A Pharmacokinetics-Neural Mass Model (PK-NMM) for the Simulation of EEG Activity during Propofol Anesthesia.

Zhenhu Liang,Cui Su,Xiaoli Li,Xuejing Duan,Logan Voss,Jamie Sleigh,Daniele Marinazzo

doi:10.1371/journal.pone.0145959

Abstract

Modeling the effects of anesthetic drugs on brain activity is very helpful in understanding anesthesia mechanisms. The aim of this study was to set up a combined model to relate actual drug levels to EEG dynamics and behavioral states during propofol-induced anesthesia. We proposed a new combined theoretical model based on a pharmacokinetics (PK) model and a neural mass model (NMM), which we termed PK-NMM—with the aim of simulating electroencephalogram (EEG) activity during propofol-induced general anesthesia. The PK model was used to derive propofol effect-site drug concentrations (C eff) based on the actual drug infusion regimen. The NMM model took C eff as the control parameter to produce simulated EEG-like (sEEG) data. For comparison, we used real prefrontal EEG (rEEG) data of nine volunteers undergoing propofol anesthesia from a previous experiment. To see how well the sEEG could describe the dynamic changes of neural activity during anesthesia, the rEEG data and the sEEG data were compared with respect to: power-frequency plots; nonlinear exponent (permutation entropy (PE)); and bispectral SynchFastSlow (SFS) parameters. We found that the PK-NMM model was able to reproduce anesthesia EEG-like signals based on the estimated drug concentration and patients’ condition. The frequency spectrum indicated that the frequency power peak of the sEEG moved towards the low frequency band as anesthesia deepened. Different anesthetic states could be differentiated by the PE index. The correlation coefficient of PE was 0.80±0.13 (mean±standard deviation) between rEEG and sEEG for all subjects. Additionally, SFS could track the depth of anesthesia and the SFS of rEEG and sEEG were highly correlated with a correlation coefficient of 0.77±0.13. The PK-NMM model could simulate EEG activity and might be a useful tool for understanding the action of propofol on brain activity.

Highlights

Understanding the mechanisms of action of general anesthetics in the central nervous system (CNS) may improve anesthetic drug administration and intra-operative monitoring
The results showed that the PK-neural mass model (NMM) model was able to reproduce EEG-like time series during propofol-induced general anesthesia
The performance of the simulated EEG-like (sEEG) in terms of the frequency spectrum, nonlinear dynamics and high order spectrum showed that sEEG could reflect many of the characteristics of the real EEG signal and reflect the cerebral dynamics during propofol-induced general anesthesia

Summary

Introduction

Understanding the mechanisms of action of general anesthetics in the central nervous system (CNS) may improve anesthetic drug administration and intra-operative monitoring. One is to use clinical or experimental observations to deduce the computation or communication mechanisms within the brain, including the analysis of physiological information obtained from monitor systems (such as the EEG), cerebral blood flow (CBF) and blood oxygenation level dependent (BOLD) signals [1,2,3,4]. During the maintenance period of propofol-induced general anesthesia, the EEG spectrum is still dominated by low frequency activity but at a magnitude somewhat less than during induction. This rise and fall in low frequency power during anesthetic induction is often referred to as the “biphasic effect.”. Burst suppression is thought to occur through the interaction between neuronal dynamics and changes in cerebral metabolic rate of oxygen (CMRO) [25]

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