Neuroscience of Consciousness
January 1, 2016
Erik Hoel, Larissa Albantakis, William Marshall et al.
153 citations
Causal interactions in complex systems like the brain can be examined at different spatiotemporal levels. While it is often assumed that the micro level is causally complete, this work shows that causal power can be stronger at macro levels. Using a measure called ΦMax, developed within integrated information theory, the authors systematically evaluated causal power at micro and macro levels in simplified neuronal-like systems. For systems with indeterminism or degeneracy, ΦMax peaked at a macro level when coarse-graining micro elements produced macro mechanisms with high irreducible causal selectivity.
Entropy
March 18, 2021
Leonardo S. Barbosa, William Marshall, Larissa Albantakis et al.
74 citations
Integrated Information Theory (IIT) begins with essential properties of consciousness and translates them into postulates that any physical system must satisfy to specify the physical substrate of consciousness. A recently introduced information measure captures three of these postulates—existence, intrinsicality, and information—and is unique. This work shows that the measure also satisfies the remaining postulates of integration and exclusion, creating a framework that identifies maximally irreducible mechanisms. These mechanisms can form maximally irreducible systems, which then specify the physical substrate of conscious experience.
Neuroscience of Consciousness
January 1, 2021
Francesco Ellia, Jeremiah Hendren, Matteo Grasso et al.
61 citations
Subjective experience can be objectively explained in physical terms by moving beyond cognitive functions and understanding how experience is structured. Integrated information theory provides a framework to account for both the essential properties of every experience and the specific properties that make particular experiences feel the way they do, avoiding the fallacy that only objective properties should be explained by science.
Entropy
February 11, 2023
William Marshall, Matteo Grasso, William G. P. Mayner et al.
19 citations
Integrated information theory (IIT) proposes that consciousness is identical to the cause-effect structure generated by a maximally irreducible substrate (a Φ-structure). This work introduces a definition for system-integrated information (φs) grounded in IIT's postulates of existence, intrinsicality, information, and integration. It examines how determinism, degeneracy, and connectivity fault lines affect system-integrated information. The proposed measure identifies complexes as systems whose φs exceeds that of any overlapping candidate systems.
Neuroscience of Consciousness
January 1, 2026
William Marshall, Graham Findlay, Larissa Albantakis et al.
Integrated information theory (IIT) holds that consciousness corresponds to a system's maximum intrinsic, specific, and unitary cause-effect power, quantified as integrated information (Φ). The appropriate grain of analysis—from micro to macro—is the one that maximizes Φ. This paper presents a formal framework for computing Φ in systems that include macro units, thereby identifying a system's intrinsic units. It extends IIT 4.0's mathematics to assess cause-effect power across grains. Simulations of simple systems show that including macro units can yield higher integrated information than micro-only systems. Three examples illustrate how different macro units increase cause-effect power. The framework provides a foundation for testing and inferring consciousness.
arXiv Preprint Archive
July 31, 2025
Larissa Albantakis
Toy models—highly simplified representations that retain only essential features of a system—are increasingly used in consciousness research. This chapter examines their role in developing and evaluating scientific theories of consciousness, particularly Integrated Information Theory (IIT) and Global Workspace Theory (GWT). These models make abstract concepts more tangible, allowing researchers to test assumptions, clarify theoretical frameworks, and probe the coherence and implications of competing accounts. They also address specific experiential features, such as spatial extendedness and temporal flow, and sharpen philosophical debates, including the distinction between functional and structural theories. By bridging abstract claims and empirical inquiry, toy models provide essential insights into building comprehensive theories of consciousness.
arXiv Preprint Archive
December 5, 2024
Graham Findlay, William Marshall, Larissa Albantakis et al.
A digital computer could simulate human behavior without replicating subjective experience, according to Integrated Information Theory (IIT). Using simple Boolean units, the authors show that two systems can be functionally equivalent—one simulating the other—yet not phenomenally equivalent. This contradicts computational functionalism, which holds that performing the right computations is necessary and sufficient for consciousness. The analysis demonstrates that functional equivalence does not guarantee phenomenal equivalence, and this conclusion holds regardless of the simulated system's function. Even a computer that simulates neurons in the brain may not experience sights, sounds, or thoughts as humans do.
PLoS Computational Biology
October 1, 2023
Christoffer Lundbak Olesen, Peter Thestrup Waade, Larissa Albantakis et al.
Two major theoretical frameworks—the Free Energy Principle, which describes how self-organizing systems maintain order, and Integrated Information Theory, which aims to mathematically characterize conscious experience—are brought together. Analyzing data from an earlier evolutionary simulation, the authors show that agents' surprisal (a measure from the Free Energy Principle) decreases as their fitness and neural integration increase over evolutionary time. Furthermore, surprisal fluctuates in tandem with IIT-based measures of consciousness within individual trials. This suggests that IIT's consciousness measures are partly shaped by the agent's interaction with its environment, making a formal link between the two theories possible.
Entropy (Basel, Switzerland)
March 3, 2023
Larissa Albantakis, Robert Prentner, Ian T. Durham
Integrated information theory (IIT) was originally developed to characterize the causal information a system specifies about itself as a theory of consciousness, but its compatibility with quantum mechanics has been unclear. This work extends IIT's latest formalism to evaluate mechanism integrated information (φ) for discrete, finite-dimensional quantum systems such as quantum logic gates. The authors translate a measure of intrinsic information into a density matrix formulation and extend conditional independence to accommodate quantum entanglement. The compositional analysis may reveal structure in composite quantum states and operators not accessible through standard information-theoretical methods. The results aim to inform theoretical arguments about the links among consciousness, causation, and physics across classical and quantum domains.
arXiv Preprint Archive
January 4, 2023
Larissa Albantakis, Robert Prentner, Ian T. Durham
Integrated information theory (IIT), originally a framework for characterizing consciousness through causal information, is extended to finite-dimensional quantum systems such as quantum logic gates. The authors translate a measure of intrinsic information into a density matrix formulation and adapt conditional independence to account for quantum entanglement. This quantum extension of IIT may reveal internal structure of composite quantum states and operators that standard information-theoretic analysis misses. The work aims to inform debates about the relationship among consciousness, causation, and physics across classical and quantum domains.
arXiv Preprint Archive
June 4, 2022
Giulio Tononi, Larissa Albantakis, Melanie Boly et al.
Integrated information theory (IIT) implies that free will exists in a fundamental sense. IIT defines consciousness as a maximum of cause-effect power in the brain, with the structure of that power determining how experiences feel. According to this theory, humans have true alternatives, make true decisions, and are the true cause of their willed actions, bearing true responsibility. The argument depends on an intrinsic powers ontology: only intrinsic entities truly exist and can cause effects, and consciousness qualifies as such an entity.