Non-Canonical Microstate Becomes Salient in High Density EEG During Propofol-Induced Altered States of Consciousness

地方政府 脑电图 意识 无意识 异丙酚 神经科学 心理学 物理 意识水平 人工智能 计算机科学 医学 麻醉 精神科 心理治疗师
作者
Wen Shi,Yamin Li,Zhian Liu,Jing Li,Qiang Wang,Xiao‐Hai Yan,Gang Wang
出处
期刊:International Journal of Neural Systems [World Scientific]
卷期号:30 (02): 2050005-2050005 被引量:24
标识
DOI:10.1142/s0129065720500057
摘要

Dynamically assessing the level of consciousness is still challenging during anesthesia. With the help of Electroencephalography (EEG), the human brain electric activity can be noninvasively measured at high temporal resolution. Several typical quasi-stable states are introduced to represent the oscillation of the global scalp electric field. These so-called microstates reflect spatiotemporal dynamics of coherent neural activities and capture the switch of brain states within the millisecond range. In this study, the microstates of high-density EEG were extracted and investigated during propofol-induced transition of consciousness. To analyze microstates on the frequency domain, a novel microstate-wise spectral analysis was proposed by the means of multivariate empirical mode decomposition and Hilbert–Huang transform. During the transition of consciousness, a map with a posterior central maximum denoted as microstate F appeared and became salient. The current results indicated that the coverage, occurrence, and power of microstate F significantly increased in moderate sedation. The results also demonstrated that the transition of brain state from rest to sedation was accompanied by significant increase in mean energy of all frequency bands in microstate F. Combined with studies on the possible cortical sources of microstates, the findings reveal that non-canonical microstate F is highly associated with propofol-induced altered states of consciousness. The results may also support the inference that this distinct topography can be derived from canonical microstate C (anterior-posterior orientation). Finally, this study further develops pertinent methodology and extends possible applications of the EEG microstate during propofol-induced anesthesia.
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