title: A computational model of a global neuronal workspace with stochastic connections.
abstract: This paper presents a model of long-range cortical communication by means of a global neuronal workspace similar to that proposed by Dehaene and Naccache (2001). The model resembles that of Shanahan (2008), which was based on reverberating circuits of one-to-one connections, but uses a stochastic wiring regime in place of the highly regular scheme used there. The paper offers a systematic analysis of the influence of certain parameters on the dynamics of networks built according to this regime. Armed with a fuller understanding of the origins of the observed behaviour in the model, the qualitative behaviour of the previous model is replicated, and further unexplored choices are examined for ongoing work.
authors.affiliation: Department of Computing, Imperial College London, 180 Queen’s Gate, London, England, UK. dustin.connor02@imperial.ac.uk
authors.forename: Dustin
authors.initials: D
authors.lastname: Connor
authors.forename: Murray
authors.initials: M
authors.lastname: Shanahan
mesh_terms: D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009433:Neural Inhibition / Q000502:physiology; D009474:Neurons / Q000502:physiology*