Structural learning in feedforward and feedback control

Abstract

Yousif N, Diedrichsen J. Structural learning in feedforward and feedback control. J Neurophysiol 108: 2373-2382, 2012. First published August 15, 2012 doi:10.1152/jn.00315.2012.-For smooth and efficient motor control, the brain needs to make fast corrections during the movement to resist possible perturbations. It also needs to adapt subsequent movements to improve future performance. It is important that both feedback corrections and feedforward adaptation need to be made based on noisy and often ambiguous sensory data. Therefore, the initial response of the motor system, both for online corrections and adaptive responses, is guided by prior assumptions about the likely structure of perturbations. In the context of correcting and adapting movements perturbed by a force field, we asked whether these priors are hard wired or whether they can be modified through repeated exposure to differently shaped force fields. We found that both feedback corrections to unexpected perturbations and feedforward adaptation to a new force field changed, such that they were appropriate to counteract the type of force field that participants had experienced previously. We then investigated whether these changes were driven by a common mechanism or by two separate mechanisms. Participants experienced force fields that were either temporally consistent, causing sustained adaptation, or temporally inconsistent, causing little overall adaptation. We found that the consistent force fields modified both feedback and feedforward responses. In contrast, the inconsistent force field modified the temporal shape of feedback corrections but not of the feedforward adaptive response. These results indicate that responses to force perturbations can be modified in a structural manner and that these modifications are at least partly dissociable for feedback and feedforward control.

Environmental Consistency Determines the Rate of Motor Adaptation

“…This finding is in line with a recent study by Yousif and Diedrichsen [16] showing that adaptive changes in feedback responses could be observed in both consistent and inconsistent environments, whereas changes in feedforward adaptation were only present in consistent environments. The positive relationship between environmental variability and feedback response strength is in line with several previous studies [17–21] and consistent with the idea that the variance of an environment informs the variance of the prior for Bayesian integration [22–25].…”

Skilled forelimb movements and internal copy motor circuits

“…In separate studies, Magescas and colleagues and Yousif and Diedrichsen found that online corrections can arise with or without adaptation depending on the nature of perturbation, implying that these phenomena, and thus their underlying mechanisms, are dissociable [28,29]. Moreover, motor learning need not result from a forward model-based process at all; Huang and colleagues have shown that task success, independent of sensory error driven adaptation, can reshape motor output [30], supporting the existence of model-free approaches to motor learning [23,26].…”

Minimally invasive surgery training using multiple port sites to improve performance

“…If surgeons are able to learn general rules about how port properties vary this may alleviate the negative consequences associated with port switching. Experimental findings show that training regimes in which task parameters are randomly or gradually varied provide support for the extraction of structural rules [2,[7][8][9]. Even when the structural rules are not extracted, motor task variation can improve future performance through other mechanisms [10][11][12][13].…”