Integrated information theory
Integrated information theory proposes a mathematical model for the consciousness of a system. It comprises a framework ultimately intended to explain why some physical systems are conscious, and to be capable of providing a concrete inference about whether any physical system is conscious, to what degree, and what particular experience it has; why they feel the particular way they do in particular states, and what it would take for other physical systems to be conscious. The theory inspired the development of new clinical techniques to empirically assess consciousness in unresponsive patients.
According to IIT, integrated information corresponds to the quantity of consciousness. That is, a system's consciousness is conjectured to be mathematically described by the system's causal structure. Therefore, it should be possible to account for the conscious experience of a physical system by unfolding its complete causal powers.
IIT was proposed by neuroscientist Giulio Tononi in 2004. Despite significant interest, IIT remains controversial. In 2023, a number of scholars characterized it as unfalsifiable pseudoscience for lacking sufficient empirical support, a claim reiterated in a 2025 Nature Neuroscience commentary. A survey of researchers in the field found only a small minority fully endorsing the "pseudoscience" label. Other researchers have defended the theory in response.
Overview
Relationship to the "hard problem of consciousness"
has argued that any attempt to explain consciousness in purely physical terms eventually runs into the so-called "hard problem". Rather than try to start from physical principles and arrive at consciousness, IIT "starts with consciousness" and reasons about the properties that a postulated physical substrate would need to have in order to account for it. The ability to perform this jump from phenomenology to mechanism rests on IIT's assumption that if the formal properties of a conscious experience can be fully accounted for by an underlying physical system, then the properties of the physical system must be constrained by the properties of the experience. The limitations on the physical system for consciousness to exist are unknown and consciousness may exist on a spectrum, as implied by studies involving split-brain patients and conscious patients with large amounts of brain matter missing.IIT aims to explain which physical systems are conscious, to what degree, and in what way. The theory begins from the phenomenological certainty that experience exists, and infers necessary physical postulates that any conscious substrate must satisfy. Specifically, IIT moves from phenomenology to mechanism by attempting to identify the essential properties of conscious experience and, from there, the essential properties of conscious physical systems.
IIT is grounded in:
- Realism – the world exists independently of experience
- Operational physicalism – physical existence means the ability to take and make a difference
- Atomism – causal power can, in principle, be reduced to interactions between minimal units
Axioms and postulates
- Intrinsicality – experience exists for itself
- Information – experience is specific
- Integration – experience is unitary
- Exclusion – experience is definite
- Composition – experience is structured
- The system must exert intrinsic cause–effect power
- It must specify a specific cause and effect state
- It must do so as a whole—irreducibly
- Only the maximally irreducible substrate is conscious
- Its subsets must specify structured distinctions and relations, forming a ''Φ-structure''
Mathematical formalism
Intrinsic information for a state s over a possible cause/effect state :
Integrated information as the irreducibility of that cause–effect structure across the minimum information partition :
Complexes are defined as the systems that locally maximize φ. Their internal distinctions and relations form the Φ-structure of the system:
corresponds to the quantity of consciousness, while the particular structure of distinctions and relations defines its quality.
Explanatory identity
IIT proposes an explanatory identity: an experience is identical to the cause–effect structure unfolded from a complex in its current state. This identity is not a correlation but a proposed explanation for how subjective experience arises from physical mechanisms.Extensions
The calculation of even a modestly-sized system's is often computationally intractable, so efforts have been made to develop heuristic or proxy measures of integrated information. For example, Masafumi Oizumi and colleagues have developed both and geometric integrated information or, which are practical approximations for integrated information. These are related to proxy measures developed earlier by Anil Seth and Adam Barrett. However, none of these proxy measures have a mathematically proven relationship to the actual value, which complicates the interpretation of analyses that use them. They can give qualitatively different results even for very small systems.In 2021, Angus Leung and colleagues published a direct application of IIT's mathematical formalism to neural data. To circumvent the computational challenges associated with larger datasets, the authors focused on neuronal population activity in the fly. The study showed that can readily be computed for smaller sets of neural data. Moreover, matching IIT's predictions, was significantly decreased when the animals underwent general anesthesia.
A significant computational challenge in calculating integrated information is finding the minimum information partition of a neural system, which requires iterating through all possible network partitions. To solve this problem, Daniel Toker and Friedrich T. Sommer have shown that the spectral decomposition of the correlation matrix of a system's dynamics is a quick and robust proxy for the minimum information partition.
Related experimental work
While the algorithm for assessing a system's and conceptual structure is relatively straightforward, its high time complexity makes it computationally intractable for many systems of interest. Heuristics and approximations can sometimes be used to provide ballpark estimates of a complex system's integrated information, but precise calculations are often impossible. These computational challenges, combined with the already difficult task of reliably and accurately assessing consciousness under experimental conditions, make testing many of the theory's predictions difficult.Despite these challenges, researchers have attempted to use measures of information integration and differentiation to assess levels of consciousness in a variety of subjects. For instance, a recent study using a less computationally-intensive proxy for was able to reliably discriminate between varying levels of consciousness in wakeful, sleeping, anesthetized, and comatose individuals.
The theory has found practical application in the development of the Perturbational Complexity Index, an empirical measure used in clinical neuroscience to assess the level of consciousness in patients by quantifying the brain's capacity for integrated information through TMS-EEG recordings.
IIT also makes several predictions which fit well with existing experimental evidence, and can be used to explain some counterintuitive findings in consciousness research. For example, IIT can be used to explain why some brain regions, such as the cerebellum do not appear to contribute to consciousness, despite their size and/or functional importance.
Reception
Integrated information theory has received both broad criticism and support.Support
Neuroscientist Christof Koch, who has helped to develop later versions of the theory, has called IIT "the only really promising fundamental theory of consciousness".Neuroscientist and consciousness researcher Anil Seth is supportive of the theory, with some caveats, claiming that "conscious experiences are highly informative and always integrated."; and that "One thing that immediately follows from is that you have a nice post hoc explanation for certain things we know about consciousness.". But he also claims "the parts of IIT that I find less promising are where it claims that integrated information actually is consciousness — that there's an identity between the two.", and has criticized the panpsychist extrapolations of the theory.
Philosopher David Chalmers, famous for the idea of the hard problem of consciousness, has expressed some enthusiasm about IIT. According to Chalmers, IIT is a development in the right direction, whether or not it is correct.
Max Tegmark has tried to address the problem of the computational complexity behind the calculations. According to Max Tegmark "the integration measure proposed by IIT is computationally infeasible to evaluate for large systems, growing super-exponentially with the system's information content." As a result, Φ can only be approximated in general. However, different ways of approximating Φ provide radically different results. Other works have shown that Φ can be computed in some large mean-field neural network models, although some assumptions of the theory have to be revised to capture phase transitions in these large systems.
In 2019, the Templeton Foundation announced funding in excess of $6,000,000 to test opposing empirical predictions of IIT and a rival theory. The originators of both theories signed off on experimental protocols and data analyses as well as the exact conditions that satisfy if their championed theory correctly predicted the outcome or not. Initial results were revealed in June 2023. None of GNWT's predictions passed what was agreed upon pre-registration while two out of three of IIT's predictions passed that threshold. The final, peer-reviewed results were published in the 30 April 2025 issue of Nature. In an accompanying editorial, the editors of Nature noted that "after the initial release of the results, an open letter was circulated in which IIT was described as a pseudoscience", and added that "such language has no place in a process designed to establish working relationships between competing groups."
In a March 2025 Nature Neuroscience commentary titled "Consciousness or pseudo-consciousness? A clash of two paradigms", proponents of IIT listed 16 peer-reviewed studies as empirical tests of the theory's core claims. A commentary in the same issue by Alex Gomez-Marin and Anil Seth, titled "A science of consciousness beyond pseudo-science and pseudo-consciousness", argued that, despite current empirical limitations, IIT remains scientifically legitimate.