Phase-based measures of cross-frequency coupling in brain electrical dynamics under general anesthesia

• Main Authors: Wong, Kin Foon (Contributor), Brown, Emery N. (Contributor), Purdon, Patrick Lee (Contributor), Mukamel, Eran A. (Author), Prerau, Michael J. (Author)
• Other Authors: Harvard University- (Contributor), Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences (Contributor)
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers (IEEE), 2014-05-01T14:43:34Z.
• Subjects: Article
• Online Access: Get fulltext

 The state of general anesthesia (GA) is associated with an increase in spectral power in scalp electroencephalogram (EEG) at frequencies below 40 Hz, including spectral peaks in the slow oscillation (SO, 0.1-1 Hz) and α (8-14 Hz) bands. Because conventional power spectral analyses are insensitive to possible cross-frequency coupling, the relationships among the oscillations at different frequencies remain largely unexplored. Quantifying such coupling is essential for improving clinical monitoring of anesthesia and understanding the neuroscience of this brain state. We tested the usefulness of two measures of cross-frequency coupling: the bispectrum-derived SynchFastSlow, which is sensitive to phase-phase coupling in different frequency bands, and modulogram analysis of coupling between SO phase and α rhythm amplitude. SynchFastSlow, a metric that is used in clinical depth-of-anesthesia monitors, showed a robust correlation with the loss of consciousness at the induction of propofol GA, but this could be largely explained by power spectral changes without considering cross-frequency coupling. Modulogram analysis revealed two distinct modes of cross-frequency coupling under GA. The waking and two distinct states under GA could be discriminated by projecting in a two-dimensional phase space defined by the SynchFastSlow and the preferred SO phase of α activity. Our results show that a stereotyped pattern of phase-amplitude coupling accompanies multiple stages of anesthetic-induced unconsciousness. These findings suggest that modulogram analysis can improve EEG based monitoring of brain state under GA.