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Särkelä, Mika O. K.; Mustola, Seppo; Seppänen, Tapio; Koskinen, Miika; Lepola, Pasi; Suominen, Kalervo; Juvonen, Tatu; Tolvanen-Laakso, Heli; Jäntti, V.

doi:10.1023/a:1016393904439

Cited by 89 publications

(34 citation statements)

References 15 publications

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“…No significant heterogeneity across the five recorded cortical sites was found. The frequency bandwidths in step (1) were varied: 5–30 Hz, 5–50 Hz, 3–125 Hz, 26 and the difference of <8 Hz and >47 Hz, 28 and found that 5–30 Hz and 5–50 Hz analyses yielded similar results, which were superior to the other two cases in almost all rats (in agreement with visual inspection). Furthermore, different values were tested for the threshold of mean+c*SD in step (3): c=3–7 and the one in best agreement with visual inspection was selected; c=3 for 8 and c=4 for 12 of 20 rats.…”

Section: Methodssupporting

confidence: 63%

“…EEG epochs were analyzed from the beginning through the end of the 12.5 min duration of Acetylcholine (ACh) sample collection, to ensure parallel information for ACh sampling and EEG recording. To validate our results, we applied two alternative methods (variance-based method 27 and nonlinear energy operator-based method 28 ) to replace the amplitude approach in step (2). In the first alternative method, the standard deviation of the bandpassed signal was computed for each 200 ms interval with a 150 ms overlap; in the second method, the energy of the bandpassed signal was calculated by the nonlinear energy operator and smoothed using a 200 ms moving average.…”

Section: Methodsmentioning

confidence: 99%

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Paradoxical Emergence

Hambrecht-Wiedbusch

Mashour

2017

Anesthesiology

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Background Promoting arousal by manipulating certain brain regions and/or neurotransmitters has been a recent research focus, with the goal of trying to improve recovery from general anesthesia. The current study tested the hypothesis that a single subanesthetic dose of ketamine during isoflurane anesthesia would increase cholinergic tone in the prefrontal cortex and accelerate recovery. Methods Adult male rats were implanted with electroencephalography electrodes (frontal, parietal, and occipital cortex) and a microdialysis guide cannula targeted for the prefrontal cortex. After establishing general anesthesia with isoflurane, animals were randomly assigned to receive a saline control or ketamine injection. When isoflurane was discontinued nearly 90 min after drug or saline administration, recovery from anesthesia was measured by experimenters and blinded observers. During the entire experiment, electrophysiologic signals were recorded and acetylcholine was quantified by high-performance liquid chromatography with electrochemical detection. Results A single dose of subanesthetic ketamine caused an initial 125% increase in burst suppression ratio (last isoflurane sample: 37.48 ± 24.11% vs. isoflurane after ketamine injection: 84.36 ± 8.95%; P < 0.0001), but also a significant 44% reduction in emergence time (saline: 877 ± 335 s vs. ketamine: 494 ± 108 s; P = 0.0005; n = 10 per treatment). Furthermore, ketamine caused a significant 317% increase in cortical acetylcholine release (mean after ketamine injection: 0.18 ± 0.16 pmol vs. ketamine recovery: 0.75 ± 0.41 pmol; P = 0.0002) after isoflurane anesthesia was discontinued. Conclusions Administration of subanesthetic doses of ketamine during isoflurane anesthesia increases anesthetic depth but—paradoxically—accelerates the recovery of consciousness, possibly through cholinergic mechanisms.

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Section: Methodssupporting

confidence: 63%

Section: Methodsmentioning

confidence: 99%

Paradoxical Emergence

Hambrecht-Wiedbusch

Mashour

2017

Anesthesiology

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“…It is characterised by alternating periods of normal to high voltage activity changing to low voltage. This kind of activity is usually seen when the concentration of anaesthetic drug is high [120,121]. To quantify this effect the burst suppression ratio (BSR) is calculated.…”

Section: Basic Design Characteristics Of Current Dga Monitorsmentioning

confidence: 99%

Monitoring the Depth of Anaesthesia

Musizza

Ribarič

2010

Sensors

112

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One of the current challenges in medicine is monitoring the patients’ depth of general anaesthesia (DGA). Accurate assessment of the depth of anaesthesia contributes to tailoring drug administration to the individual patient, thus preventing awareness or excessive anaesthetic depth and improving patients’ outcomes. In the past decade, there has been a significant increase in the number of studies on the development, comparison and validation of commercial devices that estimate the DGA by analyzing electrical activity of the brain (i.e., evoked potentials or brain waves). In this paper we review the most frequently used sensors and mathematical methods for monitoring the DGA, their validation in clinical practice and discuss the central question of whether these approaches can, compared to other conventional methods, reduce the risk of patient awareness during surgical procedures.

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“…Previously, several methods have been proposed to detect the burst suppression pattern of EEG signals [34, 35]. However, we still need to overcome several drawbacks in the existing methods for constructing a practical burst suppression detection system in EEG recordings.…”

Section: Discussionmentioning

confidence: 99%

Detection of Burst Suppression Patterns in EEG Using Recurrence Rate

Liang

Wang

Ren

et al. 2014

The Scientific World Journal

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Burst suppression is a unique electroencephalogram (EEG) pattern commonly seen in cases of severely reduced brain activity such as overdose of general anesthesia. It is important to detect burst suppression reliably during the administration of anesthetic or sedative agents, especially for cerebral-protective treatments in various neurosurgical diseases. This study investigates recurrent plot (RP) analysis for the detection of the burst suppression pattern (BSP) in EEG. The RP analysis is applied to EEG data containing BSPs collected from 14 patients. Firstly we obtain the best selection of parameters for RP analysis. Then, the recurrence rate (RR), determinism (DET), and entropy (ENTR) are calculated. Then RR was selected as the best BSP index one-way analysis of variance (ANOVA) and multiple comparison tests. Finally, the performance of RR analysis is compared with spectral analysis, bispectral analysis, approximate entropy, and the nonlinear energy operator (NLEO). ANOVA and multiple comparison tests showed that the RR could detect BSP and that it was superior to other measures with the highest sensitivity of suppression detection (96.49%, P = 0.03). Tracking BSP patterns is essential for clinical monitoring in critically ill and anesthetized patients. The purposed RR may provide an effective burst suppression detector for developing new patient monitoring systems.

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Cited by 89 publications

References 15 publications

Paradoxical Emergence

Paradoxical Emergence

Monitoring the Depth of Anaesthesia

Detection of Burst Suppression Patterns in EEG Using Recurrence Rate

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