Abstract

A new strategy for moving forward in the characterization of the Global Neuronal Workspace (GNW) is proposed. According to Dehaene, Changeux and colleagues, broadcasting is the main function of the GNW. However, the dynamic network properties described by recent graph-theoretic GNW models are consistent with many large-scale communication processes that are different from broadcasting. We propose to apply a different graph-theoretic approach, originally developed for optimizing information dissemination in communication networks, which can be used to identify the pattern of frequency and phase-specific directed functional connections that the GNW would exhibit only if it were a broadcasting network.