Abstract: Improper control of depth of anesthesia is not only detrimental to the rapid and stable recovery of anesthesia, but also affects the postoperative outcome of patients. Therefore, accurate control of anesthesia depth is an urgent clinical and scientific problem in the field of anesthesiology. At present, different algorithm models derived from electroencephalogram (EEG) signals are used to monitor the depth of anesthesia, but they cannot meet the requirements of anesthesiologists to accurately evaluate the depth of anesthesia. In recent years, the research on the mechanism and modulation of anesthesia-related neural network suggests that it has potential value as a method to monitor depth of anesthesia. Anesthesia-related neural networks mainly include sleep-wake circuit, thalamic-cortical circuit and corticocortical network. A thorough understanding of the neural network involved in the loss of consciousness caused by anesthesia will guide the depth of anesthesia monitoring more accurately and provide possibility for improving the quality of clinical anesthesia resuscitation.

Key words: general anesthesia, depth of anesthesia monitoring, neural network, consciousness