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Dehaene–Changeux model : ウィキペディア英語版
Dehaene–Changeux model

The Dehaene–Changeux model (DCM), also known as the global neuronal workspace or the global cognitive workspace model is a part of Bernard Baars's "global workspace model" for consciousness.
It is a computer model of the neural correlates of consciousness programmed as a neural network. It attempts to reproduce the swarm behaviour of the brain's ''higher cognitive functions'' such as consciousness, decision-making〔Dehaene S, Changeux JP. Reward-dependent learning in neuronal networks for planning and decision making. Prog Brain Res. 2000;126:217-29.〕 and the central executive functions. It was developed by cognitive neuroscientists Stanislas Dehaene and Jean-Pierre Changeux beginning in 1986.〔Dehaene S, Changeux JP. Experimental and theoretical approaches to conscious processing. Neuron. 2011 Apr 28;70(2):200-27.〕 It has been used to provide a predictive framework to the study of inattentional blindness and the solving of the Tower of London test.〔Changeux JP, Dehaene S. Hierarchical neuronal modeling of cognitive functions: from synaptic transmission to the Tower of London. C R Acad Sci III. 1998 Feb–Mar;321(2–3):241-7.〕〔Dehaene S, Changeux JP, Nadal JP. Neural networks that learn temporal sequences by selection. Proc Natl Acad Sci U S A. 1987 May;84(9):2727-31.〕
==History==
The Dehaene–Changeux model was initially established as a spin glass neural network attempting to represent learning and to then provide a stepping stone towards artificial learning among other objectives. It would later be used to predict observable reaction times within the priming paradigm〔Epub 2010 Jan 25. Van den Bussche E, Hughes G, Humbeeck NV, Reynvoet B The relation between consciousness and attention: an empirical study using the priming paradigm. Conscious Cogn. 2010 Mar;19(1):86–97..〕 and in inattentional blindness.

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