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

机译:全身麻醉下脑电动力学中基于频率的跨频耦合测量

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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.
机译:在低于40 Hz的频率下,全身麻醉(GA)状态与头皮脑电图(EEG)的频谱功率增加相关,包括慢振荡(SO,0.1–1 Hz)和α(8–14 Hz)的频谱峰值)乐队。由于常规功率谱分析对可能的跨频耦合不敏感,因此在不同频率下的振荡之间的关系仍未得到充分探索。量化这种耦合对于改善麻醉的临床监测和了解这种大脑状态的神经科学至关重要。我们测试了交叉频率耦合的两种测量方法的有用性:源自双谱的SynchFastSlow(对不同频带中的相位-相位耦合敏感),以及SO相和α节奏幅度之间的耦合的模块化分析。 SynchFastSlow是一种用于临床麻醉深度监测器的指标,显示出与丙泊酚GA诱导时意识丧失的密切相关,但这可以很大程度上由功率谱的变化来解释,而无需考虑跨频耦合。模图分析揭示了GA下交叉频率耦合的两种不同模式。通过在由SynchFastSlow和α活性的优选SO相定义的二维相空间中进行投影,可以区分GA下的苏醒状态和两个不同状态。我们的研究结果表明,相量耦合的定型模式伴随着麻醉药引起的意识丧失的多个阶段。这些发现表明,模块图分析可以改善基于GA的脑电图对脑状态的监测。

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