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How does a serial, integrated and very limited stream of consciousness emerge from a nervous system that is mostly unconscious, distributed, parallel and of enormous capacity?

B J Baars

Ciba Foundation symposium January 1, 1993 DOI: 10.1002/9780470514412.ch14 via PubMed

Summary

AI-generated from the abstract

Global Workspace theory proposes that conscious experience arises when specialized unconscious processors in the brain compete for access to a global broadcasting capability; the winning processor disseminates its information widely, enabling integration across separate modules. This architecture, also used in computer systems, accounts for phenomena from perceptual consciousness to problem-solving, voluntary action, and directed attention. The theory is consistent with limited-capacity mechanisms but not reducible to them. It requires competition for input to a neural global workspace and global distribution of output, functions carried out by brain structures necessary for normal conscious experience. The theory generates testable predictions for high-speed brain imaging.

Study at a glance

Characteristics Theoretical or philosophical paper Peer reviewed
Key finding Conscious experience emerges from a nervous system where multiple input processors compete for access to a global broadcasting capability, allowing the winning processor to disseminate its information globally throughout the brain.

Abstract

Much of the nervous system can be viewed as a massively parallel, distributed system of highly specialized but unconscious processors. Conscious experience on the other hand is traditionally viewed as a serial stream that integrates different sources of information but is limited to only one internally consistent content at any given moment. Global Workspace theory suggests that conscious experience emerges from a nervous system in which multiple input processors compete for access to a broadcasting capability; the winning processor can disseminate its information globally throughout the brain. Global workspace architectures have been widely employed in computer systems to integrate separate modules when they must work together to solve a novel problem or to control a coherent new response. The theory articulates a series of increasingly complex models, able to account for more and more evidence about conscious functioning, from perceptual consciousness to conscious problem-solving, voluntary control of action, and directed attention. Global Workspace theory is consistent with, but not reducible to, other theories of limited-capacity mechanisms. Global workspace architectures must show competition for input to a neural global workspace and global distribution of its output. Brain structures that are demonstrably required for normal conscious experience can carry out these two functions. The theory makes testable predictions, especially for newly emerging, high-speed brain imaging technology.

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