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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: closed (15 November 2021) | Viewed by 48378

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Guest Editor
Humanities Research Institutes, Chung-Ang University, 06974 Seoul, Korea
Interests: consciousness; mind–body problem; theory of time and space; phenomenology; causation; intentionality; subjectivity; concepts; perception; introspection
Special Issues, Collections and Topics in MDPI journals

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

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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 (14 papers)

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15 pages, 2007 KiB  
Article
Emergence of Integrated Information at Macro Timescales in Real Neural Recordings
by Angus Leung and Naotsugu Tsuchiya
Entropy 2022, 24(5), 625; https://doi.org/10.3390/e24050625 - 29 Apr 2022
Cited by 3 | Viewed by 2014
Abstract
How a system generates conscious experience remains an elusive question. One approach towards answering this is to consider the information available in the system from the perspective of the system itself. Integrated information theory (IIT) proposes a measure to capture this integrated information [...] Read more.
How a system generates conscious experience remains an elusive question. One approach towards answering this is to consider the information available in the system from the perspective of the system itself. Integrated information theory (IIT) proposes a measure to capture this integrated information (Φ). While Φ can be computed at any spatiotemporal scale, IIT posits that it be applied at the scale at which the measure is maximised. Importantly, Φ in conscious systems should emerge to be maximal not at the smallest spatiotemporal scale, but at some macro scale where system elements or timesteps are grouped into larger elements or timesteps. Emergence in this sense has been demonstrated in simple example systems composed of logic gates, but it remains unclear whether it occurs in real neural recordings which are generally continuous and noisy. Here we first utilise a computational model to confirm that Φ becomes maximal at the temporal scales underlying its generative mechanisms. Second, we search for emergence in local field potentials from the fly brain recorded during wakefulness and anaesthesia, finding that normalised Φ (wake/anaesthesia), but not raw Φ values, peaks at 5 ms. Lastly, we extend our model to investigate why raw Φ values themselves did not peak. This work extends the application of Φ to simple artificial systems consisting of logic gates towards searching for emergence of a macro spatiotemporal scale in real neural systems. Full article
(This article belongs to the Special Issue Integrated Information Theory and Consciousness)
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19 pages, 2177 KiB  
Article
From Shorter to Longer Timescales: Converging Integrated Information Theory (IIT) with the Temporo-Spatial Theory of Consciousness (TTC)
by Georg Northoff and Federico Zilio
Entropy 2022, 24(2), 270; https://doi.org/10.3390/e24020270 - 13 Feb 2022
Cited by 17 | Viewed by 3975
Abstract
Time is a key element of consciousness as it includes multiple timescales from shorter to longer ones. This is reflected in our experience of various short-term phenomenal contents at discrete points in time as part of an ongoing, more continuous, and long-term ‘stream [...] Read more.
Time is a key element of consciousness as it includes multiple timescales from shorter to longer ones. This is reflected in our experience of various short-term phenomenal contents at discrete points in time as part of an ongoing, more continuous, and long-term ‘stream of consciousness’. Can Integrated Information Theory (IIT) account for this multitude of timescales of consciousness? According to the theory, the relevant spatiotemporal scale for consciousness is the one in which the system reaches the maximum cause-effect power; IIT currently predicts that experience occurs on the order of short timescales, namely, between 100 and 300 ms (theta and alpha frequency range). This can well account for the integration of single inputs into a particular phenomenal content. However, such short timescales leave open the temporal relation of specific phenomenal contents to others during the course of the ongoing time, that is, the stream of consciousness. For that purpose, we converge the IIT with the Temporo-spatial Theory of Consciousness (TTC), which, assuming a multitude of different timescales, can take into view the temporal integration of specific phenomenal contents with other phenomenal contents over time. On the neuronal side, this is detailed by considering those neuronal mechanisms driving the non-additive interaction of pre-stimulus activity with the input resulting in stimulus-related activity. Due to their non-additive interaction, the single input is not only integrated with others in the short-term timescales of 100–300 ms (alpha and theta frequencies) (as predicted by IIT) but, at the same time, also virtually expanded in its temporal (and spatial) features; this is related to the longer timescales (delta and slower frequencies) that are carried over from pre-stimulus to stimulus-related activity. Such a non-additive pre-stimulus-input interaction amounts to temporo-spatial expansion as a key mechanism of TTC for the constitution of phenomenal contents including their embedding or nesting within the ongoing temporal dynamic, i.e., the stream of consciousness. In conclusion, we propose converging the short-term integration of inputs postulated in IIT (100–300 ms as in the alpha and theta frequency range) with the longer timescales (in delta and slower frequencies) of temporo-spatial expansion in TTC. Full article
(This article belongs to the Special Issue Integrated Information Theory and Consciousness)
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18 pages, 1365 KiB  
Article
Application of the Catecholaminergic Neuron Electron Transport (CNET) Physical Substrate for Consciousness and Action Selection to Integrated Information Theory
by Chris Rourk
Entropy 2022, 24(1), 91; https://doi.org/10.3390/e24010091 - 06 Jan 2022
Cited by 2 | Viewed by 2572
Abstract
A newly discovered physical mechanism involving incoherent electron tunneling in layers of the protein ferritin that are found in catecholaminergic neurons (catecholaminergic neuron electron transport or CNET) is hypothesized to support communication between neurons. Recent tests further confirm that these ferritin layers can [...] Read more.
A newly discovered physical mechanism involving incoherent electron tunneling in layers of the protein ferritin that are found in catecholaminergic neurons (catecholaminergic neuron electron transport or CNET) is hypothesized to support communication between neurons. Recent tests further confirm that these ferritin layers can also perform a switching function (in addition to providing an electron tunneling mechanism) that could be associated with action selection in those neurons, consistent with earlier predictions based on CNET. While further testing would be needed to confirm the hypothesis that CNET allows groups of neurons to communicate and act as a switch for selecting one of the neurons in the group to assist in reaching action potential, this paper explains how that hypothesized behavior would be consistent with Integrated Information Theory (IIT), one of a number of consciousness theories (CTs). While the sheer number of CTs suggest that any one of them alone is not sufficient to explain consciousness, this paper demonstrates that CNET can provide a physical substrate and action selection mechanism that is consistent with IIT and which can also be applied to other CTs, such as to conform them into a single explanation of consciousness. Full article
(This article belongs to the Special Issue Integrated Information Theory and Consciousness)
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9 pages, 295 KiB  
Article
On the Operational Utility of Measures of Multichannel EEGs
by David Darmon, Tomas Watanabe, Christopher Cellucci and Paul E. Rapp
Entropy 2021, 23(11), 1434; https://doi.org/10.3390/e23111434 - 30 Oct 2021
Viewed by 1246
Abstract
Multichannel EEGs were obtained from healthy participants in the eyes-closed no-task condition and in the eyes-open condition (where the alpha component is typically abolished). EEG dynamics in the two conditions were quantified with two related binary Lempel–Ziv measures of the first principal component, [...] Read more.
Multichannel EEGs were obtained from healthy participants in the eyes-closed no-task condition and in the eyes-open condition (where the alpha component is typically abolished). EEG dynamics in the two conditions were quantified with two related binary Lempel–Ziv measures of the first principal component, and with three measures of integrated information, including the more recently proposed integrated synergy. Both integrated information and integrated synergy with model order p=1 had greater values in the eyes-closed condition. When the model order of integrated synergy was determined with the Bayesian Information Criterion, this pattern was reversed, and in line with the other measures, integrated synergy was greater in the eyes-open condition. Eyes-open versus eyes-closed separation was quantified by calculating the between-condition effect size. The Lempel–Ziv complexity of the first principal component showed greater separation than the measures of integrated information. Full article
(This article belongs to the Special Issue Integrated Information Theory and Consciousness)
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19 pages, 296 KiB  
Article
Not All Structure and Dynamics Are Equal
by Garrett Mindt
Entropy 2021, 23(9), 1226; https://doi.org/10.3390/e23091226 - 18 Sep 2021
Cited by 2 | Viewed by 2580
Abstract
The hard problem of consciousness has been a perennially vexing issue for the study of consciousness, particularly in giving a scientific and naturalized account of phenomenal experience. At the heart of the hard problem is an often-overlooked argument, which is at the core [...] Read more.
The hard problem of consciousness has been a perennially vexing issue for the study of consciousness, particularly in giving a scientific and naturalized account of phenomenal experience. At the heart of the hard problem is an often-overlooked argument, which is at the core of the hard problem, and that is the structure and dynamics (S&D) argument. In this essay, I will argue that we have good reason to suspect that the S&D argument given by David Chalmers rests on a limited conception of S&D properties, what in this essay I’m calling extrinsic structure and dynamics. I argue that if we take recent insights from the complexity sciences and from recent developments in Integrated Information Theory (IIT) of Consciousness, that we get a more nuanced picture of S&D, specifically, a class of properties I’m calling intrinsic structure and dynamics. This I think opens the door to a broader class of properties with which we might naturally and scientifically explain phenomenal experience, as well as the relationship between syntactic, semantic, and intrinsic notions of information. I argue that Chalmers’ characterization of structure and dynamics in his S&D argument paints them with too broad a brush and fails to account for important nuances, especially when considering accounting for a system’s intrinsic properties. Ultimately, my hope is to vindicate a certain species of explanation from the S&D argument, and by extension dissolve the hard problem of consciousness at its core, by showing that not all structure and dynamics are equal. Full article
(This article belongs to the Special Issue Integrated Information Theory and Consciousness)
13 pages, 250 KiB  
Article
What Is Consciousness? Integrated Information vs. Inference
by James E. Cooke
Entropy 2021, 23(8), 1032; https://doi.org/10.3390/e23081032 - 11 Aug 2021
Cited by 6 | Viewed by 4114
Abstract
Any successful naturalistic account of consciousness must state what consciousness is, in terms that are compatible with the rest of our naturalistic descriptions of the world. Integrated Information Theory represents a pioneering attempt to do just this. This theory accounts for the core [...] Read more.
Any successful naturalistic account of consciousness must state what consciousness is, in terms that are compatible with the rest of our naturalistic descriptions of the world. Integrated Information Theory represents a pioneering attempt to do just this. This theory accounts for the core features of consciousness by holding that there is an equivalence between the phenomenal experience associated with a system and its intrinsic causal power. The proposal, however, fails to provide insight into the qualitative character of consciousness and, as a result of its proposed equivalence between consciousness and purely internal dynamics, into the intentional character of conscious perception. In recent years, an alternate group of theories has been proposed that claims consciousness to be equivalent to certain forms of inference. One such theory is the Living Mirror theory, which holds consciousness to be a form of inference performed by all living systems. The proposal of consciousness as inference overcomes the shortcomings of Integrated Information Theory, particularly in the case of conscious perception. A synthesis of these two perspectives can be reached by appreciating that conscious living systems are self-organising in nature. This mode of organization requires them to have a high level of integration. From this perspective, we can understand consciousness as being dependent on a system possessing non-trivial amounts of integrated information while holding that the process of inference performed by the system is the fact of consciousness itself. Full article
(This article belongs to the Special Issue Integrated Information Theory and Consciousness)
19 pages, 274 KiB  
Article
IIT’s Scientific Counter-Revolution: A Neuroscientific Theory’s Physical and Metaphysical Implications
by Francis Fallon and James C. Blackmon
Entropy 2021, 23(8), 942; https://doi.org/10.3390/e23080942 - 23 Jul 2021
Cited by 4 | Viewed by 2280
Abstract
IIT includes commitments about the very nature of physical reality, a fact both highly unusual for an empirical theory within neuroscience, and surprisingly underappreciated within the literature. These commitments are intimately tied to the theory; they are not incidental. This paper demonstrates as [...] Read more.
IIT includes commitments about the very nature of physical reality, a fact both highly unusual for an empirical theory within neuroscience, and surprisingly underappreciated within the literature. These commitments are intimately tied to the theory; they are not incidental. This paper demonstrates as much by raising certain objections in a “naive” way, and then exposing how the principled IIT responses would rely upon metaphysical positions. Along the way we draw on the IIT literature for support for these interpretations, but also point to a need for elaboration and clarification. Section 1 applies the Placement Argument in a way that leads to problem involving zombies, treated in Section 2. Section 3 frames the zombie problem as an apparent dilemma, and addresses that dilemma by drawing on claims in the IIT literature concerning physical reality. Section 4 raises a related dilemma and treats it in a way that dovetails with the treatment in Section 3 of physical reality. All of this underscores not just the breadth of IIT, but the relevance of this breadth to a full consideration of IIT’s merits. Full article
(This article belongs to the Special Issue Integrated Information Theory and Consciousness)
19 pages, 1186 KiB  
Article
A Traditional Scientific Perspective on the Integrated Information Theory of Consciousness
by Jon Mallatt
Entropy 2021, 23(6), 650; https://doi.org/10.3390/e23060650 - 22 May 2021
Cited by 14 | Viewed by 5004
Abstract
This paper assesses two different theories for explaining consciousness, a phenomenon that is widely considered amenable to scientific investigation despite its puzzling subjective aspects. I focus on Integrated Information Theory (IIT), which says that consciousness is integrated information (as ϕMax) and [...] Read more.
This paper assesses two different theories for explaining consciousness, a phenomenon that is widely considered amenable to scientific investigation despite its puzzling subjective aspects. I focus on Integrated Information Theory (IIT), which says that consciousness is integrated information (as ϕMax) and says even simple systems with interacting parts possess some consciousness. First, I evaluate IIT on its own merits. Second, I compare it to a more traditionally derived theory called Neurobiological Naturalism (NN), which says consciousness is an evolved, emergent feature of complex brains. Comparing these theories is informative because it reveals strengths and weaknesses of each, thereby suggesting better ways to study consciousness in the future. IIT’s strengths are the reasonable axioms at its core; its strong logic and mathematical formalism; its creative “experience-first” approach to studying consciousness; the way it avoids the mind-body (“hard”) problem; its consistency with evolutionary theory; and its many scientifically testable predictions. The potential weakness of IIT is that it contains stretches of logic-based reasoning that were not checked against hard evidence when the theory was being constructed, whereas scientific arguments require such supporting evidence to keep the reasoning on course. This is less of a concern for the other theory, NN, because it incorporated evidence much earlier in its construction process. NN is a less mature theory than IIT, less formalized and quantitative, and less well tested. However, it has identified its own neural correlates of consciousness (NCC) and offers a roadmap through which these NNCs may answer the questions of consciousness using the hypothesize-test-hypothesize-test steps of the scientific method. Full article
(This article belongs to the Special Issue Integrated Information Theory and Consciousness)
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18 pages, 3320 KiB  
Article
Implications of Noise on Neural Correlates of Consciousness: A Computational Analysis of Stochastic Systems of Mutually Connected Processes
by Pavel Kraikivski
Entropy 2021, 23(5), 583; https://doi.org/10.3390/e23050583 - 08 May 2021
Cited by 3 | Viewed by 1515
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)
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29 pages, 1389 KiB  
Article
Mechanism Integrated Information
by Leonardo S. Barbosa, William Marshall, Larissa Albantakis and Giulio Tononi
Entropy 2021, 23(3), 362; https://doi.org/10.3390/e23030362 - 18 Mar 2021
Cited by 22 | Viewed by 5379
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)
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20 pages, 1542 KiB  
Article
Computing Integrated Information (Φ) in Discrete Dynamical Systems with Multi-Valued Elements
by Juan D. Gomez, William G. P. Mayner, Maggie Beheler-Amass, Giulio Tononi and Larissa Albantakis
Entropy 2021, 23(1), 6; https://doi.org/10.3390/e23010006 - 22 Dec 2020
Cited by 11 | Viewed by 3976
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 [...] Read more.
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)
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23 pages, 285 KiB  
Article
The Causal Efficacy of Consciousness
by Matthew Owen
Entropy 2020, 22(8), 823; https://doi.org/10.3390/e22080823 - 28 Jul 2020
Cited by 4 | Viewed by 3298
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)
29 pages, 3118 KiB  
Article
Four-Types of IIT-Induced Group Integrity of Plecoglossus altivelis
by Takayuki Niizato, Kotaro Sakamoto, Yoh-ichi Mototake, Hisashi Murakami, Takenori Tomaru, Tomotaro Hoshika and Toshiki Fukushima
Entropy 2020, 22(7), 726; https://doi.org/10.3390/e22070726 - 30 Jun 2020
Cited by 4 | Viewed by 4875
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)
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16 pages, 6162 KiB  
Opinion
The Interstitial Pathways as the Substrate of Consciousness: A New Synthesis
by Christopher W. Tyler
Entropy 2021, 23(11), 1443; https://doi.org/10.3390/e23111443 - 31 Oct 2021
Cited by 3 | Viewed by 2153
Abstract
This paper considers three classes of analyses of the nature of consciousness: abstract theories of the functional organization of consciousness, and concrete proposals as to the neural substrate of consciousness, while providing a rationale for contesting non-neural and transcendental conceptualizations of consciousness. It [...] Read more.
This paper considers three classes of analyses of the nature of consciousness: abstract theories of the functional organization of consciousness, and concrete proposals as to the neural substrate of consciousness, while providing a rationale for contesting non-neural and transcendental conceptualizations of consciousness. It indicates that abstract theories of the dynamic core of consciousness have no force unless they are grounded in the physiology of the brain, since the organization of dynamic systems, such as the Sun, could equally well qualify as conscious under such theories. In reviewing the wealth of studies of human consciousness since the mid-20th century, it concludes that many proposals for the particular neural substrate of consciousness are insufficient in various respects, but that the results can be integrated into a novel scheme that consciousness extends through a subcortical network of interlaminar structures from the brainstem to the claustrum. This interstitial structure has both the specificity and the extended connectivity to account for the array of reportable conscious experiences. Full article
(This article belongs to the Special Issue Integrated Information Theory and Consciousness)
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