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Updated: Jun 10, 2026

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
Published on: November 1, 2019
A computational model of a global neuronal workspace with stochastic connections
Dustin Connor1, Murray Shanahan
1Department of Computing, Imperial College London, 180 Queen’s Gate, London, England, UK. dustin.connor02@imperial.ac.uk
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.
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