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Increased glymphatic influx is correlated with high EEG delta power and low heart rate in mice under anesthesia.

ABSTRACT: The glymphatic system is responsible for brain-wide delivery of nutrients and clearance of waste via influx of cerebrospinal fluid (CSF) alongside perivascular spaces and through the brain. Glymphatic system activity increases during sleep or ketamine/xylazine (K/X) anesthesia, yet the mechanism(s) facilitating CSF influx are poorly understood. Here, we correlated influx of a CSF tracer into the brain with electroencephalogram (EEG) power, heart rate, blood pressure, and respiratory rate in wild-type mice under six different anesthesia regimens. We found that glymphatic CSF tracer influx was highest under K/X followed by isoflurane (ISO) supplemented with dexmedetomidine and pentobarbital. Mice anesthetized with α-chloralose, Avertin, or ISO exhibited low CSF tracer influx. This is the first study to show that glymphatic influx correlates positively with cortical delta power in EEG recordings and negatively with beta power and heart rate.

SUBMITTER: Hablitz LM

PROVIDER: S-EPMC6392807 | biostudies-other | 2019 Feb

REPOSITORIES: biostudies-other

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Increased glymphatic influx is correlated with high EEG delta power and low heart rate in mice under anesthesia.

Hablitz Lauren M LM Vinitsky Hanna S HS Sun Qian Q Stæger Frederik Filip FF Sigurdsson Björn B Mortensen Kristian N KN Lilius Tuomas O TO Nedergaard Maiken M

Science advances 20190227 2

The glymphatic system is responsible for brain-wide delivery of nutrients and clearance of waste via influx of cerebrospinal fluid (CSF) alongside perivascular spaces and through the brain. Glymphatic system activity increases during sleep or ketamine/xylazine (K/X) anesthesia, yet the mechanism(s) facilitating CSF influx are poorly understood. Here, we correlated influx of a CSF tracer into the brain with electroencephalogram (EEG) power, heart rate, blood pressure, and respiratory rate in wild ...[more]

PMID: 30820460

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Project description:BackgroundPhase lag entropy (PLE) is a novel anesthetic depth indicator that uses four-channel electroencephalography (EEG) to measure the temporal pattern diversity in the phase relationship of frequency signals in the brain. The purpose of the study was to evaluate the anesthetic depth monitoring using PLE and to evaluate the correlation between PLE and bispectral index (BIS) values during propofol anesthesia.MethodsIn thirty-five adult patients undergoing elective surgery, anesthesia was induced with propofol using target-controlled infusion (the Schneider model). We recorded the PLE value, raw EEG, BIS value, and hemodynamic data when the target effect-site concentration (Ce) of propofol reached 2, 3, 4, 5, and 6??g/ml before intubation and 6, 5, 4, 3, 2??g/ml after intubation and injection of muscle relaxant. We analyzed whether PLE and raw EEG data from the PLE monitor reflected the anesthetic depth as the Ce of propofol changed, and whether PLE values were comparable to BIS values.ResultsPLE values were inversely correlated to changes in propofol Ce (propofol Ce from 0 to 6.0??g/ml, r2?=?-?0.83; propofol Ce from 6.0 to 2.0??g/ml, r2?=?-?0.46). In the spectral analysis of EEG acquired from the PLE monitor, the persistence spectrogram revealed a wide distribution of power at loss of consciousness (LOC) and recovery of consciousness (ROC), with a narrow distribution during unconsciousness. The power spectrogram showed the typical pattern seen in propofol anesthesia with slow alpha frequency band oscillation. The PLE value demonstrated a strong correlation with the BIS value during the change in propofol Ce from 0 to 6.0??g/ml (r2?=?0.84). PLE and BIS values were similar at LOC (62.3 vs. 61.8) (P?>?0.05), but PLE values were smaller than BIS values at ROC (64.4 vs 75.7) (P?<?0.05).ConclusionsThe PLE value is a useful anesthetic depth indicator, similar to the BIS value, during propofol anesthesia. Spectral analysis of EEG acquired from the PLE monitor demonstrated the typical patterns seen in propofol anesthesia.Trial registrationThis clinical trial was retrospectively registered at ClinicalTrials.gov at October 2017 (NCT03299621).

Project description:Highlights? Twelve entropy indices were systematically compared in monitoring depth of anesthesia and detecting burst suppression.? Renyi permutation entropy performed best in tracking EEG changes associated with different anesthesia states.? Approximate Entropy and Sample Entropy performed best in detecting burst suppression.ObjectiveEntropy algorithms have been widely used in analyzing EEG signals during anesthesia. However, a systematic comparison of these entropy algorithms in assessing anesthesia drugs' effect is lacking. In this study, we compare the capability of 12 entropy indices for monitoring depth of anesthesia (DoA) and detecting the burst suppression pattern (BSP), in anesthesia induced by GABAergic agents.MethodsTwelve indices were investigated, namely Response Entropy (RE) and State entropy (SE), three wavelet entropy (WE) measures [Shannon WE (SWE), Tsallis WE (TWE), and Renyi WE (RWE)], Hilbert-Huang spectral entropy (HHSE), approximate entropy (ApEn), sample entropy (SampEn), Fuzzy entropy, and three permutation entropy (PE) measures [Shannon PE (SPE), Tsallis PE (TPE) and Renyi PE (RPE)]. Two EEG data sets from sevoflurane-induced and isoflurane-induced anesthesia respectively were selected to assess the capability of each entropy index in DoA monitoring and BSP detection. To validate the effectiveness of these entropy algorithms, pharmacokinetic/pharmacodynamic (PK/PD) modeling and prediction probability (Pk) analysis were applied. The multifractal detrended fluctuation analysis (MDFA) as a non-entropy measure was compared.ResultsAll the entropy and MDFA indices could track the changes in EEG pattern during different anesthesia states. Three PE measures outperformed the other entropy indices, with less baseline variability, higher coefficient of determination (R (2)) and prediction probability, and RPE performed best; ApEn and SampEn discriminated BSP best. Additionally, these entropy measures showed an advantage in computation efficiency compared with MDFA.ConclusionEach entropy index has its advantages and disadvantages in estimating DoA. Overall, it is suggested that the RPE index was a superior measure. Investigating the advantages and disadvantages of these entropy indices could help improve current clinical indices for monitoring DoA.

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Increased glymphatic influx is correlated with high EEG delta power and low heart rate in mice under anesthesia.

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Increased glymphatic influx is correlated with high EEG delta power and low heart rate in mice under anesthesia.

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