Abstract
Brains fall asleep through a sequence of stages that can be coarsely defined by specific neural activation patterns in different frequency bands observable, for example, in the Electroencephalogram (EEG). The awake brain usually displays patterns faster, more diverse, and less synchronised across the cortical surface than deeper stages of sleep. Interactions between brain areas are more "complex" in consciously awake states than during relaxed drowsiness or sleep.
The present theme issue addresses the "complexity of sleep" using experimental, theoretical, and modelling approaches. It provides reviews about large-scale functional brain networks during human sleep and theoretical methods to define and measure the complexity of interacting brain networks in strict terms. It proceeds by describing state-of-the-art methods to analyse EEG and brain imaging data, and to predict them using large-scale brain models on computers. It further reports modelling work targeting on the circuits and physiological mechanisms underlying sleep-related neural activity like sleep oscillations or the daily sleep-wake cycle. Finally, it discusses how a better understanding of the sleeping brain and its complex activity on several spatial and temporal scales can open up our minds for what it physiologically means to be awake.