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Sleep is a complex physiological process, linked with the function of every bodily organ, and its dysregulation has negative impacts for well-being and health. Despite its importance, after decades of research, much uncertainty remains with respect to brain functional changes occurring when we fall asleep. The known point is that there are remarkable changes between full awake and sleep conditions and that the variety of human states of consciousness and the wakefulness–sleep (W–S) transition are based on the dynamic connectivity of brain regions that continuously interact through complex neural networks with time- and task-varying architecture.
Sleep onset is characterized by a specific and orchestrated pattern of frequency and topographical EEG changes. Conventional power analyses of electroencephalographic (EEG) and computational assessments of network dynamics have described an earlier synchronization of the centrofrontal areas rhythms and a spread of synchronizing signals from associative prefrontal to posterior areas. Here, we assess how “small world” characteristics of the brain networks, as reflected in the EEG rhythms, are modified in the wakefulness-sleep transition comparing the pre- and post-sleep onset epochs.
The results show that sleep onset is characterized by a less ordered brain network (as reflected by the higher value of small world) in the sigma band for the frontal lobes indicating stronger connectivity, and a more ordered brain network in the low frequency delta and theta bands indicating disconnection on the remaining brain areas. Our results depict the timing and topography of the specific mechanisms for the maintenance of functional connectivity of frontal brain regions at the sleep onset, also providing a possible explanation for the prevalence of the frontal-to-posterior information flow directionality previously observed after sleep onset.
This study opens interesting avenues for future researches investigating eventual modifications of brain connectivity and network organization in the evolution of sleep stages.