TY - JOUR
T1 - Dynamics of sleep
T2 - Exploring critical transitions and early warning signals
AU - de Mooij, Susanne M M
AU - Blanken, Tessa F
AU - Grasman, Raoul P P P
AU - Ramautar, Jennifer R
AU - Van Someren, Eus J W
AU - van der Maas, Han L J
N1 - Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.
PY - 2020
Y1 - 2020
N2 - BACKGROUND AND OBJECTIVES: In standard practice, sleep is classified into distinct stages by human observers according to specific rules as for instance specified in the AASM manual. We here show proof of principle for a conceptualization of sleep stages as attractor states in a nonlinear dynamical system in order to develop new empirical criteria for sleep stages.METHODS: EEG (single channel) of two healthy sleeping participants was used to demonstrate this conceptualization. Firstly, distinct EEG epochs were selected, both detected by a MLR classifier and through manual scoring. Secondly, change point analysis was used to identify abrupt changes in the EEG signal. Thirdly, these detected change points were evaluated on whether they were preceded by early warning signals.RESULTS: Multiple change points were identified in the EEG signal, mostly in interplay with N2. The dynamics before these changes revealed, for a part of the change points, indicators of generic early warning signals, characteristic of complex systems (e.g., ecosystems, climate, epileptic seizures, global finance systems).CONCLUSIONS: The sketched new framework for studying critical transitions in sleep EEG might benefit the understanding of individual and pathological differences in the dynamics of sleep stage transitions. Formalising sleep as a nonlinear dynamical system can be useful for definitions of sleep quality, i.e. stability and accessibility of an equilibrium state, and disrupted sleep, i.e. constant shifting between instable sleep states.
AB - BACKGROUND AND OBJECTIVES: In standard practice, sleep is classified into distinct stages by human observers according to specific rules as for instance specified in the AASM manual. We here show proof of principle for a conceptualization of sleep stages as attractor states in a nonlinear dynamical system in order to develop new empirical criteria for sleep stages.METHODS: EEG (single channel) of two healthy sleeping participants was used to demonstrate this conceptualization. Firstly, distinct EEG epochs were selected, both detected by a MLR classifier and through manual scoring. Secondly, change point analysis was used to identify abrupt changes in the EEG signal. Thirdly, these detected change points were evaluated on whether they were preceded by early warning signals.RESULTS: Multiple change points were identified in the EEG signal, mostly in interplay with N2. The dynamics before these changes revealed, for a part of the change points, indicators of generic early warning signals, characteristic of complex systems (e.g., ecosystems, climate, epileptic seizures, global finance systems).CONCLUSIONS: The sketched new framework for studying critical transitions in sleep EEG might benefit the understanding of individual and pathological differences in the dynamics of sleep stage transitions. Formalising sleep as a nonlinear dynamical system can be useful for definitions of sleep quality, i.e. stability and accessibility of an equilibrium state, and disrupted sleep, i.e. constant shifting between instable sleep states.
U2 - 10.1016/j.cmpb.2020.105448
DO - 10.1016/j.cmpb.2020.105448
M3 - Article
C2 - 32304989
SN - 0169-2607
VL - 193
SP - 105448
JO - Computer methods and programs in biomedicine
JF - Computer methods and programs in biomedicine
ER -