The Roles of Feedback and Feedforward as Humans Learn to Control Unknown Dynamic Systems

IEEE Trans Cybern. 2018 Feb;48(2):543-555. doi: 10.1109/TCYB.2016.2646483. Epub 2017 Jan 26.

Abstract

We present results from an experiment in which human subjects interact with an unknown dynamic system 40 times during a two-week period. During each interaction, subjects are asked to perform a command-following (i.e., pursuit tracking) task. Each subject's performance at that task improves from the first trial to the last trial. For each trial, we use subsystem identification to estimate each subject's feedforward (or anticipatory) control, feedback (or reactive) control, and feedback time delay. Over the 40 trials, the magnitudes of the identified feedback controllers and the identified feedback time delays do not change significantly. In contrast, the identified feedforward controllers do change significantly. By the last trial, the average identified feedforward controller approximates the inverse of the dynamic system. This observation provides evidence that a fundamental component of human learning is updating the anticipatory control until it models the inverse dynamics.

MeSH terms

  • Adolescent
  • Adult
  • Algorithms
  • Feedback
  • Humans
  • Learning / physiology*
  • Models, Neurological*
  • Psychomotor Performance / physiology*
  • Signal Processing, Computer-Assisted
  • Young Adult