The role of the cross-sensory error signal in visuomotor adaptation

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.

The role of explicit knowledge in compensating for a visuo-proprioceptive cue conflict

It is unclear how explicit knowledge of an externally imposed mismatch between visual and proprioceptive cues of hand position affects perceptual recalibration. The Bayesian causal inference framework might suggest such knowledge should abolish the visual and proprioceptive recalibration that occurs when individuals perceive these cues as coming from the same source (their hand), while the visuomotor adaptation literature suggests explicit knowledge of a cue conflict does not eliminate implicit compensatory processes. Here we compared visual and proprioceptive recalibration in three groups with varying levels of knowledge about the visuo-proprioceptive cue conflict. All participants estimated the position of visual, proprioceptive, or combined targets related to their left index fingertip, with a 70 mm visuo-proprioceptive offset gradually imposed. Groups 1, 2, and 3 received no information, medium information, and high information, respectively, about the offset. Information was manipulated using instructional and visual cues. All groups performed the task similarly at baseline in terms of variance, weighting, and integration. Results suggest the three groups recalibrated vision and proprioception differently, but there was no difference in variance or weighting. Participants who received only instructional cues about the mismatch (Group 2) did not recalibrate less, on average, than participants provided no information about the mismatch (Group 1). However, participants provided instructional cues and extra visual cues of their hands during the perturbation (Group 3) demonstrated significantly less recalibration than other groups. These findings are consistent with the idea that instructional cues alone are insufficient to override participants' intrinsic belief in common cause and reduce recalibration.

Perceptual error based on Bayesian cue combination drives implicit motor adaptation

The sensorimotor system can recalibrate itself without our conscious awareness, a type of procedural learning whose computational mechanism remains undefined. Recent findings on implicit motor adaptation, such as over-learning from small perturbations and fast saturation for increasing perturbation size, challenge existing theories based on sensory errors. We argue that perceptual error, arising from the optimal combination of movement-related cues, is the primary driver of implicit adaptation. Central to our theory is the increasing sensory uncertainty of visual cues with increasing perturbations, which was validated through perceptual psychophysics (Experiment 1). Our theory predicts the learning dynamics of implicit adaptation across a spectrum of perturbation sizes on a trial-by-trial basis (Experiment 2). It explains proprioception changes and their relation to visual perturbation (Experiment 3). By modulating visual uncertainty in perturbation, we induced unique adaptation responses in line with our model predictions (Experiment 4). Overall, our perceptual error framework outperforms existing models based on sensory errors, suggesting that perceptual error in locating one's effector, supported by Bayesian cue integration, underpins the sensorimotor system's implicit adaptation.

The human somatosensory cortex contributes to the encoding of newly learned movements

Recent studies have indicated somatosensory cortex involvement in motor learning and retention. However, the nature of its contribution is unknown. One possibility is that the somatosensory cortex is transiently engaged during movement. Alternatively, there may be durable learning-related changes which would indicate sensory participation in the encoding of learned movements. These possibilities are dissociated by disrupting the somatosensory cortex following learning, thus targeting learning-related changes which may have occurred. If changes to the somatosensory cortex contribute to retention, which, in effect, means aspects of newly learned movements are encoded there, disruption of this area once learning is complete should lead to an impairment. Participants were trained to make movements while receiving rotated visual feedback. The primary motor cortex (M1) and the primary somatosensory cortex (S1) were targeted for continuous theta-burst stimulation, while stimulation over the occipital cortex served as a control. Retention was assessed using active movement reproduction, or recognition testing, which involved passive movements produced by a robot. Disruption of the somatosensory cortex resulted in impaired motor memory in both tests. Suppression of the motor cortex had no impact on retention as indicated by comparable retention levels in control and motor cortex conditions. The effects were learning specific. When stimulation was applied to S1 following training with unrotated feedback, movement direction, the main dependent variable, was unaltered. Thus, the somatosensory cortex is part of a circuit that contributes to retention, consistent with the idea that aspects of newly learned movements, possibly learning-updated sensory states (new sensory targets) which serve to guide movement, may be encoded there.

Effect of visuo-proprioceptive mismatch rate on recalibration in hand perception

We estimate our hand's position by combining relevant visual and proprioceptive cues. A cross-sensory spatial mismatch can be created by viewing the hand through a prism or, more recently, rotating a visual cursor that represents hand position. This is often done in the context of target-directed reaching to study motor adaptation, the systematic updating of motor commands in response to a systematic movement error. However, a visuo-proprioceptive mismatch also elicits recalibration in the relationship between the hand's seen and felt position. The principles governing visuo-proprioceptive recalibration are poorly understood, compared to motor adaptation. For example, motor adaptation occurs robustly whether the cursor is rotated quickly or slowly, although the former may involve more explicit processes. Here, we asked whether visuo-proprioceptive recalibration, in the absence of motor adaptation, works the same way. Three groups experienced a 70 mm visuo-proprioceptive mismatch about their hand at a Slow, Medium, or Fast rate (0.84, 1.67, or 3.34 mm every two trials, respectively), with no error feedback. Once attained, the 70 mm mismatch was maintained for the remaining trials. Total recalibration differed significantly across groups, with the Fast, Medium, and Slow groups recalibrating 63.7, 56.3, and 42.8 mm on average, respectively. This suggests a slower mismatch rate may be less effective at eliciting recalibration. In contrast to motor adaptation studies, no further recalibration was observed in the maintenance phase. This may be related to the distinct mechanisms thought to contribute to perceptual recalibration via cross-sensory cue conflict versus sensory prediction errors.

Implicit Sensorimotor Adaptation Proceeds in Absence of Movement Execution

In implicit sensorimotor adaptation, a mismatch between the predicted and actual sensory feedback results in a sensory prediction error (SPE). Sensory predictions have long been thought to be linked to descending motor commands, implying a necessary contribution of movement execution to adaptation. However, recent work has shown that mere motor imagery (MI) also engages predictive mechanisms, opening up the possibility that MI might be sufficient to drive implicit adaptation. In a within-subject design in humans (n = 30), implicit adaptation was assessed in a center-out reaching task, following a single exposure to a visuomotor rotation. It was hypothesized that performing MI of a reaching movement while being provided with an animation of rotated visual feedback (MI condition) would lead to postrotation biases (PRBs) similar to those observed when the movement is executed (Execution condition). Results revealed that both the MI and Execution conditions led to significant directional biases following rotated trials. Yet the magnitude of these biases was significantly larger in the Execution condition. To further probe the contribution of MI to adaptation, a Control condition was conducted in which participants were presented with the same rotated visual animation as in the MI condition, but in which they were prevented from performing MI. Surprisingly, significant biases were also observed in the Control condition, suggesting that MI per se may not have accounted for adaptation. Overall, these results suggest that implicit adaptation can be partially supported by processes other than those that strictly pertain to generating motor commands, although movement execution does potentiate it.

Retention of visuo-proprioceptive recalibration in estimating hand position

The brain estimates hand position using visual and proprioceptive cues, which are combined to give an integrated multisensory estimate. Spatial mismatches between cues elicit recalibration, a compensatory process where each unimodal estimate is shifted closer to the other. It is unclear how well visuo-proprioceptive recalibration is retained after mismatch exposure. Here we asked whether direct vision and/or active movement of the hand can undo visuo-proprioceptive recalibration, and whether recalibration is still evident 24 h later. 75 participants performed two blocks of visual, proprioceptive, and combination trials, with no feedback or direct vision of the hand. In Block 1, a 70 mm visuo-proprioceptive mismatch was gradually imposed, and recalibration assessed. Block 2 tested retention. Between blocks, Groups 1-4 rested or made active movements with their directly visible or unseen hand for several minutes. Group 5 had a 24-h gap between blocks. All five groups recalibrated both vision and proprioception in Block 1, and Groups 1-4 retained most of this recalibration in Block 2. Interestingly, Group 5 showed an offline increase in proprioceptive recalibration, but retained little visual recalibration. Our results suggested that visuo-proprioceptive recalibration is robustly retained in the short-term. In the longer term, contextual factors may affect retention.

Reduced feedback barely slows down proprioceptive recalibration

Introducing altered visual feedback of the hand produces quick adaptation of reaching movements. Our lab has shown that the associated shifts in estimates of the felt position of the hand saturate within a few training trials. The current study investigates whether the rapid changes in felt hand position that occur during classic visuomotor adaptation are diminished or slowed when training feedback is reduced. We reduced feedback by either providing visual feedback only at the end of the reach (terminal feedback) or constraining hand movements to reduce motor adaptation-related error signals such as sensory prediction errors and task errors (exposure). We measured changes as participants completed reaches with a 30° rotation, a -30° rotation, and clamped visual feedback, with these two "impoverished" training conditions, along with classic visuomotor adaptation training, while continuously estimating their felt hand position. Training with terminal feedback slightly reduced the initial rate of change in overall adaptation. However, the rate of change in hand localization, as well as the asymptote of hand localization shifts in both the terminal feedback group and the exposure training group was not noticeably different from those in the classic training group. Taken together, shifts in felt hand position are rapid and robust responses to sensory mismatches and are at best slightly modulated when feedback is reduced. This suggests that given the speed and invariance to the quality of feedback of proprioceptive recalibration, it could immediately contribute to all kinds of reach adaptation.NEW & NOTEWORTHY Reaching to targets with altered visual feedback about hand position leads to adaptation of movements as well as shifts in estimates of felt hand position. Felt hand position can shift in as little as one trial, and here we show that there is no noticeable reduction in speed when the feedback about movements is impoverished, indicating the robustness of the process of recalibrating felt hand position.

Conscious awareness of a visuo-proprioceptive mismatch: Effect on cross-sensory recalibration

The brain estimates hand position using vision and position sense (proprioception). The relationship between visual and proprioceptive estimates is somewhat flexible: visual information about the index finger can be spatially displaced from proprioceptive information, resulting in cross-sensory recalibration of the visual and proprioceptive unimodal position estimates. According to the causal inference framework, recalibration occurs when the unimodal estimates are attributed to a common cause and integrated. If separate causes are perceived, then recalibration should be reduced. Here we assessed visuo-proprioceptive recalibration in response to a gradual visuo-proprioceptive mismatch at the left index fingertip. Experiment 1 asked how frequently a 70 mm mismatch is consciously perceived compared to when no mismatch is present, and whether awareness is linked to reduced visuo-proprioceptive recalibration, consistent with causal inference predictions. However, conscious offset awareness occurred rarely. Experiment 2 tested a larger displacement, 140 mm, and asked participants about their perception more frequently, including at 70 mm. Experiment 3 confirmed that participants were unbiased at estimating distances in the 2D virtual reality display. Results suggest that conscious awareness of the mismatch was indeed linked to reduced cross-sensory recalibration as predicted by the causal inference framework, but this was clear only at higher mismatch magnitudes (70–140 mm). At smaller offsets (up to 70 mm), conscious perception of an offset may not override unconscious belief in a common cause, perhaps because the perceived offset magnitude is in range of participants’ natural sensory biases. These findings highlight the interaction of conscious awareness with multisensory processes in hand perception.

Understanding implicit sensorimotor adaptation as a process of proprioceptive re-alignment

Multiple learning processes contribute to successful goal-directed actions in the face of changing physiological states, biomechanical constraints, and environmental contexts. Amongst these processes, implicit sensorimotor adaptation is of primary importance, ensuring that movements remain well-calibrated and accurate. A large body of work on reaching movements has emphasized how adaptation centers on an iterative process designed to minimize visual errors. The role of proprioception has been largely neglected, thought to play a passive role in which proprioception is affected by the visual error but does not directly contribute to adaptation. Here, we present an alternative to this visuo-centric framework, outlining a model in which implicit adaptation acts to minimize a proprioceptive error, the distance between the perceived hand position and its intended goal. This proprioceptive re-alignment model (PReMo) is consistent with many phenomena that have previously been interpreted in terms of learning from visual errors, and offers a parsimonious account of numerous unexplained phenomena. Cognizant that the evidence for PReMo rests on correlational studies, we highlight core predictions to be tested in future experiments, as well as note potential challenges for a proprioceptive-based perspective on implicit adaptation.

Improved proprioception does not benefit visuomotor adaptation

Visuomotor adaptation arises when reaching in an altered visual environment, where one's seen hand position does not match their felt (i.e., proprioceptive) hand position in space. Here, we asked if proprioceptive training benefits visuomotor adaptation, and if these benefits arise due to implicit (unconscious) or explicit (conscious strategy) processes. Seventy-two participants were divided equally into 3 groups: proprioceptive training with feedback (PTWF), proprioceptive training no feedback (PTNF), and Control (CTRL). The PTWF and PTNF groups completed passive proprioceptive training, where a participant's hand was moved to an unknown reference location and they judged the felt position of their unseen hand relative to their body midline on every trial. The PTWF group received verbal feedback with respect to their response accuracy on the middle 60% of trials, whereas the PTNF did not receive any feedback during training. The CTRL group did not complete proprioceptive training and instead sat quietly during this time. Following proprioceptive training or time delay, all three groups reached when seeing a cursor that was rotated 30° clockwise relative to their hand motion. The experiment ended with participants completing a series of no-cursor reaches to assess implicit and explicit adaptation. Results indicated that the PTWF group improved the accuracy of their sense of felt hand position following proprioceptive training. However, this improved proprioceptive acuity (i.e., the accuracy of their sense of felt hand) did not benefit visuomotor adaptation, as all three groups showed similar visuomotor adaptation across rotated reach training trials. Visuomotor adaptation arose implicitly, with minimal explicit contribution for all three groups. Together, these results suggest that passive proprioceptive training does not benefit, nor hinder, the extent of implicit visuomotor adaptation established immediately following reach training with a 30° cursor rotation.

Somatotopic Specificity of Perceptual and Neurophysiological Changes Associated with Visuo-proprioceptive Realignment

When visual and proprioceptive estimates of hand position disagree (e.g., viewing the hand underwater), the brain realigns them to reduce mismatch. This perceptual change is reflected in primary motor cortex (M1) excitability, suggesting potential relevance for hand movement. Here, we asked whether fingertip visuo-proprioceptive misalignment affects only the brain's representation of that finger (somatotopically focal), or extends to other parts of the limb that would be needed to move the misaligned finger (somatotopically broad). In Experiments 1 and 2, before and after misaligned or veridical visuo-proprioceptive training at the index finger, we used transcranial magnetic stimulation to assess M1 representation of five hand and arm muscles. The index finger representation showed an association between M1 excitability and visuo-proprioceptive realignment, as did the pinkie finger representation to a lesser extent. Forearm flexors, forearm extensors, and biceps did not show any such relationship. In Experiment 3, participants indicated their proprioceptive estimate of the fingertip, knuckle, wrist, and elbow, before and after misalignment at the fingertip. Proprioceptive realignment at the knuckle, but not the wrist or elbow, was correlated with realignment at the fingertip. These results suggest the effects of visuo-proprioceptive mismatch are somatotopically focal in both sensory and motor domains.

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

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.

Proprioceptive recalibration following implicit visuomotor adaptation is preserved in Parkinson's disease

Individuals with Parkinson's disease (PD) and healthy adults demonstrate similar levels of visuomotor adaptation provided that the distortion is small or introduced gradually, and hence, implicit processes are engaged. Recently, implicit processes underlying visuomotor adaptation in healthy individuals have been proposed to include proprioceptive recalibration (i.e., shifts in one's proprioceptive sense of felt hand position to match the visual estimate of their hand experienced during reaches with altered visual feedback of the hand). In the current study, we asked if proprioceptive recalibration is preserved in PD patients. PD patients tested during their "off" and "on" medication states and age-matched healthy controls reached to visual targets, while visual feedback of their unseen hand was gradually rotated 30° clockwise or translated 4 cm rightwards of their actual hand trajectory. As expected, PD patients and controls produced significant reach aftereffects, indicating visuomotor adaptation after reaching with the gradually introduced visuomotor distortions. More importantly, following visuomotor adaptation, both patients and controls showed recalibration in hand position estimates, and the magnitude of this recalibration was comparable between PD patients and controls. No differences for any measures assessed were observed across medication status (i.e., PD off vs PD on). Results reveal that patients are able to adjust their sensorimotor mappings and recalibrate proprioception following adaptation to a gradually introduced visuomotor distortion, and that dopaminergic intervention does not affect this proprioceptive recalibration. These results suggest that proprioceptive recalibration does not involve striatal dopaminergic pathways and may contribute to the preserved visuomotor adaptation that arises implicitly in PD patients.

Individual differences in proprioception predict the extent of implicit sensorimotor adaptation

Recent 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 (visually biased) sensed hand position realigns with the expected sensed position (target). When a visuo-proprioceptive discrepancy is introduced, the sensed hand position is biased toward the visual cursor, and the adaptive system counteracts 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). Although the results do not clearly favor one hypothesis over the other, they underscore the critical role of proprioception in sensorimotor adaptation.NEW & NOTEWORTHY Although the sensorimotor system uses sensory feedback to remain calibrated, this learning process is constrained, limited by the maximum degree of plasticity. The factors determining this limit remain elusive. Guided by two hypotheses, 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.

Implicit motor learning within three trials

In motor learning, the slow development of implicit learning is traditionally taken for granted. While much is known about training performance during adaptation to a perturbation in reaches, saccades and locomotion, little is known about the time course of the underlying implicit processes during normal motor adaptation. Implicit learning is characterized by both changes in internal models and state estimates of limb position. Here, we measure both as reach aftereffects and shifts in hand localization in our participants, after every training trial. The observed implicit changes were near asymptote after only one to three perturbed training trials and were not predicted by a two-rate model's slow process that is supposed to capture implicit learning. Hence, we show that implicit learning is much faster than conventionally believed, which has implications for rehabilitation and skills training.

External error attribution dampens efferent-based predictions but not proprioceptive changes in hand localization

In learning and adapting movements in changing conditions, people attribute the errors they experience to a combined weighting of internal or external sources. As such, error attribution that places more weight on external sources should lead to decreased updates in our internal models for movement of the limb or estimating the position of the effector, i.e. there should be reduced implicit learning. However, measures of implicit learning are the same whether or not we induce explicit adaptation with instructions about the nature of the perturbation. Here we evoke clearly external errors by either demonstrating the rotation on every trial, or showing the hand itself throughout training. Implicit reach aftereffects persist, but are reduced in both groups. Only for the group viewing the hand, changes in hand position estimates suggest that predicted sensory consequences are not updated, but only rely on recalibrated proprioception. Our results show that estimating the position of the hand incorporates source attribution during motor learning, but recalibrated proprioception is an implicit process unaffected by external error attribution.

The effect of age on visuomotor learning processes

Knowing where our limbs are in space is essential for moving and for adapting movements to various changes in our environments and bodies. The ability to adapt movements declines with age, and age-related cognitive decline can explain a decreased ability to adopt and deploy explicit, cognitive strategies in motor learning. Age-related sensory decline could also lead to a reduced fidelity of sensory position signals and error signals, each of which can affect implicit motor adaptation. Here we investigate two estimates of limb position; one based on proprioception, the other on predicted sensory consequences of movements. Each is considered a measure of an implicit adaptation process and may be affected by both age and cognitive strategies. Both older (n = 38) and younger (n = 42) adults adapted to a 30° visuomotor rotation in a centre-out reaching task. We make an explicit, cognitive strategy available to half of participants in each age group with a detailed instruction. After training, we first quantify the explicit learning elicited by instruction. Instructed older adults initially use the provided strategy slightly less than younger adults but show a similar ability to evoke it after training. This indicates that cognitive explanations for age-related decline in motor learning are limited. In contrast, training induced much larger shifts of state estimates of hand location in older adults compared to younger adults. This is not modulated by strategy instructions, and appears driven by recalibrated proprioception, which is almost twice as large in older adults, while predictions might not be updated in older adults. This means that in healthy aging, some implicit processes may be compensating for other changes to maintain motor capabilities, while others also show age-related decline (data: https://osf.io/qzhmy).

Split-Belt walking induces changes in active, but not passive, perception of step length

Successful motor control requires accurate estimation of our body in space for planning, executing, and evaluating the outcome of our actions. It has been shown that the estimation of limb position is susceptible to motor adaptation. However, a similar effect has not been found in locomotion, possibly due to how it was tested. We hypothesized that split-belt walking with the legs moving at different speeds changes the estimation of the legs' position when taking a step. Thus, we assessed young subjects' perception of step length (i.e., inter-feet distance at foot landing) when they moved their legs (active perception) or when the legs were moved by the experimenter (passive perception). We found that the active perception of step length was substantially altered following split-belt walking, whereas passive perception exhibited minor changes. This suggests that split-belt walking induced the adaptation of efferent signals, without altering sensory signals. We also found that active perceptual shifts were sensitive to how they were tested: they were most salient in the trailing leg and at short step lengths. Our results suggest that split-belt walking could modulate the deficient perception of step length post-stroke, which may contribute to gait asymmetries impairing patients' mobility.

Motor learning without moving: Proprioceptive and predictive hand localization after passive visuoproprioceptive discrepancy training

An accurate estimate of limb position is necessary for movement planning, before and after motor learning. Where we localize our unseen hand after a reach depends on felt hand position, or proprioception, but in studies and theories on motor adaptation this is quite often neglected in favour of predicted sensory consequences based on efference copies of motor commands. Both sources of information should contribute, so here we set out to further investigate how much of hand localization depends on proprioception and how much on predicted sensory consequences. We use a training paradigm combining robot controlled hand movements with rotated visual feedback that eliminates the possibility to update predicted sensory consequences (‘exposure training’), but still recalibrates proprioception, as well as a classic training paradigm with self-generated movements in another set of participants. After each kind of training we measure participants’ hand location estimates based on both efference-based predictions and afferent proprioceptive signals with self-generated hand movements (‘active localization’) as well as based on proprioception only with robot-generated movements (‘passive localization’). In the exposure training group, we find indistinguishable shifts in passive and active hand localization, but after classic training, active localization shifts more than passive, indicating a contribution from updated predicted sensory consequences. Both changes in open-loop reaches and hand localization are only slightly smaller after exposure training as compared to after classic training, confirming that proprioception plays a large role in estimating limb position and in planning movements, even after adaptation. (data: https://doi.org/10.17605/osf.io/zfdth, preprint: https://doi.org/10.1101/384941)

The effects of awareness of the perturbation during motor adaptation on hand localization

Awareness of task demands is often used during rehabilitation and sports training by providing instructions which appears to accelerate learning and improve performance through explicit motor learning. However, the effects of awareness of perturbations on the changes in estimates of hand position resulting from motor learning are not well understood. In this study, people adapted their reaches to a visuomotor rotation while either receiving instructions on the nature of the perturbation, experiencing a large rotation, or both to generate awareness of the perturbation and increase the contribution of explicit learning. We found that instructions and/or larger rotations allowed people to activate or deactivate part of the learned strategy at will and elicited explicit changes in open-loop reaches, while a small rotation without instructions did not. However, these differences in awareness, and even manipulations of awareness and perturbation size, did not appear to affect learning-induced changes in hand-localization estimates. This was true when estimates of the adapted hand location reflected changes in proprioception, produced when the hand was displaced by a robot, and also when hand location estimates were based on efferent-based predictions of self-generated hand movements. In other words, visuomotor adaptation led to significant shifts in predicted and perceived hand location that were not modulated by either instruction or perturbation size. Our results indicate that not all outcomes of motor learning benefit from an explicit awareness of the task. Particularly, proprioceptive recalibration and the updating of predicted sensory consequences appear to be largely implicit. (data: https://doi.org/10.17605/osf.io/mx5u2, preprint: https://doi.org/10.31234/osf.io/y53c2)

Experiencing the Cross-Sensory Error Signal During Movement Leads to Proprioceptive Recalibration

Reaching to targets in a virtual reality environment with misaligned visual feedback of the hand results in changes in movements (visuomotor adaptation) and sense of felt hand position (proprioceptive recalibration). We asked if proprioceptive recalibration arises even when the misalignment between visual and proprioceptive estimates of hand position is only experienced during movement. Participants performed a "shooting task" through the targets with a cursor that was rotated 30° clockwise relative to hand motion. Results revealed that, following training on the shooting task, participants adapted their reaches to all targets by approximately 16° and recalibrated their sense of felt hand position by 8°. Thus, experiencing a sensory misalignment between visual and proprioceptive estimates of hand position during movement leads to proprioceptive recalibration.

The fast contribution of visual-proprioceptive discrepancy to reach aftereffects and proprioceptive recalibration

Adapting reaches to altered visual feedback not only leads to motor changes, but also to shifts in perceived hand location; "proprioceptive recalibration". These changes are robust to many task variations and can occur quite rapidly. For instance, our previous study found both motor and sensory shifts arise in as few as 6 rotated-cursor training trials. The aim of this study is to investigate one of the training signals that contribute to these rapid sensory and motor changes. We do this by removing the visuomotor error signals associated with classic visuomotor rotation training; and provide only experience with a visual-proprioceptive discrepancy for training. While a force channel constrains reach direction 30o away from the target, the cursor representing the hand unerringly moves straight to the target. The resulting visual-proprioceptive discrepancy drives significant and rapid changes in no-cursor reaches and felt hand position, again within only 6 training trials. The extent of the sensory change is unexpectedly larger following the visual-proprioceptive discrepancy training. Not surprisingly the size of the reach aftereffects is substantially smaller than following classic visuomotor rotation training. However, the time course by which both changes emerge is similar in the two training types. These results suggest that even the mere exposure to a discrepancy between felt and seen hand location is a sufficient training signal to drive robust motor and sensory plasticity.

Seeing virtual while acting real: Visual display and strategy effects on the time and precision of eye-hand coordination

Effects of different visual displays on the time and precision of bare-handed or tool-mediated eye-hand coordination were investigated in a pick-and-place-task with complete novices. All of them scored well above average in spatial perspective taking ability and performed the task with their dominant hand. Two groups of novices, four men and four women in each group, had to place a small object in a precise order on the centre of five targets on a Real-world Action Field (RAF), as swiftly as possible and as precisely as possible, using a tool or not (control). Each individual session consisted of four visual display conditions. The order of conditions was counterbalanced between individuals and sessions. Subjects looked at what their hands were doing 1) directly in front of them (“natural” top-down view) 2) in top-down 2D fisheye view 3) in top-down undistorted 2D view or 4) in 3D stereoscopic top-down view (head-mounted OCULUS DK 2). It was made sure that object movements in all image conditions matched the real-world movements in time and space. One group was looking at the 2D images with the monitor positioned sideways (sub-optimal); the other group was looking at the monitor placed straight ahead of them (near-optimal). All image viewing conditions had significantly detrimental effects on time (seconds) and precision (pixels) of task execution when compared with “natural” direct viewing. More importantly, we find significant trade-offs between time and precision between and within groups, and significant interactions between viewing conditions and manipulation conditions. The results shed new light on controversial findings relative to visual display effects on eye-hand coordination, and lead to conclude that differences in camera systems and adaptive strategies of novices are likely to explain these.

Getting nowhere fast: trade-off between speed and precision in training to execute image-guided hand-tool movements

Background

The speed and precision with which objects are moved by hand or hand-tool interaction under image guidance depend on a specific type of visual and spatial sensorimotor learning. Novices have to learn to optimally control what their hands are doing in a real-world environment while looking at an image representation of the scene on a video monitor. Previous research has shown slower task execution times and lower performance scores under image-guidance compared with situations of direct action viewing. The cognitive processes for overcoming this drawback by training are not yet understood.

Methods

We investigated the effects of training on the time and precision of direct view versus image guided object positioning on targets of a Real-world Action Field (RAF). Two men and two women had to learn to perform the task as swiftly and as precisely as possible with their dominant hand, using a tool or not and wearing a glove or not. Individuals were trained in sessions of mixed trial blocks with no feed-back.

Results

As predicted, image-guidance produced significantly slower times and lesser precision in all trainees and sessions compared with direct viewing. With training, all trainees get faster in all conditions, but only one of them gets reliably more precise in the image-guided conditions. Speed-accuracy trade-offs in the individual performance data show that the highest precision scores and steepest learning curve, for time and precision, were produced by the slowest starter. Fast starters produced consistently poorer precision scores in all sessions. The fastest starter showed no sign of stable precision learning, even after extended training.

Conclusions

Performance evolution towards optimal precision is compromised when novices start by going as fast as they can. The findings have direct implications for individual skill monitoring in training programmes for image-guided technology applications with human operators.

Time Course of Reach Adaptation and Proprioceptive Recalibration during Visuomotor Learning

Training to reach with rotated visual feedback results in adaptation of hand movements, which persist when the perturbation is removed (reach aftereffects). Training also leads to changes in felt hand position, which we refer to as proprioceptive recalibration. The rate at which motor and proprioceptive changes develop throughout training is unknown. Here, we aim to determine the timescale of these changes in order to gain insight into the processes that may be involved in motor learning. Following six rotated reach training trials (30° rotation), at three radially located targets, we measured reach aftereffects and perceived hand position (proprioceptive guided reaches). Participants trained with opposing rotations one week apart to determine if the original training led to any retention or interference. Results suggest that both motor and proprioceptive recalibration occurred in as few as six rotated-cursor training trials (7.57° & 3.88° respectively), with no retention or interference present one week after training. Despite the rapid speed of both motor and sensory changes, these shifts do not saturate to the same degree. Thus, different processes may drive these changes and they may not constitute a single implicit process.

Separating Predicted and Perceived Sensory Consequences of Motor Learning

During motor adaptation the discrepancy between predicted and actually perceived sensory feedback is thought to be minimized, but it can be difficult to measure predictions of the sensory consequences of actions. Studies attempting to do so have found that self-directed, unseen hand position is mislocalized in the direction of altered visual feedback. However, our lab has shown that motor adaptation also leads to changes in perceptual estimates of hand position, even when the target hand is passively displaced. We attribute these changes to a recalibration of hand proprioception, since in the absence of a volitional movement, efferent or predictive signals are likely not involved. The goal here is to quantify the extent to which changes in hand localization reflect a change in the predicted sensory (visual) consequences or a change in the perceived (proprioceptive) consequences. We did this by comparing changes in localization produced when the hand movement was self-generated (‘active localization’) versus robot-generated (‘passive localization’) to the same locations following visuomotor adaptation to a rotated cursor. In this passive version, there should be no predicted consequences of these robot-generated hand movements. We found that although changes in localization were somewhat larger in active localization, the passive localization task also elicited substantial changes. Our results suggest that the change in hand localization following visuomotor adaptation may not be based entirely on updating predicted sensory consequences, but may largely reflect changes in our proprioceptive state estimate.

Split-belt walking adaptation recalibrates sensorimotor estimates of leg speed but not position or force

Motor learning during reaching not only recalibrates movement but can also lead to small but consistent changes in the sense of arm position. Studies have suggested that this sensory effect may be the result of recalibration of a forward model that associates motor commands with their sensory consequences. Here we investigated whether similar perceptual changes occur in the lower limbs after learning a new walking pattern on a split-belt treadmill--a task that critically involves proprioception. Specifically, we studied how this motor learning task affects perception of leg speed during walking, perception of leg position during standing or walking, and perception of contact force during stepping. Our results show that split-belt adaptation leads to robust motor aftereffects and alters the perception of leg speed during walking. This is specific to the direction of walking that was trained during adaptation (i.e., backward or forward). The change in leg speed perception accounts for roughly half of the observed motor aftereffect. In contrast, split-belt adaptation does not alter the perception of leg position during standing or walking and does not change the perception of stepping force. Our results demonstrate that there is a recalibration of a sensory percept specific to the domain of the perturbation that was applied during walking (i.e., speed but not position or force). Furthermore, the motor and sensory consequences of locomotor adaptation may be linked, suggesting overlapping mechanisms driving changes in the motor and sensory domains.

Generalization patterns for reach adaptation and proprioceptive recalibration differ after visuomotor learning

Visuomotor learning results in changes in both motor and sensory systems (Cressman EK, Henriques DY. J Neurophysiol 102: 3505-3518, 2009), such that reaches are adapted and sense of felt hand position recalibrated after reaching with altered visual feedback of the hand. Moreover, visuomotor learning has been shown to generalize such that reach adaptation achieved at a trained target location can influence reaches to novel target directions (Krakauer JW, Pine ZM, Ghilardi MF, Ghez C. J Neurosci 20: 8916-8924, 2000). We looked to determine whether proprioceptive recalibration also generalizes to novel locations. Moreover, we looked to establish the relationship between reach adaptation and changes in sense of felt hand position by determining whether proprioceptive recalibration generalizes to novel targets in a similar manner as reach adaptation. On training trials, subjects reached to a single target with aligned or misaligned cursor-hand feedback, in which the cursor was either rotated or scaled in extent relative to hand movement. After reach training, subjects reached to the training target and novel targets (including targets from a second start position) without visual feedback to assess generalization of reach adaptation. Subjects then performed a proprioceptive estimation task, in which they indicated the position of their hand relative to visual reference markers placed at similar locations as the trained and novel reach targets. Results indicated that shifts in hand position generalized across novel locations, independent of reach adaptation. Thus these distinct sensory and motor generalization patterns suggest that reach adaptation and proprioceptive recalibration arise from independent error signals and that changes in one system cannot guide adjustments in the other.

Retention of proprioceptive recalibration following visuomotor adaptation

We have recently shown that visuomotor adaptation following reaches with a misaligned cursor not only induces changes in an individual's motor output, but their proprioceptive sense of hand position as well. Long-term changes are seen in motor adaptation; however, very little is known about the retention of changes in felt hand position. We sought to evaluate whether this recalibration in proprioception, following visuomotor adaptation, is sufficiently robust to be retained the following day (~24 h later), and if so, to determine its extent. Visuomotor adaptation was induced by having subjects perform reaches to visual targets using a cursor representing their unseen hand, which had been gradually rotated 45° counterclockwise. Motor adaptation and proprioceptive recalibration were determined by assessing subjects' reach aftereffects and changes in hand bias, respectively. We found that subjects adapted their reaches and recalibrated their sense of hand position following training with a misaligned cursor, as shown in Cressman and Henriques (J Neurophysiol 102:3505-3518, 2009). More importantly, subjects who showed proprioceptive recalibration in the direction of motor adaptation on Day 1 did retain changes in felt hand position and motor adaptation on Day 2. These findings suggest that in addition to motor changes, individuals are capable of retaining sensory changes in proprioception up to 24 h later.

The cerebellum is not necessary for visually driven recalibration of hand proprioception

Decades of research have implicated both cortical and subcortical areas, such as the cerebellum, as playing an important role in motor learning, and even more recently, in predicting the sensory consequences of movement. Still, it is unknown whether the cerebellum also plays a role in recalibrating sensory estimates of hand position following motor learning. To test this, we measured proprioceptive estimates of static hand position in 19 cerebellar patients with local ischemic lesions and 19 healthy controls, both before and after reach training with altered visual feedback of the hand. This altered visual feedback, (30° cursor-rotation) was gradually introduced in order to facilitate reach adaptation in the patient group. We included two different types of training (in separate experiments): the typical visuomotor rotation training where participants had full volition of their hand movements when reaching with the cursor, and sensory exposure training where the direction of participants׳ hand movements were constrained and gradually deviated from the cursor motion (Cressman, E. K., Henriques, D. Y., 2010. Reach adaptation and proprioceptive recalibration following exposure to misaligned sensory input. J. Neurophysiol., vol. 103, pp. 1888-1895). We found that both healthy individuals and patients showed equivalent shifts in their felt hand position following both types of training. Likewise, as expected given that the cursor-rotation was introduced gradually, patients showed comparable reach aftereffects to those of controls in both types of training. The robust change in felt hand position across controls and cerebellar patients suggests that the cerebellum is not involved in proprioceptive recalibration of the hand.

Reach adaptation and proprioceptive recalibration following terminal visual feedback of the hand

We have shown that when subjects reach with continuous, misaligned visual feedback of their hand, their reaches are adapted and proprioceptive sense of hand position is recalibrated to partially match the visual feedback (Salomonczyk et al., 2011). It is unclear if similar changes arise after reaching with visual feedback that is provided only at the end of the reach (i.e., terminal feedback), when there are shorter temporal intervals for subjects to experience concurrent visual and proprioceptive feedback. Subjects reached to targets with an aligned hand-cursor that provided visual feedback at the end of each reach movement across a 99-trial training block, and with a rotated cursor over three successive blocks of 99 trials each. After each block, no cursor reaches, to measure aftereffects, and felt hand positions were measured. Felt hand position was determined by having subjects indicate the position of their unseen hand relative to a reference marker. We found that subjects adapted their reaches following training with rotated terminal visual feedback, yet slightly less (i.e., reach aftereffects were smaller), than subjects from a previous study who experienced continuous visual feedback. Nonetheless, current subjects recalibrated their sense of felt hand position in the direction of the altered visual feedback, but this proprioceptive change increased incrementally over the three rotated training blocks. Final proprioceptive recalibration levels were comparable to our previous studies in which subjects performed the same task with continuous visual feedback. Thus, compared to reach training with continuous, but altered visual feedback, subjects who received terminal altered visual feedback of the hand produced significant but smaller reach aftereffects and similar changes in hand proprioception when given extra training. Taken together, results suggest that terminal feedback of the hand is sufficient to drive motor adaptation, and also proprioceptive recalibration.