Levels of explanation and the workings of science

Abstract

I address two questions that underlie most of the articles in this special issue: 1) What do different levels of explanation in psychology reveal? And 2) how do the dynamics of science affect what can be learned? I suggest that understanding hypothesis testing and generation in the abstract can provide a useful framework for understanding how cognitive modelling and neuroscience may interact. I further suggest that the preference for simple explanations and the dynamics of hypothesis testing may play out in different ways within the two fields, and that their overlap may prove most useful in the realm of hypothesis generation.