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 How Morphological Computation Shapes Integrated Information in Embodied Agents

2021 ◽  
Vol 12 ◽  
Author(s):  
Carlotta Langer ◽  
Nihat Ay
Keyword(s):  
Information Integration ◽  
The Body ◽  
Information Flows ◽  
Morphological Computation ◽  
The One ◽  
Goal Directed Behavior ◽  
The Brain ◽  
Integrated Information Theory ◽  
Embodied Agent ◽  
Integrated Information

The Integrated Information Theory provides a quantitative approach to consciousness and can be applied to neural networks. An embodied agent controlled by such a network influences and is being influenced by its environment. This involves, on the one hand, morphological computation within goal directed action and, on the other hand, integrated information within the controller, the agent's brain. In this article, we combine different methods in order to examine the information flows among and within the body, the brain and the environment of an agent. This allows us to relate various information flows to each other. We test this framework in a simple experimental setup. There, we calculate the optimal policy for goal-directed behavior based on the “planning as inference” method, in which the information-geometric em-algorithm is used to optimize the likelihood of the goal. Morphological computation and integrated information are then calculated with respect to the optimal policies. Comparing the dynamics of these measures under changing morphological circumstances highlights the antagonistic relationship between these two concepts. The more morphological computation is involved, the less information integration within the brain is required. In order to determine the influence of the brain on the behavior of the agent it is necessary to additionally measure the information flow to and from the brain.

scholarly journals Scaling Behaviour and Critical Phase Transitions in Integrated Information Theory

Entropy ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. 1198 ◽  
Author(s):  
Miguel Aguilera
Keyword(s):  
Information Theory ◽  
Phase Transitions ◽  
Computational Cost ◽  
Homogeneous Distribution ◽  
Kinetic Ising Model ◽  
Information Measures ◽  
Scaling Behaviour ◽  
Critical Phase ◽  
Integrated Information Theory ◽  
Integrated Information

Integrated Information Theory proposes a measure of conscious activity ( Φ ), characterised as the irreducibility of a dynamical system to the sum of its components. Due to its computational cost, current versions of the theory (IIT 3.0) are difficult to apply to systems larger than a dozen units, and, in general, it is not well known how integrated information scales as systems grow larger in size. In this article, we propose to study the scaling behaviour of integrated information in a simple model of a critical phase transition: an infinite-range kinetic Ising model. In this model, we assume a homogeneous distribution of couplings to simplify the computation of integrated information. This simplified model allows us to critically review some of the design assumptions behind the measure and connect its properties with well-known phenomena in phase transitions in statistical mechanics. As a result, we point to some aspects of the mathematical definitions of IIT that 3.0 fail to capture critical phase transitions and propose a reformulation of the assumptions made by integrated information measures.

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 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.

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