Recovery of Brain Network Integration and Segregation During the Loss and Recovery of Consciousness Induced by Sevoflurane

Abstract

Anesthetic-induced loss of consciousness (LOC) has been studied using functional connectivity (FC) and functional network analysis (FNA), manifested as fragmentation of the whole-brain functional network. However, how the fragmented brain networks reversibly recover during the recovery of consciousness (ROC) remains vague. This study aims to investigate the changes in brain network structure during ROC, to better understand the network fragmentation during anesthesia, thus providing insights into consciousness monitoring. We analyzed EEG data recorded from 15 individuals anesthetized by sevoflurane. By investigating the properties of functional networks generated using different brain atlases and performing community detection for functional networks, we explored the changes in brain network structure to understand how fragmented brain networks recover during the ROC. We observed an overall larger FC magnitude during LOC than in the conscious state. The ROC was accompanied by the increasing binary network efficiency, decreasing FC magnitude, and decreasing community similarity with the functional atlas. Furthermore, we observed a negative correlation between modularity and community number (p <0.001 and BF 10 >4000, linear regression test), in which modularity increased and community number decreased during ROC. Our results show that a larger FC magnitude reveals excessive synchronization of neuronal activities during LOC. The increasing binary network efficiency, decreasing community number, and decreasing community similarity indicate the recovery of functional network integration. The increas-Manuscript

Multidimensional assessment of heartbeat‐evoked responses in disorders of consciousness

“…We also found that HER complexity was marginally higher in conscious participants, which has not been previously reported but is consistent with studies reporting higher complexity in EEG measures in the presence of consciousness (Abásolo et al, 2015; Andrillon et al, 2016; Casali et al, 2013). While the HER segregation–integration ratio has not been evaluated before, previous evidence suggests that excessive coordination in the brain is associated with reduced segregation in altered states of consciousness (Dong et al, 2022). Finally, the HER specificity index helps to confirm whether the measurement corresponds to actual neural activity, addressing a common concern in studies of HERs (Park & Blanke, 2019).…”

The EEG complexity, information integration and brain network changes in minimally conscious state patients during general anesthesia

“…In normal individuals, the breakdown of brain networks during GA is consistently associated with increased path length, increased levels of modularity, and reduced small-world properties at the global level of sensor space and source space [50,62,63]. However, patients with MCS exhibited distinct alterations in global brain network parameters during anesthesia compared to those observed in normal individuals.…”

“…Next, we constructed a reference head model using the OpenMEEG boundary element method. Finally, we utilized the Beamformer algorithm to compute the cortical distributed current density values [50]. Recent study has demonstrated the feasibility of using the Beamformer algorithm to estimate EEG sources in low-density EEG [51].…”