4.7 Article

NREM sleep stages specifically alter dynamical integration of large-scale brain networks

Journal

ISCIENCE
Volume 24, Issue 1, Pages -

Publisher

CELL PRESS
DOI: 10.1016/j.isci.2020.101923

Keywords

-

Funding

  1. Swiss National Science Foundation [205321-163376, 320030-159862, 320030-135653]
  2. National Institute for the Humanities and Social Sciences (NIHSS) [SDS14/1117]
  3. German Academic Exchange Service (DAAD) [91570813]
  4. National Research Foundation of South Africa (NRF) [83341]
  5. Harry Oppenheimer Memorial Trust, South Africa [OMT 20027]
  6. National Center of Competence in Research (NCCR) Affective Sciences - Swiss National Science Foundation [51NF40-104897]
  7. Mercier Foundation

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The study found that as sleep depth increases, the dynamic properties of functional brain networks change, with network activity predominating in NREM stage 2 and sharply decreasing in NREM stage 3. As sleep depth increases, functional connectivity and mutual dependencies between networks progressively break down.
Functional dissociations in the brain observed during non-rapid eye movement (NREM) sleep have been associated with reduced information integration and impaired consciousness that accompany increasing sleep depth. Here, we explored the dynamical properties of large-scale functional brain networks derived from transient brain activity using functional magnetic resonance imaging. Spatial brain maps generally display significant modifications in terms of their tendency to occur across wakefulness and NREM sleep. Unexpectedly, almost all networks predominated in activity during NREM stage 2 before an abrupt loss of activity is observed in NREM stage 3. Yet, functional connectivity and mutual dependencies between these networks progressively broke down with increasing sleep depth. Thus, the efficiency of information transfer during NREM stage 2 is low despite the high attempt to communicate. Critically, our approach provides relevant data for evaluating functional brain network integrity and our findings robustly support a significant advance in our neural models of human sleep and consciousness.

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