Philosophical Transactions of the Royal Society B: Biological Sciences
May 19, 2015
G. Tononi, C. Koch
Integrated information theory (IIT) proposes that consciousness can be understood by starting from the essential properties of experience itself, such as its intrinsic existence, composition, information, integration, and exclusion. From these axioms, the theory derives physical requirements for a system to be conscious. IIT offers a principled account of both the quantity and quality of experience, and provides a calculus to determine whether a physical system is conscious. It explains clinical and laboratory findings, makes testable predictions, and suggests that consciousness is graded and common among biological organisms, including some simple systems. In contrast, it predicts that feed-forward networks and digital computers, even those simulating the human brain, would experience little to nothing.
PLoS Comput. Biol.
May 1, 2014
Masafumi Oizumi, L. Albantakis, G. Tononi
Integrated Information Theory (IIT) 3.0 proposes that consciousness is identical to a maximally irreducible conceptual structure (MICS) generated by a physical system. Starting from phenomenological axioms—information (each experience is specific), integration (each experience is unified), and exclusion (each experience has unique borders and grain)—IIT formalizes postulates for how mechanisms like neurons must be configured to produce experience. The theory defines intrinsic information as differences that make a difference within a system and integrated information as information of a whole irreducible to its parts. A MICS specifies the quality of an experience, and integrated information (ΦMax) its quantity. The theory entails that consciousness is always about the system itself, that inactive elements can generate experience, and that feed-forward systems can be unconscious zombies functionally equivalent to conscious complexes.