Characterization of Spatial Temporal Dynamic of Brain Network in Disorder of Consciousness via Community Analysis

A critical question in network neuroscience lies in how neural units cluster into densely interconnected groups that can provide the coordinated activity characterized by perception, action, and adaptive behavior. The topology of network in modularity problem has been widely studied and can reflect many features of human brain. However, there are few researches on spatial structure and dynamic structure. In our research, we collect resting-state electroencephalogram (EEG) from 24 healthy controls, 45 patients with unresponsive wakefulness syndrome (UWS) and 25 patients with minimally conscious state (MCS). After dividing the EEG signal analysis into five bands, function network is constructed based on phase synchronization of the network. Then, we perform statistical analysis between groups of different frequency bands. The results show that there are statistically significant differences in the within-and between –module connectivity, community average spatial distance, community spatial diameter and network flexibility. In addition, most of the parameters are positively correlated with the consciousness level of the subjects. Our results suggest that the analysis of the modularized structure of complex networks including topology structure, spatial structure and dynamic structure may help to clarify the process of consciousness recovery and its pathophysiology in patients with disorder of consciousness (DOC), and may contribute to the clinical treatment and evaluation of patients with DOC.