Temporal structure of motor variability is dynamically regulated and predicts motor learning ability

Abstract

Individual differences in motor learning ability are widely acknowledged, yet little is known about the factors that underlie them. Here we explore whether movement-to-movement variability in motor output, a ubiquitous if often unwanted characteristic of motor performance, predicts motor learning ability. Surprisingly, we found that higher levels of task-relevant motor variability predicted faster learning both across individuals and across tasks in two different paradigms, one relying on reward-based learning to shape specific arm movement trajectories and the other relying on error-based learning to adapt movements in novel physical environments. We proceeded to show that training can reshape the temporal structure of motor variability, aligning it with the trained task to improve learning. These results provide experimental support for the importance of action exploration, a key idea from reinforcement learning theory, showing that motor variability facilitates motor learning in humans and that our nervous systems actively regulate it to improve learning.

Automated Feedback Selection for Robot-Assisted Training

“…Findings of prediction models that generalize to new subjects could help to improve feedback designs. Researchers often conclude in their data analyses that certain measures can be used to predict the degree of motor learning (Joiner & Smith, 2008;Wu, Miyamoto, Castro, Ölveczky, & Smith, 2014). However, we have not found any literature that creates predictive models of such a finding, and quantifies generalization to new subjects in new experiments.…”

A Lag in Speech Motor Coordination During Sentence Production Is Associated With Stuttering Persistence in Young Children

“…Under a dynamic view of development, the unstable speech motor control of some CWS-Per may be an adaptive effect of a maturational lag in neurodevelopment underlying language acquisition. Although speculative, the relatively greater speech motor plasticity of some CWS-Per may indicate a period of dynamic speech-language learning and movement exploration (Goffman, 2010;Wu, Miyamoto, Castro, Ölveczky, & Smith, 2014). In contrast, the speech motor abilities of CWS-Rec have stabilized to the level of typically developing fluent children.…”

Motor neuronal activity varies least among individuals when it matters most for behavior

“…Variations in "motor program styles" have been observed in a wide variety of animals (e.g., leech; Calabrese et al 2011) and in humans. For example, a recent study in humans showed that regulation of individual temporal variability in motor output could enhance learning speed (Wu et al 2014).…”

“…11). The methodology described in this report is likely to be of general use for the study of motor systems, muscle synergies, the role of sensory feedback, how humans may exploit variability to improve in motor tasks, and behavioral discrimination (e.g., Kim and Shadlen 1999;Tresch and Jarc 2009;Wu et al 2014). …”

“…If a squirrel monkey succeeds in plucking a breadfruit, different hand trajectories or force profiles are adaptively equivalent. Variations in responses and in individuals have been found in animals ranging from insects (Hooper et al 2006) to humans (Borzelli et al 1999;Nussbaum and Chaffin 1997;Wu et al 2014).…”