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VI. Earth Life Emergence: Development of Body, Brain, Selves and Societies

4. Conscious Integrated Information Knowledge

Hameroff, Stuart, et al, eds. Toward a Science of Consciousness. Cambridge: MIT Press, 1996. A large book from the first Tuscon, Arizona international conference on the subject as an indication of the growing philosophical and scientific interest in the phenomena of consciousness.

Hameroff, Stuart, et al, eds. Toward a Science of Consciousness II. Cambridge: MIT Press, 1998. A compendium of papers from the second meeting on the many facets of mind science. In general, evolution is perceived most of all as a learning process.

Hernandez-Espinosa, Alberto, et al. Estimations of Integrated Information Based on Algorithmic Complexity and Dynamic Querying. arXiv:1904.10393. A H-E, National Autonomous University of Mexico, along with Hector Zenil, Narsis Kiani, and Jesper Tegner, Karolinska Institute, Sweden apply their long experience with computational mathematics to foster understandings and applications of this popular theorey of knowing consciousness. Section headings include Finding Simple Rules in Complex Behavior and The Fractal Distribution of Information.

We establish and build theoretical and numerical connections between the theories and methods of integrated information and algorithmic complexity. We introduce a method for estimating integrated information by way of a programmability test rooted in algorithmic information dynamics. Our method is based on the idea that simple rules of causal dynamical systems can shorten the calculation needed to estimate integrated information. On the basis of the perturbation test, we demonstrate how a system can be regarded as providing explanations for its own behaviour. We expect this approach to contribute toward a better understanding of integrated information and of its connections to other, more established areas of science such as dynamical systems and algorithmic information theory. (Abstract excerpt)

Hofstadter, Douglas. What Is It Like to Be a Strange Loop? Kriegel, Uriah and Kenneth Williford, eds. Self-Representational Approaches to Consciousness. Cambridge: MIT Press, 2006. The Indiana University author and polymath continues his luminous inquiry of whoever and however we might think we are. A gist of this long article, to be expanded to book length, is that people achieve their individualities by sequential degrees and layers up to and into adulthood. Such selves are sustained by iterations and recursions, looping back and forth, from which a nested hierarchy emerges, not without difficulty, of whom a person may uniquely be. But is this real or an illusion, asks Douglas, ever in reflective wonderment. For an example, a “thinkodynamics” due to a “statistical mentalics,” is proposed similar to thermodynamics, so as to connect us to a similarly iterative cosmos. Google the words Hofstadter+Analogy to access a recent talk at Stanford University entitled Analogy as the Core of Cognition for further insights.

Hogberg, Anders, et al. Knowing, Learning and Teaching – How Homo Became Docens. Cambridge Archaeological Journal. 225/4, 2015. With Peter Gardenfors and Lars Larsson, Swedish cognitive anthropologists make the case that a most distinctive quality of hominid evolution was an educative propensity for communal and generational knowledge acquisition, increase, and transmission. See also a later essay The Archeology of Teaching and the Evolution of Homo docens in Current Anthropology (58/2, 2017).

Khajehabdollahi, Sina, et al. Emergence of Integrated Information, Complexity, and Consciousness at Criticality. bioRxiv. January 15, 2019. Western University, Ontario physicists and a psychologist theorize that recent evidential perceptions of sentience rising in tandem with knowledge can be seen as seeking an optimum balanced state between relative order and disorder. See also Criticality as a Determinant of Integrated Information in Human Brain Networks by Hyoungkyu Kim and UnCheol Lee herein for a similar surmise.

Using the critical Ising model of the brain, integrated information as a measure of consciousness is evaluated by generic neural network models. Monte Carlo simulations are run on 159 random weighted networks analogous to small 5-node neural network motifs. The integrated information generated by this sample is quantified across the model parameter space. It is observed that integrated information, as a type of order parameter not unlike a concept like magnetism, undergoes a phase transition at the critical point in the model. This critical point is where the ‘consciousness’ of the system is maximally at a boundary between an ordered and disordered form. This study adds further evidence to support that the emergence of consciousness coincides with the more universal patterns of self-organized criticality, evolution, the emergence of complexity, and the integration of complex systems. (Abstract excerpt)

This result, combined with a body of evidence highlighting the preferred state of critical systems suggests that, like many other complex phenomenon, consciousness may simply follow from/emerge out of the tendency of a system to self-organize to criticality. (1)

Kim, Hyoungkyu and UnCheol Lee. Criticality as a Determinant of Integrated Information in Human Brain Networks. Entropy. 21/10, 2019. As this well quantified perception of a deep, evolutionary relation between sentient awareness and knowledge content grows in validity and employ, University of Michigan Medical School, Center for Consciousness Science researchers advise that a further feature seems to be an optimum state of critical poise between a more or less orderly condition. As being found everywhere from quantum physical bases to natural and social phases (see Critical Complementarity) cerebral phenomena likewise proceed to fine tune themselves in this way. A concurrent, independent paper Emergence of Integrated Information, Complexity, and Consciousness at Criticality (Sina Khajehabdollahi, herein) comes to the same finding.

Integrated information theory (IIT) describes consciousness as integrated across differentiated knowledgeable systems. However, in a complex dynamic brain, the optimal conditions for integrating information have not been elucidated. In this study, we propose that network criticality, a balanced state between a large variation in functional configuration and a large constraint on structural configuration, may be the basis of the emergence of an integrated information. We tested these hypotheses with a whole brain network model and high-density electroencephalography (EEG) during various levels of human consciousness under general anesthesia. The EEG study demonstrated an explicit relationship between criticality, and level of consciousness. (Abstract excerpt)

Criticality was originally introduced for studying phase transition in physics, simply defined as a balanced state between order and disorder. This property has been observed broadly in physical and non-physical systems and has been suggested as an optimal state for information storage, transmission, and integration. In particular, several computational modeling and empirical studies suggest that the brain dynamics associated with consciousness reside near a critical state. (1)

We demonstrated for the first time an explicit relationship between criticality, integrated information, and human consciousness with computational modeling and EEG analysis. We propose that network criticality is a condition for integrated information. Understanding this relationship may open a new way to study diverse states of consciousness situated near to and far from a critical state. (12)

Kleiner, Johannes and Sean Tull. The Mathematical Structure of Integrated Information Theory. arXiv:2002.07655. As another example of how these malleable IIT insights have gained much employ, University of Munich and Oxford University postdoc computational scholars scope out a generalization so as to give it even broader veracity. See also a companion paper Integrated Information in Process Theories at 2002.07654.

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, we propound the mathematical structure of the theory, separating the essentials from auxiliary formal tools. We provide a definition of a generalized IIT which has IIT 3.0 of Tononi et al, as well as the Quantum IIT introduced by Zanardi et. al. as special cases. This provides an axiomatic definition of the theory which may serve as the starting point for future investigations and as an introduction for new researchers. (Abstract)

Koch, Christof. The Feeling of Life Itself. Cambridge: MIT Press, 2019. The veteran neuroscientist (search) is now is President and Chief Scientist of the Allen Institute for Brain Science in Seattle. A decade after his Consciousness book, this edition continues to affirm that a form of sentient awareness pervades and vivifies human and animal realms and much beyond. But any purely computational basis or machine-like embodiment is ruled out. In collaborator with Giulio Tononi (search), the core theme is an exposition of his popular Integrated Information Theory (IIT), which as the section reports, traces a parallel path of personal awareness and complex knowledge. (This 2010s version is a quite fulfills Pierre Teilhard’s 1930s evolutionary pairing of complexity and consciousness, whom Koch lauds in his earlier work.) The Global Neuronal Workspace model is then reviewed along with double detail and image hemispheres, which altogether seem to infer a waxing worldwide Uber-Mind. In closing, Koch notes that this tandem ascent well recovers a 21st century scala naturae, once again from deep substance to human acumen.

Koch, Christoph and Florian Mormann. The Neurobiology of Consciousness. Zewail, Ahmed, ed. Physical Biology: From Atoms to Medicine. London: Imperial College Press, 2008. In an affirmation of David Chalmers’ contention, Caltech neuroscientists affirm that sentient awareness is most characterized and distinguished by its informational content. See also Giulio Tononi herein.

The most promising candidate for such a theoretical framework is the information integration theory of consciousness. It posits that the most property of consciousness is that it is extraordinarily informative. (392) Based on these and other considerations, the theory claims that a physical system can generate consciousness to the extent that it can integrate information. (392)

Kriegel, Uriah and Kenneth Williford, eds. Self-Representational Approaches to Consciousness. Cambridge: MIT Press, 2006. Forthcoming in May, this work will argue that consciousness always involves some form of self-awareness, which is said to go beyond and improve on reductive theories. Check the publisher’s website.

Kriegeskorte, Nikolaus and Jorn Diedrichsen. Peeling the Onion of Brain Representations. Annual Review of Neuroscience. 42/407, 2019. Columbia University and Western University, Ontario neurotheorists open by noting that the brain’s capability to compose, retain and refer to cognitive remembrances of external phenomena has long been debated. The issue is here cast in favor of informational memories via a nested, layered model. The chapter closes with a caveat that brains are not conventional computers. While they do contain stored content, some dynamic (enactive) system may yet be in effect.

The brain's function is to enable adaptive behavior in the world by processing information. The concept of representation links the information processed by the brain back to the world. Although disputed, making the connection between brain activity and what it represents requires knowing which aspects of brain activity matter, how the code works, and how it computes adaptive behavior. In this review, we argue that representation provides a useful link between dynamics and function and suggest which aspects of brain activity should be analyzed to achieve a representational understanding. We peel the onion of brain representations in search of layers (aspects of brain activity) that are involved in computation. (Abstract excerpt)

The onion of brain representations organizes the different aspects of brain-activity data into a nested hierarchy. As we peel it, we focus progressively on aspects that appear more directly related to the representational content. We hope to peel away layers that reflect developmental coincidences, random biological variation, and other epiphenomena without functional relevance, to arrive at the brain’s representational core: the neural code used by the brain itself to mind and manipulate the world. (427)

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