Functional Importance Backbones of the Brain at Rest, Wakefulness, and Sleep

<b>Background</b>: The brain is never truly at rest. Even in the absence of external tasks, it remains active, continuously organizing itself into large-scale resting-state networks involved in shaping our internal thoughts and experiences. Understanding the networks' structure and dynamics is key to uncovering how the brain functions as a whole. While previous studies have mapped resting-state networks and explored the roles of individual brain regions (network vertices), the relevance of the time-dependent functional interactions (network edges) between them remains largely unexplored. <b>Methods</b>: Here, we assess this relevance by elucidating the time-evolving importance of both brain regions and their interactions, associated with the networks' constituents, using the fundamental concept of centrality. We investigate long-term electrophysiological recordings of brain dynamics from more than 100 participants and reveal new insights into how resting-state networks are organized over longer times. <b>Results</b>: Our findings reveal that the functional architecture of brain networks in a resting state is critically shaped by the dynamic interplay between brain regions. We identified functional importance backbones-core sets of dynamically central vertices and edges-whose configuration varies significantly between subgroups and further varies with different brain states, including wakefulness and sleep. Notably, regions associated with the default mode network exhibited adaptable patterns of centrality, challenging the notion of static network cores. <b>Conclusions</b>: By considering the temporal evolution of both vertices and edges, we provide a more comprehensive understanding of intrinsic brain activity and its functional relevance. This dynamic perspective reveals how the brain's intrinsic activity is coordinated across space and time, highlighting the existence of functional importance backbones that adapt to different brain states.