Hostname: page-component-848d4c4894-8bljj Total loading time: 0 Render date: 2024-07-04T12:25:03.709Z Has data issue: false hasContentIssue false
  • English
  • Français

To be or to know? Information in the pristine present

Published online by Cambridge University Press:  23 March 2022

Larissa Albantakis Open the ORCID record for Larissa Albantakis [Opens in a new window]
Larissa Albantakis*
Affiliation:
Department of Psychiatry, Center for Sleep and Consciousness, University of Wisconsin–Madison, Madison, WI53719, USA. albantakis@wisc.eduhttps://centerforsleepandconsciousness.psychiatry.wisc.edu/people/larissa-albantakis/
Get access Rights & Permissions [Opens in a new window]

Abstract

To be true of every experience, the axioms of Integrated information theory (IIT) are necessarily basic properties and should not be “over-psychologized.” Information, for example, merely asserts that experience is specific, not generic. It does not require “access.” The information a system specifies about itself in its current state is revealed by its unfolded cause–effect structure and quantified by its integrated information.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 45 , 2022 , e42
Check for updates
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Albantakis, L. (2018). A tale of Two animats: What does It take to have goals? Springer, pp. 5–15.Google Scholar
Albantakis, L., Hintze, A., Koch, C., Adami, C., & Tononi, G. (2014). Evolution of integrated causal structures in animats exposed to environments of increasing complexity. PLoS Computational Biology 10, e1003966.10.1371/journal.pcbi.1003966CrossRefGoogle ScholarPubMed
Albantakis, L., & Tononi, G. (2019). Causal composition: Structural differences among dynamically equivalent systems. Entropy 21(10), 989.10.3390/e21100989CrossRefGoogle Scholar
Balduzzi, D., & Tononi, G. (2008). Integrated information in discrete dynamical systems: Motivation and theoretical framework. PLoS Computational Biology 4:e1000091.10.1371/journal.pcbi.1000091CrossRefGoogle ScholarPubMed
Barbosa, L. S., Marshall, W., Albantakis, L., & Tononi, G. (2021). Mechanism integrated information. Entropy 23, 362.10.3390/e23030362CrossRefGoogle ScholarPubMed
Haun, A., & Tononi, G. (2019). Why does space feel the way it does? Towards a principled account of spatial experience. Entropy 21, 1160.10.3390/e21121160CrossRefGoogle Scholar
Hoel, E. P., Albantakis, L., Marshall, W., & Tononi, G. (2016). Can the macro beat the micro? Integrated information across spatiotemporal scales. Neurosci Conscious 2016(1), niw012. https://doi.org/10.1093/nc/niw012CrossRefGoogle ScholarPubMed
Marshall, W., Albantakis, L., & Tononi, G. (2018). Black-boxing and cause–effect power. PLoS Computational Biology 14, e1006114.10.1371/journal.pcbi.1006114CrossRefGoogle ScholarPubMed
Marshall, W., Gomez-Ramirez, J., & Tononi, G. (2016). Integrated information and state differentiation. Frontiers in Psychology 7, 926.10.3389/fpsyg.2016.00926CrossRefGoogle ScholarPubMed
Oizumi, M., Albantakis, L., & Tononi, G. (2014). From the phenomenology to the mechanisms of consciousness: Integrated information theory 3.0. PLoS Computational Biology 10, e1003588.10.1371/journal.pcbi.1003588CrossRefGoogle Scholar
Tononi, G. (2008). Consciousness as integrated information: A provisional manifesto. Biological Bulletin 215, 216–242.10.2307/25470707CrossRefGoogle ScholarPubMed
Tononi, G., Boly, M., Gosseries, O., & Laureys, S. (2016a). The neurology of consciousness: An overview. In S. Laureys, O. Gosseries, & G. Tononi (Eds.) The neurology of consciousness: Cognitive neuroscience and neuropathology (2nd Ed.) (pp. 407–461). Elsevier.10.1016/B978-0-12-800948-2.00025-XCrossRefGoogle Scholar
Tononi, G., Boly, M., Massimini, M., & Koch, C. (2016b). Integrated information theory: From consciousness to its physical substrate. Nature Reviews Neuroscience 17, 450–461.10.1038/nrn.2016.44CrossRefGoogle Scholar