scholarly journals What might interoceptive inference reveal about consciousness?

2021 ◽  
Author(s):  
Niia Emilova Nikolova ◽  
Peter Thestrup Waade ◽  
Karl Friston ◽  
Micah Allen
Keyword(s):  
Information Theory ◽  
Rapid Development ◽  
Higher Order ◽  
Predictive Processing ◽  
New Approaches ◽  
The Brain ◽  
Integrated Information Theory ◽  
Mainstream Science ◽  
Philosophical Understanding ◽  
Integrated Information

The mainstream science of consciousness offers a few predominate views of how the brain gives rise to awareness. Chief among these are the Higher Order Thought Theory, Global Neuronal Workspace Theory, Integrated Information Theory, and hybrids thereof. In parallel, rapid development in predictive processing approaches have begun to outline concrete mechanisms by which interoceptive inference shapes selfhood, affect, and exteroceptive perception. Here, we consider these new approaches in terms of what they might offer our empirical, phenomenological, and philosophical understanding of consciousness and its neurobiological roots.

scholarly journals Efficient Algorithms for Searching the Minimum Information Partition in Integrated Information Theory

Entropy ◽  
2018 ◽  
Vol 20 (3) ◽  
pp. 173 ◽  
Author(s):  
Jun Kitazono ◽  
Ryota Kanai ◽  
Masafumi Oizumi
Keyword(s):  
Information Theory ◽  
Information Integration ◽  
Computational Cost ◽  
Simulated Data ◽  
Essential Property ◽  
Minimum Information ◽  
Neural Data ◽  
The Brain ◽  
Integrated Information Theory ◽  
Integrated Information

The ability to integrate information in the brain is considered to be an essential property for cognition and consciousness. Integrated Information Theory (IIT) hypothesizes that the amount of integrated information ( Φ ) in the brain is related to the level of consciousness. IIT proposes that, to quantify information integration in a system as a whole, integrated information should be measured across the partition of the system at which information loss caused by partitioning is minimized, called the Minimum Information Partition (MIP). The computational cost for exhaustively searching for the MIP grows exponentially with system size, making it difficult to apply IIT to real neural data. It has been previously shown that, if a measure of Φ satisfies a mathematical property, submodularity, the MIP can be found in a polynomial order by an optimization algorithm. However, although the first version of Φ is submodular, the later versions are not. In this study, we empirically explore to what extent the algorithm can be applied to the non-submodular measures of Φ by evaluating the accuracy of the algorithm in simulated data and real neural data. We find that the algorithm identifies the MIP in a nearly perfect manner even for the non-submodular measures. Our results show that the algorithm allows us to measure Φ in large systems within a practical amount of time.

scholarly journals The Mathematical Structure of Integrated Information Theory

2021 ◽  
Vol 6 ◽  
Author(s):  
Johannes Kleiner ◽  
Sean Tull
Keyword(s):  
Information Theory ◽  
Conscious Experience ◽  
Mathematical Structure ◽  
Starting Point ◽  
Special Cases ◽  
Axiomatic Definition ◽  
Definition Of ◽  
The Brain ◽  
Integrated Information Theory ◽  
Integrated Information

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 formal investigations and as an introduction suitable for researchers with a formal background.

scholarly journals Awareness and integrated information theory identify plant meristems as sites of conscious activity

PROTOPLASMA ◽  
2021 ◽  
Author(s):  
Anthony Trewavas
Keyword(s):  
Information Theory ◽  
Nervous System ◽  
Complex Networks ◽  
Environmental Changes ◽  
Biological Function ◽  
Human Consciousness ◽  
Extrinsic Information ◽  
Integrated Information Theory ◽  
Conscious Activity ◽  
Integrated Information

AbstractLacking an anatomical brain/nervous system, it is assumed plants are not conscious. The biological function of consciousness is an input to behaviour; it is adaptive (subject to selection) and based on information. Complex language makes human consciousness unique. Consciousness is equated to awareness. All organisms are aware of their surroundings, modifying their behaviour to improve survival. Awareness requires assessment too. The mechanisms of animal assessment are neural while molecular and electrical in plants. Awareness of plants being also consciousness may resolve controversy. The integrated information theory (IIT), a leading theory of consciousness, is also blind to brains, nerves and synapses. The integrated information theory indicates plant awareness involves information of two kinds: (1) communicative, extrinsic information as a result of the perception of environmental changes and (2) integrated intrinsic information located in the shoot and root meristems and possibly cambium. The combination of information constructs an information nexus in the meristems leading to assessment and behaviour. The interpretation of integrated information in meristems probably involves the complex networks built around [Ca2+]i that also enable plant learning, memory and intelligent activities. A mature plant contains a large number of conjoined, conscious or aware, meristems possibly unique in the living kingdom.

How to Catch an AI Zombie

2020 ◽  
pp. 439-458
Author(s):  
Susan Schneider
Keyword(s):  
Information Theory ◽  
Natural Language ◽  
Real World ◽  
Phenomenal Consciousness ◽  
Artificial Consciousness ◽  
High Level ◽  
Integrated Information Theory ◽  
Integrated Information

How can we determine if AI is conscious? The chapter begins by illustrating that there are potentially very serious real-world costs to getting facts about AI consciousness wrong. It then proposes a provisional framework for investigating artificial consciousness that involves several tests or markers. One test is the AI Consciousness Test, which challenges an AI with a series of increasingly demanding natural-language interactions. Another test is based on the Integrated Information Theory, developed by Giulio Tononi and others, and considers whether a machine has a high level of “integrated information.” A third test is a Chip Test, where speculatively an individual’s brain is gradually replaced with durable microchips. If this individual being tested continues to report having phenomenal consciousness, the chapter argues that this could be a reason to believe that some machines could have consciousness.

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