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

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.

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.

Neural correlates of bilateral proprioception and adaptation with training

Bilateral proprioception includes the ability to sense the position and motion of one hand relative to the other, without looking. This sensory ability allows us to perform daily activities seamlessly, and its impairment is observed in various neurological disorders such as cerebral palsy and stroke. It can undergo experience-dependent plasticity, as seen in trained piano players. If its neural correlates were better understood, it would provide a useful assay and target for neurorehabilitation for people with impaired proprioception. We designed a non-invasive electroencephalography-based paradigm to assess the neural features relevant to proprioception, especially focusing on bilateral proprioception, i.e., assessing the limb distance from the body with the other limb. We compared it with a movement-only task, with and without the visibility of the target hand. Additionally, we explored proprioceptive accuracy during the tasks. We tested eleven Controls and nine Skilled musicians to assess whether sensorimotor event-related spectral perturbations in μ (8-12Hz) and low-β (12-18Hz) rhythms differ in people with musical instrument training, which intrinsically involves a bilateral proprioceptive component, or when new sensor modalities are added to the task. The Skilled group showed significantly reduced μ and low-β suppression in bilateral tasks compared to movement-only, a significative difference relative to Controls. This may be explained by reduced top-down control due to intensive training, despite this, proprioceptive errors were not smaller for this group. Target visibility significantly reduced proprioceptive error in Controls, while no change was observed in the Skilled group. During visual tasks, Controls exhibited significant μ and low-β power reversals, with significant differences relative to proprioceptive-only tasks compared to the Skilled group-possibly due to reduced uncertainty and top-down control. These results provide support for sensorimotor μ and low-β suppression as potential neuromarkers for assessing proprioceptive ability. The identification of these features is significant as they could be used to quantify altered proprioceptive neural processing in skill and movement disorders. This in turn can be useful as an assay for pre and post sensory-motor intervention research.

Proprioceptive short-term memory in passive motor learning

A physical trainer often physically guides a learner's limbs to teach an ideal movement, giving the learner proprioceptive information about the movement to be reproduced later. This instruction requires the learner to perceive kinesthetic information and store the instructed information temporarily. Therefore, (1) proprioceptive acuity to accurately perceive the taught kinesthetics and (2) short-term memory to store the perceived information are two critical functions for reproducing the taught movement. While the importance of proprioceptive acuity and short-term memory has been suggested for active motor learning, little is known about passive motor learning. Twenty-one healthy adults (mean age 25.6 years, range 19-38 years) participated in this study to investigate whether individual learning efficiency in passively guided learning is related to these two functions. Consequently, learning efficiency was significantly associated with short-term memory capacity. In particular, individuals who could recall older sensory stimuli showed better learning efficiency. However, no significant relationship was observed between learning efficiency and proprioceptive acuity. A causal graph model found a direct influence of memory on learning and an indirect effect of proprioceptive acuity on learning via memory. Our findings suggest the importance of a learner's short-term memory for effective passive motor learning.

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.

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.

Effects of guided exploration on reaching measures of auditory peripersonal space

Despite the recognized importance of bodily movements in spatial audition, few studies have integrated action-based protocols with spatial hearing in the peripersonal space. Recent work shows that tactile feedback and active exploration allow participants to improve performance in auditory distance perception tasks. However, the role of the different aspects involved in the learning phase, such as voluntary control of movement, proprioceptive cues, and the possibility of self-correcting errors, is still unclear. We study the effect of guided reaching exploration on perceptual learning of auditory distance in peripersonal space. We implemented a pretest-posttest experimental design in which blindfolded participants must reach for a sound source located in this region. They were divided into three groups that were differentiated by the intermediate training phase: Guided, an experimenter guides the participant’s arm to contact the sound source; Active, the participant freely explores the space until contacting the source; and Control, without tactile feedback. The effects of exploration feedback on auditory distance perception in the peripersonal space are heterogeneous. Both the Guided and Active groups change their performance. However, participants in the Guided group tended to overestimate distances more than those in the Active group. The response error of the Guided group corresponds to a generalized calibration criterion over the entire range of reachable distances. Whereas the Active group made different adjustments for proximal and distal positions. The results suggest that guided exploration can induce changes on the boundary of the auditory reachable space. We postulate that aspects of agency such as initiation, control, and monitoring of movement, assume different degrees of involvement in both guided and active tasks, reinforcing a non-binary approach to the question of activity-passivity in perceptual learning and supporting a complex view of the phenomena involved in action-based learning.

Sensing hand position in Ehlers-Danlos syndrome

PURPOSE

To explore the effect of joint hypermobility on acuity, and precision, of hand proprioception.

MATERIALS AND METHODS

We compared proprioceptive acuity, and precision, between EDS patients and controls. We then measured any changes in their estimates of hand position after participants adapted their reaches in response to altered visual feedback of their hand. The Beighton Scale was used to quantify the magnitude of joint hypermobility.

RESULTS

There were no differences between the groups in the accuracy of estimates of hand location, nor in the visually induced changes in hand location. However, EDS patients' estimates were less precise when based purely on proprioception and could be partially predicted by Beighton score.

CONCLUSIONS

EDS patients are less precise at estimating their hand's location when only afferent information is available, but the presence of efferent signalling may reduce this imprecision. Those who are more hypermobile are more likely to be imprecise.

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.

Passive Motor Learning: Oculomotor Adaptation in the Absence of Behavioral Errors

Motor adaptation is commonly thought to be a trial-and-error process in which the accuracy of movement improves with repetition of behavior. We challenged this view by testing whether erroneous movements are necessary for motor adaptation. In the eye movement system, the association between movements and errors can be disentangled, since errors in the predicted stimulus trajectory can be perceived even without movements. We modified a smooth pursuit eye movement adaptation paradigm in which monkeys learn to make an eye movement that predicts an upcoming change in target direction. We trained the monkeys to fixate on a target while covertly, an additional target initially moved in one direction and then changed direction after 250 ms. The monkeys showed a learned response to infrequent probe trials in which they were instructed to follow the moving target. Additional experiments confirmed that probing learning or residual eye movements during fixation did not drive learning. These results show that motor adaptation can be elicited in the absence of movement and provide an animal model for studying the implementation of passive motor learning. Current models assume that the interaction between movement and error signals underlies adaptive motor learning. Our results point to other mechanisms that may drive learning in the absence of movement.

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).

A condition that produces sensory recalibration and abolishes multisensory integration

We examined the influence of extended exposure to a visuomotor rotation, which induces both motor adaptation and sensory recalibration, on (partial) multisensory integration in a cursor-control task. Participants adapted to a 30° (adaptation condition) or 0° (control condition) visuomotor rotation by making center-out movements to remembered targets. In subsequent test trials of sensory integration, they made center-out movements with variable visuomotor rotations and judged the position of hand or cursor at the end of these movements. Test trials were randomly embedded among twice the number of maintenance trials with 30° or 0° rotation. The biases of perceived hand (or cursor) position toward the cursor (or hand) position were measured. We found motor adaptation together with proprioceptive and visual recalibrations in the adaptation condition. Unexpectedly, multisensory integration was absent in both the adaptation and control condition. The absence stemmed from the extensive experience of constant visuomotor rotations of 30° or 0°, which probably produced highly precise predictions of the visual consequences of hand movements. The frequently confirmed predictions then dominated the estimate of the visual movement consequences, leaving no influence of the actual visuomotor rotations in the minority of test trials. Conversely, multisensory integration was present for sensed hand positions when these were indirectly assessed from movement characteristics, indicating that the relative weighting of discrepant estimates of hand position was different for motor control. The existence of a condition that abolishes multisensory integration while keeping sensory recalibration suggests that mechanisms that reduce sensory discrepancies (partly) differ between integration and recalibration.

Early stages of sensorimotor map acquisition: learning with free exploration, without active movement or global structure

One of the puzzles of learning to talk or play a musical instrument is how we learn which movement produces a particular sound: an audiomotor map. The initial stages of map acquisition can be studied by having participants learn arm movements to auditory targets. The key question is what mechanism drives this early learning. Three learning processes from previous literature were tested: map learning may rely on active motor outflow (target), on error correction, and on the correspondence between sensory and motor distances (i.e., that similar movements map to similar sounds). Alternatively, we hypothesized that map learning can proceed without these. Participants made movements that were mapped to sounds in a number of different conditions that each precluded one of the potential learning processes. We tested whether map learning relies on assumptions about topological continuity by exposing participants to a permuted map that did not preserve distances in auditory and motor space. Further groups were tested who passively experienced the targets, kinematic trajectories produced by a robot arm, and auditory feedback as a yoked active participant (hence without active motor outflow). Another group made movements without receiving targets (thus without experiencing errors). In each case we observed substantial learning, therefore none of the three hypothesized processes is required for learning. Instead early map acquisition can occur with free exploration without target error correction, is based on sensory-to-sensory correspondences, and possible even for discontinuous maps. The findings are consistent with the idea that early sensorimotor map formation can involve instance-specific learning.NEW & NOTEWORTHY This study tested learning of novel sensorimotor maps in a variety of unusual circumstances, including learning a mapping that was permuted in such as way that it fragmented the sensorimotor workspace into discontinuous parts, thus not preserving sensory and motor topology. Participants could learn this mapping, and they could learn without motor outflow or targets. These results point to a robust learning mechanism building on individual instances, inspired from machine learning literature.