This chapter discusses the importance of dynamics to understanding cognition. The author turns to the issue of how dynamics have been integrated into various theories of cognition. The author describes strengths and weaknesses of three main contenders in cognitive science, in relation to their incorporation of time into their methods of model construction. The neural engineering framework (NEF) is a general theory of neurobiological systems. Neural dynamics are characterized by considering neural representations as control theoretic state variables. Thus, the dynamics of neurobiological systems can be analyzed using control theory. The model employs biologically realistic neurons to learn the relevant structural transformations appropriate for a given context, and it generalizes such transformations to novel contents with the same syntactic structure. The intent of the NEF is to provide a suggestion as to how we might take seriously many of the important insights generated from cognitive science.