Special Issue "Integrated Information Theory and Consciousness"

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".

Deadline for manuscript submissions: 31 May 2021.

Special Issue Editor

Prof. Kyumin Moon
E-Mail
Guest Editor
Institute for Urban Humanities, University of Seoul, Seoul 08826, Korea
Interests: consciousness; mind–body problem; theory of time and space; phenomenology; causation; intentionality; subjectivity; concepts; perception; introspection

Special Issue Information

Dear Colleagues,

Maybe we are facing ‘the rise of the science of consciousness’ now. Among the variety of working hypotheses, integrated information theory of consciousness (IIT) would be one of the most ambitious and controversial scientific programs in the field. Since it was suggested by Giulio Tononi, IIT has evolved and been upgraded over and over. However, the current version, IIT 4.0, still needs some clarifications and developments.

IIT is unique in its methodology, mathematical model, theoretical framework, and philosophical perspective. For instance, methodologically, IIT starts from ‘axioms’ of consciousness and draws ‘postulates’ about physical substrates of consciousness. From these postulates, it suggests that a maximally integrated conceptual structure (MICS) generated by a system is a conscious experience. The Φ value of MICS, which measures the irreducible causal power of a system as a whole, captures the levels of consciousness, and the ‘shape’ of MICS represented in multidimensional space specifies the qualities of consciousness. Since IIT directly identifies MICS with consciousness, everything that generates MICS is conscious. All these features raise some questions: Is such ‘phenomenology first’ well grounded? Is there any precise and efficient way to get around the computational burden in applying IIT to real biological systems? Further, is Φ well defined enough to be generally applied to all physical systems? Is MICS-experience identification justifiable? Is there any problematic consequence of such an identification? If there is, what is it and how can IIT avoid it?

These questions naturally require wide, productive interdisciplinary research. In this Special Issue, we invite researchers from all disciplines concerned with the intellectual fever toward the science of consciousness.

Prof. Kyumin Moon
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • consciousness
  • information
  • causation
  • phenomenology
  • emergence
  • neural correlates of consciousness
  • qualia
  • defining phi
  • computing integrated information
  • animal consciousness
  • artificial consciousness
  • mathematics and consciousness

Published Papers (5 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Open AccessArticle
Implications of Noise on Neural Correlates of Consciousness: A Computational Analysis of Stochastic Systems of Mutually Connected Processes
by
Entropy 2021, 23(5), 583; https://doi.org/10.3390/e23050583 (registering DOI) - 08 May 2021
Viewed by 137
Abstract
Random fluctuations in neuronal processes may contribute to variability in perception and increase the information capacity of neuronal networks. Various sources of random processes have been characterized in the nervous system on different levels. However, in the context of neural correlates of consciousness, [...] Read more.
Random fluctuations in neuronal processes may contribute to variability in perception and increase the information capacity of neuronal networks. Various sources of random processes have been characterized in the nervous system on different levels. However, in the context of neural correlates of consciousness, the robustness of mechanisms of conscious perception against inherent noise in neural dynamical systems is poorly understood. In this paper, a stochastic model is developed to study the implications of noise on dynamical systems that mimic neural correlates of consciousness. We computed power spectral densities and spectral entropy values for dynamical systems that contain a number of mutually connected processes. Interestingly, we found that spectral entropy decreases linearly as the number of processes within the system doubles. Further, power spectral density frequencies shift to higher values as system size increases, revealing an increasing impact of negative feedback loops and regulations on the dynamics of larger systems. Overall, our stochastic modeling and analysis results reveal that large dynamical systems of mutually connected and negatively regulated processes are more robust against inherent noise than small systems. Full article
(This article belongs to the Special Issue Integrated Information Theory and Consciousness)
Open AccessArticle
Mechanism Integrated Information
Entropy 2021, 23(3), 362; https://doi.org/10.3390/e23030362 - 18 Mar 2021
Viewed by 938
Abstract
The Integrated Information Theory (IIT) of consciousness starts from essential phenomenological properties, which are then translated into postulates that any physical system must satisfy in order to specify the physical substrate of consciousness. We recently introduced an information measure (Barbosa et al., 2020) [...] Read more.
The Integrated Information Theory (IIT) of consciousness starts from essential phenomenological properties, which are then translated into postulates that any physical system must satisfy in order to specify the physical substrate of consciousness. We recently introduced an information measure (Barbosa et al., 2020) that captures three postulates of IIT—existence, intrinsicality and information—and is unique. Here we show that the new measure also satisfies the remaining postulates of IIT—integration and exclusion—and create the framework that identifies maximally irreducible mechanisms. These mechanisms can then form maximally irreducible systems, which in turn will specify the physical substrate of conscious experience. Full article
(This article belongs to the Special Issue Integrated Information Theory and Consciousness)
Show Figures

Figure 1

Open AccessArticle
Computing Integrated Information (Φ) in Discrete Dynamical Systems with Multi-Valued Elements
Entropy 2021, 23(1), 6; https://doi.org/10.3390/e23010006 - 22 Dec 2020
Cited by 1 | Viewed by 1324
Abstract
Integrated information theory (IIT) provides a mathematical framework to characterize the cause-effect structure of a physical system and its amount of integrated information (Φ). An accompanying Python software package (“PyPhi”) was recently introduced to implement this framework for the causal analysis of discrete dynamical systems of binary elements. Here, we present an update to PyPhi that extends its applicability to systems constituted of discrete, but multi-valued elements. This allows us to analyze and compare general causal properties of random networks made up of binary, ternary, quaternary, and mixed nodes. Moreover, we apply the developed tools for causal analysis to a simple non-binary regulatory network model (p53-Mdm2) and discuss commonly used binarization methods in light of their capacity to preserve the causal structure of the original system with multi-valued elements. Full article
(This article belongs to the Special Issue Integrated Information Theory and Consciousness)
Show Figures

Figure 1

Open AccessArticle
The Causal Efficacy of Consciousness
Entropy 2020, 22(8), 823; https://doi.org/10.3390/e22080823 - 28 Jul 2020
Viewed by 892
Abstract
Mental causation is vitally important to the integrated information theory (IIT), which says consciousness exists since it is causally efficacious. While it might not be directly apparent, metaphysical commitments have consequential entailments concerning the causal efficacy of consciousness. Commitments regarding the ontology of [...] Read more.
Mental causation is vitally important to the integrated information theory (IIT), which says consciousness exists since it is causally efficacious. While it might not be directly apparent, metaphysical commitments have consequential entailments concerning the causal efficacy of consciousness. Commitments regarding the ontology of consciousness and the nature of causation determine which problem(s) a view of consciousness faces with respect to mental causation. Analysis of mental causation in contemporary philosophy of mind has brought several problems to the fore: the alleged lack of psychophysical laws, the causal exclusion problem, and the causal pairing problem. This article surveys the threat each problem poses to IIT based on the different metaphysical commitments IIT theorists might make. Distinctions are made between what I call reductive IIT, non-reductive IIT, and non-physicalist IIT, each of which make differing metaphysical commitments regarding the ontology of consciousness and nature of causation. Subsequently, each problem pertaining to mental causation is presented and its threat, or lack thereof, to each version of IIT is considered. While the lack of psychophysical laws appears unthreatening for all versions, reductive IIT and non-reductive IIT are seriously threatened by the exclusion problem, and it is difficult to see how they could overcome it while maintaining a commitment to the causal closure principle. Yet, non-physicalist IIT denies the principle but is therefore threatened by the pairing problem, to which I have elsewhere provided a response that is briefly outlined here. This problem also threatens non-reductive IIT, but unlike non-physicalist IIT it lacks an evident response. The ultimate aim of this survey is to provide a roadmap for IIT theorists through the maze of mental causation, by clarifying which commitments lead to which problems, and how they might or might not be overcome. Such a survey can aid IIT theorists as they further develop and hone the metaphysical commitments of IIT. Full article
(This article belongs to the Special Issue Integrated Information Theory and Consciousness)
Open AccessArticle
Four-Types of IIT-Induced Group Integrity of Plecoglossus altivelis
Entropy 2020, 22(7), 726; https://doi.org/10.3390/e22070726 - 30 Jun 2020
Cited by 2 | Viewed by 1812
Abstract
Integrated information theory (IIT) was initially proposed to describe human consciousness in terms of intrinsic-causal brain network structures. Particularly, IIT 3.0 targets the system’s cause–effect structure from spatio-temporal grain and reveals the system’s irreducibility. In a previous study, we tried to apply IIT [...] Read more.
Integrated information theory (IIT) was initially proposed to describe human consciousness in terms of intrinsic-causal brain network structures. Particularly, IIT 3.0 targets the system’s cause–effect structure from spatio-temporal grain and reveals the system’s irreducibility. In a previous study, we tried to apply IIT 3.0 to an actual collective behaviour in Plecoglossus altivelis. We found that IIT 3.0 exhibits qualitative discontinuity between three and four schools of fish in terms of Φ value distributions. Other measures did not show similar characteristics. In this study, we followed up on our previous findings and introduced two new factors. First, we defined the global parameter settings to determine a different kind of group integrity. Second, we set several timescales (from Δ t = 5 / 120 to Δ t = 120 / 120 s). The results showed that we succeeded in classifying fish schools according to their group sizes and the degree of group integrity around the reaction time scale of the fish, despite the small group sizes. Compared with the short time scale, the interaction heterogeneity observed in the long time scale seems to diminish. Finally, we discuss one of the longstanding paradoxes in collective behaviour, known as the heap paradox, for which two tentative answers could be provided through our IIT 3.0 analysis. Full article
(This article belongs to the Special Issue Integrated Information Theory and Consciousness)
Show Figures

Figure 1

Back to TopTop