Models of Consciousness

One in a series of talks from the 2019 Models of Consciousness conference. John Barnden

School of Computer Science, University of Birmingham, UK

I assume that [phenomenal] consciousness is a property physical processes can have, and that it involves pre-reflective auto-sensitivity (PRAS), which is related to the much-discussed pre-reflective self-consciousness [3,4]. I then argue that PRAS requires conscious processes to be directly and causally sensitive to their own inner causation as such, and not merely to their own trajectories of physical states as ordinarily understood. That causal sensitivity is therefore metacausation. Metacausation here is where instances of causation are themselves, directly and in their own right, causes or effects. Metacausation (aka higher-order causation) is rarely discussed at all, and has apparently not previously been linked to consciousness. But the proposal is yet more radical as I merely use "causation" to mean microphysical dynamism. I assume (anti-Humeanly) that the universe's law-governed unfolding is a dynamism irreducible to sheer regular patterning over spacetime of familiar physical quantities (masses, charges, fields, curvatures, etc.). Furthermore, I strongly reify dynamism: spatiotemporally specific instances of it are a ``new'' realm of fundamental physical quantities, themselves dynamically interacting in their own right with other quantities (familiar or new). That dynamic interaction is a new level of dynamism, namely metadynamism, with its own laws explicitly mentioning dynamism instances. As causation is just dynamism, metacausation is metadynamism. The poster summarizes the arguments (revising earlier versions [1,2]) and sketches initial formalization steps for metadynamism. It also indicates how metadynamism might be co-opted to enrich other consciousness theories, notably IIT and Orch-OR.

References:

[1] Barnden, J.A. (2014). Running into consciousness. J. Consciousness Studies, 21 (5-6), pp.33-56.

[2] Barnden, J.A. (2018). Phenomenal consciousness, meta-causation and developments concerning casual powers and time passage. Poster presented at 22nd Conference for the Association for the Scientific

Study of Consciousness, 26-29 June 2018, Krakow.

[3] Gallagher, S. & Zahavi, D. (2015). Phenomenological approaches to self-consciousness. In Edward N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy (Spring 2015 Edition).

[4] Sebastian, M.A. (2012). Experiential awareness: Do you prefer ``it''

to ``me''? Philosophical Topics, 40(2), pp.155-177."

Filmed at the Models of Consciousness conference, University of Oxford, September 2019. Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

One in a series of talks from the 2019 Models of Consciousness conference. Pedro Mediano

Department of Computing, Imperial College London

In a seminal series of papers, Tononi, Sporns, and Edelman (TSE) introduced the idea that the neural dynamics underlying conscious states are characterised by a balance of integration and differentiation between system components. This idea remains prevalent in consciousness research today, influencing theoretical and experimental work.

Such work has faced a number of challenges. For example, distinct measures designed to measure such a balance behave very differently in practice,

making it hard to choose which is the "right one", and dynamics of conscious and unconscious brains defy some of the predictions of this framework. We argue that these problems arise, at least in part, from the non-specific nature of the concepts of integration and differentiation.

Here, we present a revised mathematical theory of neural complexity: we introduce a new measure, called O-information, that quantifies the balance between redundancy and synergy within a system, and is more effective than TSE’s original measure at describing phenomena where large-scale correlation and short-scale independence coexist; and develop a formalism to decompose different "modes" of information dynamics, providing an exhaustive taxonomy of redundant and synergistic effects. These developments allow us to place previous measures within a common framework and explain their their similarities and differences.

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One in a series of talks from the 2019 Models of Consciousness conference. Inês Hipólito

University of Wollongong

Building on the modular architecture of mind (Fodor 1983), Modularity Networks is claimed as a theory well equipped to explain neural connectivity and reuse (Stanley et al.; 2019, Zerrili 2019). This paper takes the case of the oculomotor system to show that even if Modularity Network’s tools are useful to describe brain’s functional connectivity, they are limited in explaining why such connections are formed and dynamic. To show this, section 1 starts by laying down the reasons for adopting Modularity Networks as well suited for explaining neural connectivity. Section 2 introduces the oculomotor system as a dynamic integration of action and vision. Section 3 argues that however valuable in describing the functional connectivity of the oculomotor system, Modularity Networks fails to explain why such connections are formed and dynamic (dependent on activity). This failure is made evident by acknowledging a fundamental distinction in the metaphysics of inference. The nature of inference is taken differently in functional connectivity as a description of inference as opposed to effective connectivity as an explanation of inference (Friston 2011). Section 4 introduces Dynamic Causal Modelling (DCM) as a better resource to capture effective connectivity. It allows explaining how and why brain connections, as generative models of cognitive integration, are dependent on the dynamic activity within the environment. This conclusion speaks against modular arguments for encapsulation, innateness and specificity of cognitive organisation.

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One in a series of talks from the 2019 Models of Consciousness conference. Gustav Bernroider

University of Salzburg, Dept. of Biosciences, Austria

Are there knowable criteria for subjective entities such as conscious experience? I think there are, even physical ones. I advocate the view that the basic dualism between subject and object or mind and matter can be figured by an intuitively simple version of an inside out or inversion relation between two opposing physical domains. I propose a particular topology for subject-object relations and argue that we can find a physical realisation in the brain of living organism that provides a conformal transformation between both domains. The transformation combines two physical domains related by inversion or parity symmetry or simply by mirror reflections. This view puts topological aspects behind inversion and the associated hidden symmetries in physics into the foreground.

I introduce the model along three steps: i) evidence and motivation for the role of mirror symmetries from psychobiology based on previous studies (Senso- motory invariance in animal feelings [Bernroider G, Panksepp J. (2011), Neurosci & Biobehav. Rev., 35, 2009-2016.] and mirror-writing in (my grand-) children), ii) an intuitive diagrammatic demonstrating subject-object together with cause and effect relations mapped onto an inversive plane geometry and iii) a more formal outline and extension into the algebraic topology of non- orientable surfaces, the real and complex projective plane.

The concept suggested here offers several testable predictions for the relation of ionic brain function to inversion symmetries realised by the molecular architecture of excitable membranes. For example, this aspect seems to be evidenced by enantio-selective electronic transitions during ion conduction in the brain [Bernroider G. (2017) JIN 16, 105-113]. Going beyond these technical aspects, the present view on modelling subjectivity shifts the role of canonical coordinates together with their static dimensional geometry into the background. It favours ideas behind general covariance. A parity transformation, if purely defined at the level of Cartesian coordinates with changing signs, is discrete, the transient itself only inferential, non-physical, with no known conserved quantity associated with this transformation in the sense of Emmy Noether’s theorem. However, if the same transformation is laid out continuously on the geometry of non-orientable surfaces (e.g. on a Möbius band), the transients gain some physics and offer a conserved quantity. I will discuss this conserved quantity with respect to subjectivity and consciousness.

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One in a series of talks from the 2019 Models of Consciousness conference. Marc Ebner

Universität Greifswald, Germany

The seemingly hard problem of consciousness is the problem of explaining why subjective conscious experience exist. However, Qualia is nothing mysterious. Our subjective conscious experience is comparable across individuals because we are a product of evolution. It is grounded in reality and we use it to communicate with each other. Consciousness seems to be intertwined with language. Its primary role is to serve communication between individuals. We need Qualia to communicate with others. We perceive objects within our visual field relative to the orientation of our head. This information is then stored and can also be communicated to others either during perception or at a later time. The same holds for the perception of sounds or smells. According to the theory proposed here, an assembly of neurons in the brain is in charge of consciousness. The job of this assembly is simply (a) to look at what the body does, (b) to keep a record of it, and (c) to explain it to our peers.

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One in a series of talks from the 2019 Models of Consciousness conference. Diana Stanciu

University of Bucharest; Berlin-Brandenburg Academy of Sciences and Humanities (BBAW)

I will argue that epistemic structural realism (ESR) can offer a feasible theoretical framework for the study of consciousness and its associated neurophysiological phenomena. While structural realism has already been employed in physics or biology (cf. Tegmark 2007, Leng 2010, Ainsworth 2010, 2011, McArthur 2011, Pincock 2011, Woodin 2011, Landry and Rickels 2012, Bain 2013, Andreas and Zenker 2014, Schurz 2014), its application to the study of consciousness is new indeed. Out of its two variants: ontic structural realism (OSR) and ESR, I consider the latter more suitable when studying the neurophysiological bases of consciousness since the OSR drastically claims that ‘there are’ actually no ‘objects’ and that ‘structure’ is all ‘there is’, while the ESR more moderately states that all we can ‘know’ is the ‘structure of the relations between objects’ and not the objects themselves (cf. Van Fraassen 2006). Thus, while not denying the existence of ‘objects’ (even if they are hard to pinpoint when discussing the neurophysiological bases of consciousness), the ESR still emphasises ‘relations’ vs. ‘objects’ and the retention of structure across theory change. In other words, it emphasies the continuity across theory change through the structural or mathematical aspects of our theories (cf. Stanford 2006).

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One in a series of talks from the 2019 Models of Consciousness conference. Aïda Elamrani

Institut Jean Nicod, ENS

The young field of consciousness science involves highly interdisciplinary research. For this reason, it is producing heterogeneous results which are hard to compare. This emerging discipline could benefit from a unifying, theory- neutral framework for analytical purposes. To this end, we must firstly identify a common ground between concurrent models. A brief scan through history reveals that consciousness has consistently revolved around the mind vs matter dichotomy. This binary split can be argued to span a sufficiently broad and flexible domain to semantically hold any contemporary scientific formulation of the consciousness problem, since most of them strive to provide a physical account of subjective experience. Accordingly, our reverse- engineered general frame is expected to map elements from mind-space to elements from matter-space, accepting a simple functional notation: Consciousness (INPUT) = OUTPUT. Although this equation might evoke Hilary Putnam’s functionalism, essential differences with the meta-model are emphasized by introducing its relation to Shannon’s information. Finally, alternative implementations and applications of this representation are used to illustrate and compare current accounts of consciousness.

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One in a series of talks from the 2019 Models of Consciousness conference. Chetan Prakash

California State University, San Bernardino

A scientific understanding of the process whereby physical entities produce consciousness has not come about, despite decades of investigation. This suggests exploring the reversal of the celebrated “hard problem of consciousness,” i.e., take consciousness as fundamental and the physical world as emergent. We describe D. Hoffman’s Interface Theory of Perception in which perceptual experiences do not approximate properties of an “objective” world, but reside in simplified, species-specific, user interfaces. Building on this, the Conscious Realism Thesis states that the objective world consists entirely of a social network of ‘conscious agents’ and their experiences, which together create the objects and properties of our common physical world.

Using evolutionary game theory, we justify interface theory by showing that perceptual strategies reporting the truth will be driven to extinction by those tuned instead to fitness. We state further theorems on fitness beating truth, by showing that perceived structures, such as symmetries, partial orders and probabilities, will likely not be possessed by a world. We define “conscious agents,” suggesting that space-time is a property of the perceptual interface of human conscious agents: physical “objects” are akin to icons on that interface; physical “phenomena” are properties of apparently interacting icons.

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One in a series of talks from the 2019 Models of Consciousness conference. Quanlong Wang

Department of Computer Science, University of Oxford

Natural science has a basic assumption that there exists a kind of objectivity in the world independent of any consciousness. But how could one verify such objectivity given the fact that human beings can only perceive any existence through their own consciousness? On the other hand, there is a possibility for the existence of pure consciousness which could support the appearance of all phenomena, as claimed by the Yogācāra school of Indian philosophy. Based on this philosophy, any consciousness consists of two divisions: the perceived division (nimittabhaga in Sanskrit) and the perceiving division (darsanabhaga in Sanskrit). The perceiving division can recognise the information presented by the perceived division, they interact with each other as a whole unity. It is based on these two divisions that objectivity and subjectivity are established.

In this talk, we give a mathematical model for characterising the interacting processes between the perceived division and the perceiving division within the framework of ZW-calculus, which is a graphical language representing quantum processes in compact closed categories. We expect that using this model some key interacting processes between the perceived division and the perceiving division can be characterised, which then paves the way for further research on modelling consciousness.

Filmed at the Models of Consciousness conference, University of Oxford, September 2019. Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

One in a series of talks from the 2019 Models of Consciousness conference. Pierre Baudot

Median Technologies, Marseille, France.

Elementary quantitative and qualitative aspects of consciousness are investigated conjointly from the biology, neuroscience, physic and mathematic point of view, by the mean of a theory written with Bennequin that derives and extends information theory within algebraic topology. Information structures, that accounts for statistical dependencies within n-body interacting systems are interpreted a la Leibniz within a monadic-panpsychic framework where consciousness is information and physical, and arise from collective interactions. The electrodynamic intrinsic nature of consciousness, sustained by an analogical code, is illustrated by standard neuroscience and psychophysic results. It accounts for the diversity of the learning mechanisms, including adaptive and homeostatic processes on multiple scales, and details their expression within information theory. The axiomatization and logic of cognition are rooted in measure theory expressed within a topos intrinsic probabilistic constructive logic, allowing to express the information of mathematical formula as a Gödel code. Information topology provides a synthesis of the main models of consciousness (integrated information, global neuronal workspace, free energy principle) within a formal Gestalt theory, an expression of information structures and patterns in correspondence with Galois cohomology and symmetries. We give several examples of the application of information topology to standard recognition challenges in AI- machine learning.

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