Anesthesiology
May 1, 2024
Zhenhu Liang, Bo Tang, Yu Chang et al.
13 citations
Two new measures of EEG microstate complexity—type I, quantifying randomness, and type II, quantifying fluctuation complexity—track anesthetic-induced unconsciousness independently of the drug used (propofol or esketamine). In 20 patients, type I complexity increased from wakefulness to unconsciousness and decreased upon recovery, while type II complexity showed the opposite pattern. Both measures changed significantly under both anesthetics, suggesting they reflect the state of consciousness rather than the specific drug. These complexity measures may serve as state-related neural correlates of consciousness during general anesthesia.
British journal of anaesthesia
March 1, 2024
Zhenhu Liang, Yu Chang, Xiaoge Liu et al.
10 citations
Information integration and brain network measures derived from EEG can distinguish conscious from unconscious states induced by three different anaesthetics. In 72 participants given propofol, dexmedetomidine, or ketamine until they lost responsiveness, permutation cross mutual information (PCMI) within frontal, parietal, and occipital regions decreased during unresponsiveness—for example, frontal within-area PCMI fell from 0.54 to 0.46. Alpha-band PCMI in the frontal region and gamma-band PCMI in posterior areas also dropped. Network analyses showed reduced clustering coefficients and nodal efficiency in frontal, parietal, and occipital areas, while normalized path length increased in delta, theta, and gamma bands, indicating impaired global integration. The three drugs produced similar changes, suggesting a common EEG signature of anaesthesia-induced unconsciousness.
NeuroImage
July 18, 2025
Xin Wen, Yu Chang, Sijie Li et al.
1 citation
A new measure called Φcopula, which uses a Gaussian copula approach to estimate integrated information, outperforms common estimators by maintaining the lowest bias and mean squared error even in non-Gaussian high-dimensional systems. Applied to electroencephalographic data across awake, propofol-induced unresponsive, and NREM sleep states, alpha-band Φcopula significantly decreased during both anesthesia and sleep. Φcopula-based classifiers distinguished arousal states more accurately than functional connectivity and network efficiency measures. The dorsal attention network and default mode network contributed most to Φcopula, with the cingulate and posterior cortices showing the greatest contributions. The posterior cortex, especially the posterior cingulate cortex, appears critical for arousal-related information integration and consciousness.
Frontiers in neuroscience
January 1, 2025
Fa Lu, Lunxu Li, Juan Wang et al.
Global signal regression (GSR), a common preprocessing step in fMRI analysis, affects brain activity patterns differently depending on the anesthetic agent used. Using fMRI data from patients under general anesthesia, the work shows that GSR alters specific network connections under propofol but broadly reduces connectivity differences under sevoflurane. Network topology analyses reveal that GSR minimally affects propofol-induced changes in graph theoretical measures but significantly diminishes sevoflurane-related network alterations. These findings indicate that GSR's impact on functional brain organization is anesthetic-specific, with sevoflurane-induced changes being particularly sensitive to global signal removal. The results suggest that GSR should be applied cautiously when comparing different anesthetic agents.