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.

EEG response of dexmedetomidine during drug induced sleep endoscopy

“…Other commonly used EEG monitoring metrics, such as the patient state index (PSI), have not been well described with dexmedetomidine sedation. Characterizing EEG complexity via nonlinear dynamical changes that occur under anesthesia has been shown to reveal new insights into the activity of the unconscious brain (Natarajan et al, 2004;Stam, 2005;Eagleman et al, 2019). One complexity measure that significantly differs among arousal states is correlation dimension (CD) (Grassberger and Procaccia, 1983), a type of fractal dimension frequently applied to time series data, including EEG.…”