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Aïda Elamrani - Inputs, outputs, and meta-models

Series
Models of Consciousness
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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.

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

Episode Information

Series
Models of Consciousness
People
Aïda Elamrani
Keywords
oxford
computer science
consciousness
neuroscience
mathematics
Department: Department of Computer Science
Date Added: 13/10/2019
Duration: 00:20:30

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Chetan Prakash - Structure Invention by Conscious Agents

Series
Models 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.

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

Episode Information

Series
Models of Consciousness
People
Chetan Prakash
Keywords
oxford
computer science
consciousness
neuroscience
mathematics
Department: Department of Computer Science
Date Added: 13/10/2019
Duration: 00:53:10

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Quanlong Wang - Modelling consciousness divisions in ZW-calculus

Series
Models of Consciousness
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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 Licence
Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK (BY-NC-SA): England & Wales; https://creativecommons.org/licenses/by-nc-sa/2.0/uk/

Episode Information

Series
Models of Consciousness
People
Quanlong Wang
Keywords
oxford
computer science
consciousness
neuroscience
mathematics
Department: Department of Computer Science
Date Added: 13/10/2019
Duration: 00:14:21

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Pierre Baudot - Information cohomology and probabilistic topos for consciousness modeling: from elementary perception to machine learning

Series
Models of Consciousness
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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.

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

Episode Information

Series
Models of Consciousness
People
Pierre Baudot
Keywords
oxford
computer science
consciousness
neuroscience
mathematics
Department: Department of Computer Science
Date Added: 13/10/2019
Duration: 00:21:46

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Paul Baird - A model for perceptual states

Series
Models of Consciousness
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One in a series of talks from the 2019 Models of Consciousness conference.
Paul Baird
Université de Bretagne Atlantique

I will present a mathematical model which encapsulates 3D perception from planar 2D data: to a combinatorial graph, we associate its "geometric spectrum"; eigenstates then correspond to local realizations of the graph in Euclidean 3-space as "invariant" frameworks. In this way geometry emerges from the structure, rather than being imposed upon it.

One may attempt to construct a model universe based on such structures, in which state realization enacts change; change being synonymous with time, which at an elementary level, we hypothesize, is the realization of temporal states. A coherent time should then emerge from a "survival of the fittest" principle. Conscious entities might then be considered as systems which possess "higher order universality", that is, which process potential information (rather than hard information) such as a "potential" 3D cube, to enact their own change.

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Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK (BY-NC-SA): England & Wales; https://creativecommons.org/licenses/by-nc-sa/2.0/uk/

Episode Information

Series
Models of Consciousness
People
Paul Baird
Keywords
oxford
computer science
consciousness
neuroscience
mathematics
Department: Department of Computer Science
Date Added: 13/10/2019
Duration: 00:21:34

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Mauro D’Ariano - Awareness: an operational theoretical approach

Series
Models of Consciousness
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One in a series of talks from the 2019 Models of Consciousness conference.
Mauro D’Ariano
Dipartimento di Fisica, Università degli Studi di Pavia

I will explore the possibility of drawing definite theoretical assertions about “awareness”, including possible experimental falsification. Awareness will be regarded as a manifestation of a special kind of “information”, and, as such, formalised as an operational probabilistic theory (OPT) [1]. Awareness would correspond to “the feeling of the process” experienced by the OPT-systems involved in the process.

As a kind of information “awareness” is special in being “private”. Assuming
that such privacy is an in-principle one implies a number of interesting consequences. For example, according to a theorem about information privacy in OPTs [2], investigation will be restricted to OPTs that are essentially non classical, among which the most relevant instance is the quantum theory.
After presenting the OPT framework, assessing its methodological robustness in separating objective from theoretical elements, and examining postulates guaranteeing experimental control and falsifiability, I will compare postulates of relevant OPTs, and provide mathematical definitions of notions as holism, causality, complementarity, purification, and information privacy.
Finally, I will explore the hypothesis of “awareness as quantum coherence”, providing a list of motivations and consequences, and discussing the possibility of experimental tests in cognitive sciences, including the evaluation of the number of qubits involved in the awareness, the existence of complementary observables, and violations of local-realism bounds.

[1] G. M. D’Ariano, G. Chiribella, and P. Perinotti, “Quantum Theory from First Principles: An Informational Approach” (Cambridge University Press 2017)
[2] G. M. D’Ariano, P. Perinotti, A. Tosini, “Information and disturbance in operational probabilistic theories”, unpublished

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

Episode Information

Series
Models of Consciousness
People
Mauro D’Ariano
Keywords
oxford
computer science
consciousness
neuroscience
mathematics
Department: Department of Computer Science
Date Added: 13/10/2019
Duration: 00:44:59

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Anita Mehta - Chasing memories

Series
Models of Consciousness
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One in a series of talks from the 2019 Models of Consciousness conference.
Anita Mehta
Leverhulme Visiting Professor, University of Oxford

Short- and long-term memories are distinguished by their forgettability. Most of what we perceive and store is lost rather quickly to noise, as new sensations replace older ones, while some memories last for as long as we live. Synaptic dynamics is key to the process of memory storage; in this talk I will discuss a few approaches we have taken to this problem, culminating in a model of synaptic networks containing both cooperative and competitive dynamics. It turns out that the competition between synapses is key to the natural emergence of long-term memory in this model, as in reality.

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

Episode Information

Series
Models of Consciousness
People
Anita Mehta
Keywords
oxford
computer science
consciousness
neuroscience
mathematics
Department: Department of Computer Science
Date Added: 13/10/2019
Duration: 00:22:07

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Ramón Guevara Erra - Statistical mechanics of consciousness: maximization of information content of neuronal networks is associated with conscious awareness

Series
Models of Consciousness
Embed
One in a series of talks from the 2019 Models of Consciousness conference.
Ramón Guevara Erra
Integrative Neuroscience and Cognition Center (UMR 8002), CNRS and
Université Paris Descartes, Paris, France

It has been argued that consciousness could be an emergent property of large neuronal networks, associated to the integration of information in the brain. However, it is not yet clear how is consciousness related to the complexity of functional brain networks. Based on a statistical mechanics approach, we sought to identify features of brain organization that are optimal for sensory processing, and that may guide the emergence of consciousness, by analyzing neurophysiological recordings in conscious and unconscious states. We find a surprisingly simple result: Normal wakeful states are characterized by the greatest number of possible configurations of interactions between brain networks, representing highest entropy values. Therefore, the information content is larger in the network associated to conscious states, suggesting that consciousness could be the result of an optimization of information processing. These findings help to guide in a more formal sense inquiry into how consciousness arises from the organization of matter.

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

Episode Information

Series
Models of Consciousness
People
Ramón Guevara Erra
Keywords
oxford
computer science
consciousness
neuroscience
mathematics
Department: Department of Computer Science
Date Added: 13/10/2019
Duration: 00:20:50

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Michael Silberstein - Quantum mechanics and the consistency of conscious experience

Series
Models of Consciousness
Embed
One in a series of talks from the 2019 Models of Consciousness conference.
Michael Silberstein
Department of Philosophy, Elizabethtown College;
Department of Philosophy, University of Maryland

We discuss the implications for the determinateness and intersubjective consistency of conscious experience in two gedanken experiments from quantum mechanics (QM). In particular, we discuss Wigner's friend and the delayed choice quantum eraser experiment with a twist. These are both cases (experiments) where quantum phenomena, or at least allegedly possible quantum phenomena/experiments, and the content/ecacy of conscious experience seem to bear on one another. We discuss why these two cases raise concerns for the determinateness and intersubjective consistency of conscious experience. We outline a 4D-global constraint-based approach to explanation in general and for QM in particular that resolves any such concerns without having to invoke metaphysical quietism (as with pragmatic accounts of QM), objective collapse mechanisms or subjective collapse. In short, we provide an account of QM free from any concerns associated with either the standard formalism or relative-state formalism, an account that yields a single 4D block universe with determinate and intersubjectively consistent conscious experience for all conscious agents.

Essentially the mystery in both experiments is caused by a dynamical/causal view of QM, e.g., time-evolved states in Hilbert space, and as we show this mystery can be avoided by a spatiotemporal, constraint-based view of QM, e.g., path integral calculation of probability amplitudes using future boundary conditions. What will become clear is that rather than furiously seeking some way to make dubious deep connections between quantum physics and conscious experience, the kinds of 4D adynamical global constraints that are fundamental to both classical and quantum physics and the relationship between them, also constrain conscious experience. That is, physics properly understood, already is psychology.

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

Episode Information

Series
Models of Consciousness
People
Michael Silberstein
Keywords
oxford
computer science
consciousness
neuroscience
mathematics
Department: Department of Computer Science
Date Added: 13/10/2019
Duration: 00:27:47

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Yakov Kremnitzer - Quantum collapse models and awareness

Series
Models of Consciousness
Embed
One in a series of talks from the 2019 Models of Consciousness conference.
Yakov Kremnitzer
Mathematical Institute, University of Oxford

In this talk I will explore how quantum collapse models can be a key to understanding awareness. I will explain the mathematical structure of quantum collapse models and give an example where collapse is caused by a quantum version of integrated information (this is joint with Andre Ranchin).

I will then look at the possibility of understanding awareness from collapse models and how this could be used to model consciousness as an emergent phenomenon (joint work in progress with Johannes Kleiner).

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

Episode Information

Series
Models of Consciousness
People
Yakov Kremnitzer
Keywords
oxford
computer science
consciousness
neuroscience
mathematics
Department: Department of Computer Science
Date Added: 13/10/2019
Duration: 00:56:14

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