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Escaping from the IIT Munchausen method: Re-establishing the scientific method in the study of consciousness

Published online by Cambridge University Press:  23 March 2022

Paul Verschure Open the ORCID record for Paul Verschure [Opens in a new window]
Paul Verschure*
Affiliation:
Cognition and Behaviour - Centre for Neuroscience (DCN-FNWI), 6500 GL Nijmegen, The Netherlands. [email protected]://www.specs-lab.com
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Abstract

Integrated information theory (IIT) is an example of “ironic science” and obstructs the scientific study of consciousness. By confusing the ontological status of a method to quantify network complexity with that of a theory of consciousness, IIT has to square the circle and spirals toward its panpsychism conclusion. I analyze the consequences of this fallacy and suggest how the study of consciousness can be brought back into the realm of rational, empirical science.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 45 , 2022 , e63
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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References

Barron, A. B., & Klein, C. (2016). What insects can tell us about the origins of consciousness. Proceedings of the National Academy of Sciences, 113(18), 4900–4908. https://doi.org/10.1073/pnas.1520084113CrossRefGoogle ScholarPubMed
Edelman, G. M., Reeke, G. N. J., Gall, W. E., Tononi, G., Williams, D., Sporns, O., & Reeke, G. N. Jr. (1992). Synthetic neural modeling applied to a real-world artifact. Proceedings of the National Academy of Sciences of the United States of America 89(15), 7267–7771.CrossRefGoogle ScholarPubMed
Estefan, D. P., Zucca, R., Arsiwalla, X., Principe, A., Zhang, H., Rocamora, R., … Verschure, P. F. M. J. (2021). Volitional learning promotes theta phase coding in the human hippocampus. Proceedings of the National Academy of Sciences 118(10), e2021238118. https://doi.org/10.1073/pnas.2021238118CrossRefGoogle Scholar
Feigin, V. L., Roth, G. A., Naghavi, M., Parmar, P., Krishnamurthi, R., Chugh, S., … Forouzanfar, M. H. (2016). Global burden of stroke and risk factors in 188 countries, during 1990–2013: A systematic analysis for the global burden of disease study 2013. The Lancet. Neurology 15(9), 913–924. https://doi.org/10.1016/S1474-4422(16)30073-4CrossRefGoogle ScholarPubMed
Hameroff, S., & Penrose, R. (1996). Orchestrated reduction of quantum coherence in brain microtubules: A model for consciousness. Mathematics and Computers in Simulation 40(3–4), 453–480.CrossRefGoogle Scholar
Horgan, J. (1996). The end of science: Facing the limits of knowledge in the twilight of the scientific age. Broadway.Google Scholar
Maffei, G., Santos-Pata, D., Marcos, E., Sánchez-Fibla, M., & Verschure, P. F. M. J. P. F. M. J. (2015). An embodied biologically constrained model of foraging: From classical and operant conditioning to adaptive real-world behavior in DAC-X. Neural Networks, 72, 88–108. https://doi.org/10.1016/j.neunet.2015.10.004CrossRefGoogle ScholarPubMed
Melloni, L., Mudrik, L., Pitts, M., & Koch, C. (2021). Making the hard problem of consciousness easier. Science (New York, N.Y.) 372(6545), 911–912.CrossRefGoogle ScholarPubMed
Merker, B. (2007). Consciousness without a cerebral cortex: A challenge for neuroscience and medicine. The Behavioral and Brain Sciences 30(1), 63–81, discussion 81–134. https://doi.org/10.1017/S0140525X07000891CrossRefGoogle ScholarPubMed
Noel, J.-P., Ishizawa, Y., Patel, S. R., Eskandar, E. N., & Wallace, M. T. (2019). Leveraging nonhuman primate multisensory neurons and circuits in assessing consciousness theory. Journal of Neuroscience 39(38), 7485–7500.CrossRefGoogle ScholarPubMed
Phillips, K. G., Beretta, A., & Whitaker, H. A. (2014) Mind and brain: Toward an understanding of dualism. In Smith, C. U. M. & Whitaker, H. (Eds.) Brain, mind and consciousness in the history of neuroscience, pp. 355–369. Springer.CrossRefGoogle Scholar
Sasai, S., Boly, M., Mensen, A., & Tononi, G. (2016). Functional split brain in a driving/listening paradigm. Proceedings of the National Academy of Sciences 113(50), 14444–14449.CrossRefGoogle Scholar
Tononi, G. (2012). Phi: A voyage from the brain to the soul. Pantheon.Google Scholar
Tononi, G., Sporns, O., & Edelman, G. M. (1994). A measure for brain complexity: Relating functional segregation and integration in the nervous system. Proceedings of the National Academy of Sciences 91(11), 5033–5037.CrossRefGoogle ScholarPubMed
Trübutschek, D., Marti, S., Ojeda, A., King, J.-R., Mi, Y., Tsodyks, M., & Dehaene, S. (2017). A theory of working memory without consciousness or sustained activity. eLife 6, e23871.CrossRefGoogle ScholarPubMed
Verschure, P. F. M. J. (2016). Synthetic consciousness: The distributed adaptive control perspective. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 371(1701), 263–275. https://doi.org/10.1098/rstb.2015.0448Google ScholarPubMed