Long-term retention of proprioceptive recalibration

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.

The Influence of Age on the Intermanual Transfer and Retention of Implicit Visuomotor Adaptation

We examined age-related changes in intermanual transfer and retention of implicit visuomotor adaptation. We further asked if providing augmented somatosensory feedback regarding movement endpoint would enhance visuomotor adaptation. Twenty young adults and twenty older adults were recruited and randomly divided into an Augmented Feedback group and a Control group. All participants reached to five visual targets with visual feedback rotated 30° counter-clockwise relative to their actual hand motion. Augmented somatosensory feedback was provided at the end of the reach via the robotic handle that participants held. Implicit adaptation was assessed in the absence of visual feedback in the right trained hand and in the left untrained hand following rotated training trials to establish implicit adaptation and intermanual transfer of adaptation respectively. Participants then returned 24 hours later to assess retention in the trained and untrained hands. Results revealed that older adults demonstrated a comparable magnitude of implicit adaptation, transfer and retention of visuomotor adaptation as observed in younger adults, regardless of the presence of augmented somatosensory feedback. To conclude, when visuomotor adaptation is driven implicitly, intermanual transfer and retention do not differ significantly between young and older adults, even when the availability of augmented somatosensory feedback is manipulated.

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.

Intermanual transfer and retention of visuomotor adaptation to a large visuomotor distortion are driven by explicit processes

Reaching with a visuomotor distortion in a virtual environment leads to reach adaptation in the trained hand, and in the untrained hand. In the current study we asked if reach adaptation in the untrained (right) hand is due to transfer of explicit adaptation (EA; strategic changes in reaches) and/or implicit adaptation (IA; unconscious changes in reaches) from the trained (left) hand, and if this transfer changes depending on instructions provided. We further asked if EA and IA are retained in both the trained and untrained hands. Participants (n = 60) were divided into 3 groups (Instructed (provided with instructions on how to counteract the visuomotor distortion), Non-Instructed (no instructions provided), and Control (EA not assessed)). EA and IA were assessed in both the trained and untrained hands immediately following rotated reach training with a 40° visuomotor distortion, and again 24 hours later by having participants reach in the absence of cursor feedback. Participants were to reach (1) so that the cursor landed on the target (EA + IA), and (2) so that their hand landed on the target (IA). Results revealed that, while initial EA observed in the trained hand was greater for the Instructed versus Non-Instructed group, the full extent of EA transferred between hands for both groups and was retained across days. IA observed in the trained hand was greatest in the Non-Instructed group. However, IA did not significantly transfer between hands for any of the three groups. Limited retention of IA was observed in the trained hand. Together, these results suggest that while initial EA and IA in the trained hand are dependent on instructions provided, transfer and retention of visuomotor adaptation to a large visuomotor distortion are driven almost exclusively by EA.

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)

Visual and proprioceptive recalibrations after exposure to a visuomotor rotation

Adaptation to a visuomotor rotation in a cursor-control task is accompanied by proprioceptive recalibration, whereas the existence of visual recalibration is uncertain and has even been doubted. In the present study, we tested both visual and proprioceptive recalibration; proprioceptive recalibration was not only assessed by means of psychophysical judgments of the perceived position of the hand, but also by an indirect procedure based on movement characteristics. Participants adapted to a gradually introduced visuomotor rotation of 30° by making center-out movements to remembered targets. In subsequent test trials, they made center-out movements without visual feedback or observed center-out motions of a cursor without moving the hand. In each test trial, they judged the endpoint of hand or cursor by matching the position of the hand or of a visual marker, respectively, moving along a semicircular path. This path ran through all possible endpoints of the center-out movements. We observed proprioceptive recalibration of 7.3° (3.1° with the indirect procedure) and a smaller, but significant, visual recalibration of 1.3°. Total recalibration of 8.6° was about half as strong as motor adaptation, the adaptive shift of the movement direction. The evidence of both proprioceptive and visual recalibration was obtained with a judgment procedure that suggests that recalibration is restricted to the type of movement performed during exposure to a visuomotor rotation. Consequently, identical physical positions of the hand can be perceived differently depending on how they have been reached, and similarly identical positions of a cursor on a monitor can be perceived differently.

Going offline: differences in the contributions of movement control processes when reaching in a typical versus novel environment

Human movements are remarkably adaptive. We are capable of completing movements in a novel visuomotor environment with similar accuracy to those performed in a typical environment. In the current study, we examined if the control processes underlying movements under typical conditions were different from those underlying novel visuomotor conditions. 16 participants were divided into two groups, one receiving continuous visual feedback during all reaches (CF), and the other receiving terminal feedback regarding movement endpoint (TF). Participants trained in a virtual environment by completing 150 reaches to three targets when (1) a cursor accurately represented their hand motion (i.e., typical environment) and (2) a cursor was rotated 45° clockwise relative to their hand motion (i.e., novel environment). Analyses of within-trial measures across 150 reaching trials revealed that participants were able to demonstrate similar movement outcomes (i.e., movement time and angular errors) regardless of visual feedback or reaching environment by the end of reach training. Furthermore, a reduction in variability across several measures (i.e., reaction time, movement time, time after peak velocity, and jerk score) over time showed that participants improved the consistency of their movements in both reaching environments. However, participants took more time and were less consistent in the timing of initiating their movements when reaching in a novel environment compared to reaching in a typical environment, even at the end of training. As well, angular error variability at different proportions of the movement trajectory was consistently greater when reaching in a novel environment across trials and within a trial. Together, the results suggest a greater contribution of offline control processes and less effective online corrective processes when reaching in a novel environment compared to when reaching in a typical environment.