Neuroscience of Consciousness
2026
William Marshall, Graham Findlay, Larissa Albantakis et al.
Integrated information theory (IIT) aims to account for the quality and quantity of consciousness in physical terms. According to IIT, a substrate of consciousness must be a system of units (e.g. synapses, neurons, minicolumns, etc.) that is a maximum of intrinsic, specific, unitary cause-effect power, quantified by integrated information ([Formula: see text]). The grain of each unit must be...
arXiv Preprint Archive
July 31, 2025
Larissa Albantakis
Toy models are highly idealized and deliberately simplified models that retain only the essential features of a system in order to explore specific theoretical questions. Long used in physics and other sciences, they have recently begun to play a more visible role in consciousness research. This chapter examines the potential utility of toy models for developing and evaluating scientific...
arXiv Preprint Archive
December 5, 2024
Graham Findlay, William Marshall, Larissa Albantakis et al.
Developments in machine learning and computing power suggest that artificial general intelligence is within reach. This raises the question of artificial consciousness: if a computer were to be functionally equivalent to a human, being able to do all we do, would it experience sights, sounds, and thoughts, as we do when we are conscious? Answering this question in a principled manner can only...
PLoS Computational Biology
October 1, 2023
Christoffer Lundbak Olesen, Peter Thestrup Waade, Larissa Albantakis et al.
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...
Entropy (Basel, Switzerland)
March 3, 2023
Larissa Albantakis, Robert Prentner, Ian T. Durham
Originally conceived as a theory of consciousness, integrated information theory (IIT) provides a theoretical framework intended to characterize the compositional causal information that a system, in its current state, specifies about itself. However, it remains to be determined whether IIT as a theory of consciousness is compatible with quantum mechanics as a theory of microphysics. Here, we...
Entropy
February 11, 2023
William Marshall, Matteo Grasso, William G. P. Mayner et al.
19 citations
Integrated information theory (IIT) starts from consciousness itself and identifies a set of properties (axioms) that are true of every conceivable experience. The axioms are translated into a set of postulates about the substrate of consciousness (called a complex), which are then used to formulate a mathematical framework for assessing both the quality and quantity of experience. The...
arXiv Preprint Archive
January 4, 2023
Larissa Albantakis, Robert Prentner, Ian T. Durham
Originally conceived as a theory of consciousness, integrated information theory (IIT) provides a theoretical framework intended to characterize the compositional causal information that a system, in its current state, specifies about itself. However, it remains to be determined whether IIT as a theory of consciousness is compatible with quantum mechanics as a theory of microphysics. Here, we...
arXiv Preprint Archive
June 4, 2022
Giulio Tononi, Larissa Albantakis, Melanie Boly et al.
preprint
This essay addresses the implications of integrated information theory (IIT) for free will. IIT is a theory of what consciousness is and of how its presence and quality can be accounted for in physical terms. According to IIT, the presence of consciousness is accounted for by a maximum of cause-effect power in the brain. Moreover, the way an experience feels is accounted for by how that...
arXiv Preprint Archive
June 4, 2022
Giulio Tononi, Larissa Albantakis, Melanie Boly et al.
This essay addresses the implications of integrated information theory (IIT) for free will. IIT is a theory of what consciousness is and what it takes to have it. According to IIT, the presence of consciousness is accounted for by a maximum of cause-effect power in the brain. Moreover, the way specific experiences feel is accounted for by how that cause-effect power is structured. If IIT is...
Entropy
March 18, 2021
Leonardo S. Barbosa, William Marshall, Larissa Albantakis et al.
74 citations
The Integrated Information Theory (IIT) of consciousness starts from essential phenomenological properties, which are then translated into postulates that any physical system must satisfy in order to specify the physical substrate of consciousness. We recently introduced an information measure (Barbosa et al., 2020) that captures three postulates of IIT-existence, intrinsicality and...
Neuroscience of Consciousness
2021
Francesco Ellia, Jeremiah Hendren, Matteo Grasso et al.
61 citations
Objective correlates-behavioral, functional, and neural-provide essential tools for the scientific study of consciousness. But reliance on these correlates should not lead to the 'fallacy of misplaced objectivity': the assumption that only objective properties should and can be accounted for objectively through science. Instead, what needs to be explained scientifically is what experience is...
Neuroscience of Consciousness
2016
Erik Hoel, Larissa Albantakis, William Marshall et al.
153 citations
Causal interactions within complex systems such as the brain can be analyzed at multiple spatiotemporal levels. It is widely assumed that the micro level is causally complete, thus excluding causation at the macro level. However, by measuring effective information—how much a system’s mechanisms constrain its past and future states—we recently showed that causal power can be stronger at macro...
PLoS Comput. Biol.
May 1, 2014
Masafumi Oizumi, Larissa Albantakis, Giulio Tononi
This paper presents Integrated Information Theory (IIT) of consciousness 3.0, which incorporates several advances over previous formulations. IIT starts from phenomenological axioms: information says that each experience is specific – it is what it is by how it differs from alternative experiences; integration says that it is unified – irreducible to non-interdependent components; exclusion...