ABSTRACT
Computational models (CMs) have increased in popularity in the psychological sciences over the three decades since the parallel distributed processing revolution of the mid-1980s. As the use of CMs has increased in popularity, diverse frameworks have been developed to implement a range of theoretical concepts. The domain of executive function (EF) development presents unique challenges for theoretical explanations. The first challenge concerns definitions and terminology. EF is commonly characterized as a multi-faceted construct. Central aspects of EF such as working memory, inhibition, and attention have been the focus of theoretical debate. Computational models of EF development have focused on the same touchstone paradigms: the A-not-B task and the Dimensional Change Card Sort task. These tasks have garnered so much attention because they provide rich information about development. Both tasks reveal a qualitative shift in performance that is accompanied by change in neural activation.
