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How much information do large brain networks integrate as a whole over the sum of their parts? Can the dynamical complexity of such networks be globally quantified in an information-theoretic way and be meaningfully coupled to brain…

Neurons and Cognition · Quantitative Biology 2016-12-22 Xerxes D. Arsiwalla , Paul Verschure

The data-driven characterization of the ``complexity'' present in dynamical systems remains an open problem with broad applications across the physical sciences. We investigate the ``structural complexity'' of the 2D ferromagnetic Ising…

Statistical Mechanics · Physics 2026-02-18 Cooper Jacobus

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

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

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

It is known that statistical model selection as well as identification of dynamical equations from available data are both very challenging tasks. Physical systems behave according to their underlying dynamical equations which, in turn, can…

Mathematical Physics · Physics 2017-10-11 Sean Alan Ali , Carlo Cafaro

Information geometry and inductive inference methods can be used to model dynamical systems in terms of their probabilistic description on curved statistical manifolds. In this article, we present a formal conceptual reexamination of the…

Mathematical Physics · Physics 2010-11-29 C. Cafaro , A. Giffin , S. A. Ali , D. -H. Kim

An outstanding problem in neuroscience is to understand how information is integrated across the many modules of the brain. While classic information-theoretic measures have transformed our understanding of feedforward information…

Neurons and Cognition · Quantitative Biology 2019-02-12 Daniel Toker , Friedrich T. Sommer

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

We introduce a quantum integrated-information measure $\Phi$ for multipartite states within the Relational Quantum Dynamics (RQD) framework. $\Phi(\rho)$ is defined as the minimum quantum Jensen-Shannon distance between an n-partite density…

Quantum Physics · Physics 2025-10-31 Arash Zaghi

Complex systems, from the human brain to the global economy, are made of multiple elements that interact in such ways that the behaviour of the `whole' often seems to be more than what is readily explainable in terms of the `sum of the…

Neurons and Cognition · Quantitative Biology 2021-09-28 Pedro A. M. Mediano , Fernando E. Rosas , Andrea I Luppi , Robin L. Carhart-Harris , Daniel Bor , Anil K. Seth , Adam B. Barrett

In this paper, we present some results on information, complexity and entropy as defined below and we discuss their relations with the Kolmogorov-Sinai entropy which is the most important invariant of a dynamical system. These results have…

Dynamical Systems · Mathematics 2019-08-17 Vieri Benci , Claudio Bonanno , Stefano Galatolo , Giulia Menconi , Federico Ponchio

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

Our understanding of complex systems rests on our ability to characterise how they perform distributed computation and integrate information. Advances in information theory have introduced several quantities to describe complex information…

Information Theory · Computer Science 2026-04-13 Alberto Liardi , George Blackburne , Hardik Rajpal , Fernando E. Rosas , Pedro A. M. Mediano

Background: Many authors have proposed Quantitative Theories of Consciousness (QTC) based on theoretical principles like information theory, Granger causality and complexity. Recently, Virmani and Nagaraj (arXiv:1608.08450v2 [cs.IT]) noted…

Neurons and Cognition · Quantitative Biology 2017-06-30 Suresh Jois , Nithin Nagaraj

The problem of N interacting spins on a lattice is equivalent to one of N clusters linked in a specific manner. The energy of any configuration of spins can be expressed in terms of the energy levels of this cluster. A new expression is…

Statistical Mechanics · Physics 2007-05-23 T. R. S. Prasanna

The central object of this PhD thesis is known under different names in the fields of computer science and statistical mechanics. In computer science, it is called the Maximum Cut problem, one of the famous twenty-one Karp's original…

Machine Learning · Computer Science 2022-08-31 Mikhail Krechetov

The high-performance scalable parallel algorithm for rigorous calculation of partition function of lattice systems with finite number Ising spins was developed. The parallel calculations run by C++ code with using of Message Passing…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-02-21 Alexey A. Peretyatko , Ivan A. Bogatyrev , Vitaliy Yu. Kapitan , Yury V. Kirienko , Konstantin V. Nefedev , Valery I. Belokon

Most information dynamics and statistical causal analysis frameworks rely on the common intuition that causal interactions are intrinsically pairwise -- every 'cause' variable has an associated 'effect' variable, so that a 'causal arrow'…

Neurons and Cognition · Quantitative Biology 2019-09-06 Pedro A. M. Mediano , Fernando Rosas , Robin L. Carhart-Harris , Anil K. Seth , Adam B. Barrett

The Free Energy Principle (FEP) is a leading framework for mathematically modeling self-organization and learning, while Integrated Information Theory (IIT) is a computational ontology of consciousness oriented around irreducible cause and…

Neurons and Cognition · Quantitative Biology 2026-05-14 Alexander Kearney