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Published on: July 23, 2020
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Cortical complexity and connectivity during isoflurane-induced general anesthesia: a rat study.
Zhijie Wang1,2, Fengrui Zhang3,4, Lupeng Yue3,4
1Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, People's Republic of China.
Journal of Neural Engineering
|April 26, 2022
Summary
Anesthetic-induced loss of consciousness (LOC) reduces brain complexity and information integration. Permutation entropy (PE), permutation Lempel-Ziv complexity (PLZC), and permutation cross mutual information (PCMI) effectively quantify these changes.
Area of Science:
- Neuroscience
- Anesthesiology
- Computational Neuroscience
Background:
- Investigating anesthetic drug-induced loss of consciousness (LOC) mechanisms using entropy, complexity, and information integration theories is a growing research area.
- Systematic research characterizing these neurophysiologic changes at the mesoscopic level remains limited.
Purpose of the Study:
- To systematically analyze electrocorticography (ECoG) data during isoflurane-induced unconsciousness in rats.
- To characterize changes in complexity and connectivity using advanced computational metrics.
- To evaluate the effectiveness of permutation entropy (PE), permutation Lempel-Ziv complexity (PLZC), and permutation cross mutual information (PCMI) in quantifying anesthetic effects.
Main Methods:
- Analysis of ECoG data from nine rats during isoflurane-induced LOC and recovery.
- Calculation of ECoG power spectrum, PE, PLZC, and PCMI across frontal, parietal, and occipital regions.
- Construction and analysis of PCMI-based cortical brain networks, including local and global network parameters.
Main Results:
- LOC was associated with increased ECoG beta power and decreased high gamma power.
- PE and PLZC decreased after LOC and increased upon recovery, particularly in the lower frequency band (0.1-45 Hz).
- PCMI significantly declined in both lower and higher frequency bands, indicating reduced information integration.
- Local network parameters (clustering coefficient, nodal efficiency) decreased in the frontal region; global network parameters showed non-significant changes.
Conclusions:
- Isoflurane-induced LOC is characterized by decreased brain complexity and information integration.
- PE, PLZC, and PCMI are effective quantitative metrics for assessing the neurophysiologic effects of anesthetics.
- These findings provide insights into the mesoscopic mechanisms underlying anesthetic-induced unconsciousness.
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