Informational Structures and Informational Fields as a Prototype for the Description of Postulates of the Integrated Information Theory

Informational Structures (IS) and Informational Fields (IF) have been recently introduced to deal with a continuous dynamical systems-based approach to Integrated Information Theory (IIT). IS and IF contain all the geometrical and topological constraints in the phase space. This allows one to characterize all the past and future dynamical scenarios for a system in any particular state. In this paper, we develop further steps in this direction, describing a proper continuous framework for an abstract formulation, which could serve as a prototype of the IIT postulates.

[1]  Dante R. Chialvo,et al.  Critical Brain Dynamics at Large Scale , 2012, 1210.3632.

[2]  Carlos J. Melián,et al.  The nested assembly of plant–animal mutualistic networks , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[3]  Pablo Varona,et al.  Chunking dynamics: heteroclinics in mind , 2014, Front. Comput. Neurosci..

[4]  R. Temam Infinite Dimensional Dynamical Systems in Mechanics and Physics Springer Verlag , 1993 .

[5]  C. Conley Isolated Invariant Sets and the Morse Index , 1978 .

[6]  Marcello Massimini,et al.  Fractal dimension analysis of states of consciousness and unconsciousness using transcranial magnetic stimulation , 2019, Comput. Methods Programs Biomed..

[7]  S. Wiggins Introduction to Applied Nonlinear Dynamical Systems and Chaos , 1989 .

[8]  José A. Langa,et al.  Attracting Complex Networks , 2016 .

[9]  J. Langa,et al.  Architecture of attractor determines dynamics on mutualistic complex networks , 2017 .

[10]  Norihiko Adachi,et al.  The existence of globally stable equilibria of ecosystems of the generalized Volterra type , 1980 .

[11]  Jordi Bascompte,et al.  The architecture of mutualistic networks minimizes competition and increases biodiversity , 2009, Nature.

[12]  D. Long Networks of the Brain , 2011 .

[13]  O. Sporns,et al.  Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.

[14]  M. Hurley Chain recurrence, semiflows, and gradients , 1995 .

[15]  Mikhail I. Rabinovich,et al.  Metastability and Transients in Brain Dynamics: Problems and Rigorous Results , 2010 .

[16]  G. Tononi,et al.  Rethinking segregation and integration: contributions of whole-brain modelling , 2015, Nature Reviews Neuroscience.

[17]  Jordi Bascompte,et al.  Plant-Animal Mutualistic Networks: The Architecture of Biodiversity , 2007 .

[18]  C J Stam,et al.  Characterization of anatomical and functional connectivity in the brain: a complex networks perspective. , 2010, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[19]  Stability of gradient semigroups under perturbations , 2011 .

[20]  G. Deco,et al.  Ongoing Cortical Activity at Rest: Criticality, Multistability, and Ghost Attractors , 2012, The Journal of Neuroscience.

[21]  Fernando Soler-Toscano,et al.  Informational structures: A dynamical system approach for integrated information , 2018, PLoS Comput. Biol..

[22]  Gustavo Deco,et al.  Functional connectivity dynamics: Modeling the switching behavior of the resting state , 2015, NeuroImage.

[23]  Gustavo Deco,et al.  The dynamics of resting fluctuations in the brain: metastability and its dynamical cortical core , 2016, bioRxiv.

[24]  José A. Langa,et al.  Attractors for infinite-dimensional non-autonomous dynamical systems , 2012 .

[25]  Jack K. Hale,et al.  Slow-motion manifolds, dormant instability, and singular perturbations , 1989 .

[26]  Continuity of Lyapunov functions and of energy level for a generalized gradient semigroup , 2012 .

[27]  Shlomo Havlin,et al.  Dynamic interdependence and competition in multilayer networks , 2017 .

[28]  Krzysztof P. Rybakowski,et al.  The Homotopy Index and Partial Differential Equations , 1987 .

[29]  J. Hale Asymptotic Behavior of Dissipative Systems , 1988 .

[30]  Y. Takeuchi Global Dynamical Properties of Lotka-Volterra Systems , 1996 .

[31]  J. Kelso,et al.  The Metastable Brain , 2014, Neuron.

[32]  Zhang Yi,et al.  Foundations of Implementing the Competitive Layer Model by Lotka–Volterra Recurrent Neural Networks , 2010, IEEE Transactions on Neural Networks.

[33]  Gustavo Deco,et al.  How anatomy shapes dynamics: a semi-analytical study of the brain at rest by a simple spin model , 2012, Front. Comput. Neurosci..

[34]  Maurizio Corbetta,et al.  Resting-State Temporal Synchronization Networks Emerge from Connectivity Topology and Heterogeneity , 2015, PLoS Comput. Biol..

[35]  Christophe Lenglet,et al.  Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI , 2018, Scientific Reports.

[36]  Gerhard Werner,et al.  Metastability, criticality and phase transitions in brain and its models , 2007, Biosyst..

[37]  Jack K. Hale,et al.  Infinite dimensional dynamical systems , 1983 .

[38]  R. Kötter,et al.  Cortical network dynamics with time delays reveals functional connectivity in the resting brain , 2008, Cognitive Neurodynamics.

[39]  M. Kringelbach,et al.  Metastability and Coherence: Extending the Communication through Coherence Hypothesis Using A Whole-Brain Computational Perspective , 2016, Trends in Neurosciences.

[40]  Larissa Albantakis,et al.  From the Phenomenology to the Mechanisms of Consciousness: Integrated Information Theory 3.0 , 2014, PLoS Comput. Biol..

[41]  Daniel B. Henry Geometric Theory of Semilinear Parabolic Equations , 1989 .

[42]  Ramón Huerta,et al.  Transients versus attractors in Complex Networks , 2010, Int. J. Bifurc. Chaos.

[43]  V. Afraimovich,et al.  Two-dimensional heteroclinic attractor in the generalized Lotka–Volterra system , 2015, 1509.04570.

[44]  V. Zhigulin,et al.  On the origin of reproducible sequential activity in neural circuits. , 2004, Chaos.

[45]  O. Ladyzhenskaya,et al.  Attractors for Semigroups and Evolution Equations , 1991 .

[46]  Olaf Sporns,et al.  Mapping the Connectome: Multi-Level Analysis of Brain Connectivity , 2012, Front. Neuroinform..

[47]  Karl J. Friston,et al.  Structural and Functional Brain Networks: From Connections to Cognition , 2013, Science.

[48]  Douglas E. Norton The fundamental theorem of dynamical systems , 1995 .

[49]  Olaf Sporns,et al.  Network structure of cerebral cortex shapes functional connectivity on multiple time scales , 2007, Proceedings of the National Academy of Sciences.

[50]  Mauro Patrão,et al.  Semiflows on Topological Spaces: Chain Transitivity and Semigroups , 2006 .