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Biophysical Model: A Promising Method in the Study of the Mechanism of Propofol: A Narrative Review

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Specialty Biology
Date 2022 May 27
PMID 35619772
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Abstract

The physiological and neuroregulatory mechanism of propofol is largely based on very limited knowledge. It is one of the important puzzling issues in anesthesiology and is of great value in both scientific and clinical fields. It is acknowledged that neural networks which are comprised of a number of neural circuits might be involved in the anesthetic mechanism. However, the mechanism of this hypothesis needs to be further elucidated. With the progress of artificial intelligence, it is more likely to solve this problem through using artificial neural networks to perform temporal waveform data analysis and to construct biophysical computational models. This review focuses on current knowledge regarding the anesthetic mechanism of propofol, an intravenous general anesthetic, by constructing biophysical computational models.

References
1.
Ertugrul O . A novel type of activation function in artificial neural networks: Trained activation function. Neural Netw. 2018; 99:148-157. DOI: 10.1016/j.neunet.2018.01.007. View

2.
Srinivasan R, Thorpe S, Nunez P . Top-down influences on local networks: basic theory with experimental implications. Front Comput Neurosci. 2013; 7:29. PMC: 3629312. DOI: 10.3389/fncom.2013.00029. View

3.
Franks N . Molecular targets underlying general anaesthesia. Br J Pharmacol. 2006; 147 Suppl 1:S72-81. PMC: 1760740. DOI: 10.1038/sj.bjp.0706441. View

4.
Lee J, Whittington M, Kopell N . Potential Mechanisms Underlying Intercortical Signal Regulation via Cholinergic Neuromodulators. J Neurosci. 2015; 35(45):15000-14. PMC: 4642235. DOI: 10.1523/JNEUROSCI.0629-15.2015. View

5.
Walsh E, Lee J, Terzakis K, Zhou D, Burns S, Buie T . Age-Dependent Changes in the Propofol-Induced Electroencephalogram in Children With Autism Spectrum Disorder. Front Syst Neurosci. 2018; 12:23. PMC: 6024139. DOI: 10.3389/fnsys.2018.00023. View