# What is integrated information theory? > Integrated information theory (IIT), proposed by Giulio Tononi in 2004, says that consciousness is integrated information: how much a system as a whole constrains its own past and future beyond what its parts do, measured by a quantity called Φ. It predicts that consciousness depends on the causal structure of the posterior cortex. It is influential, hard to compute and heavily debated. Author: Mikhail Savchenko Updated: 2026-09-26 Canonical: https://neuralcosmology.com/en/answers/integrated-information-theory Locale: en Translations: en, ru, pt, es License: CC-BY-4.0 (https://creativecommons.org/licenses/by/4.0/) --- ## The core idea Most theories of consciousness start from the brain and ask which activity is conscious. Giulio Tononi started from experience itself. Every experience, he argued, is **integrated** (you see a red ball, not a separate red and a separate round) and **informative** (it is one specific experience out of a vast number possible). A physical system can support consciousness only if it has the same properties. From this, IIT (*BMC Neuroscience*, 2004; latest version IIT 4.0, Albantakis et al., *PLOS Computational Biology*, 2023) defines consciousness as integrated information and measures it with **Φ**. ## What Φ measures Take a system of interacting parts. Ask how much its current state constrains its past and future states as a whole, and compare that with what you would get if you cut it into independent pieces along the weakest seam. The difference is Φ. - A pile of sand has almost no Φ: cutting it changes nothing. - A feed-forward circuit, where signals flow one way, has zero Φ however complex it is. - A densely recurrent network, where parts constantly influence each other, can have high Φ. IIT also says which part of a system is conscious: the subset with maximal Φ, called the main complex. ## Predictions - **Posterior cortex.** IIT predicts that the core of experience lies in densely interconnected posterior regions of the cortex, a "posterior hot zone", more than in the frontal areas that report and plan. - **Loss of consciousness.** In deep sleep and anaesthesia, integration should break down even if activity continues. The perturbational complexity index (Casali et al., *Science Translational Medicine*, 2013) tests this: a magnetic pulse to the cortex produces a complex, widespread echo in waking and dreaming, and a simple local one in dreamless sleep and anaesthesia. - **Machines.** Because Φ depends on physical causal structure, a conventional computer running any program has very low Φ. ## The tests against global workspace theory A consortium of labs (Cogitate) designed preregistered experiments in which IIT and global neuronal workspace theory predict different outcomes. The results, published in *Nature* in 2025, supported some predictions of each and contradicted others: the sustained synchronisation within posterior cortex that IIT predicted did not appear. The exercise changed the field more than the verdict did: theories of consciousness now compete on predictions that can fail. ## Criticism - **Computability.** Exact Φ requires checking every way of cutting a system, which is impossible for a brain. - **Counterintuitive cases.** Scott Aaronson showed in 2014 that simple grid-like arrangements of logic gates can have Φ far higher than a human brain, which many take as a reductio. - **Testability.** In 2023 more than a hundred researchers called IIT pseudoscience in an open letter; others replied that it makes more testable predictions than most rivals. The disagreement is still live. ## Alternatives to Φ Several groups propose other integration measures that are cheaper to compute. The *Pointer Architecture* preprint on this site defines a substrate-side measure, **Φ_PA**, which is non-zero only for an observer that reads its own state back, with non-trivial scope and lifespan. It predicts, for example, zero for a single transformer forward pass and a positive value when the model reuses its own cache. The predictions are so far checked on toy encodings. Details are on the [preprint page](/en/science/pointer-architecture). ## Bottom line IIT is the most mathematically developed theory of consciousness. It explains why integration matters and has produced a useful clinical tool. Its central quantity cannot be computed for real brains, and some of its implications strike many researchers as absurd. It is a serious theory that is still under active test. ## FAQ ### What does Φ (phi) measure? Φ measures how much a system's cause–effect structure is irreducible: how much would be lost if you cut the system into independent parts. A system with Φ = 0 is just a collection of parts; a system with high Φ acts as an integrated whole. ### Is IIT used in medicine? An offshoot is. The perturbational complexity index (PCI), developed by Marcello Massimini's group, stimulates the cortex with a magnetic pulse and measures how complex the EEG response is. It separates wakefulness, sleep, anaesthesia and disorders of consciousness and is being used to assess unresponsive patients. ### Why is IIT controversial? Φ cannot be computed for real brains, some simple lattice-like systems would have enormous Φ, and the theory implies consciousness in many systems people find implausible. In 2023 over a hundred researchers signed a letter calling it pseudoscience, which many others rejected. ### Can AI be conscious according to IIT? IIT ties consciousness to physical causal structure, not to behaviour or software. On standard digital hardware, IIT predicts very low Φ regardless of how intelligent the program seems.