Neuromotor Noise Limits Motor Performance, But Not Motor Adaptation, in Children

Abstract

Children do not typically appear to move with the same skill and dexterity as adults, although they can still improve their motor performance in specific tasks with practice. One possible explanation is that their motor performance is limited by an inherently higher level of movement variability, but that their motor adaptive ability is robust to this variability. To test this hypothesis, we examined motor adaptation of 43 children (ages 6-17) and 12 adults as they reached while holding the tip of a lightweight robot. The robot applied either a predictable, velocity-dependent field (the "mean field") or a similar field that incorporated stochastic variation (the "noise field"), thereby further enhancing the variability of the subjects' movements. We found that children exhibited greater initial trial-to-trial variability in their unperturbed movements but were still able to adapt comparably to adults in both the mean and noise fields. Furthermore, the youngest children (ages 6-8) were able to reduce their variability with practice to levels comparable to the remaining children groups although not as low as adults. These results indicate that children as young as age 6 possess adult-like neural systems for motor adaptation and internal model formation that allow them to adapt to novel dynamic environments as well as adults on average despite increased neuromotor or environmental noise. Performance after adaptation is still more variable than adults, however, indicating that movement inconsistency, not motor adaptation inability, ultimately limits motor performance by children and may thus account for their appearance of incoordination and more frequent motor accidents (e.g., spilling, tripping). The results of this study also suggest that movement variability in young children may arise from two sources--a relatively constant, intrinsic source related to fundamental physiological constraints of the developing motor system and a more rapidly modifiable source that is modulated depending on the current motor context.

Motor learning in childhood reveals distinct mechanisms for memory retention and re-learning

“…However, our results indicate that age is the better predictor of re-learning than variability in the motor pattern. This is consistent with previous work from our group and others (Takahashi et al 2003), which showed that increased movement variability did not limit motor adaptation (i.e., learning). Furthermore, in adults increased motor variability during baseline was found to facilitate same-day learning during reaching adaptation (Wu et al 2014).…”

Impairment of Spatial Performance by Environmental Noise

“…So silent conditions (LI in this experiment) may be associated with under-arousal so that noise may elevate arousal to a more optimal level; thereby increasing task performance [24]. Another suggestion of this improvement is about adaptation with moderate levels so that rats can have an appropriate attention and good performance [6,13,25,26].…”

“…For example, noise impairs human task performance most likely in the case of unexpected bursts of noise presented during tasks, whether it involves the continuous intake of new information [1,2], and also the psychomotor task impaired by brief experimentally imposed noise in human [3]. In contrast of these studies, It has been shown that addition of an appropriate amount of noise can improve signal detection in a nonlinear system called stochastic resonance [4]; human hearing and the ability of encoding temporal information can increase by noise [5][6][7]. Nevill et al [8] found that crowd noise influenced referee's decisions at favor of the home team.…”

Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review

“…Among other topics, research on human motor control focuses on motor adaptation within a changing environment (e.g., Shadmehr & Mussa-Ivaldi, 1994), age-related learning (e.g., Takahashi et al, 2003), generalization and transfer of skills from one movement to another (e.g., Conditt, Gandolfo, & Mussa-Ivaldi, 1997;Oakley & O'Modhrain, 2005), internal versus external focus during task execution (e.g., Criscimagna-Hemminger, Donchin, Gazzaniga, & Shadmehr, 2003;Shadmehr & Moussavi, 2000), and internal movement representation (e.g., Haruno et al, 2001;Todorov, 2004). To investigate these topics, researchers have developed devices that provide haptic interaction and assess a subject's performance simultaneously.…”