Integrated information theory

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Integrated information theory (IIT) proposes a mathematical model for the consciousness of a system. It comprises a framework ultimately intended to explain why some physical systems (such as human 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 is having; 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]

According to IIT, a system's consciousness (what it is like subjectively) is conjectured to be identical to its causal properties (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.^[4]

IIT was proposed by neuroscientist

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 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^[7] and conscious patients with large amounts of brain matter missing.^[8]

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").

Mathematics: formalization of the postulates

For a complete and thorough account of the mathematical formalization of IIT this paper,^[9] is the one advised.

Extensions

The calculation of even a modestly-sized system's ${\displaystyle \Phi ^{\textrm {Max}}}$ is often computationally intractable,^[9] so efforts have been made to develop heuristic or proxy measures of integrated information. For example, Masafumi Oizumi and colleagues have developed both ${\displaystyle \Phi ^{*}}$^[10] and geometric integrated information or ${\displaystyle \Phi ^{G}}$,^[11] which are practical approximations for integrated information. These are related to proxy measures developed earlier by Anil Seth and Adam Barrett.^[12] However, none of these proxy measures have a mathematically proven relationship to the actual ${\displaystyle \Phi ^{\textrm {Max}}}$ value, which complicates the interpretation of analyses that use them. They can give qualitatively different results even for very small systems.^[13]

In 2021, Angus Leung and colleagues published a direct application of IIT's mathematical formalism to neural data.^[14] To circumvent the computational challenges associated with larger datasets, the authors focused on neuronal population activity in the fly. The study showed that ${\displaystyle \Phi ^{\textrm {Max}}}$ can readily be computed for smaller sets of neural data. Moreover, matching IIT's predictions, ${\displaystyle \Phi ^{\textrm {Max}}}$was significantly decreased when the animals underwent general anesthesia.^[14]

A significant computational challenge in calculating integrated information is finding the

While the algorithm[9]^[16] for assessing a system's ${\displaystyle \Phi ^{\textrm {Max}}}$ and conceptual structure is relatively straightforward, its high time complexity makes it computationally intractable for many systems of interest.^[9] 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.^[17][18] For instance, a recent study using a less computationally-intensive proxy for ${\displaystyle \Phi ^{\textrm {Max}}}$ 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.^[19]

IIT also makes several predictions which fit well with existing experimental evidence, and can be used to explain some counterintuitive findings in consciousness research.^[1] 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".^[20]

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 [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.",^[21] and has criticized the panpsychist extrapolations of the theory.^[22]

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.^[23]

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."^[24] As a result, Φ can only be approximated in general. However, different ways of approximating Φ provide radically different results.^[25] 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.^[26][27]

Criticism

Influential philosopher John Searle has given a critique of theory saying "The theory implies panpsychism" 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.".^[28] However, whether or not a theory has panpsychist implications (that all or most of what exists physically must be, be part of something that is, or be composed of parts that are, conscious) has no bearing on the scientific validity of the theory. Searle's take has also been countered by other philosophers, for misunderstanding and misrepresenting a theory that is actually resonant with his own ideas.^[29]

Theoretical computer scientist Scott Aaronson has criticized IIT by demonstrating through its own formulation that an inactive series of logic gates, arranged in the correct way, would not only be conscious but be "unboundedly more conscious than humans are."^[30] 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 of cytoarchitecture followed by large portions of the cerebral cortex,^[31][32] specially at the back of the brain,^[2] which is the most likely neuroanatomical correlate of consciousness according to some reviews.^[33]

Philosopher Tim Bayne has criticized the axiomatic foundations of the theory.^[34] He concludes that "the so-called 'axioms' that Tononi et al. appeal to fail to qualify as genuine axioms".

A peer-reviewed commentary by 58 scholars involved in the scientific study of consciousness rejects these conclusions about logic gates as "mysterious and unfalsifiable claims" that should be distinguished from "empirically productive hypotheses".^{[35][clarification needed]} 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.^[36] IIT has also been denounced by other members of the consciousness field as requiring "an unscientific leap of faith", but it is not clear that this is in fact the case if the theory is properly understood.^[37] 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."^[38] Neuroscientist Michael Graziano, proponent of the competing attention schema theory, rejects IIT as pseudoscience. He claims IIT is a "magicalist theory" that has "no chance of scientific success or understanding".^[39] Similarly, IIT was criticized that its claims are "not scientifically established or testable at the moment".^[40]

However, while it is true that the complete analysis suggested by IIT cannot be completed at the moment for human brains, IIT has already been applied to models of visual cortex to explain why visual space feels the way it does.^[2]

Neuroscientists

In 2019, the Templeton 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).^[44][45] 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.^[46][47] Initial results were revealed in June 2023.^[48] None of GNWT's predictions passed what was agreed upon pre-registration while two out of three of IIT's predictions passed that threshold.^[49]

See also

References

External links

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Related papers

• Tononi, Giulio; Boly, Melanie; Massimini, Marcello; Koch, Christof (2016). "Integrated information theory: From consciousness to its physical substrate". Nature Reviews Neuroscience. 17 (7): 450–461.
  S2CID 21347087
  .
• Tononi, Giulio (2015). "Integrated information theory". Scholarpedia. 10 (1): 4164.
  doi:10.4249/scholarpedia.4164
  .
• Oizumi, Masafumi; Albantakis, Larissa; Tononi, Giulio (2014). "From the Phenomenology to the Mechanisms of Consciousness: Integrated Information Theory 3.0". PLOS Computational Biology. 10 (5): e1003588.
  S2CID 2578087
  .
• Integrated Information Theory: An Updated Account (2012) (First presentation of IIT 3.0)
• Tononi, Giulio (2008). "Consciousness as Integrated Information: A Provisional Manifesto". The Biological Bulletin. 215 (3): 216–242.
  PMID 19098144
  .
• Tononi, Giulio (2004). "An information integration theory of consciousness". BMC Neuroscience. 5: 42.
  PMID 15522121
  .

Websites

• integratedinformationtheory.org: resource for learning about IIT; features a graphical user interface to PyPhi.
• "Integrated Information Theory of Consciousness". Internet Encyclopedia of Philosophy.

Software

• PyPhi: an open-source Python package for calculating integrated information.
  • Mayner, William G. P.; Marshall, William; Albantakis, Larissa; Findlay, Graham; Marchman, Robert; Tononi, Giulio (2018). "PyPhi: A toolbox for integrated information theory". PLOS Computational Biology. 14 (7): e1006343.
    PMID 30048445
    .
  • Graphical user interface
  • Documentation

Books

• The Feeling of Life Itself: Why Consciousness is Widespread but Can't Be Computed by Christof Koch (2019)
• Phi: A Voyage from the Brain to the Soul by Giulio Tononi (2012)

News articles

• New Scientist (2019): How does consciousness work? A radical theory has mind-blowing answers
• Nautilus (2017): Is Matter Conscious?
• Aeon (2016): Consciousness creep
• MIT Technology Review (2014): What It Will Take for Computers to Be Conscious
• Wired (2013): A Neuroscientist's Radical Theory of How Networks Become Conscious
• The New Yorker (2013): How Much Consciousness Does an iPhone Have?
• New York Times (2010): Sizing Up Consciousness by Its Bits
• Scientific American (2009): A "Complex" Theory of Consciousness
• IEEE Spectrum (2008): A Bit of Theory: Consciousness as Integrated Information Theory

Talks

• David Chalmers (2014): How do you explain consciousness?
• Christof Koch (2014): The Integrated Information Theory of Consciousness