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A Synergistic Workspace for Human Consciousness Revealed by Integrated Information Decomposition

View ORCID ProfileAndrea I. Luppi, View ORCID ProfilePedro A.M. Mediano, View ORCID ProfileFernando E. Rosas, Judith Allanson, John D. Pickard, View ORCID ProfileRobin L. Carhart-Harris, View ORCID ProfileGuy B. Williams, Michael M Craig, View ORCID ProfilePaola Finoia, View ORCID ProfileAdrian M. Owen, View ORCID ProfileLorina Naci, View ORCID ProfileDavid K. Menon, View ORCID ProfileDaniel Bor, View ORCID ProfileEmmanuel A. Stamatakis
doi: https://doi.org/10.1101/2020.11.25.398081
Andrea I. Luppi
aDivision of Anaesthesia, School of Clinical Medicine, University of Cambridge, United Kingdom
bDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
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  • For correspondence: al857@cam.ac.uk
Pedro A.M. Mediano
cDepartment of Psychology, University of Cambridge, Cambridge, United Kingdom
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  • ORCID record for Pedro A.M. Mediano
Fernando E. Rosas
dCenter for Psychedelic Research, Department of Brain Science, Imperial College London, London, United Kingdom
eData Science Institute, Imperial College London, London, United Kingdom
fCentre for Complexity Science, Imperial College London, London, United Kingdom
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Judith Allanson
bDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
gDepartment of Neurosciences, Cambridge University Hospitals NHS Foundation, Addenbrooke’s Hospital, Cambridge, United Kingdom
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John D. Pickard
bDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
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Robin L. Carhart-Harris
dCenter for Psychedelic Research, Department of Brain Science, Imperial College London, London, United Kingdom
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Guy B. Williams
bDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
hWolfson Brain Imaging Centre, University of Cambridge, Cambridge, United Kingdom
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Michael M Craig
aDivision of Anaesthesia, School of Clinical Medicine, University of Cambridge, United Kingdom
bDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
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Paola Finoia
bDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
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Adrian M. Owen
iDepartment of Psychology and Department of Physiology and Pharmacology, The Brain and Mind Institute, University of Western Ontario, London, Ontario, Canada
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Lorina Naci
jTrinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
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David K. Menon
aDivision of Anaesthesia, School of Clinical Medicine, University of Cambridge, United Kingdom
hWolfson Brain Imaging Centre, University of Cambridge, Cambridge, United Kingdom
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Daniel Bor
cDepartment of Psychology, University of Cambridge, Cambridge, United Kingdom
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Emmanuel A. Stamatakis
aDivision of Anaesthesia, School of Clinical Medicine, University of Cambridge, United Kingdom
bDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
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Abstract

A central goal of neuroscience is to understand how the brain synthesises information from multiple inputs to give rise to a unified conscious experience. This process is widely believed to require integration of information. Here, we combine information theory and network science to address two fundamental questions: how is the human information-processing architecture functionally organised? And how does this organisation support human consciousness? To address these questions, we leverage the mathematical framework of Integrated Information Decomposition to delineate a cognitive architecture wherein specialised modules interact with a “synergistic global workspace,” comprising functionally distinct gateways and broadcasters. Gateway regions gather information from the specialised modules for processing in the synergistic workspace, whose contents are then further integrated to later be made widely available by broadcasters. Through data-driven analysis of resting-state functional MRI, we reveal that gateway regions correspond to the brain’s well-known default mode network, whereas broadcasters of information coincide with the executive control network. Demonstrating that this synergistic workspace supports human consciousness, we further apply Integrated Information Decomposition to BOLD signals to compute integrated information across the brain. By comparing changes due to propofol anaesthesia and severe brain injury, we demonstrate that most changes in integrated information happen within the synergistic workspace. Furthermore, it was found that loss of consciousness corresponds to reduced integrated information between gateway, but not broadcaster, regions of the synergistic workspace. Thus, loss of consciousness may coincide with breakdown of information integration by this synergistic workspace of the human brain. Together, these findings demonstrate that refining our understanding of information-processing in the human brain through Integrated Information Decomposition can provide powerful insights into the human neurocognitive architecture, and its role in supporting consciousness.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted November 26, 2020.
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A Synergistic Workspace for Human Consciousness Revealed by Integrated Information Decomposition
Andrea I. Luppi, Pedro A.M. Mediano, Fernando E. Rosas, Judith Allanson, John D. Pickard, Robin L. Carhart-Harris, Guy B. Williams, Michael M Craig, Paola Finoia, Adrian M. Owen, Lorina Naci, David K. Menon, Daniel Bor, Emmanuel A. Stamatakis
bioRxiv 2020.11.25.398081; doi: https://doi.org/10.1101/2020.11.25.398081
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A Synergistic Workspace for Human Consciousness Revealed by Integrated Information Decomposition
Andrea I. Luppi, Pedro A.M. Mediano, Fernando E. Rosas, Judith Allanson, John D. Pickard, Robin L. Carhart-Harris, Guy B. Williams, Michael M Craig, Paola Finoia, Adrian M. Owen, Lorina Naci, David K. Menon, Daniel Bor, Emmanuel A. Stamatakis
bioRxiv 2020.11.25.398081; doi: https://doi.org/10.1101/2020.11.25.398081

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