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

Abstract

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.

Sensing hand position in Ehlers-Danlos Syndrome

“…We found a significant main effect of training (F (1, 28) = 58.85, p < .001, ŋ² = 0.220), a significant main effect of localization type (F (1, 28) = 5.78, p = .023, ŋ² = 0.005) and a significant interaction between training and localization type (F (1, 28) = 17.77, p < .001, ŋ² = 0.009). This suggests that estimates of unseen hand location shifted following reach training with a rotated cursor and that the size of these shifts were slightly larger for active localization compared to passive localization (illustrated in figures 5C & 5D), as found in previous studies from our lab [11][12][13]. Since the focus of the current study is concerned with exploring these patterns in EDS, we then investigated group differences in active and passive localization shifts (by subtracting aligned localizations from rotated localizations to create a measure of localization shift) and conducted a 2 X 2 mixed design ANOVA on localization shifts with localization type (active or passive) as a within-subjects factor and group (EDS or control) as a between-subjects factor.…”

“…The hand localization tasks (figure 1B) were used to measure acuity of unseen hand localization and have been established as a reliable measure of proprioceptive abilities [9][10][11][12][13][14]. In the active hand localization tasks, participants moved their own hand to a self-chosen position on the arc, and thus both afferent and efferent information was available.…”

Implicit motor learning within three trials

“…More compelling evidence comes from previous studies where a strong correlation between these measures was found 24 , 26 . We have shown that the size of both proprioceptive and predictive components of hand localization shifts can predict separate components of reach aftereffects 41 . However, all evidence that hand localization shifts contribute to reach aftereffects is correlational, so that the mechanism remains unknown.…”

“…In the second approach for measuring implicit adaptation, which uses error-clamped feedback to get at the time course of implicit adaptation, participants are instructed about the nature of the paradigm, prompted to ignore the visual feedback, and faced with unnaturally smooth reach trajectories throughout the task 12 , 40 . Since this context necessarily increases external error attribution it should also suppress implicit learning 41 . This could explain why error-clamped feedback paradigms slow down implicit adaptation compared to how it naturally occurs here.…”

Individual differences in proprioception predict the extent of implicit sensorimotor adaptation

“…The size of the shift tends to range between 5 and 10 and remains relatively stable, evidenced by probing sensed hand position following passive hand displacement at various timepoints in an adaptation study (12,(29)(30)(31)(32)(33)(34)(35)(36). Similar to multisensory integration, this shift presumably reflects the operation of a system seeking to establish a unified percept from discrepant sensory signals.…”