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Consciousness-specific dynamic interactions of brain integration and functional diversity

Author

Listed:
  • Andrea I. Luppi

    (University of Cambridge, Addenbrooke’s Hospital
    University of Cambridge, Addenbrooke’s Hospital)

  • Michael M. Craig

    (University of Cambridge, Addenbrooke’s Hospital
    University of Cambridge, Addenbrooke’s Hospital)

  • Ioannis Pappas

    (University of Cambridge, Addenbrooke’s Hospital
    University of Cambridge, Addenbrooke’s Hospital
    210 Barker Hall, University of California – Berkeley)

  • Paola Finoia

    (University of Cambridge, Addenbrooke’s Hospital
    University of Cambridge, Addenbrooke’s Hospital)

  • Guy B. Williams

    (University of Cambridge, Addenbrooke’s Hospital
    University of Cambridge, Cambridge Biomedical Campus (Box 65))

  • Judith Allanson

    (University of Cambridge, Addenbrooke’s Hospital
    Cambridge University Hospitals NHS Foundation, Addenbrooke’s Hospital)

  • John D. Pickard

    (University of Cambridge, Addenbrooke’s Hospital
    University of Cambridge, Addenbrooke’s Hospital
    University of Cambridge, Cambridge Biomedical Campus (Box 65))

  • Adrian M. Owen

    (Western Interdisciplinary Research Building, N6A 5B7 University of Western Ontario)

  • Lorina Naci

    (Lloyd Building, Trinity College Dublin)

  • David K. Menon

    (University of Cambridge, Addenbrooke’s Hospital
    University of Cambridge, Cambridge Biomedical Campus (Box 65))

  • Emmanuel A. Stamatakis

    (University of Cambridge, Addenbrooke’s Hospital
    University of Cambridge, Addenbrooke’s Hospital)

Abstract

Prominent theories of consciousness emphasise different aspects of neurobiology, such as the integration and diversity of information processing within the brain. Here, we combine graph theory and dynamic functional connectivity to compare resting-state functional MRI data from awake volunteers, propofol-anaesthetised volunteers, and patients with disorders of consciousness, in order to identify consciousness-specific patterns of brain function. We demonstrate that cortical networks are especially affected by loss of consciousness during temporal states of high integration, exhibiting reduced functional diversity and compromised informational capacity, whereas thalamo-cortical functional disconnections emerge during states of higher segregation. Spatially, posterior regions of the brain’s default mode network exhibit reductions in both functional diversity and integration with the rest of the brain during unconsciousness. These results show that human consciousness relies on spatio-temporal interactions between brain integration and functional diversity, whose breakdown may represent a generalisable biomarker of loss of consciousness, with potential relevance for clinical practice.

Suggested Citation

  • Andrea I. Luppi & Michael M. Craig & Ioannis Pappas & Paola Finoia & Guy B. Williams & Judith Allanson & John D. Pickard & Adrian M. Owen & Lorina Naci & David K. Menon & Emmanuel A. Stamatakis, 2019. "Consciousness-specific dynamic interactions of brain integration and functional diversity," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-12658-9
    DOI: 10.1038/s41467-019-12658-9
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    Cited by:

    1. Hyunwoo Jang & George A. Mashour & Anthony G. Hudetz & Zirui Huang, 2024. "Measuring the dynamic balance of integration and segregation underlying consciousness, anesthesia, and sleep in humans," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    2. Minji Lee & Leandro R. D. Sanz & Alice Barra & Audrey Wolff & Jaakko O. Nieminen & Melanie Boly & Mario Rosanova & Silvia Casarotto & Olivier Bodart & Jitka Annen & Aurore Thibaut & Rajanikant Panda &, 2022. "Quantifying arousal and awareness in altered states of consciousness using interpretable deep learning," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    3. Andrea I. Luppi & Helena M. Gellersen & Zhen-Qi Liu & Alexander R. D. Peattie & Anne E. Manktelow & Ram Adapa & Adrian M. Owen & Lorina Naci & David K. Menon & Stavros I. Dimitriadis & Emmanuel A. Sta, 2024. "Systematic evaluation of fMRI data-processing pipelines for consistent functional connectomics," Nature Communications, Nature, vol. 15(1), pages 1-24, December.
    4. Ang Li & Haiyang Liu & Xu Lei & Yini He & Qian Wu & Yan Yan & Xin Zhou & Xiaohan Tian & Yingjie Peng & Shangzheng Huang & Kaixin Li & Meng Wang & Yuqing Sun & Hao Yan & Cheng Zhang & Sheng He & Ruquan, 2023. "Hierarchical fluctuation shapes a dynamic flow linked to states of consciousness," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    5. Dian Lyu & Shruti Naik & David K. Menon & Emmanuel A. Stamatakis, 2022. "Intrinsic brain dynamics in the Default Mode Network predict involuntary fluctuations of visual awareness," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    6. Alessandra Griffa & Mathieu Mach & Julien Dedelley & Daniel Gutierrez-Barragan & Alessandro Gozzi & Gilles Allali & Joanes Grandjean & Dimitri Ville & Enrico Amico, 2023. "Evidence for increased parallel information transmission in human brain networks compared to macaques and male mice," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    7. Andrea I. Luppi & Lynn Uhrig & Jordy Tasserie & Camilo M. Signorelli & Emmanuel A. Stamatakis & Alain Destexhe & Bechir Jarraya & Rodrigo Cofre, 2024. "Local orchestration of distributed functional patterns supporting loss and restoration of consciousness in the primate brain," Nature Communications, Nature, vol. 15(1), pages 1-22, December.
    8. Yuqi Liang & Junhao Liang & Chenchen Song & Mianxin Liu & Thomas Knöpfel & Pulin Gong & Changsong Zhou, 2023. "Complexity of cortical wave patterns of the wake mouse cortex," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    9. S. Parker Singleton & Andrea I. Luppi & Robin L. Carhart-Harris & Josephine Cruzat & Leor Roseman & David J. Nutt & Gustavo Deco & Morten L. Kringelbach & Emmanuel A. Stamatakis & Amy Kuceyeski, 2022. "Receptor-informed network control theory links LSD and psilocybin to a flattening of the brain’s control energy landscape," Nature Communications, Nature, vol. 13(1), pages 1-13, December.

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