@article{174936,
  author = {Raphael Schween and Samuel D. McDougle and Mathias Hegele and Jordan A. Taylor},
  title = {Assessing explicit strategies in force field adaptation},
  abstract = { In recent years, it has become increasingly clear that a number of learning processes are at play in visuomotor adaptation tasks. In addition to implicitly adapting to a perturbation, learners can develop explicit knowledge allowing them to select better actions in responding to it. Advances in visuomotor rotation experiments have underscored the important role of such {\textquotedblleft}explicit learning{\textquotedblright} in shaping adaptation to kinematic perturbations. Yet, in adaptation to dynamic perturbations, its contribution has been largely overlooked. We therefore sought to approach the assessment of explicit learning in adaptation to dynamic perturbations, by developing two novel modifications of a force field experiment. First, we asked learners to abandon any cognitive strategy before selected force channel trials to expose consciously accessible parts of overall learning. Here, learners indeed reduced compensatory force compared with standard Catch channels. Second, we instructed a group of learners to mimic their right hand{\textquoteright}s adaptation by moving with their na{\"\i}ve left hand. While a control group displayed negligible left hand force compensation, the mimicking group reported forces that approximated right hand adaptation but appeared to under-report the velocity component of the force field in favor of a more position-based component. Our results highlight the viability of explicit learning as a potential contributor to force field adaptation, though the fraction of learning under participants{\textquoteright} deliberate control on average remained considerably smaller than that of implicit learning, despite task conditions favoring explicit learning. The methods we employed provide a starting point for investigating the contribution of explicit strategies to force field adaptation. },
  year = {2020},
  journal = {J Neurophysiol},
  volume = {123},
  pages = {1552-1565},
  doi = {10.1152/jn.00427.2019},
  language = {eng},
}