Integrated information theory (IIT) proposes a mathematical model for theconsciousness of a system. It comprises a framework ultimately intended to explain why some physical systems (such ashuman brains) are conscious,[1] 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 (e.g. why our visual field appears extended when we gaze out at the night sky),[2] and what it would take for other physical systems to be conscious (Are other animals conscious?Might the whole universe be?).[3] The theory inspired the development of new clinical techniques to empirically assess consciousness in unresponsive patients.[4]
According to IIT,integrated information (Φ) corresponds to thequantity of consciousness. That is, a system's consciousness (what it is like subjectively) is conjectured to be mathematically described by the system's causal structure (what it is like objectively). Therefore, it should be possible to account for the conscious experience of a physical system by unfolding its complete causal powers.[5]
IIT was proposed by neuroscientistGiulio Tononi in 2004.[6] Despite significant interest, IIT remains controversial. In 2023, a number of scholars characterized it asunfalsifiablepseudoscience for lacking sufficient empirical support, a claim reiterated in a 2025Nature Neuroscience commentary. A survey of researchers in the field found only a small minority fully endorsing the "pseudoscience" label.[7] Other researchers have defended the theory in response.[8]
David Chalmers has argued that any attempt to explain consciousness in purely physical terms (i.e., to start with the laws of physics as they are currently formulated and derive the necessary and inevitable existence of consciousness) eventually runs into the so-called "hard problem". Rather than try to start from physical principles and arrive at consciousness, IIT "starts with consciousness" (accepts the existence of our own consciousness as certain) 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 fromphenomenology 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[9] and conscious patients with large amounts of brain matter missing.[10]
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 (dubbed "axioms") and, from there, the essential properties of conscious physical systems (dubbed "postulates").
Intrinsic information (ii) for a state s over a possible cause/effect state:
Integrated information (φ) as the irreducibility of that cause–effect structure across the minimum information partition (MIP):
Complexes are defined as the systems (subsets of units) that locally maximize φ. Their internaldistinctions (mechanism states) andrelations (their overlap) form the Φ-structure (asimplicial complex) of the system:
corresponds to thequantity of consciousness, while the particular structure of distinctions and relations defines itsquality.
IIT proposes an explanatory identity: an experienceis identical to the cause–effect structure (Φ-structure) unfolded from acomplex in its current state. This identity is not a correlation but a proposed explanation for how subjective experience arises from physical mechanisms.[11]
The calculation of even a modestly-sized system's is often computationally intractable,[12] so efforts have been made to develop heuristic or proxy measures of integrated information. For example, Masafumi Oizumi and colleagues have developed both[13] and geometric integrated information or,[14] which are practical approximations for integrated information. These are related to proxy measures developed earlier byAnil Seth and Adam Barrett.[15] 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.[16]
In 2021, Angus Leung and colleagues published a direct application of IIT's mathematical formalism to neural data.[17] 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.[17]
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.[18]
While the algorithm[12][19] for assessing a system's and conceptual structure is relatively straightforward, its hightime complexity makes it computationally intractable for many systems of interest.[12] 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.[20][21] 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 (dreaming vs. non-dreaming), anesthetized, and comatose (vegetative vs. minimally-conscious vs. locked-in) individuals.[22]
The theory has found practical application in the development of thePerturbational Complexity Index (PCI), an empirical measure used inclinical neuroscience to assess the level of consciousness in patients by quantifying the brain's capacity for integrated information throughTMS-EEG recordings.[4]
IIT also makes several predictions which fit well with existing experimental evidence, and can be used to explain some counterintuitive findings in consciousness research.[23] For example, IIT can be used to explain why some brain regions, such as thecerebellum do not appear to contribute to consciousness, despite their size and/or functional importance.
NeuroscientistChristof Koch, who has helped to develop later versions of the theory, has called IIT "the only really promising fundamental theory of consciousness".[24]
Neuroscientist and consciousness researcherAnil 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 [IIT] 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.",[25] and has criticized thepanpsychist extrapolations of the theory.[26]
PhilosopherDavid Chalmers, famous for the idea ofthe 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.[27]
Max Tegmark has tried to address the problem of thecomputational 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."[28] As a result, Φ can only be approximated in general. However, different ways of approximating Φ provide radically different results.[29] 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.[30][31]
In 2019, theTempleton Foundation announced funding in excess of $6,000,000 to test opposing empirical predictions of IIT and a rival theory (Global Neuronal Workspace Theory, GNWT).[32][33] 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.[34][35] Initial results were revealed in June 2023.[36] None of GNWT's predictions passed what was agreed upon pre-registration while two out of three of IIT's predictions passed that threshold.[37] The final, peer-reviewed results were published in the 30 April 2025 issue ofNature.[38] In an accompanying editorial, the editors ofNature 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."[39]
In a March 2025Nature 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.[40] A commentary in the same issue by Alex Gomez-Marin andAnil Seth, titled "A science of consciousness beyond pseudo-science and pseudo-consciousness", argued that, despite current empirical limitations, IIT remains scientifically legitimate.[41]
Influential philosopherJohn Searle has given a critique of the theory saying "The theory impliespanpsychism" and "The problem with panpsychism is not that it is false; it does not get up to the level of being false. It is strictly speaking meaningless because no clear notion has been given to the claim."[42] Searle's take has itself been criticized by other philosophers for misunderstanding and misrepresenting a theory that may actually be resonant with his own ideas.[43]
Theoretical computer scientistScott Aaronson has criticized IIT by demonstrating through its own formulation that an inactive series oflogic gates, arranged in the correct way, would not only be conscious but be "unboundedly more conscious than humans are."[44] Tononi himself agrees with the assessment and argues that according to IIT, an even simpler arrangement of inactive logic gates, if large enough, would also be conscious. However he further argues that this is a strength of IIT rather than a weakness, because that's exactly the sort ofcytoarchitecture followed by large portions of thecerebral cortex,[45][46] specially at the back of the brain,[2] which is the most likely neuroanatomicalcorrelate of consciousness according to some reviews.[47]
Philosopher Tim Bayne has criticized the axiomatic foundations of the theory.[48] He concludes that "the so-called 'axioms' that Tononi et al. appeal to fail to qualify as genuine axioms".
IIT as a scientific theory of consciousness has been criticized in the scientific literature as only able to be "either false or unscientific" by its own definitions.[49] IIT has also been denounced by other members of the consciousness field as requiring "an unscientific leap of faith".[50] The theory has also been derided for failing to answer the basic questions required of a theory of consciousness. Philosopher Adam Pautz says "As long as proponents of IIT do not address these questions, they have not put a clear theory on the table that can be evaluated as true or false."[51] NeuroscientistMichael Graziano, proponent of the competingattention schema theory, rejects IIT aspseudoscience. He claims IIT is a "magicalist theory" that has "no chance of scientific success or understanding".[52] Similarly, IIT was criticized that its claims are "not scientifically established or testable at the moment".[53]
NeuroscientistsBjörn Merker,David Rudrauf and PhilosopherKenneth Williford co-authored a paper criticizing IIT on several grounds. Firstly, by not demonstrating that all members of systems which do in fact combine integration and differentiation in the formal IIT sense are conscious, systems which demonstrate high levels of integration and differentiation of information might provide the necessary conditions for consciousness but those combinations of attributes do not amount to the conditions for consciousness. Secondly that the measure, Φ, reflects efficiency of global information transfer rather than level of consciousness, and that the correlation of Φ with level of consciousness through different states of wakefulness (e.g. awake, dreaming and dreamless sleep, anesthesia, seizures and coma) actually reflect the level of efficient network interactions performed for cortical engagement. Hence Φ reflects network efficiency rather than consciousness, which would be one of the functions served by cortical network efficiency.[54]
A letter published on 15 September 2023 in the preprint repositoryPsyArXiv and signed by 124 scholars asserted that until IIT is empirically testable, it should be labeled pseudoscience.[55] A number of researchers defended the theory in response.[8] An anonymized public survey invited all authors from peer-reviewed papers published between 2013 and 2023 found by a query ofWeb of Science using "consciousness AND theor*". Of the 60 respondents, 8% "fully" agreed, and 20% did "not at all" agree with the letter, with the remainder falling in between these poles.[7]
The 10 March 2025Nature Neuroscience commentary "What Makes a Theory of Consciousness Unscientific?" was signed by many of the same writers as the letter. It asserts that "the core ideas of IIT lack empirical support and are metaphysical, and not scientific" and refers to "the core claims of IIT, which we argue are unscientific".[56]
^Ferrante, O.; et al. (Cogitate Consortium) (26 June 2023). "An adversarial collaboration to critically evaluate theories of consciousness".bioRxiv10.1101/2023.06.23.546249.
^Merker, Björn (19 May 2021). "The Integrated Information Theory of consciousness: A case of mistaken identity".Behavioral and Brain Sciences.45 e41.doi:10.1017/S0140525X21000881.PMID34006338.
IIT-wiki: An online learning resource aimed at teaching the foundations of IIT; includes texts, slideshows, interactive coding exercises, and sections for discussion and asking questions.
