Characterization of network switching in disorder of consciousness at multiple time scales.

Recent works have shown that the flexible information processing is closely related to the reconfiguration of human brain networks underlying brain functions. However, the role of network switching for consciousness is poorly explored and whether such transition can indicate the behavioral performance of patients with disorder of consciousness (DOC) remains unknown. Here, we investigate the relationship between the switching of brain networks (states) over time and the consciousness levels.By applying multilayer network methods, we calculated time-resolved functional connectivity from source-level EEG data in different frequency bands. At various time scales, we explored how the human brain change its community structure and traverses across defined network states (integrated and segregated states) in the subjects with different consciousness levels.The network switching in human brain is decreased with increasing time scale opposite to that in random system. Transitions of community assignment (denoted by flexibility) are negatively correlated with the consciousness levels (particularly in alpha band) on short time scales. While on long time scales, an opposite trend is found. Compared to the healthy controls, the patients show a new balance between dynamic segregation and integration, with decreased proportion and mean duration of segregated state (contrary to those of integrated state) at small scales.These findings may contribute to the development of EEG-based network analysis and shed new light on the pathological mechanisms of neurological disorder like DOC.