Network dynamics scale with levels of awareness.
Spindler, Lennart RB
Luppi, Andrea I
Williams, Guy B
Pickard, John D
Owen, Adrian M
Menon, David K
Stamatakis, Emmanuel A
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Coppola, P., Spindler, L. R., Luppi, A. I., Adapa, R., Naci, L., Allanson, J., Finoia, P., et al. (2022). Network dynamics scale with levels of awareness.. Neuroimage, (119128), 119128-119128. https://doi.org/10.1016/j.neuroimage.2022.119128
Small world topologies are thought to provide a valuable insight into human brain organisation and consciousness. However, functional magnetic resonance imaging studies in consciousness have not yielded consistent results. Given the importance of dynamics for both consciousness and cognition, here we investigate how the diversity of small world dynamics (quantified by sample entropy; dSW-E1) scales with decreasing levels of awareness (i.e., sedation and disorders of consciousness). Paying particular attention to result reproducibility, we show that dSW-E is a consistent predictor of levels of awareness even when controlling for the underlying functional connectivity dynamics. We find that dSW-E of subcortical, and cortical areas are predictive, with the former showing higher and more robust effect sizes across analyses. We find that the network dynamics of intermodular communication in the cerebellum also have unique predictive power for levels of awareness. Consequently, we propose that the dynamic reorganisation of the functional information architecture, in particular of the subcortex, is a characteristic that emerges with awareness and has explanatory power beyond that of the complexity of dynamic functional connectivity.
This work was supported by grants from the Wellcome Trust Clinical Research Training Fellowship [to RA] (grant number: 083660/Z/07/Z); the UK Medical Research Council (U.1055.01.002.00001.01) [to AMO and JDP]; The James S. McDonnell Foundation [to AMO and JDP]; The Canada Excellence Research Chairs program (215063) [to AMO]; The Canadian Institute for Advanced Research (CIFAR) [to AMO, DKM and EAS]; The National Institute for Health Research (NIHR, UK), Cambridge Biomedical Research Centre and NIHR Senior Investigator Awards [to JDP and DKM]; The British Oxygen Professorship of the Royal College of Anaesthetists [to DKM]; The Evelyn Trust, Cambridge and the East of England Collaboration for Leadership in Applied Health Research and Care fellowship [to JA]; The L’Oreal-Unesco for Women in Science Excellence Research Fellowship [to LN]; The Stephen Erskine Fellowship, Queens’ College, University of Cambridge [to EAS]; the Gates Cambridge Trust [to AIL] and the Cambridge Trust [to PC and LRBS]. The research was also supported by the NIHR Brain Injury Healthcare Technology Co-operative based at Cambridge University Hospitals NHS Foundation Trust and University of Cambridge. Computing infrastructure at the Wolfson Brain Imaging Centre (WBIC-HPHI) was funded by the MRC research infrastructure award (MR/M009041/1).
Wellcome Trust (083660/Z/07/Z)
Medical Research Council (MR/M009041/1)
External DOI: https://doi.org/10.1016/j.neuroimage.2022.119128
This record's URL: https://www.repository.cam.ac.uk/handle/1810/335451
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Licence URL: https://creativecommons.org/licenses/by-nc-nd/4.0/