tightly controlled human participant experiments to an online setting. We developed and deployed an online experimental platform modeled after established in-laboratory visuomotor rotation experiments to serve as a case study examining remotely collected data quality for an 80-min experiment. Current online motor learning experiments have thus far not exceeded 60 min, and current online crowdsourced studies have a median duration of approximately 10 min. Thus, the impact of a longer-duration, web-based experiment is unknown. We used our online platform to evaluate perturbation-driven motor adaptation behavior under three rotation sizes (±10°, ±35°, and ±65°) and two sensory uncertainty conditions. We hypothesized that our results would follow predictions by the relevance estimation hypothesis. Remote execution allowed us to double (n = 49) the typical participant population size from similar studies. Subsequently, we performed an in-depth examination of data quality by analyzing single-trial data quality, participant variability, and potential temporal effects across trials. Results replicated in-laboratory findings and provided insight on the effect of induced sensory uncertainty on the relevance estimation hypothesis. Our experiment also highlighted several specific challenges associated with online data collection including potentially smaller effect sizes, higher data variability, and lower recommended experiment duration thresholds. Overall, online paradigms present both opportunities and challenges for future motor learning research.

Facilitated adaptation via structural learning increases bimanual interference.

Bimanual coordination is an essential feature of the motor system, yet interactions between the limbs during independent control remain poorly understood. Interference between the two hands, or the assimilation of movement characteristics between the two effectors, can be induced by perturbing one arm (e.g., via visuomotor rotation) and then measuring the effects in the contralateral limb. In this study, we sought to further determine the role adaptation plays in bimanual interference using a structural learning paradigm to alter feedback regulation in reaching. We trained healthy participants to counter 60 unique random rotations in right hand visual feedback over 240 reaches. Following this, we assessed feedforward and feedback measures of interference in a bimanual reaching task where the right hand was exposed to a fixed visual feedback rotation while the left hand reached without visual feedback. We found that participants who had been exposed to the structural training task in the right hand showed increased left hand interference during the first 20 trials of the test task. Moreover, interference was greater in feedback, rather than feedforward control parameters. The results further suggest that structural learning enhances bimanual interference via sensory feedback upregulation.

Interaction between decision-making and motor learning when selecting reach targets in the presence of bias and noise.

Motor errors can have both bias and noise components. Bias can be compensated for by adaptation and, in tasks in which the magnitude of noise varies across the environment, noise can be reduced by identifying and then acting in less noisy regions of the environment. Here we examine how these two processes interact when participants reach under a combination of an externally imposed visuomotor bias and noise. In a center-out reaching task, participants experienced noise (zero-mean random visuomotor rotations) that was target-direction dependent with a standard deviation that increased linearly from a least-noisy direction. They also experienced a constant bias, a visuomotor rotation that varied (across groups) from 0 to 40 degrees. Critically, on each trial, participants could select one of three targets to reach to, thereby allowing them to potentially select targets close to the least-noisy direction. The group who experienced no bias (0 degrees) quickly learned to select targets close to the least-noisy direction. However, groups who experienced a bias often failed to identify the least-noisy direction, even though they did partially adapt to the bias. When noise was introduced after participants experienced and adapted to a 40 degrees bias (without noise) in all directions, they exhibited an improved ability to find the least-noisy direction. We developed two models-one for reach adaptation and one for target selection-that could explain participants' adaptation and target-selection behavior. Our data and simulations indicate that there is a trade-off between adaptation and selection. Specifically, because bias learning is local, participants can improve performance, through adaptation, by always selecting targets that are closest to a chosen direction. However, this comes at the expense of improving performance, through selection, by reaching toward targets in different directions to find the least-noisy direction.

Theoretical limits on the speed of learning inverse models explain the rate of adaptation in arm reaching tasks

An essential aspect of human motor learning is the formation of inverse models, which map desired actions to motor commands. Inverse models can be learned by adjusting parameters in neural circuits to minimize errors in the performance of motor tasks through gradient descent. However, the theory of gradient descent establishes limits on the learning speed. Specifically, the eigenvalues of the Hessian of the error surface around a minimum determine the maximum speed of learning in a task. Here, we use this theoretical framework to analyze the speed of learning in different inverse model learning architectures in a set of isometric arm-reaching tasks. We show theoretically that, in these tasks, the error surface and, thus the speed of learning, are determined by the shapes of the force manipulability ellipsoid of the arm and the distribution of targets in the task. In particular, rounder manipulability ellipsoids generate a rounder error surface, allowing for faster learning of the inverse model. Rounder target distributions have a similar effect. We tested these predictions experimentally in a quasi-isometric reaching task with a visuomotor transformation. The experimental results were consistent with our theoretical predictions. Furthermore, our analysis accounts for the speed of learning in previous experiments with incompatible and compatible virtual surgery tasks, and with visuomotor rotation tasks with different numbers of targets. By identifying aspects of a task that influence the speed of learning, our results provide theoretical principles for the design of motor tasks that allow for faster learning.

Neural representations for multi-context visuomotor adaptation and the impact of common representation on multi-task performance: a multivariate decoding approach.

The human brain's remarkable motor adaptability stems from the formation of context representations and the use of a common context representation (e.g., an invariant task structure across task contexts) derived from structural learning. However, direct evaluation of context representations and structural learning in sensorimotor tasks remains limited. This study aimed to rigorously distinguish neural representations of visual, movement, and context levels crucial for multi-context visuomotor adaptation and investigate the association between representation commonality across task contexts and adaptation performance using multivariate decoding analysis with fMRI data. Here, we focused on three distinct task contexts, two of which share a rotation structure (i.e., visuomotor rotation contexts with -90° and +90° rotations, in which the mouse cursor's movement was rotated 90 degrees counterclockwise and clockwise relative to the hand-movement direction, respectively) and the remaining one does not (i.e., mirror-reversal context where the horizontal movement of the computer mouse was inverted). This study found that visual representations (i.e., visual direction) were decoded in the occipital area, while movement representations (i.e., hand-movement direction) were decoded across various visuomotor-related regions. These findings are consistent with prior research and the widely recognized roles of those areas. Task-context representations (i.e., either -90° rotation, +90° rotation, or mirror-reversal) were also distinguishable in various brain regions. Notably, these regions largely overlapped with those encoding visual and movement representations. This overlap suggests a potential intricate dependency of encoding visual and movement directions on the context information. Moreover, we discovered that higher task performance is associated with task-context representation commonality, as evidenced by negative correlations between task performance and task-context-decoding accuracy in various brain regions, potentially supporting structural learning. Importantly, despite limited similarities between tasks (e.g., rotation and mirror-reversal contexts), such association was still observed, suggesting an efficient mechanism in the brain that extracts commonalities from different task contexts (such as visuomotor rotations or mirror-reversal) at multiple structural levels, from high-level abstractions to lower-level details. In summary, while illuminating the intricate interplay between visuomotor processing and context information, our study highlights the efficiency of learning mechanisms, thereby paving the way for future exploration of the brain's versatile motor ability.

Motor adaptation does not differ when a perturbation is introduced abruptly or gradually.

People continuously adapt their movements to ever-changing circumstances, and particularly in skills training and rehabilitation, it is crucial that we understand how to optimize implicit adaptation in order for these processes to require as little conscious effort as possible. Although it is generally assumed that the way to do this is by introducing perturbations gradually, the literature is ambivalent on the effectiveness of this approach. Here, we tested whether there are differences in motor performance when adapting to an abrupt compared to a ramped visuomotor rotation. Using a within-subjects design, we tested this question under 3 different rotation sizes: 30-degrees, 45-degrees, and 60-degrees, as well as in 3 different populations: younger adults, older adults, and patients with mild cerebellar ataxia. We find no significant differences in either the behavioural outcomes, or model fits, between abrupt and gradual learning across any of the different conditions. Neither age, nor cerebellar ataxia had any significant effect on error-sensitivity either. These findings together indicate that error-sensitivity is not modulated by introducing a perturbation abruptly compared to gradually, and is also unaffected by age or mild cerebellar ataxia.

The effects of a single bout of moderate-intensity aerobic exercise on visuomotor adaptation and its savings

Performing exercise before or after motor skill learning is thought to have a positive impact on acquisition and retention of motor memories stored in our nervous system. It has been shown that performing 25 min of moderate-intensity aerobic exercise prior to visuomotor adaptation can enhance both visuomotor adaptation and its retention compared to 25 min of rest before the adaptation. To determine whether a single bout of aerobic exercise could actually facilitate the formation of a neural representation associated with a novel visuomotor condition, we examined aftereffects and savings associated with a visuomotor adaptation task following either an exercise or a rest condition. Sixteen healthy young individuals (18–35 years) first experienced 25 min of moderate-intensity cycling or rest, and then adapted to a 30-degree visuomotor rotation condition. Immediately following that, participants experienced a washout session, which was followed by a readaptation session. Results indicated that all subjects adapted to the visuomotor rotation completely, although no difference was found between the cycling and rest conditions. Aftereffects and savings were also observed in both conditions, but with no difference between the conditions. These findings suggest that compared to a short rest session, a single bout of moderate-intensity cycling may not have a greater impact for enhancing visuomotor adaptation and its retention. Further research is needed, in which the effects of certain factors such as exercise intensity, duration and timing are more systematically investigated.

Using tools as cues for dual adaptation to opposing visuomotor rotations in virtual reality

Using tools as cues for dual adaptation to opposing visuomotor rotations in virtual reality