Integrated Information Theory Research Articles

Consciousness transitions during epilepsy seizures through the lens of integrated information theory

Consciousness is one of the most complex aspects of human experience. Studying the mechanisms involved in the transitions among different levels of consciousness remains as one of the greatest challenges in neuroscience. In this study we use a measure of integrated information (ΦAR) to evaluate dynamic changes during consciousness transitions. We applied the measure to intracranial electroencephalography (SEEG) recordings collected from 6 patients that suffer from refractory epilepsy, taking into account inter-ictal, pre-ictal and ictal periods. We analyzed the dynamical evolution of ΦAR in groups of electrode contacts outside the epileptogenic region and compared it with the Consciousness Seizure Scale (CCS). We show that changes on ΦAR are significantly correlated with changes in the reported states of consciousness.

What is it like to be an AI bat?

Consciousness is a natural phenomenon, familiar to every person. At the same time, it cannot be described in singular terms. The rise of Artificial Intelligence in recent years has made the topic of Artificial Consciousness highly debated. The paper discusses the main general theories of consciousness and their relationship with proposed Artificial Consciousness solutions. There are a number of well-established models accepted in the area of research: Higher Order Thoughts/Higher Order Perception, Global Network Workspace, Integrated Information Theory, reflexive, representative, functional, connective, Multiple Draft Model, Neural Correlate of Consciousness, quantum consciousness, to name just a few. Some theories overlap, which allows for speaking about more advanced, complex models. The disagreement in theories leads to different views on animal consciousness and human conscious states. As a result, there are also variations in the opinions about Artificial Consciousness based on the discrepancy between qualia and the nature of AI. The hard problem of consciousness, an epitome of qualia, is often seen as an insurmountable barrier or, at least, an “explanatory gap”. Nevertheless, AI constructs allow imitations of some models in silico, which are presented by several authors as full-fledged Artificial Consciousness or as strong AI. This itself does not make the translation of consciousness into the AI space easier but allows decent progress in the domain. As argued in this paper, there will be no universal solution to the Artificial Consciousness problem, and the answer depends on the type of consciousness model. A more pragmatic view suggests the instrumental interaction between humans and AI in the environment of the Fifth Industrial Revolution, limiting expectations of strong AI outcomes to cognition but not consciousness in wide terms.

Global Versus Local Theories of Consciousness and the Consciousness Assessment Issue in Brain Organoids

Any attempt at consciousness assessment in organoids requires careful consideration of the theory of consciousness that researchers will rely on when performing this task. In cognitive neuroscience and the clinic, there are tools and theories used to detect and measure consciousness, typically in human beings, but none of them is neither fully consensual nor fit for the biological characteristics of organoids. I discuss the existing attempt relying on the Integrated Information Theory and its models and tools. Then, I revive the distinction between global theories of consciousness and local theories of consciousness as a thought-provoking one for those engaged in the difficult task of adapting models of consciousness to the biological reality of brain organoids. The “microconsciousness theory” of Semir Zeki is taken as an exploratory path and illustration of a theory defending that minimal networks can support a form of consciousness. I suggest that the skepticism prevailing in the neuroscience community regarding the possibility of organoid consciousness relies on some assumptions related to a globalist account of consciousness and that other accounts are worth exploring at this stage.

What is it like to be an AI bat?

Consciousness is a natural phenomenon, familiar to every person. At the same time, it cannot be described in singular terms. The rise of Artificial Intelligence in recent years has made the topic of Artificial Consciousness highly debated. The paper discusses the main general theories of consciousness and their relationship with proposed Artificial Consciousness solutions. There are a number of well-established models accepted in the area of research: Higher Order Thoughts/Higher Order Perception, Global Network Workspace, Integrated Information Theory, reflexive, representative, functional, connective, Multiple Draft Model, Neural Correlate of Consciousness, quantum consciousness, to name just a few. Some theories overlap, which allows for speaking about more advanced, complex models. The disagreement in theories leads to different views on animal consciousness and human conscious states. As a result, there are also variations in the opinions about Artificial Consciousness based on the discrepancy between qualia and the nature of AI. The hard problem of consciousness, an epitome of qualia, is often seen as an insurmountable barrier or, at least, an “explanatory gap”. Nevertheless, AI constructs allow imitations of some models in silico, which are presented by several authors as full-fledged Artificial Consciousness or as strong AI. This itself does not make the translation of consciousness into the AI space easier but allows decent progress in the domain. As argued in this paper, there will be no universal solution to the Artificial Consciousness problem, and the answer depends on the type of consciousness model. A more pragmatic view suggests the instrumental interaction between humans and AI in the environment of the Fifth Industrial Revolution, limiting expectations of strong AI outcomes to cognition but not consciousness in wide terms.

Entropic Consciousness: a proposal

The present work aims to be an advancement in the field of the science of consciousness, with the creation of a new conceptual formulation, “Entropic Consciousness” (EC). It starts from the milestones of Tononi’s Integrated Information Theory (IIT), and deepens them, looking at the conscious phenomenon from another perspective. By means of the MEI equivalence and the Landauer limit it equates the three energetic forms - information, energy, mass - and develops a new lens from which derive important implications regarding conscious experience and its consequences. Finally, he inserts the “free energy principle” developed by Friston into the discussion of consciousness, integrating it with the theorizations developed.

Carving Nature at Its Joints: A Comparison of CEMI Field Theory with Integrated Information Theory and Global Workspace Theory.

The quest to comprehend the nature of consciousness has spurred the development of many theories that seek to explain its underlying mechanisms and account for its neural correlates. In this paper, I compare my own conscious electromagnetic information field (cemi field) theory with integrated information theory (IIT) and global workspace theory (GWT) for their ability to 'carve nature at its joints' in the sense of predicting the entities, structures, states and dynamics that are conventionally recognized as being conscious or nonconscious. I go on to argue that, though the cemi field theory shares features of both integrated information theory and global workspace theory, it is more successful at carving nature at its conventionally accepted joints between conscious and nonconscious systems, and is thereby a more successful theory of consciousness.

Electronic Health System Integration Framework for Secure M-Health Services: A Case of University of Nairobi Hospital

The purpose of this article sought to design a secure framework that can be used in M-Health systems development. The researcher used the integrated information theory as a framework for enforcing system security as a holistic approach. To actualize this study, objectives that were meant to guide in carrying out the research were: To evaluate the significance of Confidentiality, Integrity and availability on the security of M-health systems and to develop a framework for secure integration of M-Health systems. The researcher used University of Nairobi Hospital because of ease of accessibility and financial resources available to conduct the research. The study adopted a cross section survey design methodology that included a sample size of 44 ICT personnel and users of University Health System at the University of Nairobi Hospital. Data collection methods were observation, conducting interviews and filling questionnaires that were administered to the target population in the University Hospital. The target population were handed the questionnaires and had them filled. The filled in questionnaires were then picked later from the respondents. SPSS version 23 was used for data analysis, then presented in frequency tables, bar charts, pie charts and standard deviation.

On the qualitative nature of conscious states: Insights from a structuralist theory of mind and meaning

AbstractThe point of departure of this paper is Penrose's definition of conscious action as that in which stimulus and response are linked by a non‐algorithmic relationship, which Penrose defines as ‘understanding’. My purpose is to explore the nature of this understanding by means of a two‐step process. The first step is provided by Tononi's Integrated Information Theory of consciousness. This theory provides us with a quantitative measure of conscious states that we need to transform into qualitative meaning. In the second step, we obtain this qualitative meaning with the help of the structuralist theory of mind. From this perspective, meaning originates in the set of qualitative contrasts that define the alternative courses of action that might have been implemented. Work on the analogy between quantitative bits and qualitative binary oppositions does not solve the hard problem of consciousness, but it might help to reformulate it in a new, productive way.

Phi fluctuates with surprisal: An empirical pre-study for the synthesis of the free energy principle and integrated information theory.

The Free Energy Principle (FEP) and Integrated Information Theory (IIT) are two ambitious theoretical approaches. The first aims to make a formal framework for describing self-organizing and life-like systems in general, and the second attempts a mathematical theory of conscious experience based on the intrinsic properties of a system. They are each concerned with complementary aspects of the properties of systems, one with life and behavior, the other with meaning and experience, so combining them has potential for scientific value. In this paper, we take a first step towards such a synthesis by expanding on the results of an earlier published evolutionary simulation study, which show a relationship between IIT-measures and fitness in differing complexities of tasks. We relate a basic information theoretic measure from the FEP, surprisal, to this result, finding that the surprisal of simulated agents' observations is inversely related to the general increase in fitness and integration over evolutionary time. Moreover, surprisal fluctuates together with IIT-based consciousness measures in within-trial time. This suggests that the consciousness measures used in IIT indirectly depend on the relation between the agent and the external world, and that it should therefore be possible to relate them to the theoretical concepts used in the FEP. Lastly, we suggest a future approach for investigating this relationship empirically.

Theoretical Neurobiology of Consciousness Applied to Human Cerebral Organoids.

Organoids and specifically human cerebral organoids (HCOs) are one of the most relevant novelties in the field of biomedical research. Grown either from embryonic or induced pluripotent stem cells, HCOs can be used as in vitro three-dimensional models, mimicking the developmental process and organization of the developing human brain. Based on that, and despite their current limitations, it cannot be assumed that they will never at any stage of development manifest some rudimentary form of consciousness. In the absence of behavioral indicators of consciousness, the theoretical neurobiology of consciousness being applied to unresponsive brain-injured patients can be considered with respect to HCOs. In clinical neurology, it is difficult to discern a capacity for consciousness in unresponsive brain-injured patients who provide no behavioral indicators of consciousness. In such scenarios, a validated neurobiological theory of consciousness, which tells us what the neural mechanisms of consciousness are, could be used to identify a capacity for consciousness. Like the unresponsive patients that provide a diagnostic difficulty for neurologists, HCOs provide no behavioral indicators of consciousness. Therefore, this article discusses how three prominent neurobiological theories of consciousness apply to human cerebral organoids. From the perspective of the Temporal Circuit Hypothesis, the Global Neuronal Workspace Theory, and the Integrated Information Theory, we discuss what neuronal structures and functions might indicate that cerebral organoids have a neurobiological capacity to be conscious.

Integrated information theory (IIT) 4.0: Formulating the properties of phenomenal existence in physical terms.

This paper presents Integrated Information Theory (IIT) 4.0. IIT aims to account for the properties of experience in physical (operational) terms. It identifies the essential properties of experience (axioms), infers the necessary and sufficient properties that its substrate must satisfy (postulates), and expresses them in mathematical terms. In principle, the postulates can be applied to any system of units in a state to determine whether it is conscious, to what degree, and in what way. IIT offers a parsimonious explanation of empirical evidence, makes testable predictions concerning both the presence and the quality of experience, and permits inferences and extrapolations. IIT 4.0 incorporates several developments of the past ten years, including a more accurate formulation of the axioms as postulates and mathematical expressions, the introduction of a unique measure of intrinsic information that is consistent with the postulates, and an explicit assessment of causal relations. By fully unfolding a system's irreducible cause-effect power, the distinctions and relations specified by a substrate can account for the quality of experience.

The Fundamental Tension in Integrated Information Theory 4.0's Realist Idealism.

Integrated Information Theory (IIT) is currently one of the most influential scientific theories of consciousness. Here, we focus specifically on a metaphysical aspect of the theory's most recent version (IIT 4.0), what we may call its idealistic ontology, and its tension with a kind of realism about the external world that IIT also endorses. IIT 4.0 openly rejects the mainstream view that consciousness is generated by the brain, positing instead that consciousness is ontologically primary while the physical domain is just "operational". However, this philosophical position is presently underdeveloped and is not rigorously formulated in IIT, potentially leading to many misinterpretations and undermining its overall explanatory power. In the present paper we aim to address this issue. We argue that IIT's idealistic ontology should be understood as a specific combination of phenomenal primitivism, reductionism regarding Φ-structures and complexes, and eliminativism about non-conscious physical entities. Having clarified this, we then focus on the problematic tension between IIT's idealistic ontology and its simultaneous endorsement of realism, according to which there is some kind of external reality independent of our minds. After refuting three potential solutions to this theoretical tension, we propose the most plausible alternative: understanding IIT's realism as an assertion of the existence of other experiences beyond one's own, what we call a non-solipsistic idealist realism. We end with concluding remarks and future research avenues.

Reply to Rourk, C. Comment on "Albantakis et al. Computing the Integrated Information of a Quantum Mechanism. Entropy 2023, 25, 449".

In response to a comment by Chris Rourk on our article Computing the Integrated Information of a Quantum Mechanism, we briefly (1) consider the role of potential hybrid/classical mechanisms from the perspective of integrated information theory (IIT), (2) discuss whether the (Q)IIT formalism needs to be extended to capture the hypothesized hybrid mechanism, and (3) clarify our motivation for developing a QIIT formalism and its scope of applicability.

Comment on Albantakis et al. Computing the Integrated Information of a Quantum Mechanism. Entropy 2023, 25, 449.

Integrated information theory (IIT) is a powerful tool that provides a framework for evaluating consciousness, whether in the human brain or in other systems. In Computing the Integrated Information of a Quantum Mechanism, the authors extend IIT from digital gates to a quantum CNOT logic gate, and while they explicitly distinguish the analysis from quantum theories of consciousness, they nonetheless provide an analytical road map for extending IIT not only to other quantum mechanisms but also to hybrid computing structures like the brain. This comment provides additional information relating to an adiabatic quantum mechanical energy routing mechanism that is part of a hybrid biological computer that provides an action selection mechanism, which has been hypothesized to exist in the human brain and for which predicted evidence has been subsequently observed, and it hopes to motivate the further evaluation and extension of IIT not only to that hypothesized mechanism but also to other hybrid biological computers.

Simultaneity of consciousness with physical reality: the key that unlocks the mind-matter problem.

The problem of explaining the relationship between subjective experience and physical reality remains difficult and unresolved. In most explanations, consciousness is epiphenomenal, without causal power. The most notable exception is Integrated Information Theory (IIT), which provides a causal explanation for consciousness. However, IIT relies on an identity between subjectivity and a particular type of physical structure, namely with an information structure that has intrinsic causal power greater than the sum of its parts. Any theory that relies on a psycho-phyiscal identity must eventually appeal to panpsychism, which undermines that theory's claim to be fundamental. IIT has recently pivoted towards a strong version of causal emergence, but macroscopic structures cannot be stronger causally than their microphysical parts without some new physical law or governing principle. The approach taken here is designed to uncover such a principle. The decisive argument is entirely deductive from initial premises that are phenomenologically certain. If correct, the arguments prove that conscious experience is sufficient to create additional degrees of causal freedom independently of the content of experience, and in a manner that is unpredictable and unobservable by any temporally sequential means. This provides a fundamental principle about consciousness, and a conceptual bridge between it and the physics describing what is experienced. The principle makes testable predictions about brain function, with notable differences from IIT, some of which are also empirically testable.

Integrated Information is not Causation: Why Integrated Information Theory’s Causal Structures do not Beat Causal Reductionism

In a recent work (Grasso et al., 2021), practitioners of the Integrated Information Theory (IIT) claim to have overcome the weaknesses of causal reductionism in producing a coherent account of causation, as causal reductionism would blatantly conflate causation with prediction and could not answer the question of ‘what caused what.’ In this paper, I reject such a dismissal of causal reductionism since IIT anti-reductionists misunderstand the reductionist stance. The reductionists can still invoke a causal account stemming from the causal power of the universe’s basic units and interactions that, eventually, may lead to structures supporting integrated information. Additionally, I claim that the IIT-inspired misunderstanding of causal reductionism originates from the former’s metaphysical deficit, conflating information with causation. However, as a possible way out, if IIT is complemented with a deeper metaphysical ground, such as nested hylomorphism, an improved argument against causal reductionism can be made to work by invoking formal causality as the ultimate cause of integration in natural systems.

Method for quantifying arousal and consciousness in healthy states and severe brain injury via EEG-based measures of corticothalamic physiology

Background:Characterization of normal arousal states has been achieved by fitting predictions of corticothalamic neural field theory (NFT) to electroencephalographic (EEG) spectra to yield relevant physiological parameters. New Method:A prior fitting method is extended to distinguish conscious and unconscious states in healthy and brain injured subjects by identifying additional parameters and clusters in parameter space. Results:Fits of NFT predictions to EEG spectra are used to estimate neurophysiological parameters in healthy and brain injured subjects. Spectra are used from healthy subjects in wake and sleep and from patients with unresponsive wakefulness syndrome, in a minimally conscious state (MCS), and emerged from MCS. Subjects cluster into three groups in parameter space: conscious healthy (wake and REM), sleep, and brain injured. These are distinguished by the difference X−Y between corticocortical (X) and corticothalamic (Y) feedbacks, and by mean neural response rates α and β to incoming spikes. X−Y tracks consciousness in healthy individuals, with smaller values in wake/REM than sleep, but cannot distinguish between brain injuries. Parameters α and β differentiate deep sleep from wake/REM and brain injury. Comparison with existing methods:Other methods typically rely on laborious clinical assessment, manual EEG scoring, or evaluation of measures like Φ from integrated information theory, for which no efficient method exists. In contrast, the present method can be automated on a personal computer. Conclusion:The method provides a means to quantify consciousness and arousal in healthy and brain injured subjects, but does not distinguish subtypes of brain injury.

An Implementation of Integrated Information Theory in Resting-State fMRI

An Implementation of Integrated Information Theory in Resting-State fMRI

An implementation of integrated information theory in resting-state fMRI

Integrated Information Theory was developed to explain and quantify consciousness, arguing that conscious systems consist of elements that are integrated through their causal properties. This study presents an implementation of Integrated Information Theory 3.0, the latest version of this framework, to functional MRI data. Data were acquired from 17 healthy subjects who underwent sedation with propofol, a short-acting anaesthetic. Using the PyPhi software package, we systematically analyze how Φmax, a measure of integrated information, is modulated by the sedative in different resting-state networks. We compare Φmax to other proposed measures of conscious level, including the previous version of integrated information, Granger causality, and correlation-based functional connectivity. Our results indicate that Φmax presents a variety of sedative-induced behaviours for different networks. Notably, changes to Φmax closely reflect changes to subjects’ conscious level in the frontoparietal and dorsal attention networks, which are responsible for higher-order cognitive functions. In conclusion, our findings present important insight into different measures of conscious level that will be useful in future implementations to functional MRI and other forms of neuroimaging.

On the non-uniqueness problem inintegrated information theory.

Integrated Information Theory (IIT) 3.0 is among the leading theories of consciousness in contemporary neuroscience. The core of the theory relies on the calculation of a scalar mathematical measure of consciousness, Φ, which is inspired by the phenomenological axioms of the theory. Here, we show that despite its widespread application, Φ is not a well-defined mathematical concept in the sense that the value it specifies is non-unique. To demonstrate this, we introduce an algorithm that calculates all possible Φ values for a given system in strict accordance with the mathematical definition from the theory. We show that, to date, all published Φ values under consideration are selected arbitrarily from a multitude of equally valid alternatives. Crucially, both [Formula: see text] and [Formula: see text] are often predicted simultaneously, rendering any interpretation of these systems as conscious or not, non-decidable in the current formulation of IIT.