Electroencephalogram-Based Anesthesia Indices Differently React to Modulations of Alpha-Oscillatory Activity.

BACKGROUND: The electroencephalographic (EEG) provides the anesthesiologist with information regarding the level of anesthesia. Processed EEG indices are available that reflect the level of anesthesia as a single number. Strong oscillatory EEG activity in the alpha-band may be associated with an adequate level of anesthesia and a lower incidence of cognitive sequelae. So far, we do not know how the processed indices would react to changes in the alpha-band activity. Hence, we modulated the alpha-oscillatory activity of intraoperative EEG to assess possible index changes. METHODS: We performed our analyses based on data from 2 studies. Intraoperative EEG was extracted, and we isolated the alpha-band activity by band-pass filtering (8-12 Hz). We added or subtracted this activity to the original EEG in different steps with different amplifications of the alpha signal. We then replayed these signals to the bispectral index (BIS), the Entropy Module (state entropy [SE]), the CONOX (qCON), and the SEDLine (patient state index [PSI]); and evaluated the alpha-band modulation's impact on the respective index. RESULTS: The indices behaved differently to the modulation. In general, indices decreased with stronger alpha-band activity, but the rate of change was different with SE showing the strongest change (9% per step) and PSI and BIS (<5% per step) showing the weakest change. A simple regression analysis revealed a decrease of 0.02 to 0.09 index points with increasing alpha amplification. CONCLUSIONS: While the alpha-band in the intraoperative EEG seems to carry information regarding the quality of anesthesia, changes in the alpha-band activity do neither strongly nor uniformly influence processed EEG indices. Hence, to assess alpha-oscillatory activity's strength, the user needs to focus on the raw EEG or its spectral representation also displayed on the monitoring systems.

Impact of Age on the Occurrence of Processed Electroencephalographic Burst Suppression.

BACKGROUND: Patient age is assumed to be an important risk factor for the occurrence of burst suppression, yet this has still to be confirmed by large datasets. METHODS: In this single-center retrospective analysis at a university hospital, the electronic patient records of 38,628 patients (≥18 years) receiving general anesthesia between January 2016 and December 2018 were analyzed. Risk factors for burst suppression were evaluated using univariate and multivariable analysis. We measured the incidence of burst suppression as indicated by the burst suppression ratio (BSR) of the Entropy Module, the maximum and mean BSR values, relative burst suppression duration, mean volatile anesthetic concentrations, and mean age-adjusted minimum alveolar concentrations (aaMAC) at burst suppression, and cases of potentially misclassified burst suppression episodes. Analyses were done separately for the total anesthesia period, as well as for the Induction and Maintenance phase. The association with age was evaluated using linear and polynomial fits and by calculating correlation coefficients. RESULTS: Of the 54,266 patients analyzed, 38,628 were included, and 19,079 patients exhibited episodes with BSR >0. Patients with BSR >0 were significantly older, and age had the highest predictive power for BSR >0 (area under the receiving operating characteristic [AUROC] = 0.646 [0.638-0.654]) compared to other patient or procedural factors. The probability of BSR >0 increased linearly with patient age (ρ = 0.96-0.99) between 1.9% and 9.8% per year. While maximal and mean BSR showed a nonlinear relationship with age, relative burst suppression duration also increased linearly during maintenance (ρ = 0.83). Further, episodes potentially indicating burst suppression that were not detected by the Entropy BSR algorithm also became more frequent with age. Volatile anesthetic concentrations sufficient to induce BSR >0 were negatively correlated with age (sevoflurane: ρ = -0.71), but remained close to an aaMAC of 1.0. CONCLUSIONS: The probability of burst suppression during general anesthesia increases linearly with age in adult patients, while lower anesthetic concentrations induce burst suppression with increasing patient age. Simultaneously, algorithm-based burst suppression detection appears to perform worse in older patients. These findings highlight the necessity to further enhance EEG application and surveillance strategies in anesthesia.

Effect of transcranial direct current stimulation and narrow-band auditory stimulation on the intraoperative electroencephalogram: an exploratoratory feasibility study.

Introduction: During general anesthesia, frontal electroencephalogram (EEG) activity in the alpha frequency band (8-12 Hz) correlates with the adequacy of analgesia. Transcranial direct current stimulation (tDCS) and auditory stimulation, two noninvasive neuromodulation techniques, can entrain alpha activity in awake or sleeping patients. This study evaluates their effects on alpha oscillations in patients under general anesthesia. Methods: 30 patients receiving general anesthesia for surgery were enrolled in this two-by-two randomized clinical trial. Each participant received active or sham tDCS followed by auditory stimulation or silence according to assigned group (TDCS/AUD, TDCS/SIL, SHAM/AUD, SHAM/SIL). Frontal EEG was recorded before and after neuromodulation. Patients with burst suppression, mid-study changes in anesthetic, or incomplete EEG recordings were excluded from analysis. The primary outcome was post-stimulation change in oscillatory alpha power, compared in each intervention group against the change in the control group SHAM/SIL by Wilcoxon Rank Sum testing. Results: All 30 enrolled participants completed the study. Of the 22 included for analysis, 8 were in TDCS/AUD, 4 were in TDCS/SIL, 5 were in SHAM/AUD, and 5 were in SHAM/SIL. The median change in oscillatory alpha power was +4.7 dB (IQR 4.4, 5.8 dB) in SHAM/SIL, +2.8 dB (IQR 1.5, 8.9 dB) in TDCS/SIL (p = 0.730), +5.5 dB in SHAM/AUD (p = 0.421), and -6.1 dB (IQR -10.2, -2.2 dB) in TDCS/AUD (p = 0.045). Conclusion: tDCS and auditory stimulation can be administered safely intraoperatively. However, these interventions did not increase alpha power as administered and measured in this pilot study.

Isoflurane anesthesia and sleep deprivation trigger delayed and selective sleep alterations.

Isoflurane anesthesia (IA) partially compensates NREM sleep (NREMS) and not REM sleep (REMS) requirement, eliciting post-anesthetic REMS rebound. Sleep deprivation triggers compensatory NREMS rebounds and REMS rebounds during recovery sleep as a result of the body's homeostatic mechanisms. A combination of sleep deprivation and isoflurane anesthesia is common in clinical settings, especially prior to surgeries. This study investigates the effects of pre-anesthetic sleep deprivation on post-anesthetic sleep-wake architecture. The effects of isoflurane exposure (90 min) alone were compared with the effects of isoflurane exposure preceded by experimental sleep deprivation (6 h, gentle handling) on recovery sleep in adult mice by studying the architecture of post-anesthetic sleep for 3 consecutive post-anesthetic days. Effects of isoflurane anesthesia on recovery sleep developed only during the first dark period after anesthesia, the active phase in mice. During this time, mice irrespective of preceding sleep pressure, showed NREMS and REMS rebound and decreased wakefulness during recovery sleep. Additionally, sleep deprivation prior to isoflurane treatment caused a persistent reduction of theta power during post-anesthetic REMS at least for 3 post-anesthetic days. We showed that isoflurane causes NREMS rebound during recovery sleep which suggests that isoflurane may not fully compensate for natural NREMS. The study also reveals that isoflurane exposure preceded by sleep deprivation caused a persistent disruption of REMS quality. We suggest that preoperative sleep deprivation may impair postoperative recovery through lasting disruption in sleep quality.

Substance specific EEG patterns in mice undergoing slow anesthesia induction.

The exact mechanisms and the neural circuits involved in anesthesia induced unconsciousness are still not fully understood. To elucidate them valid animal models are necessary. Since the most commonly used species in neuroscience are mice, we established a murine model for commonly used anesthetics/sedatives and evaluated the epidural electroencephalographic (EEG) patterns during slow anesthesia induction and emergence. Forty-four mice underwent surgery in which we inserted a central venous catheter and implanted nine intracranial electrodes above the prefrontal, motor, sensory, and visual cortex. After at least one week of recovery, mice were anesthetized either by inhalational sevoflurane or intravenous propofol, ketamine, or dexmedetomidine. We evaluated the loss and return of righting reflex (LORR/RORR) and recorded the electrocorticogram. For spectral analysis we focused on the prefrontal and visual cortex. In addition to analyzing the power spectral density at specific time points we evaluated the changes in the spectral power distribution longitudinally. The median time to LORR after start anesthesia ranged from 1080 [1st quartile: 960; 3rd quartile: 1080]s under sevoflurane anesthesia to 1541 [1455; 1890]s with ketamine. Around LORR sevoflurane as well as propofol induced a decrease in the theta/alpha band and an increase in the beta/gamma band. Dexmedetomidine infusion resulted in a shift towards lower frequencies with an increase in the delta range. Ketamine induced stronger activity in the higher frequencies. Our results showed substance-specific changes in EEG patterns during slow anesthesia induction. These patterns were partially identical to previous observations in humans, but also included significant differences, especially in the low frequencies. Our study emphasizes strengths and limitations of murine models in neuroscience and provides an important basis for future studies investigating complex neurophysiological mechanisms.

Continuity with caveats in anesthesia: state and response entropy of the EEG.

The growing use of neuromonitoring in general anesthesia provides detailed insights into the effects of anesthetics on the brain. Our study focuses on the processed EEG indices State Entropy (SE), Response Entropy (RE), and Burst Suppression Ratio (BSR) of the GE EntropyTM Module, which serve as surrogate measures for estimating the level of anesthesia. While retrospectively analyzing SE and RE index values from patient records, we encountered a technical anomaly with a conspicuous distribution of index values. In this single-center, retrospective study, we analyzed processed intraoperative electroencephalographic (EEG) data from 15,608 patients who underwent general anesthesia. We employed various data visualization techniques, including histograms and heat maps, and fitted custom non-Gaussian curves. Individual patients' anesthetic periods were evaluated in detail. To compare distributions, we utilized the Kolmogorov-Smirnov test and Kullback-Leibler divergence. The analysis also included the influence of the BSR on the distribution of SE and RE values. We identified distinct pillar indices for both SE and RE, i.e., index values with a higher probability of occurrence than others. These pillar index values were not age-dependent and followed a non-equidistant distribution pattern. This phenomenon occurs independently of the BSR distribution. SE and RE index values do not adhere to a continuous distribution, instead displaying prominent pillar indices with a consistent pattern of occurrence across all age groups. The specific features of the underlying algorithm responsible for this pattern remain elusive.

Correction: Dreismickenbecker et al. Electroencephalography-Based Effects of Acute Alcohol Intake on the Pain Matrix. Brain Sci. 2023, 13, 1659.

This paper [...].

Electroencephalographic guided propofol-remifentanil TCI anesthesia with and without dexmedetomidine in a geriatric population: electroencephalographic signatures and clinical evaluation.

Elderly and multimorbid patients are at high risk for developing unfavorable postoperative neurocognitive outcomes; however, well-adjusted and EEG-guided anesthesia may help titrate anesthesia and improve postoperative outcomes. Over the last decade, dexmedetomidine has been increasingly used as an adjunct in the perioperative setting. Its synergistic effect with propofol decreases the dose of propofol needed to induce and maintain general anesthesia. In this pilot study, we evaluate two highly standardized anesthetic regimens for their potential to prevent burst suppression and postoperative neurocognitive dysfunction in a high-risk population. Prospective, randomized clinical trial with non-blinded intervention. Operating room and post anesthesia care unit at Hospital Base San José, Osorno/Universidad Austral, Valdivia, Chile. 23 patients with scheduled non-neurologic, non-cardiac surgeries with age > 69 years and a planned intervention time > 60 min. Patients were randomly assigned to receive either a propofol-remifentanil based anesthesia or an anesthetic regimen with dexmedetomidine-propofol-remifentanil. All patients underwent a slow titrated induction, followed by a target controlled infusion (TCI) of propofol and remifentanil (n = 10) or propofol, remifentanil and continuous dexmedetomidine infusion (n = 13). We compared the perioperative EEG signatures, drug-induced changes, and neurocognitive outcomes between two anesthetic regimens in geriatric patients. We conducted a pre- and postoperative Montreal Cognitive Assessment (MoCa) test and measured the level of alertness postoperatively using a sedation agitation scale to assess neurocognitive status. During slow induction, maintenance, and emergence, burst suppression was not observed in either group; however, EEG signatures differed significantly between the two groups. In general, EEG activity in the propofol group was dominated by faster rhythms than in the dexmedetomidine group. Time to responsiveness was not significantly different between the two groups (p = 0.352). Finally, no significant differences were found in postoperative cognitive outcomes evaluated by the MoCa test nor sedation agitation scale up to one hour after extubation. This pilot study demonstrates that the two proposed anesthetic regimens can be safely used to slowly induce anesthesia and avoid EEG burst suppression patterns. Despite the patients being elderly and at high risk, we did not observe postoperative neurocognitive deficits. The reduced alpha power in the dexmedetomidine-treated group was not associated with adverse neurocognitive outcomes.

Permutation Entropy Does Not Track the Electroencephalogram-Related Manifestations of Paradoxical Excitation During Propofol-Induced Loss of Responsiveness: Results From a Prospective Observational Cohort Study.

BACKGROUND: During the anesthetic-induced loss of responsiveness (LOR), a "paradoxical excitation" with activation of ß-frequencies in the electroencephalogram (EEG) can be observed. Thus, spectral parameters-as widely used in commercial anesthesia monitoring devices-may mistakenly indicate that patients are awake when they are actually losing responsiveness. Nonlinear time-domain parameters such as permutation entropy (PeEn) may analyze additional EEG information and appropriately reflect the change in cognitive state during the transition. Determining which parameters correctly track the level of anesthesia is essential for designing monitoring algorithms but may also give valuable insight regarding the signal characteristics during state transitions. METHODS: EEG data from 60 patients who underwent general anesthesia were extracted and analyzed around LOR. We derived the following information from the power spectrum: (i) spectral band power, (ii) the spectral edge frequency as well as 2 parameters known to be incorporated in monitoring systems, (iii) beta ratio, and (iv) spectral entropy. We also calculated (v) PeEn as a time-domain parameter. We used Friedman's test and Bonferroni correction to track how the parameters change over time and the area under the receiver operating curve to separate the power spectra between time points. RESULTS: Within our patient collective, we observed a "paradoxical excitation" around the time of LOR as indicated by increasing beta-band power. Spectral edge frequency and spectral entropy values increased from 19.78 [10.25-34.18] Hz to 25.39 [22.46-30.27] Hz (P = .0122) and from 0.61 [0.54-0.75] to 0.77 [0.64-0.81] (P < .0001), respectively, before LOR, indicating a (paradoxically) higher level of high-frequency activity. PeEn and beta ratio values decrease from 0.78 [0.77-0.82] to 0.76 [0.73-0.81] (P < .0001) and from -0.74 [-1.14 to -0.09] to -2.58 [-2.83 to -1.77] (P < .0001), respectively, better reflecting the state transition into anesthesia. CONCLUSIONS: PeEn and beta ratio seem suitable parameters to monitor the state transition during anesthesia induction. The decreasing PeEn values suggest a reduction of signal complexity and information content, which may very well describe the clinical situation at LOR. The beta ratio mainly focuses on the loss of power in the gamma-band. PeEn, in particular, may present a single parameter capable of tracking the LOR transition without being affected by paradoxical excitation.

Altered sleep behavior strengthens face validity in the ArcAß mouse model for Alzheimer's disease.

Demographic changes will expand the number of senior citizens suffering from Alzheimer's disease (AD). Key aspects of AD pathology are sleep impairments, associated with onset and progression of AD. AD mouse models may provide insights into mechanisms of AD-related sleep impairments. Such models may also help to establish new biomarkers predicting AD onset and monitoring AD progression. The present study aimed to establish sleep-related face validity of a widely used mouse model of AD (ArcAß model) by comprehensively characterizing its baseline sleep/wake behavior. Chronic EEG recordings were performed continuously on four consecutive days in freely behaving mice. Spectral and temporal sleep/wake parameters were assessed and analyzed. EEG recordings showed decreased non-rapid eye movement sleep (NREMS) and increased wakefulness in transgenic mice (TG). Vigilance state transitions were different in TG mice when compared to wildtype littermates (WT). During NREMS, TG mice had lower power between 1 and 5 Hz and increased power between 5 and 30 Hz. Sleep spindle amplitudes in TG mice were lower. Our study strongly provides sleep-linked face validity for the ArcAß model. These findings extend the potential of the mouse model to investigate mechanisms of AD-related sleep impairments and the impact of sleep impairments on the development of AD.

Nociceptive Processing of Elite Athletes Varies between Sport-Specific Loads: An EEG-Based Study Approach.

INTRODUCTION: For the downstream nociceptive processing of elite athletes, recent studies indicate that athletes probably tolerate more pain as compared with a normally active population. Phenotyping the nociceptive processing of athletes in different types of endurance sports can provide insight into training-specific effects, which may help in understanding the long-term effects of specific exercise. METHODS: Twenty-six elite endurance athletes from the disciplines of rowing, triathlon, and running and 26 age- and sex-matched, recreationally active control subjects who participated in the subjective pain perception and processing of standardized noxious stimuli were investigated by EEG. This included standardized heat pain thresholds (HPT) and contact heat-evoked potentials from heat stimulation, measured with EEG as well as pinprick-evoked potentials from mechanical stimulation. RESULTS: After noxious stimulation, athletes showed a higher activation of the event-related spectral perturbation (ERSP) patterns in the N2P2 EEG response at the Cz Electrode compared with the controls. After noxious contact heat stimulation, triathletes had a higher ERSP activation compared with the controls, whereas the rowers had a higher ERSP activation after noxious mechanical stimulation. Also, HPT in triathletes were increased despite their increased central activation after thermal stimulation. We found a correlation between increased HPT and training hours and years, although athletes did not differ within these variables. CONCLUSIONS: Although we were able to identify differences between athletes of different endurance sports, the reasons and implications of these differences remain unclear. The study of sport-specific somatosensory profiles may help to understand the mechanisms of exercise-related long-term effects on pain processing and perception. Furthermore, sport-specific somatosensory effects may support the personalization of exercise interventions and identify risk factors for chronic pain in elite athletes.

Electroencephalographic monitoring of anesthesia during surgical procedures in mice using a modified clinical monitoring system.

Monitoring brain activity and associated physiology during the administration of general anesthesia (GA) in mice is pivotal to guarantee postanesthetic health. Clinically, electroencephalogram (EEG) monitoring is a well-established method to guide GA. There are no established methods available for monitoring EEG in mice (Mus musculus) during surgery. In this study, a minimally invasive rodent intraoperative EEG monitoring system was implemented using subdermal needle electrodes and a modified EEG-based commercial patient monitor. EEG recordings were acquired at three different isoflurane concentrations revealing that surgical concentrations of isoflurane anesthesia predominantly contained burst suppression patterns in mice. EEG suppression ratios and suppression durations showed strong positive correlations with the isoflurane concentrations. The electroencephalographic indices provided by the monitor did not support online monitoring of the anesthetic status. The online available suppression duration in the raw EEG signals during isoflurane anesthesia is a straight forward and reliable marker to assure safe, adequate and reproducible anesthesia protocols.

Separation of responsive and unresponsive patients under clinical conditions: comparison of symbolic transfer entropy and permutation entropy.

Electroencephalogram (EEG)-based monitoring during general anesthesia may help prevent harmful effects of high or low doses of general anesthetics. There is currently no convincing evidence in this regard for the proprietary algorithms of commercially available monitors. The purpose of this study was to investigate whether a more mechanism-based parameter of EEG analysis (symbolic transfer entropy, STE) can separate responsive from unresponsive patients better than a strictly probabilistic parameter (permutation entropy, PE) under clinical conditions. In this prospective single-center study, the EEG of 60 surgical ASA I-III patients was recorded perioperatively. During induction of and emergence from anesthesia, patients were asked to squeeze the investigators' hand every 15s. Time of loss of responsiveness (LoR) during induction and return of responsiveness (RoR) during emergence from anesthesia were registered. PE and STE were calculated at -15s and +30s of LoR and RoR and their ability to separate responsive from unresponsive patients was evaluated using accuracy statistics. 56 patients were included in the final analysis. STE and PE values decreased during anesthesia induction and increased during emergence. Intra-individual consistency was higher during induction than during emergence. Accuracy values during LoR and RoR were 0.71 (0.62-0.79) and 0.60 (0.51-0.69), respectively for STE and 0.74 (0.66-0.82) and 0.62 (0.53-0.71), respectively for PE. For the combination of LoR and RoR, values were 0.65 (0.59-0.71) for STE and 0.68 (0.62-0.74) for PE. The ability to differentiate between the clinical status of (un)responsiveness did not significantly differ between STE and PE at any time. Mechanism-based EEG analysis did not improve differentiation of responsive from unresponsive patients compared to the probabilistic PE.Trial registration: German Clinical Trials Register ID: DRKS00030562, November 4, 2022, retrospectively registered.

An in-depth analysis of parameter settings and probability distributions of specific ordinal patterns in the Shannon permutation entropy during different states of consciousness in humans.

As electrical activity in the brain has complex and dynamic properties, the complexity measure permutation entropy (PeEn) has proven itself to reliably distinguish consciousness states recorded by the EEG. However, it has been shown that the focus on specific ordinal patterns instead of all of them produced similar results. Moreover, parameter settings influence the resulting PeEn value. We evaluated the impact of the embedding dimension m and the length of the EEG segment on the resulting PeEn. Moreover, we analysed the probability distributions of monotonous and non-occurring ordinal patterns in different parameter settings. We based our analyses on simulated data as well as on EEG recordings from volunteers, obtained during stable anaesthesia levels at defined, individualised concentrations. The results of the analysis on the simulated data show a dependence of PeEn on different influencing factors such as window length and embedding dimension. With the EEG data, we demonstrated that the probability P of monotonous patterns performs like PeEn in lower embedding dimension (m = 3, AUC = 0.88, [0.7, 1] in both), whereas the probability P of non-occurring patterns outperforms both methods in higher embedding dimensions (m = 5, PeEn: AUC = 0.91, [0.77, 1]; P(non-occurring patterns): AUC = 1, [1, 1]). We showed that the accuracy of PeEn in distinguishing consciousness states changes with different parameter settings. Furthermore, we demonstrated that for the purpose of separating wake from anaesthesia EEG solely pieces of information used for PeEn calculation, i.e., the probability of monotonous patterns or the number of non-occurring patterns may be equally functional.

Substance-dependent EEG during recovery from anesthesia and optimization of monitoring.

The electroencephalographic (EEG) activity during anesthesia emergence contains information about the risk for a patient to experience postoperative delirium, but the EEG dynamics during emergence challenge monitoring approaches. Substance-specific emergence characteristics may additionally limit the reliability of commonly used processed EEG indices during emergence. This study aims to analyze the dynamics of different EEG indices during anesthesia emergence that was maintained with different anesthetic regimens. We used the EEG of 45 patients under general anesthesia from the emergence period. Fifteen patients per group received sevoflurane, isoflurane (+ sufentanil) or propofol (+ remifentanil) anesthesia. One channel EEG and the bispectral index (BIS A-1000) were recorded during the study. We replayed the EEG back to the Conox, Entropy Module, and the BIS Vista to evaluate and compare the index behavior. The volatile anesthetics induced significantly higher EEG frequencies, causing higher indices (AUC > 0.7) over most parts of emergence compared to propofol. The median duration of "awake" indices (i.e., > 80) before the return of responsiveness (RoR) was significantly longer for the volatile anesthetics (p < 0.001). The different indices correlated well under volatile anesthesia (rs > 0.6), with SE having the weakest correlation. For propofol, the correlation was lower (rs < 0.6). SE was significantly higher than BIS and, under propofol anesthesia, qCON. Systematic differences of EEG-based indices depend on the drugs and devices used. Thus, to avoid early awareness or anesthesia overdose using an EEG-based index during emergence, the anesthetic regimen, the monitor used, and the raw EEG trace should be considered for interpretation before making clinical decisions.

Development of Postanesthesia Care Unit Delirium Is Associated with Differences in Aperiodic and Periodic Alpha Parameters of the Electroencephalogram during Emergence from General Anesthesia: Results from a Prospective Observational Cohort Study.

BACKGROUND: Intraoperative alpha-band power in frontal electrodes may provide helpful information about the balance of hypnosis and analgesia and has been associated with reduced occurrence of delirium in the postanesthesia care unit. Recent studies suggest that narrow-band power computations from neural power spectra can benefit from separating periodic and aperiodic components of the electroencephalogram. This study investigates whether such techniques are more useful in separating patients with and without delirium in the postanesthesia care unit at the group level as opposed to conventional power spectra. METHODS: Intraoperative electroencephalography recordings of 32 patients who developed perioperative neurocognitive disorders and 137 patients who did not were considered in this post hoc secondary analysis. The power spectra were calculated using conventional methods and the "fitting oscillations and one over f" algorithm was applied to separate aperiodic and periodic components to see whether the electroencephalography signature is different between groups. RESULTS: At the group level, patients who did not develop perioperative neurocognitive disorders presented with significantly higher alpha-band power and a broadband increase in power, allowing a "fair" separation based on conventional power spectra. Within the first third of emergence, the difference in median absolute alpha-band power amounted to 8.53 decibels (area under the receiver operator characteristics curve, 0.74 [0.65; 0.82]), reaching its highest value. In relative terms, the best separation was achieved in the second third of emergence, with a difference in medians of 7.71% (area under the receiver operator characteristics curve, 0.70 [0.61; 0.79]). The area under the receiver operator characteristics curve values were generally lower toward the end of emergence with increasing arousal. CONCLUSIONS: Increased alpha-band power during emergence in patients who did not develop perioperative neurocognitive disorders can be traced back to an increase in oscillatory alpha activity and an overall increase in aperiodic broadband power. Although the differences between patients with and without perioperative neurocognitive disorders can be detected relying on traditional methods, the separation of the signal allows a more detailed analysis. This may enable clinicians to detect patients at risk for developing perioperative neurocognitive disorders in the postanesthesia care unit early in the emergence phase.

Electroencephalography-Based Effects of Acute Alcohol Intake on the Pain Matrix.

The effects of acute and chronic intakes of high doses of alcohol on pain perception are well known, ranging from short-term analgesic effects to long-term sensitization and polyneuropathies. The short-term analgesic effects of ethanol consumption on subjective pain perception have been well studied in the literature. Recent advances in neuroimaging allow for an insight into pain-related structures in the brain, fostering the mechanistic understanding of the processing of nociceptive input and pain. We aimed to utilize EEG, combined with standardized noxious mechanical/thermal stimulation and subjective pain testing, to research the effects of acute alcohol intake on nociceptive processing and pain perception. We recruited 12 healthy subjects in an unblinded cross-over study design and aimed at achieving a blood alcohol level of 0.1%. Our data revealed a significant reduction in subjective pain ratings to noxious thermal and mechanical stimuli after alcohol ingestion. Our EEG data revealed suppressing effects on the cortical structures responsible for processing pain, the "pain matrix". We conclude that in addition to its analgesic effects, as expressed by the reduction in subjective pain, alcohol has a further impact on the "pain matrix" and directly affects the salience to a nociceptive stimulus.

Ketamine-Propofol Coadministration for Induction and Infusion Maintenance in Anesthetized Dogs: Effects on Electroencephalography and Antinociception.

The effects of concurrent ketamine and propofol (ketofol) constant rate infusion (CRI) were examined in six dogs. The K:P ratio was 1:2, with an initial CRI of 0.25/0.5 mg/kg/min over ten minutes, followed by a 0.5 mg/kg ketamine bolus for induction. During induction, a comprehensive EEG frequency spectrum from delta to gamma was observed, accompanied by subanesthetic-dose ketofol-induced behavioral excitation, including nystagmus, tongue flicking, salivation and active muscle activity. The dogs were maintained on three 15 min decremental doses of ketofol CRI (0.8/1.6, 0.4/0.8 and 0.2/0.4 mg/kg/min). This phase featured a significant decrease in the Patient State Index, electromyographic activity and a shift to low beta waves (SEF95: 13-18 Hz). Additionally, profound antinociception to electric stimulation and a stable heart rate and blood pressure (MBP 81.5-110 mmHg) were observed, as well as a merging of ketamine and propofol EEG characteristics during maintenance. In the recovery phase, a return to beta and gamma EEG patterns and excitement behavior occurred, accompanied by a significant reduction in antinociception, highlighting features of low doses of ketofol. This study reveals biphasic EEG dynamic changes, associated behaviors and robust antinociception and cardiovascular function, suggesting the utility of ketofol as a total intravenous anesthetic combination in dogs.