Brain connectivity changes of propofol-induced altered states of consciousness using High-Density EEG Source Estimation

Through source estimation, high-density electroencephalogram (EEG) signals at scalp level can be converted into signals at cerebral cortex level, which helps to measure cortical activity during anesthesia induced changes in consciousness level to explore the mechanism. In this research, the high-density EEG of propofol-induced consciousness states alterations in 20 healthy adults were converted into cortical signals of 68 regions of interest (ROI), after alpha bandpass filtering, the pairwise orthogonal power envelope connectivity (PEC) was calculated. Then, due to the number of PECs was huge, the least absolute shrinkage and selection operator (LASSO) was used to select as few PECs as possible as the indicators to distinguish baseline (BS) and moderate sedation (MD) states. The results show that most PECs that can be used as indicators are related to ROI related to default mode network (DMN). At the same time, changes of thalamocortical connectivity and frontal-parietal connectivity could be observed, similar to the neuroimaging method of directly measuring cerebral cortical activity. By extracting the PEC as a classifier to classify the BS and MD States, the accuracy could reach more than 70%. Therefore, this method can not only reflect the mechanism of cortical activity alterations induced by anesthetics, but also provide a new idea for monitoring the depth of anesthesia in the future. Clinical Relevance - This shows that the high-density EEG of scalp level can be converted into cortical signals by source estimation, which is similar to the neuroimaging method of directly measuring cortical activity.