Network Efficiency and Posterior Alpha Patterns Are Markers of Recovery from General Anesthesia: A High-Density Electroencephalography Study in Healthy Volunteers

Abstract

Recent studies have investigated local oscillations, long-range connectivity, and global network patterns to identify neural changes associated with anesthetic-induced unconsciousness. These studies typically employ anesthetic protocols that either just cross the threshold of unconsciousness, or induce deep unconsciousness for a brief period of time—neither of which models general anesthesia for major surgery. To study neural patterns of unconsciousness and recovery in a clinically-relevant context, we used a realistic anesthetic regimen to induce and maintain unconsciousness in eight healthy participants for 3 h. High-density electroencephalogram (EEG) was acquired throughout and for another 3 h after emergence. Seven epochs of 5-min eyes-closed resting states were extracted from the data at baseline as well as 30, 60, 90, 120, 150, and 180-min post-emergence. Additionally, 5-min epochs were extracted during induction, unconsciousness, and immediately prior to recovery of consciousness, for a total of 10 analysis epochs. The EEG data in each epoch were analyzed using source-localized spectral analysis, phase-lag index, and graph theoretical techniques. Posterior alpha power was significantly depressed during unconsciousness, and gradually approached baseline levels over the 3 h recovery period. Phase-lag index did not distinguish between states of consciousness or stages of recovery. Network efficiency was significantly depressed and network clustering coefficient was significantly increased during unconsciousness; these graph theoretical measures returned to baseline during the 3 h recovery period. Posterior alpha power may be a potential biomarker for normal recovery of functional brain networks after general anesthesia.

Brain network motifs are markers of loss and recovery of consciousness

“…Graph theoretical analysis revealed inconsistent changes of the global network across states of consciousness based on measures of clustering coefficient, binary small-worldness and modularity, and no changes in the global efficiency of the network between conscious and unconscious epochs. While the increased clustering coefficients and modularity we observed for unconscious brain networks are similar to previous findings [12,27], these characteristics were not consistently increased across the entire period of unconsciousness. Indeed, both clustering coefficients and modularity were not statistically different between baseline and unconsciousness.…”

“…Both electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) studies have shown that propofol-, sevoflurane-, and ketamine-induced unconsciousness induce a functional disconnection of anterior and posterior regions of the cortex [3][4][5][6][7][8], while propofol and sevoflurane also induce an anteriorization of alpha power from the occipital to the frontal cortex [9][10][11]. Graph theoretical analysis has demonstrated that global and topographic properties of brain networks are altered during anesthetic-induced unconsciousness [12][13][14][15][16]. While these advances have led to a clearer understanding of how anesthetic-induced unconsciousness creates inhospitable conditions for information processing and transfer [17], these measures describe whole-brain network processes rather than region-specific changes in brain functioning.…”

“…Nine healthy subjects underwent a 3-hour anesthetic protocol while 128-channel electroencephalography (EEG) was recorded. In the alpha (8)(9)(10)(11)(12)(13) band, five-minute epochs of EEG were extracted for: baseline; induction; unconsciousness; 30-, 10-and 5-minutes pre-recovery of consciousness; 30-and 180-minutes post-recovery of consciousness. We constructed a functional brain network using both the weighted and the directed phase lag index, on which we calculated graph theoretical network properties, and the frequency and topography of 3-node motifs.…”

Electroencephalogram Similarity Analysis Using Temporal and Spectral Dynamics Analysis for Propofol and Desflurane Induced Unconsciousness

“…Our observations only focus on the regular surgery anesthetic level variability of patients' EEG in clinical settings. This naturally poses a doubt about the more detailed information with the time resolved spectral fluctuations [26,38]. Therefore, data specifications might need to be set precisely according to future study requirements, such as agent concentration level, anesthetic depth, aging effect, etc.…”

“…Furthermore, multichannel analysis becomes popular more recently [26,37,38], which would enable spatial and source analysis of EEG features. For example, propofol was found with the anteriorization of alpha power [38,39]. It should be further studied in prospective high-density EEG investigations, such as connectivity and brain network study.…”