Building on the previous chapters, this final chapter addresses the preeminently multidisciplinary question of how human cognitive architecture might be implemented in the brain's neural architecture. Focusing on perceptual organization, this question is addressed in a pluralist way which — sustained by neuroscientific evidence and metatheoretical considerations — combines complementary insights from representational, connectionist, and dynamic systems approaches to cognition. To this end, I expand on van der Helm (2012) and I revisit several things from the previous chapters to discuss them in the light of this cognitive architecture question. Next, I briefly introduce the main ingredients.

Cognitive architecture. The term cognitive architecture (or unified theory of cognition) refers to computational models of not only resulting behavior but also structural properties of intelligent systems (Anderson, 1983; Newell, 1990). These structural properties can be physical properties as well as more abstract properties implemented in physical systems such as computers and brains. There is no consensus about what these structural properties should be, and indeed, many different cognitive architecture models have been proposed (for extensive reviews, see, e.g., Langley, Laird, & Rogers, 2009; Sun, 2004). These models differ, for instance, in whether they involve fixed or flexible architectures, in what forms of processing they allow, and in the extent to which they are based on a set of symbolic information-processing rules applied by one central processor or rely on emergent properties of many interacting processing units.