Complexity measures of the electroencephalograph capture loss and recovery of consciousness in patients anesthetized with propofol

Abstract

Propofol is one of the most widely used anesthetics for routine surgical anesthesia. Propofol administration alone produces EEG spectral characteristics similar to most hypnotics; however, inter-individual variation can make spectral measures inconsistent. Complexity measures of EEG signals could offer universal measures to better capture anesthetic depth as brain activity exhibits nonlinear behavior at several scales. We tested the potential of nonlinear dynamics analyses to identify loss and recovery of consciousness at clinically relevant timepoints. Patients undergoing propofol general anesthesia for various surgical procedures were identified as having changes in states of consciousness by the loss and recovery of response to verbal stimuli after induction and upon cessation of anesthesia, respectively. Nonlinear dynamics analyses showed more significant differences between consciousness states than most spectral measures. Thus, complexity measures could provide a means for reliably capturing depth of consciousness based on subtle EEG changes at the beginning and end of anesthesia administration.