Feedforward compensation for novel dynamics depends on force field orientation but is similar for the left and right arms

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Abstract
There are well-documented differences in the way that people typically perform identical motor tasks with their dominant and the nondominant arms. According to Yadav and Sainburg's (Neuroscience 196: 153–167, 2011) hybrid-control model, this is because the two arms rely to different degrees on impedance control versus predictive control processes. Here, we assessed whether differences in limb control mechanisms influence the rate of feedforward compensation to a novel dynamic environment. Seventy-five healthy, right-handed participants, divided into four subsamples depending on the arm (left, right) and direction of the force field (ipsilateral, contralateral), reached to central targets in velocity-dependent curl force fields. We assessed the rate at which participants developed predictive compensation for the force field using intermittent error-clamp trials and assessed both kinematic errors and initial aiming angles in the field trials. Participants who were exposed to fields that pushed the limb toward ipsilateral space reduced kinematic errors more slowly, built up less predictive field compensation, and relied more on strategic reaiming than those exposed to contralateral fields. However, there were no significant differences in predictive field compensation or kinematic errors between limbs, suggesting that participants using either the left or the right arm could adapt equally well to novel dynamics. It therefore appears that the distinct preferences in control mechanisms typically observed for the dominant and nondominant arms reflect a default mode that is based on habitual functional requirements rather than an absolute limit in capacity to access the controller specialized for the opposite limb.
Funding Information
  • Department of Industry, Innovation, Science, Research and Tertiary Education, Australian Government | Australian Research Council (ARC) (FT120100391)
  • University of Queensland, HaBs Research Collaboration Seeding Grant
  • University of Queensland, Postdoctoral Research Fellowship (2014001463)

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