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Sedation induces changes in electroencephalography (EEG) dynamics. However, the distinct EEG dynamic characteristics at comparable sedation levels have not been well studied, resulting in potential interpretation errors in EEG monitoring during sedation. We aimed to analyze the EEG dynamics of dexmedetomidine and propofol at comparable sedation levels and to explore EEG changes with increased sedation levels for each agent. We measured the Bispectral Index (BIS) and 20-channel EEG under dexmedetomidine and propofol sedation from wakefulness, moderate sedation, and deep sedation to recovery in healthy volunteers (n = 10) in a randomized, 2-day, crossover study. Observer's Assessment of Alertness and Sedation (OAA/S) score was used to assess sedation levels. Despite similar changes in increased delta oscillations, multiple differences in the EEG spatiotemporal dynamics were observed between these two agents. During moderate sedation, both dexmedetomidine and propofol induced increased spindle power; however, dexmedetomidine decreased the global alpha/beta/gamma power, whereas propofol decreased the alpha power in the occipital area and increased the global spindle/beta/gamma power. During deep sedation, dexmedetomidine was associated with increased fronto-central spindle power and decreased global alpha/beta/gamma power, but propofol was associated with increased theta/alpha/spindle/beta power, which was maximized in the frontal area. The transition of topographic alpha/spindle/beta power distribution from moderate sedation to deep sedation completely differed between these two agents. Our study demonstrated that there was a distinct hierarchy of EEG changes with increased sedation depths by propofol and dexmedetomidine. Differences in EEG dynamics at the same sedation level might account for differences in the BIS value and reflect the different sedation mechanisms. EEG-based clinical sedation monitoring should consider the effect of drug types on EEG dynamics.
Pubmed ID: 29920532
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Interactive Matlab toolbox for processing continuous and event-related EEG, MEG and other electrophysiological data incorporating independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data. First developed on Matlab 5.3 under Linux, EEGLAB runs on Matlab v5 and higher under Linux, Unix, Windows, and Mac OS X (Matlab 7+ recommended). EEGLAB provides an interactive graphic user interface (GUI) allowing users to flexibly and interactively process their high-density EEG and other dynamic brain data using independent component analysis (ICA) and/or time/frequency analysis (TFA), as well as standard averaging methods. EEGLAB also incorporates extensive tutorial and help windows, plus a command history function that eases users'' transition from GUI-based data exploration to building and running batch or custom data analysis scripts. EEGLAB offers a wealth of methods for visualizing and modeling event-related brain dynamics, both at the level of individual EEGLAB ''datasets'' and/or across a collection of datasets brought together in an EEGLAB ''studyset.'' For experienced Matlab users, EEGLAB offers a structured programming environment for storing, accessing, measuring, manipulating and visualizing event-related EEG data. For creative research programmers and methods developers, EEGLAB offers an extensible, open-source platform through which they can share new methods with the world research community by publishing EEGLAB ''plug-in'' functions that appear automatically in the EEGLAB menu of users who download them. For example, novel EEGLAB plug-ins might be built and released to ''pick peaks'' in ERP or time/frequency results, or to perform specialized import/export, data visualization, or inverse source modeling of EEG, MEG, and/or ECOG data. EEGLAB Features * Graphic user interface * Multiformat data importing * High-density data scrolling * Defined EEG data structure * Open source plug-in facility * Interactive plotting functions * Semi-automated artifact removal * ICA & time/frequency transforms * Many advanced plug-in toolboxes * Event & channel location handling * Forward/inverse head/source modeling
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