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      Frontal–temporal functional connectivity of EEG signal by standardized permutation mutual information during anesthesia

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          Abstract

          Quantifying brain dynamics during anesthesia is an important challenge for understanding the neurophysiological mechanisms of anesthetic drug effect. Several single channel Electroencephalogram (EEG) indices have been proposed for monitoring anesthetic drug effect. The most commonly used single channel commercial index is the Bispectral index (BIS). However, this monitor has shown some drawbacks. In this study, a nonlinear functional connectivity measure named Standardized Permutation Mutual Information (SPMI) is proposed to describe communication between two-channel EEG signals at frontal and temporal brain regions during a controlled propofol-induced anesthesia and recovery design from eight subjects. The SPMI index has higher correlation with estimated propofol effect-site concentration and has better ability to distinguish three anesthetic states of patient than the other functional connectivity indexes (cross-correlation, coherence, phase analysis) and also the BIS index. Moreover, the SPMI index has a faster reaction to the effect of drug concentration, less variability at the consciousness state and better robustness to noise than BIS.

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          Author and article information

          Contributors
          fahimeh.afshani@gmail.com
          00989122163201 , shalbaf@sbmu.ac.ir
          shalbaf@iricss.org
          Jamie.Sleigh@waikatodhb.health.nz
          Journal
          Cogn Neurodyn
          Cogn Neurodyn
          Cognitive Neurodynamics
          Springer Netherlands (Dordrecht )
          1871-4080
          1871-4099
          22 August 2019
          December 2019
          : 13
          : 6
          : 531-540
          Affiliations
          [1 ] GRID grid.411463.5, ISNI 0000 0001 0706 2472, Department of Biomedical Engineering, Electronic Branch, , Islamic Azad University, ; Tehran, Iran
          [2 ] GRID grid.411600.2, Department of Biomedical Engineering and Medical Physics, School of Medicine, , Shahid Beheshti University of Medical Sciences, ; Tehran, Iran
          [3 ] GRID grid.482821.5, ISNI 0000 0004 0382 4515, Institute for Cognitive Science Studies, ; Tehran, Iran
          [4 ] GRID grid.413952.8, ISNI 0000 0004 0408 3667, Department of Anesthesia, , Waikato Hospital, ; Hamilton, New Zealand
          Article
          PMC6825117 PMC6825117 6825117 9553
          10.1007/s11571-019-09553-w
          6825117
          31741690
          03c845ba-2cd6-4f1a-b707-129ac26d0207
          © Springer Nature B.V. 2019
          History
          : 4 January 2019
          : 28 July 2019
          : 16 August 2019
          Categories
          Research Article
          Custom metadata
          © Springer Nature B.V. 2019

          Bispectral index,Mutual information,Depth of anesthesia,Electroencephalogram

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