Measures of explicit and implicit in motor learning: what we know and what we don’t

Multiple different processes are known to contribute to sensorimotor learning, and adaptation tasks have been a key tool in characterizing these underlying processes. Recently, much interest has focused on quantifying the explicit and implicit components of motor adaptation using a variety of methods. The methods differ in their underlying assumptions and ideas. In some cases, they yield similar findings, in others they do not. We review the literature with a focus on the agreement and inconsistencies between different measures of explicit adaptation. Some aspects of explicit adaptation seem robust across different measurements: the fast time constant of the explicit system and the slow time constant of the implicit system, for instance. Other aspects seem to reflect quite differently across measures: for example, the extent to which explicit and implicit combine linearly. To help understand these differences, we explored ideas of explicit and implicit learning in the context of the larger field of cognitive science. We found that non-linearity and a possible bias in the measurements make explicit and implicit learning difficult to measure across different fields within cognitive science. We relate this back to the study of motor adaptation, arguing that the only way forward is through a strong experimental characterization of the phenomenology of our visuomotor adaptation and a rich set of models to test on it.