Network dynamics scale with levels of awareness
Peter Coppola, Lennart R.b. Spindler, Andrea I. Luppi, Ram Adapa, Lorina Naci, Judith Allanson, Paola Finoia, Guy B. Williams, John D. Pickard, Adrian M. Owen, David K. Menon, Emmanuel A. Stamatakis
bioRxiv Preprint Server April 12, 2021 preprint DOI: 10.1101/2021.04.12.439452 via bioRxiv
Summary
The diversity of brain dynamics within small-world network topology, measured as sample entropy (dSW-E), consistently predicts levels of awareness across sedation and disorders of consciousness, even after accounting for underlying functional connectivity dynamics. Both subcortical and cortical areas show predictive value, but subcortical regions exhibit higher and more robust effect sizes. The dynamic reorganization of the functional information architecture, especially in the subcortex, emerges with awareness and offers explanatory power beyond the complexity of dynamic functional connectivity alone.
Study at a glance
| Characteristics | Observational cohort |
|---|---|
| Population | Humans under sedation and with disorders of consciousness |
| Key finding | The diversity of brain dynamics within small-world topology (dSW-E) consistently predicts levels of awareness, with subcortical areas showing higher and more robust effect sizes than cortical areas. |
Abstract
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 brain dynamics pertaining to small world topology (quantified by sample entropy; dSW-E) 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. 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.