Dissociable effects of the implicit and explicit memory systems on learning control of reaching

Abstract

Adaptive control of reaching depends on internal models that associate states in which the limb experienced a force perturbation with motor commands that can compensate for it. Limb state can be sensed via both vision and proprioception. However, adaptation of reaching in novel dynamics results in generalization in the intrinsic coordinates of the limb, suggesting that the proprioceptive states in which the limb was perturbed dominate representation of limb state. To test this hypothesis, we considered a task where position of the hand during a reach was correlated with patterns of force perturbation. This correlation could be sensed via vision, proprioception, or both. As predicted, when the correlations could be sensed only via proprioception, learning was significantly better as compared to when the correlations could only be sensed through vision. We found that learning with visual correlations resulted in subjects who could verbally describe the patterns of perturbations but this awareness was never observed in subjects who learned the task with only proprioceptive correlations. We manipulated the relative values of the visual and proprioceptive parameters and found that the probability of becoming aware strongly depended on the correlations that subjects could visually observe. In all conditions, aware subjects demonstrated a small but significant advantage in their ability to adapt their motor commands. Proprioceptive correlations produced an internal model that strongly influenced reaching performance yet did not lead to awareness. Visual correlations strongly increased the probability of becoming aware, yet had a much smaller but still significant effect on reaching performance. Therefore, practice resulted in acquisition of both implicit and explicit internal models.

A dissociation between visual and motor workspace inhibits generalization of visuomotor adaptation across the limbs

“…Similarly, Galea et al (2007) recently reported that a concurrent adaptation to two opposing force fields with one arm transferred positively to improve subsequent performance of the same task with other arm across an intrinsic coordinative system, whereas across an extrinsic coordinative system, neither positive nor negative transfer was observed, probably because the information to be transferred was not useful (i.e., incompatible). This interpretation of the current finding also appears to be somewhat consistent with an idea recently proposed by Hwang et al (2006), which states that two internal models are formed during adaptation to novel dynamics, one based on proprioception and the other on vision, and that performance is a sum of these two internal models. Especially given that the planning of reaches to visual and proprioceptive targets may involve distinct sensorimotor transformations , it seems plausible that a conflict between these two types of internal representations may pose a serious computation problem to the motor control system.…”

Adaptation Paths to Novel Motor Tasks Are Shaped by Prior Structure Learning

“…It is well known, for example, that if a visuomotor perturbation or a force field is introduced gradually, then subjects successfully adapt to it without ever becoming aware of any perturbation (Jakobson and Goodale, 1989;Kagerer et al, 1997;Klassen et al, 2005;Michel et al, 2007). Even though the effects of an explicit cognitive strategy and implicit, "genuine," motor adaptation are often hard to disentangle, carefully designed experiments allow to separate them (Malfait and Ostry, 2004;Hwang et al, 2006;Mazzoni and Krakauer, 2006). In a similar vein, our present results show that structure learning is part of the implicit motor system.…”

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

“…Similarly, the current and previous experiments suggest that error clamps can serve as both readouts for processes captured by state-space models and a trigger for additional learning processes. Zero-errorclamp trials, in which feedback is constrained to zero and decoupled from subjects' behavior, have led to insights into learning processes that are well captured by state-space models (Hwang et al, 2006;Criscimagna-Hemminger and Shadmehr, 2008;Tanaka et al, 2009). However, an increasing body of evidence has demonstrated that zero-error clamps are not innocuous but can induce subjects to actively change their learning policy (Pekny et al, 2011;Shmuelof et al, 2011;Vaswani and Shadmehr, 2013).…”