ABSTRACT
We address an omnipresent and pervasive form of human learning—skill refinement, the improvement in performance of a cognitive or motor skill with practice. A simple and well studied example of skill refinement is the psychological phenomenon of long-term repetition priming:: Participants asked to identify briefly presented words are more accurate if they recently viewed the word. We simulate various phenomena of repetition priming using a probabilistic model that characterizes the time course of information transmission through processing pathways. The model suggests two distinct mechanisms of adaptation with experience, one that updates prior probabilities of pathway outputs, and one that increases the instantaneous probability of information transmission through a pathway. These two mechanisms loosely correspond to bias and sensitivity effects that have been observed in experimental studies of priming. The mechanisms are extremely sensible from a rational perspective, and can also explain phenomena of skill learning, such as the power law of practice. Although other models have been proposed of these phenomena, we argue for the probabilistic pathway model on grounds of parsimony and the elegant computational perspective it offers.
