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The Global Neuronal Workspace Model of Conscious Access: From Neuronal Architectures to Clinical Applications

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Characterizing Consciousness: From Cognition to the Clinic?

Abstract

While a considerable body of experimental data has been accumulated on the differences between conscious and non-conscious processing, a theory is needed to bridge the neuro-psychological gap and establish a causal relationship between objective neurophysiological data and subjective reports. In the present review, we first briefly outline the detailed postulates and predictions of our working hypothesis, referred to as the global neuronal workspace (GNW) model. We then compare these predictions to experimental studies that have attempted to delineate the physiological signatures of conscious sensory perception by contrasting it with subliminal processing, using a variety of methods: behavioral, PET and fMRI imaging, time-resolved imaging with ERP and MEG, and finally single-cell electrophysiology. In a final section, we examine the relevance of these findings for pathologies of consciousness in coma and vegetative states.

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Acknowledgment

This chapter is based in part on an earlier draft of a review article by S. Dehaene and J.P. Changeux, entitled “Experimental and Theoretical Approaches to Conscious Processing”, to appear in Neuron in May 2011. We gratefully acknowledge extensive discussions with Sid Kouider, Jérôme Sackur, Bechir Jarraya, and Pierre-Marie Lledo as well as commens on previous drafts by Stuart Edelstein, Raphaël Gaillard, Biyu He and Henri Korn. This work was supported by Collège de France, INSERM, CNRS, European Research Council and Human Frontiers Science Program (S.D.), and Skaggs Research Foundation at UCSD School of Pharmacy (J.P.C.).

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Dehaene, S., Changeux, JP., Naccache, L. (2011). The Global Neuronal Workspace Model of Conscious Access: From Neuronal Architectures to Clinical Applications. In: Dehaene, S., Christen, Y. (eds) Characterizing Consciousness: From Cognition to the Clinic?. Research and Perspectives in Neurosciences. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18015-6_4

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