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

Liang Z, Duan X, Su C, Voss L, Sleigh J, Li X - PLoS ONE (2015)

Bottom Line: The PK model was used to derive propofol effect-site drug concentrations (C(eff)) based on the actual drug infusion regimen.The correlation coefficient of PE was 0.80 ± 0.13 (mean ± standard deviation) between rEEG and sEEG for all subjects.The PK-NMM model could simulate EEG activity and might be a useful tool for understanding the action of propofol on brain activity.

View Article: PubMed Central - PubMed

Affiliation: Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China.

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.

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The effect-site concentration of propofol for one subject under four weights.(A) is the Ceff for one single subject under four weights (60, 80, 100, 120kg), (B) is the corresponding rCeff under the four weights.
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pone.0145959.g009: The effect-site concentration of propofol for one subject under four weights.(A) is the Ceff for one single subject under four weights (60, 80, 100, 120kg), (B) is the corresponding rCeff under the four weights.

Mentions: Another important issue that needs to be addressed is the effect of inter-subject variations (weight, age, height etc) on the EEG. Consider weight, four weights (60, 80, 100, 120 kg) were selected for each subject. The Ceff figures, just as for Fig 4(B), but now under the four weights for one single subject were shown in Fig 9(A). It can be seen from Fig 9(A), the Ceff showed differences under the four weights. As described earlier, to make the values of Ceff correspond with the input range of the NMM model, we made a transformation (eq 4) to give the rCeff, which was the real input of the NMM model. The rCeff figures under the four weights for the same subject were shown in Fig 9(B). It is observed that the figures in (A) now collapse basically on one "normalized" figure (B). So the simulated EEG under the four weights would not show much difference, which meant that this procedure removed the EEG dependence on the weight.


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

Liang Z, Duan X, Su C, Voss L, Sleigh J, Li X - PLoS ONE (2015)

The effect-site concentration of propofol for one subject under four weights.(A) is the Ceff for one single subject under four weights (60, 80, 100, 120kg), (B) is the corresponding rCeff under the four weights.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4697853&req=5

pone.0145959.g009: The effect-site concentration of propofol for one subject under four weights.(A) is the Ceff for one single subject under four weights (60, 80, 100, 120kg), (B) is the corresponding rCeff under the four weights.
Mentions: Another important issue that needs to be addressed is the effect of inter-subject variations (weight, age, height etc) on the EEG. Consider weight, four weights (60, 80, 100, 120 kg) were selected for each subject. The Ceff figures, just as for Fig 4(B), but now under the four weights for one single subject were shown in Fig 9(A). It can be seen from Fig 9(A), the Ceff showed differences under the four weights. As described earlier, to make the values of Ceff correspond with the input range of the NMM model, we made a transformation (eq 4) to give the rCeff, which was the real input of the NMM model. The rCeff figures under the four weights for the same subject were shown in Fig 9(B). It is observed that the figures in (A) now collapse basically on one "normalized" figure (B). So the simulated EEG under the four weights would not show much difference, which meant that this procedure removed the EEG dependence on the weight.

Bottom Line: The PK model was used to derive propofol effect-site drug concentrations (C(eff)) based on the actual drug infusion regimen.The correlation coefficient of PE was 0.80 ± 0.13 (mean ± standard deviation) between rEEG and sEEG for all subjects.The PK-NMM model could simulate EEG activity and might be a useful tool for understanding the action of propofol on brain activity.

View Article: PubMed Central - PubMed

Affiliation: Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China.

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.

Show MeSH
Related in: MedlinePlus