Integrated information theory

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Short description: Theory within consciousness research (proposed 2004)


Phi; the symbol used for integrated information

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 (see Central identity).[4]

IIT was proposed by neuroscientist Giulio Tononi in 2004.[5] Despite significant interest, IIT remains controversial and has been widely criticized, with some claiming that it is unfalsifiable pseudoscience.[6]

Overview

Relationship to the "hard problem of consciousness"

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, see reference.[9]

Extensions

The calculation of even a modestly-sized system's [math]\displaystyle{ \Phi^{\textrm{Max}} }[/math] is often computationally intractable,[10] so efforts have been made to develop heuristic or proxy measures of integrated information. For example, Masafumi Oizumi and colleagues have developed both [math]\displaystyle{ \Phi^* }[/math][11] and geometric integrated information or [math]\displaystyle{ \Phi^G }[/math],[12] which are practical approximations for integrated information. These are related to proxy measures developed earlier by Anil Seth and Adam Barrett.[13] However, none of these proxy measures have a mathematically proven relationship to the actual [math]\displaystyle{ \Phi^{\textrm{Max}} }[/math] value, which complicates the interpretation of analyses that use them. They can give qualitatively different results even for very small systems.[14]

In 2021, Angus Leung and colleagues published a direct application of IIT's mathematical formalism to neural data.[15] To circumvent the computational challenges associated with larger datasets, the authors focused on neuronal population activity in the fly. The study showed that [math]\displaystyle{ \Phi^{\textrm{Max}} }[/math] can readily be computed for smaller sets of neural data. Moreover, matching IIT's predictions, [math]\displaystyle{ \Phi^{\textrm{Max}} }[/math]was significantly decreased when the animals underwent general anesthesia.[15]

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.[16]

Related experimental work

While the algorithm[10][17] for assessing a system's [math]\displaystyle{ \Phi^{\textrm{Max}} }[/math] and conceptual structure is relatively straightforward, its high time complexity makes it computationally intractable for many systems of interest.[10] 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.[18][19] For instance, a recent study using a less computationally-intensive proxy for [math]\displaystyle{ \Phi^{\textrm{Max}} }[/math] 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.[20]

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".[21]

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.",[22] and has criticized the panpsychist extrapolations of the theory.[23]

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.[24]

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."[25] As a result, Φ can only be approximated in general. However, different ways of approximating Φ provide radically different results.[26] 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.[27][28]

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.".[29] 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.[30]

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."[31] 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,[32][33] specially at the back of the brain,[2] which is the most likely neuroanatomical correlate of consciousness according to some reviews.[34]

Philosopher Tim Bayne has criticized the axiomatic foundations of the theory.[35] 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".[36][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.[37] 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.[38] 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."[39] 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".[40] Similarily, IIT was criticized that its claims are "not scientifically established or testable at the moment".[41]

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 Björn Merker, David Rudrauf and Philosopher Kenneth 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.[42]

A letter published on 15 September 2023 in the preprint repository PsyArXiv and signed by 124 scholars asserted that until IIT is empirically testable, it should be labeled pseudoscience.[43] A number of researchers defended the theory in response.[6] Regarding this letter, IIT, and what he considers a similarly unscientific theory, Assembly theory (AT), University of Cambridge and University of Oxford computer scientist Hector Zenil made criticisms based on the lack of correspondence of the methods and theory in some of the IIT research papers and the media frenzy.[44] Zenil criticized both the shallowness and misleading nature of the media coverage, including in apparently respected journals such as Nature and Science. He also criticized testing methods and evidence used by IIT proponents, noting that one test amounted to simply applying LZW compression to measure entropy rather than to indicate consciousness as proponents claimed.

Adversarial Collaboration to test GNW and IIT

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).[45][46] 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.[47][48] Initial results were revealed in June 2023.[49] None of GNWT's predictions passed what was agreed upon pre-registration while two out of three of IIT's predictions passed that threshold.[50]

See also


References

  1. ↑ 1.0 1.1 Tononi, Giulio (2015). "Integrated information theory". Scholarpedia 10 (1): 4164. doi:10.4249/scholarpedia.4164. Bibcode: 2015SchpJ..10.4164T. 
  2. ↑ 2.0 2.1 2.2 Haun, Andrew; Tononi, Giulio (December 2019). "Why Does Space Feel the Way it Does? Towards a Principled Account of Spatial Experience" (in en). Entropy 21 (12): 1160. doi:10.3390/e21121160. Bibcode: 2019Entrp..21.1160H. 
  3. ↑ Tononi, Giulio; Koch, Christof (2015-05-19). "Consciousness: here, there and everywhere?" (in en). Philosophical Transactions of the Royal Society B: Biological Sciences 370 (1668): 20140167. doi:10.1098/rstb.2014.0167. ISSN 0962-8436. PMID 25823865. 
  4. ↑ 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. doi:10.1038/nrn.2016.44. PMID 27225071. 
  5. ↑ Tononi, Giulio (2004-11-02). "An information integration theory of consciousness". BMC Neuroscience 5 (1): 42. doi:10.1186/1471-2202-5-42. ISSN 1471-2202. PMID 15522121. 
  6. ↑ 6.0 6.1 Mariana Lenharo (20 September 2023). "Consciousness theory slammed as 'pseudoscience' — sparking uproar". Nature. https://www.nature.com/articles/d41586-023-02971-1. 
  7. ↑ De Haan, Edward H. F.; Corballis, Paul M.; Hillyard, Steven A.; Marzi, Carlo A.; Seth, Anil; Lamme, Victor A. F.; Volz, Lukas; Fabri, Mara et al. (2020). "Split-Brain: What We Know Now and Why This is Important for Understanding Consciousness". Neuropsychology Review 30 (2): 224–233. doi:10.1007/s11065-020-09439-3. PMID 32399946. 
  8. ↑ Feuillet, Lionel; Dufour, Henry; Pelletier, Jean (2007). "Brain of a white-collar worker". The Lancet 370 (9583): 262. doi:10.1016/S0140-6736(07)61127-1. PMID 17658396. https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(07)61127-1/fulltext. 
  9. ↑ Albantakis, Larissa (October 17, 2023). "Integrated information theory (IIT) 4.0: Formulating the properties of phenomenal existence in physical terms". PLOS Computational Biology 19 (10): e1011465. doi:10.1371/journal.pcbi.1011465. PMID 37847724. 
  10. ↑ 10.0 10.1 10.2 Mayner, William G. P.; Marshall, William; Albantakis, Larissa; Findlay, Graham; Marchman, Robert; Tononi, Giulio (2018-07-26). "PyPhi: A toolbox for integrated information theory". PLOS Computational Biology 14 (7): e1006343. doi:10.1371/journal.pcbi.1006343. ISSN 1553-7358. PMID 30048445. Bibcode: 2018PLSCB..14E6343M. 
  11. ↑ Oizumi, Masafumi; Amari, Shun-ichi; Yanagawa, Toru; Fujii, Naotaka; Tsuchiya, Naotsugu (2015-05-17). "Measuring integrated information from the decoding perspective". PLOS Computational Biology 12 (1): e1004654. doi:10.1371/journal.pcbi.1004654. PMID 26796119. Bibcode: 2016PLSCB..12E4654O. 
  12. ↑ Oizumi, Masafumi; Tsuchiya, Naotsugu; Amari, Shun-ichi (20 December 2016). "Unified framework for information integration based on information geometry". Proceedings of the National Academy of Sciences 113 (51): 14817–14822. doi:10.1073/pnas.1603583113. PMID 27930289. Bibcode: 2016PNAS..11314817O. 
  13. ↑ Barrett, A.B.; Seth, A.K. (2011). "Practical measures of integrated information for time-series data". PLOS Comput. Biol. 7 (1): e1001052. doi:10.1371/journal.pcbi.1001052. PMID 21283779. Bibcode: 2011PLSCB...7E1052B. 
  14. ↑ Mediano, Pedro; Seth, Anil; Barrett, Adam (2018-12-25). "Measuring Integrated Information: Comparison of Candidate Measures in Theory and Simulation". Entropy 21 (1): 17. doi:10.3390/e21010017. ISSN 1099-4300. PMID 33266733. Bibcode: 2018Entrp..21...17M. 
  15. ↑ 15.0 15.1 Leung, Angus; Cohen, Dror; van Swinderen, Bruno; Tsuchiya, Naotsugu (2021). "Integrated information structure collapses with anesthetic loss of conscious arousal in Drosophila melanogaster". PLOS Computational Biology 17 (2): e1008722. doi:10.1371/journal.pcbi.1008722. ISSN 1553-7358. PMID 33635858. Bibcode: 2021PLSCB..17E8722L. 
  16. ↑ Toker, Daniel; Sommer, Friedrich T.; Marinazzo, Daniele (7 February 2019). "Information integration in large brain networks". PLOS Computational Biology 15 (2): e1006807. doi:10.1371/journal.pcbi.1006807. PMID 30730907. Bibcode: 2019PLSCB..15E6807T. 
  17. ↑ "CSC-UW/iit-pseudocode". https://github.com/CSC-UW/iit-pseudocode. 
  18. ↑ Massimini, M.; Ferrarelli, F.; Murphy, Mj; Huber, R.; Riedner, Ba; Casarotto, S.; Tononi, G. (2010-09-01). "Cortical reactivity and effective connectivity during REM sleep in humans". Cognitive Neuroscience 1 (3): 176–183. doi:10.1080/17588921003731578. ISSN 1758-8936. PMID 20823938. 
  19. ↑ Ferrarelli, Fabio; Massimini, Marcello; Sarasso, Simone; Casali, Adenauer; Riedner, Brady A.; Angelini, Giuditta; Tononi, Giulio; Pearce, Robert A. (2010-02-09). "Breakdown in cortical effective connectivity during midazolam-induced loss of consciousness". Proceedings of the National Academy of Sciences of the United States of America 107 (6): 2681–2686. doi:10.1073/pnas.0913008107. ISSN 1091-6490. PMID 20133802. Bibcode: 2010PNAS..107.2681F. 
  20. ↑ Casali, Adenauer G.; Gosseries, Olivia; Rosanova, Mario; Boly, Mélanie; Sarasso, Simone; Casali, Karina R.; Casarotto, Silvia; Bruno, Marie-Aurélie et al. (2013-08-14). "A Theoretically Based Index of Consciousness Independent of Sensory Processing and Behavior" (in en). Science Translational Medicine 5 (198): 198ra105. doi:10.1126/scitranslmed.3006294. ISSN 1946-6234. PMID 23946194. https://orbi.uliege.be/handle/2268/171542. 
  21. ↑ Zimmer, Carl (2010-09-20). "Sizing Up Consciousness by Its Bits". The New York Times. ISSN 0362-4331. https://www.nytimes.com/2010/09/21/science/21consciousness.html. 
  22. ↑ Falk, Dan (2021-09-30). "Anil Seth Finds Consciousness in Life's Push Against Entropy" (in en). https://www.quantamagazine.org/anil-seth-finds-consciousness-in-lifes-push-against-entropy-20210930/. 
  23. ↑ akseth (2018-02-01). "Conscious spoons, really? Pushing back against panpsychism" (in en). https://neurobanter.com/2018/02/01/conscious-spoons-really-pushing-back-against-panpsychism/. 
  24. ↑ Chalmers, David (2014-07-14) (in en), How do you explain consciousness?, https://www.ted.com/talks/david_chalmers_how_do_you_explain_consciousness, retrieved 2021-12-16 
  25. ↑ Tegmark, Max (2016). "Improved Measures of Integrated Information". PLOS Computational Biology 12 (11): e1005123. doi:10.1371/journal.pcbi.1005123. PMID 27870846. Bibcode: 2016PLSCB..12E5123T. 
  26. ↑ Mediano, Pedro; Seth, Anil; Barrett, Adam (2019). "Measuring Integrated Information: Comparison of Candidate Measures in Theory and Simulation". Entropy 21 (1): 17. doi:10.3390/e21010017. PMID 33266733. Bibcode: 2018Entrp..21...17M. 
  27. ↑ Aguilera, Miguel; Di Paolo, Ezequiel (2019). "Integrated information in the thermodynamic limit". Neural Networks 114: 136–146. doi:10.1016/j.neunet.2019.03.001. PMID 30903946. 
  28. ↑ Aguilera, Miguel (2019). "Scaling Behaviour and Critical Phase Transitions in Integrated Information Theory". Entropy 21 (12): 1198. doi:10.3390/e21121198. Bibcode: 2019Entrp..21.1198A. 
  29. ↑ Searle, John. Can Information Theory Explain Consciousness?. https://www.nybooks.com/articles/2013/01/10/can-information-theory-explain-consciousness/. 
  30. ↑ Fallon, Francis (2020-09-01). "Integrated Information Theory, Searle, and the Arbitrariness Question" (in en). Review of Philosophy and Psychology 11 (3): 629–645. doi:10.1007/s13164-018-0409-0. ISSN 1878-5166. 
  31. ↑ Aaronson, Scott (21 May 2014). "Why I Am Not An Integrated Information Theorist (or, The Unconscious Expander)". https://www.scottaaronson.com/blog/?p=1799. 
  32. ↑ Aaronson, Scott (30 May 2014). "Giulio Tononi and Me: A Phi-nal Exchange". https://www.scottaaronson.com/blog/?p=1823. 
  33. ↑ Tononi, Giulio. "Why Scott should stare at a blank wall and reconsider (or, the conscious grid)". http://www.scottaaronson.com/tononi.docx. 
  34. ↑ Boly, Melanie; Massimini, Marcello; Tsuchiya, Naotsugu; Postle, Bradley R.; Koch, Christof; Tononi, Giulio (2017-10-04). "Are the Neural Correlates of Consciousness in the Front or in the Back of the Cerebral Cortex? Clinical and Neuroimaging Evidence" (in en). Journal of Neuroscience 37 (40): 9603–9613. doi:10.1523/JNEUROSCI.3218-16.2017. ISSN 0270-6474. PMID 28978697. PMC 5628406. https://www.jneurosci.org/content/37/40/9603. 
  35. ↑ Bayne, Tim (2018). "On the axiomatic foundations of the integrated information theory of consciousness". Neuroscience of Consciousness 2018 (1): niy007. doi:10.1093/nc/niy007. PMID 30042860. 
  36. ↑ Michel, Matthias; Beck, Diane; Block, Ned; Blumenfeld, Hal; Brown, Richard; Carmel, David; Carrasco, Marisa; Chirimuuta, Mazviita et al. (February 4, 2019). "Opportunities and challenges for a maturing science of consciousness". Nature Human Behaviour 3 (2): 104–107. doi:10.1038/s41562-019-0531-8. PMID 30944453. 
  37. ↑ Doerig, Adrian; Schruger, Aaron; Hess, Kathryn; Herzog, Michael (2019). "The unfolding argument: Why IIT and other causal structure theories cannot explain consciousness". Consciousness and Cognition 72: 49–59. doi:10.1016/j.concog.2019.04.002. PMID 31078047. 
  38. ↑ Lau, Hakwan; Michel, Matthias (2019). "On the dangers of conflating strong and weak versions of a theory of consciousness". PsyArXiv. doi:10.31234/osf.io/hjp3s. http://psyarxiv.com/hjp3s/. 
  39. ↑ Pautz, Adam (2019). "What is Integrated Information Theory?: A Catalogue of Questions". Journal of Consciousness Studies 26` (1): 188–215. 
  40. ↑ Jarrett, Christian (5 April 2020). "Consciousness: how can we solve the greatest mystery in science?". BBC Science Focus Magazine. https://www.sciencefocus.com/the-human-body/consciousness-how-can-we-solve-the-greatest-mystery-in-science/. Retrieved 2 February 2021. 
  41. ↑ Lau, Hakwan (28 May 2020). "Open letter to NIH on Neuroethics Roadmap (BRAIN initiative) 2019". https://inconsciousnesswetrust.blogspot.com/2020/05/open-letter-to-nih-on-neuroethics.html. .
  42. ↑ 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. PMID 34006338. 
  43. ↑ Fleming, S. M. et al. (2023). The Integrated Information Theory of Consciousness as Pseudoscience. doi:10.31234/osf.io/zsr78. https://psyarxiv.com/zsr78/. Retrieved 2023-09-18. 
  44. ↑ Zenil, Hector. "How Some Scientific Journalism is Failing Us, to both Readers & (less self-promotional) Scientists – Medium" (in en-US). https://hectorzenil.medium.com/how-scientific-journalism-is-failing-us-to-both-readers-and-non-self-promotional-scientists-5899dde19d7e. 
  45. ↑ "Accelerating Research on Consciousness: An Adversarial Collaboration to Test Contradictory Predictions of Global Neuronal Workspace and Integrated Information Theory" (in en). https://www.templetonworldcharity.org/projects-database/0389. 
  46. ↑ Melloni, Lucia; Mudrik, Liad; Pitts, Michael; Koch, Christof (2021-05-28). "Making the hard problem of consciousness easier" (in en). Science 372 (6545): 911–912. doi:10.1126/science.abj3259. ISSN 0036-8075. PMID 34045342. https://www.science.org/doi/10.1126/science.abj3259. 
  47. ↑ Melloni, Lucia; Mudrik, Liad; Pitts, Michael; Blumenfeld, Hal; Lange, Floris de; Jensen, Ole; Kreiman, Gabriel; Luo, Huan et al. (2019-01-16) (in en). Adversarial Collaboration to test GNW and IIT.. https://osf.io/mbcfy/. 
  48. ↑ Melloni, Lucia; Mudrik, Liad; Pitts, Michael; Bendtz, Katarina; Ferrante, Oscar; Gorska, Urszula; Hirschhorn, Rony; Khalaf, Aya et al. (2023-02-10). "An adversarial collaboration protocol for testing contrasting predictions of global neuronal workspace and integrated information theory" (in en). PLOS ONE 18 (2): e0268577. doi:10.1371/journal.pone.0268577. ISSN 1932-6203. PMID 36763595. Bibcode: 2023PLoSO..1868577M. 
  49. ↑ Finkel, Elizabeth (2023-06-30). "Consciousness hunt yields results but not clarity" (in en). Science 380 (6652): 1309–1310. doi:10.1126/science.adj4498. ISSN 0036-8075. PMID 37384689. Bibcode: 2023Sci...380.1309F. https://www.science.org/doi/10.1126/science.adj4498. 
  50. ↑ Ferrante, O.; et al. (Cogitate Consortium) (2023-06-26). "An adversarial collaboration to critically evaluate theories of consciousness". bioRxiv 10.1101/2023.06.23.546249.

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