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The dynamical mechanism underlying the processes of anesthesia-induced lossof consciousness and recovery is key to gaining insights into the working ofthe nervous system. Previous experiments revealed an asymmetry between neuralsignals during the anesthesia and recovery processes. Here we obtainexperimental evidence for the hysteresis loop and articulate the dynamicalmechanism based on percolation on multilayer complex networks withself-similarity. Model analysis reveals that, during anesthesia, the network isable to maintain its neural pathways despite the loss of a substantial fractionof the edges. A predictive and potentially testable result is that, in theforward process of anesthesia, the average shortest path and the clusteringcoefficient of the neural network are markedly smaller than those associatedwith the recovery process. This suggests that the network strives to maintaincertain neurological functions by adapting to a relatively more compactstructure in response to anesthesia.

Hysteresis in anesthesia and recovery: Experimental observation and dynamical mechanism