Credit assignment between body and object probed by an object transportation task

Movement-goal relevant object shape properties act as poor but viable cues for the attribution of motor errors to external objects

When a context change is detected during motor learning, motor memories-internal models for executing movements within some context-may be created or existing motor memories may be activated and modified. Assigning credit to plausible causes of errors can allow for fast retrieval and activation of a motor memory, or a combination of motor memories, when the presence of such causes is detected. Features of the movement-context intrinsic to the movement dynamics, such as posture of the end effector, are often effective cues for detecting context change whereas features extrinsic to the movement dynamics, such as the colour of an object being moved, are often not. These extrinsic cues are typically not relevant to the motor task at hand and can be safely ignored by the motor system. We conducted two experiments testing if extrinsic but movement-goal relevant object-shape cues during an object-transport task can act as viable contextual cues for error assignment to the object, and the creation of new, object-shape-associated motor memories. In the first experiment we find that despite the object-shape cues, errors are primarily attributed to the hand transporting the object. In a second experiment, we find participants can execute differing movements cued by the object shape in a dual adaptation task, but the extent of adaptation is small, suggesting that movement-goal relevant object-shape properties are poor but viable cues for creating context specific motor memories.

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.

How different effectors and action effects modulate the formation of separate motor memories

Humans can operate a variety of modern tools, which are often associated with different visuomotor transformations. Studies investigating this ability have shown that separate motor memories can be acquired implicitly when different sensorimotor transformations are associated with distinct (intended) postures or explicitly when abstract contextual cues are leveraged by aiming strategies. It still remains unclear how different transformations are remembered implicitly when postures are similar. We investigated whether features of planning to manipulate a visual tool, such as its visual identity or the environmental effect intended by its use (i.e. action effect) would enable implicit learning of opposing visuomotor rotations. Results show that neither contextual cue led to distinct implicit motor memories, but that cues only affected implicit adaptation indirectly through generalization around explicit strategies. In contrast, a control experiment where participants practiced opposing transformations with different hands did result in contextualized aftereffects differing between hands across generalization targets. It appears that different (intended) body states are necessary for separate aftereffects to emerge, suggesting that the role of sensory prediction error-based adaptation may be limited to the recalibration of a body model, whereas establishing separate tool models may proceed along a different route.

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)

Sensorimotor priors are effector dependent

During sensorimotor tasks, subjects use sensory feedback but also prior information. It is often assumed that the sensorimotor prior is just given by the experiment and that the details for acquiring this prior (e.g., the effector) are irrelevant. However, recent research has suggested that the construction of priors is nontrivial. To test if the sensorimotor details matter for the construction of a prior, we designed two tasks that differ only in the effectors that subjects use to indicate their estimate. For both a typical reaching setting and an atypical wrist rotation setting, prior and feedback uncertainty matter as quantitatively predicted by Bayesian statistics. However, in violation of simple Bayesian models, the importance of the prior differs across effectors. Subjects overly rely on their prior in the typical reaching case compared with the wrist case. The brain is not naively Bayesian with a single and veridical prior. NEW & NOTEWORTHY Traditional Bayesian models often assume that we learn statistics of movements and use the information as a prior to guide subsequent movements. The effector is merely a reporting modality for information processing. We asked subjects to perform a visuomotor learning task with different effectors (finger or wrist). Surprisingly, we found that prior information is used differently between the effectors, suggesting that learning of the prior is related to the movement context such as the effector involved or that naive models of Bayesian behavior need to be extended.