A cortical architecture for parallel anticipation of sensorimotor sequences

The basic idea of the authors´ anticipatory approach to perception is to avoid the common separation of perception and generation of behavior and to fuse both aspects into a consistent neural process. The authors´ approach is based on the prediction of the consequences of hypothetically executed actions. In this sense, perception of space and shape is assumed to be a generative process of anticipating the course of events resulting from different sequences of actions. The authors present a biologically motivated computational model that is able to anticipate and evaluate hypothetical sensorimotor sequences. Their model for anticipation based on cortical representations (MACOR) allows a completely parallel search at the neocortical level using assemblies of rate coded neurons for grouping, separation, and selection of sensorimotor sequences