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Related papers: A Principled Infotheoretic \phi-like Measure

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According to the Integrated Information Theory of Consciousness, consciousness is a fundamental observer-independent property of physical systems, and the measure Phi of integrated information is identical to the quantity or level of…

Neurons and Cognition · Quantitative Biology 2019-02-13 Adam B. Barrett , Pedro A. M. Mediano

Accumulating evidence indicates that the capacity to integrate information in the brain is a prerequisite for consciousness. Integrated Information Theory (IIT) of consciousness provides a mathematical approach to quantifying the…

Neurons and Cognition · Quantitative Biology 2016-02-22 Masafumi Oizumi , Shun-ichi Amari , Toru Yanagawa , Naotaka Fujii , Naotsugu Tsuchiya

Integrated information theory (IIT) starts from consciousness itself and identifies a set of properties (axioms) that are true of every conceivable experience. The axioms are translated into a set of postulates about the substrate of…

The integrated information theory of consciousness (IIT) is uniquely ambitious in proposing a mathematical formula, derived from apparently fundamental properties of conscious experience, to describe the quantity and quality of…

Neurons and Cognition · Quantitative Biology 2026-04-14 Adam B. Barrett , Borjan Milinkovic , Pedro A. M. Mediano , Fernando E. Rosas , Daniel Bor , Lionel Barnett , Anil K. Seth

Integrated Information Theory (IIT) is a prominent theory of consciousness that has at its centre measures that quantify the extent to which a system generates more information than the sum of its parts. While several candidate measures of…

Neurons and Cognition · Quantitative Biology 2019-01-30 Pedro A. M. Mediano , Anil K. Seth , Adam B. Barrett

Although there is growing interest in measuring integrated information in computational and cognitive systems, current methods for doing so in practice are computationally unfeasible. Existing and novel integration measures are investigated…

Neurons and Cognition · Quantitative Biology 2017-02-08 Max Tegmark

Originally conceived as a theory of consciousness, integrated information theory (IIT) provides a theoretical framework intended to characterize the compositional causal information that a system, in its current state, specifies about…

Quantum Physics · Physics 2023-03-22 Larissa Albantakis , Robert Prentner , Ian Durham

Researchers in many disciplines have previously used a variety of mathematical techniques for analyzing group interactions. Here we use a new metric for this purpose, called 'integrated information' or 'phi.' Phi was originally developed by…

Social and Information Networks · Computer Science 2018-11-21 David Engel , Thomas W. Malone

Integrated information theory (IIT) has established itself as one of the leading theories for the study of consciousness. IIT essentially proposes that quantitative consciousness is identical to maximally integrated conceptual information,…

Neurons and Cognition · Quantitative Biology 2017-03-06 Stephan Krohn , Dirk Ostwald

Originally developed as a theory of consciousness, integrated information theory provides a mathematical framework to quantify the causal irreducibility of systems and subsets of units in the system. Specifically, mechanism integrated…

Neurons and Cognition · Quantitative Biology 2024-04-23 Alireza Zaeemzadeh , Giulio Tononi

Quantifying integrated information is a leading approach towards building a fundamental theory of consciousness. Integrated Information Theory (IIT) has gained attention in this regard due to its theoretically strong framework. However, it…

Information Theory · Computer Science 2016-12-15 Mohit Virmani , Nithin Nagaraj

Information theory is widely accepted as a powerful tool for analyzing complex systems and it has been applied in many disciplines. Recently, some central components of information theory - multivariate information measures - have found…

Information Theory · Computer Science 2012-08-30 Nicholas Timme , Wesley Alford , Benjamin Flecker , John M. Beggs

Integrated Information Theory is one of the leading models of consciousness. It aims to describe both the quality and quantity of the conscious experience of a physical system, such as the brain, in a particular state. In this contribution,…

Neurons and Cognition · Quantitative Biology 2020-02-19 Johannes Kleiner , Sean Tull

Partial information decomposition (PID) of the multivariate mutual information describes the distinct ways in which a set of source variables contains information about a target variable. The groundbreaking work of Williams and Beer has…

Information Theory · Computer Science 2021-03-31 Abdullah Makkeh , Aaron J. Gutknecht , Michael Wibral

Information theory is a mathematical theory of learning with deep connections with topics as diverse as artificial intelligence, statistical physics, and biological evolution. Many primers on information theory paint a broad picture with…

Information Theory · Computer Science 2019-03-26 Philip Chodrow

The ability to integrate information in the brain is considered to be an essential property for cognition and consciousness. Integrated Information Theory (IIT) hypothesizes that the amount of integrated information ($\Phi$) in the brain is…

Neurons and Cognition · Quantitative Biology 2018-04-04 Jun Kitazono , Ryota Kanai , Masafumi Oizumi

Information theory is an outstanding framework to measure uncertainty, dependence and relevance in data and systems. It has several desirable properties for real world applications: it naturally deals with multivariate data, it can handle…

Machine Learning · Statistics 2024-10-30 Valero Laparra , J. Emmanuel Johnson , Gustau Camps-Valls , Raul Santos-Rodríguez , Jesus Malo

The partial information decomposition (PID) framework is concerned with decomposing the information that a set of (two or more) random variables (the sources) has about another variable (the target) into three types of information: unique,…

Information Theory · Computer Science 2025-02-28 André F. C. Gomes , Mário A. T. Figueiredo

Information theory provides a mathematical foundation to measure uncertainty in belief. Belief is represented by a probability distribution that captures our understanding of an outcome's plausibility. Information measures based on…

Information Theory · Computer Science 2020-01-17 Jed A. Duersch , Thomas A. Catanach

Motivated by the possible applications that a better understanding of consciousness might bring, we follow Tononi's idea and calculate analytically a complexity index for two systems of Ising spins with parallel update dynamics, the…

Statistical Mechanics · Physics 2023-04-28 Otavio Citton , Nestor Caticha
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