Persistent Residual Errors in Motor Adaptation Tasks: Reversion to Baseline and Exploratory Escape

Abstract

When movements are perturbed in adaptation tasks, humans and other animals show incomplete compensation, tolerating small but sustained residual errors that persist despite repeated trials. State-space models explain this residual asymptotic error as interplay between learning from error and reversion to baseline, a form of forgetting. Previous work using zero-error-clamp trials has shown that reversion to baseline is not obligatory and can be overcome by manipulating feedback. We posited that novel error-clamp trials, in which feedback is constrained but has nonzero error and variance, might serve as a contextual cue for recruitment of other learning mechanisms that would then close the residual error. When error clamps were nonzero and had zero variance, human subjects changed their learning policy, using exploration in response to the residual error, despite their willingness to sustain such an error during the training block. In contrast, when the distribution of feedback in clamp trials was naturalistic, with persistent mean error but also with variance, a statespace model accounted for behavior in clamps, even in the absence of task success. Therefore, when the distribution of errors matched those during training, state-space models captured behavior during both adaptation and error-clamp trials because error-based learning dominated; when the distribution of feedback was altered, other forms of learning were triggered that did not follow the state-space model dynamics exhibited during training. The residual error during adaptation appears attributable to an error-dependent learning process that has the property of reversion toward baseline and that can suppress other forms of learning.

Characteristics of Implicit Sensorimotor Adaptation Revealed by Task-irrelevant Clamped Feedback

“…Previous studies have used clamped visual feedback to induce adaptation, but their participants were not informed that feedback would be clamped; as such, the participants likely believed that changes in their behavior could affect this feedback to reinstate good task performance (Vaswani et al, 2015; Scheidt, Conditt, Secco, & Mussa-Ivaldi, 2005). A critical difference between previous clamp studies and our method is that we fully informed participants of the nature of the manipulation and asked them to ignore it.…”

Formation of a long-term memory for visuomotor adaptation following only a few trials of practice

“…Why would one remember an action or aiming direction that was ultimately unsuccessful (i.e., led to a target miss), as is often the case given the bias toward baseline often exhibited at asymptote (Kitago et al 2013;van der Kooij et al 2015;Vaswani et al 2015)? It is plausible that a memory for action could be formed because of strong positive reward prediction errors experienced by subjects during the initial course of adaptation.…”

Of hands, tools, and exploding dots: How different action states and effects separate visuomotor memories

“…Under this view, implicit, context-dependent learning could, for example, be achieved by proceduralization of strategies at the action selection level, in line with canonical views of skill learning (Fitts and Posner 1967;Willingham 1998). Recent findings have shown that that new policies can be learned by exploration and reinforcement (Shmuelof et al 2012;Vaswani et al 2015), and that this is closely tied to explicit strategies Holland et al 2018). A possibility is that explicit action selection tendencies may become proceduralized by associative learning.…”