Biphasic EEG changes in relation to loss of consciousness during induction with thiopental, propofol, etomidate, midazolam or sevoflurane

Comparative Analysis of the Performance of Electroencephalogram Parameters for Monitoring the Depth of Sedation During Remimazolam Target-Controlled Infusion

BACKGROUND

The changes in hypnotic indicators in remimazolam sedation remain unclear. We investigated the correlation of the electroencephalogram (EEG) parameters with the effect-site remimazolam concentration and the depth of sedation in patients receiving a target-controlled infusion of remimazolam.

METHODS

This prospective observational study enrolled 35 patients (32 analyzed) who underwent lower extremity varicose vein surgery or lower extremity orthopedic surgery under spinal anesthesia. We administered remimazolam by target-controlled infusion using the pharmacokinetic model introduced by Schüttler et al. The EEG data were continuously recorded, including the bispectral index (BIS), patient state index (PSI), spectral edge frequency (SEF), and raw EEG signals. The relative beta ratio (RBR), defined as log (spectral power [30-47 Hz]/spectral power [11-20 Hz]), was obtained by analyzing raw EEG. The level of sedation corresponding to each effect-site remimazolam concentration was assessed using the Modified Observer's Assessment of Alertness/Sedation (MOAA/S). The prediction probability (Pk) and Spearman's correlation coefficients (R) were calculated between effect-site remimazolam concentration, MOAA/S, and EEG parameters.

RESULTS

BIS and PSI showed significantly higher Pk for effect-site remimazolam concentration (Pk = 0.76 [0.72-0.79], P < .001 for BIS; Pk = 0.76 [0.73-0.79], P < .001 for PSI) compared to RBR (Pk = 0.71 [0.68-0.74], P < .001) and SEF (Pk = 0.58 [0.53-0.63], P = .002). BIS, PSI, and RBR showed significantly higher correlation coefficients for effect-site remimazolam concentration (R = -0.70 [-0.78 to -0.63], P < .001 for BIS; R = -0.72 [-0.79 to -0.66], P < .001 for PSI; R = -0.61 [-0.69 to -0.54], P < .001 for RBR) compared to SEF (R = -0.22 [-0.36 to -0.08], P = .002). BIS and PSI also had significantly higher Pk and correlation coefficients for MOAA/S (Pk = 0.81 [0.79-0.83], P < .001; R = 0.84 [0.81-0.88], P < .001 for BIS) (Pk = 0.80 [0.78-0.83], P < .001; R = 0.82 [0.78-0.87], P < .001 for PSI) compared to RBR (Pk = 0.74 [0.72-0.77], P < .001; R = 0.72 [0.65-0.78], P < .001) and SEF (Pk = 0.55 [0.50-0.59], P = .041; R = 0.13 [-0.01 to 0.27], P = .067).

CONCLUSIONS

BIS, PSI, and RBR showed an acceptable correlation with the effect-site remimazolam concentration and depth of sedation in this study, suggesting that these EEG-derived parameters are potentially reliable hypnotic indicators during remimazolam sedation. BIS and PSI showed superior performance as hypnotic indicators to RBR and SEF in patients receiving target-controlled infusion of remimazolam.

Spatio-temporal electroencephalographic power distribution in experimental pigs receiving propofol

INTRODUCTION

When assessing the spatio-temporal distribution of electroencephalographic (EEG) activity, characteristic patterns have been identified for several anesthetic drugs in humans. A shift in EEG power from the occipital to the prefrontal regions has been widely observed during anesthesia induction. This has been called "anteriorization" and has been correlated with loss of consciousness in humans. The spatio-temporal distribution of EEG spectral power in pigs and its modulation by anesthetics have not been described previously. The aim of the present study was to analyze EEG power across an anterior-posterior axis in pigs receiving increasing doses of propofol to 1) characterize the region of highest EEG power during wakefulness, 2) depict its spatio-temporal modification during propofol infusion, and 3) determine the region demonstrating the most significant modulations across different doses administered.

MATERIALS AND METHODS

Six pigs with a body weight of 33.3 ± 3.6 kg and aged 11.3 ± 0.5 weeks were included in a prospective experimental study. Electroencephalographic activity was collected at the occipital, parietal and prefrontal regions at increasing doses of propofol (starting at 10 mg kg-1 h-1 and increasing it by 10 mg kg-1 h-1 every 15 minutes). The EEG power was assessed using a generalized linear mixed model in which propofol doses and regions were treated as fixed effects, whereas pig was used as a random effect. Pairwise comparisons of marginal linear predictions were used to assess the change in power when the specific propofol dose (or region) was considered.

RESULTS

During both wakefulness and propofol infusion, the highest EEG power was located in the prefrontal region (p<0.001). The EEG power, both total and for each frequency band, mostly followed the same pattern, increasing from awake until propofol 20 mg kg-1 h-1 and then decreasing at propofol 30 mg kg-1 h-1. The region showing the strongest differences in EEG power across propofol doses was the prefrontal.

CONCLUSION

In juvenile pigs receiving increasing doses of propofol, the prefrontal region showed the highest EEG power both during wakefulness and propofol administration and was the area in which the largest frequency-band specific variations were observed across different anesthetic doses. The assessment of the spectral EEG activity at this region could be favorable to distinguish DoA levels in pigs.

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.

Intravenous Ganaxolone: Pharmacokinetics, Pharmacodynamics, Safety, and Tolerability in Healthy Adults

Ganaxolone, a neuroactive steroid anticonvulsant that modulates both synaptic and extrasynaptic γ-aminobutyric acid type A (GABAA ) receptors, is in development for treatment of status epilepticus (SE) and rare epileptic disorders, and has been approved in the United States for treatment of seizures associated with cyclin-dependent kinase-like 5 deficiency disorder in patients ≥2 years old. This phase 1 study in 36 healthy volunteers evaluated the pharmacokinetics, pharmacodynamics, and safety of intravenous ganaxolone administered as a (i) single bolus, (ii) infusion, and (iii) bolus followed by continuous infusion. After a single bolus over 2 minutes (20 mg) or 5 minutes (10 or 30 mg), ganaxolone was detected in plasma with a median Tmax of 5 minutes, whereas a 60-minute infusion (10 or 30 mg) or a bolus (6 mg over 5 minutes) followed by infusion (20 mg/h) for 4 hours achieved a median Tmax of approximately 1 and 3 hours, respectively. Cmax was dose and administration-time dependent, ranging from 73.8 ng/mL (10 mg over 5 minutes) to 1240 ng/mL (30 mg over 5 minutes). Bolus doses above 10 mg of ganaxolone markedly influenced the bispectral index score with a rapid decline; smaller changes occurred on the Modified Observer's Assessment of Alertness/Sedation scale and in quantitative electroencephalogram. Most adverse events were of mild severity, with 2 events of moderate severity; none were reported as serious. No effects on systemic hemodynamics or respiratory functions were reported. Overall, ganaxolone was generally well tolerated at the doses studied and demonstrated pharmacokinetic and pharmacodynamic properties suitable to treat SE.

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 β-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.

Meta-analysis of the effect of entropy-assisted general anesthesia on the quality of postoperative recovery

BACKGROUND

To evaluate the effect of the quality of postoperative anesthetic resuscitation in patients with entropy index monitoring assisted general anesthesia versus standard clinical practice.

METHODS

The randomized controlled trials on the application of entropy index monitoring in general anesthesia were searched in PubMed, Web of Science, Embase, The Cochrane Library, CNKI, Wanfang, VIP, and other databases by computer. The data were collected from inception to January 2022. Two researchers independently screened the retrieved literature according to the inclusion and exclusion criteria and used Cochrane's risk-of-bias assessment criteria to evaluate the quality of the literature. The evaluation indicators included respiratory recovery time, extubation time, consciousness recovery time, emergence agitation, postoperative nausea and vomiting (PONV), and intraoperative awareness. The RevMan 5.4.1 software was used for the meta-analysis of the data.

RESULTS

A total of 860 patients from 10 eligible randomized controlled trials were included in this study. The results showed that compared with the control group, the respiratory recovery time (MD = -3.37, 95% CI: -5.09 to -1.85, P < .0001), extubation time (MD = -4.57, 95% CI: -6.08 to -3.95, P < .00001), and consciousness recovery time (MD = -4.95, 95% CI: -7.21 to -2.70, P < .00001) in the entropy index group were significantly shortened. The incidence of emergence agitation in the entropy index group (RR = 0.23, 95% CI: 0.11-0.47, P < .0001) decreased significantly. The incidence of PONV (RR = 0.46, 95% CI: 0.27-0.79, P = .004) was significantly reduced. However, the incidence of intraoperative awareness (RR = 0.33, 95% CI: 0.04-3.16, P = .34) wasn't significantly different.

CONCLUSION

The application of the entropy index can improve the recovery quality of patients under general anesthesia, not only shortening the postoperative recovery time but also reducing the occurrence of agitation and PONV. It does not affect the incidence of intraoperative awareness.

Unveiling age-independent spectral markers of propofol-induced loss of consciousness by decomposing the electroencephalographic spectrum into its periodic and aperiodic components

Background

Induction of general anesthesia with propofol induces radical changes in cortical network organization, leading to unconsciousness. While perioperative frontal electroencephalography (EEG) has been widely implemented in the past decades, validated and age-independent EEG markers for the timepoint of loss of consciousness (LOC) are lacking. Especially the appearance of spatially coherent frontal alpha oscillations (8-12 Hz) marks the transition to unconsciousness.Here we explored whether decomposing the EEG spectrum into its periodic and aperiodic components unveiled markers of LOC and investigated their age-dependency. We further characterized the LOC-associated alpha oscillations by parametrizing the adjusted power over the aperiodic component, the center frequency, and the bandwidth of the peak in the alpha range.

Methods

In this prospective observational trial, EEG were recorded in a young (18-30 years) and an elderly age-cohort (≥ 70 years) over the transition to propofol-induced unconsciousness. An event marker was set in the EEG recordings at the timepoint of LOC, defined with the suppression of the lid closure reflex. Spectral analysis was conducted with the multitaper method. Aperiodic and periodic components were parametrized with the FOOOF toolbox. Aperiodic parametrization comprised the exponent and the offset. The periodic parametrization consisted in the characterization of the peak in the alpha range with its adjusted power, center frequency and bandwidth. Three time-segments were defined: preLOC (105 - 75 s before LOC), LOC (15 s before to 15 s after LOC), postLOC (190 - 220 s after LOC). Statistical significance was determined with a repeated-measures ANOVA.

Results

Loss of consciousness was associated with an increase in the aperiodic exponent (young: p = 0.004, elderly: p = 0.007) and offset (young: p = 0.020, elderly: p = 0.004) as well as an increase in the adjusted power (young: p < 0.001, elderly p = 0.011) and center frequency (young: p = 0.008, elderly: p < 0.001) of the periodic alpha peak. We saw age-related differences in the aperiodic exponent and offset after LOC as well as in the power and bandwidth of the periodic alpha peak during LOC.

Conclusion

Decomposing the EEG spectrum over induction of anesthesia into its periodic and aperiodic components unveiled novel age-independent EEG markers of propofol-induced LOC: the aperiodic exponent and offset as well as the center frequency and adjusted power of the power peak in the alpha range.

Fractal Properties of Heart Rate Dynamics: A New Biomarker for Anesthesia-Biphasic Changes in General Anesthesia and Decrease in Spinal Anesthesia

Processed electroencephalogram (EEG) has been considered a useful tool for measuring the depth of anesthesia (DOA). However, because of its inability to detect the activities of the brain stem and spinal cord responsible for most of the vital signs, a new biomarker for measuring the multidimensional activities of the central nervous system under anesthesia is required. Detrended fluctuation analysis (DFA) is a new technique for detecting the scaling properties of nonstationary heart rate (HR) behavior. This study investigated the changes in fractal properties of heart rate variability (HRV), a nonlinear analysis, under intravenous propofol, inhalational desflurane, and spinal anesthesia. We compared the DFA method with traditional spectral analysis to evaluate its potential as an alternative biomarker under different levels of anesthesia. Eighty patients receiving elective procedures were randomly allocated different anesthesia. HRV was measured with spectral analysis and DFA short-term (4-11 beats) scaling exponent (DFAα1). An increase in DFAα1 followed by a decrease at higher concentrations during propofol or desflurane anesthesia is observed. Spinal anesthesia decreased the DFAα1 and low-/high-frequency ratio (LF/HF ratio). DFAα1 of HRV is a sensitive and specific method for distinguishing changes from baseline to anesthesia state. The DFAα1 provides a potential real-time biomarker to measure HRV as one of the multiple dimensions of the DOA.

Electrophysiological correlates and predictors of the antidepressant response to repeated ketamine infusions in treatment-resistant depression

BACKGROUND

Sub-anesthetic ketamine doses rapidly reduce depressive symptoms, although additional investigations of the underlying neural mechanisms and the prediction of response outcomes are needed. Electroencephalographic (EEG)-derived measures have shown promise in predicting antidepressant response to a variety of treatments, and are sensitive to ketamine administration. This study examined their utility in characterizing changes in depressive symptoms following single and repeated ketamine infusions.

METHODS

Recordings were obtained from patients with treatment-resistant major depressive disorder (MDD) (N = 24) enrolled in a multi-phase clinical ketamine trial. During the randomized, double-blind, crossover phase (Phase 1), patients received intravenous ketamine (0.5 mg/kg) and midazolam (30 μg/kg), at least 1 week apart. For each medication, three resting, eyes-closed recordings were obtained per session (pre-infusion, immediately post-infusion, 2 h post-infusion), and changes in power (delta, theta1/2/total, alpha1/2/total, beta, gamma), alpha asymmetry, theta cordance, and theta source-localized anterior cingulate cortex activity were quantified. The relationships between ketamine-induced changes with early (Phase 1) and sustained (Phases 2,3: open-label repeated infusions) decreases in depressive symptoms (Montgomery-Åsberg Depression Rating Score, MADRS) and suicidal ideation (MADRS item 10) were examined.

RESULTS

Both medications decreased alpha and theta immediately post-infusion, however, only midazolam increased delta (post-infusion), and only ketamine increased gamma (immediately post- and 2 h post-infusion). Regional- and frequency-specific ketamine-induced EEG changes were related to and predictive of decreases in depressive symptoms (theta, gamma) and suicidal ideation (alpha). Early and sustained treatment responders differed at baseline in surface-level and source-localized theta.

CONCLUSIONS

Ketamine exerts frequency-specific changes on EEG-derived measures, which are related to depressive symptom decreases in treatment-resistant MDD and provide information regarding early and sustained individual response to ketamine.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov: Action of Ketamine in Treatment-Resistant Depression, NCT01945047.

Developing a Real-Time Electroencephalogram-Guided Anesthesia-Management Curriculum for Educating Residents: A Single-Center Randomized Controlled Trial

BACKGROUND

Different anesthetic drugs and patient factors yield unique electroencephalogram (EEG) patterns. Yet, it is unclear how best to teach trainees to interpret EEG time series data and the corresponding spectral information for intraoperative anesthetic titration, or what effect this might have on outcomes.

METHODS

We developed an electronic learning curriculum (ELC) that covered EEG spectrogram interpretation and its use in anesthetic titration. Anesthesiology residents at a single academic center were randomized to receive this ELC and given spectrogram monitors for intraoperative use versus standard residency curriculum alone without intraoperative spectrogram monitors. We hypothesized that this intervention would result in lower inhaled anesthetic administration (measured by age-adjusted total minimal alveolar concentration [MAC] fraction and age-adjusted minimal alveolar concentration [aaMAC]) to patients ≥60 old during the postintervention period (the primary study outcome). To study this effect and to determine whether the 2 groups were administering similar anesthetic doses pre- versus postintervention, we compared aaMAC between control versus intervention group residents both before and after the intervention. To measure efficacy in the postintervention period, we included only those cases in the intervention group when the monitor was actually used. Multivariable linear mixed-effects modeling was performed for aaMAC fraction and hospital length of stay (LOS; a non-prespecified secondary outcome), with a random effect for individual resident. A multivariable linear mixed-effects model was also used in a sensitivity analysis to determine if there was a group (intervention versus control group) by time period (post- versus preintervention) interaction for aaMAC. Resident EEG knowledge difference (a prespecified secondary outcome) was compared with a 2-sided 2-group paired t test.

RESULTS

Postintervention, there was no significant aaMAC difference in patients cared for by the ELC group (n = 159 patients) versus control group (N = 325 patients; aaMAC difference = -0.03; 95% confidence interval [CI], -0.09 to 0.03; P =.32). In a multivariable mixed model, the interaction of time period (post- versus preintervention) and group (intervention versus control) led to a nonsignificant reduction of -0.05 aaMAC (95% CI, -0.11 to 0.01; P = .102). ELC group residents (N = 19) showed a greater increase in EEG knowledge test scores than control residents (N = 20) from before to after the ELC intervention (6-point increase; 95% CI, 3.50-8.88; P < .001). Patients cared for by the ELC group versus control group had a reduced hospital LOS (median, 2.48 vs 3.86 days, respectively; P = .024).

CONCLUSIONS

Although there was no effect on mean aaMAC, these results demonstrate that this EEG-ELC intervention increased resident knowledge and raise the possibility that it may reduce hospital LOS.

Depth of anesthesia prediction via EEG signals using convolutional neural network and ensemble empirical mode decomposition

According to a recently conducted survey on surgical complication mortality rate, 47% of such cases are due to anesthetics overdose. This indicates that there is an urgent need to moderate the level of anesthesia. Recently deep learning (DL) methods have played a major role in estimating the depth of Anesthesia (DOA) of patients and has played an essential role in control anesthesia overdose. In this paper, Electroencephalography (EEG) signals have been used for the prediction of DOA. EEG signals are very complex signals which may require months of training and advanced signal processing techniques. It is a point of debate whether DL methods are an improvement over the already existing traditional EEG signal processing approaches. One of the DL algorithms is Convolutional neural network (CNN) which is very popular algorithm for object recognition and is widely growing its applications in processing hierarchy in the human visual system. In this paper, various decomposition methods have been used for extracting the features EEG signal. After acquiring the necessary signals values in image format, several CNN models have been deployed for classification of DOA depending upon their Bispectral Index (BIS) and the signal quality index (SQI). The EEG signals were converted into the frequency domain using and Empirical Mode Decomposition (EMD), and Ensemble Empirical Mode Decomposition (EEMD). However, because of the inter mode mixing observed in EMD method; EEMD have been utilized for this study. The developed CNN models were used to predict the DOA based on the EEG spectrum images without the use of handcrafted features which provides intuitive mapping with high efficiency and reliability. The best trained model gives an accuracy of 83.2%. Hence, this provides further scope and research which can be carried out in the domain of visual mapping of DOA using EEG signals and DL methods.

Brain activity complexity has a nonlinear relation to the level of propofol sedation

BACKGROUND

Brain activity complexity is a promising correlate of states of consciousness. Previous studies have shown higher complexity for awake compared with deep anaesthesia states. However, little attention has been paid to complexity in intermediate states of sedation.

METHODS

We analysed the Lempel-Ziv complexity of EEG signals from subjects undergoing moderate propofol sedation, from an open access database, and related it to behavioural performance as a continuous marker of the level of sedation and to plasma propofol concentrations. We explored its relation to spectral properties, to propofol susceptibility, and its topographical distribution.

RESULTS

Subjects who retained behavioural performance despite propofol sedation showed increased brain activity complexity compared with baseline (M=13.9%, 95% confidence interval=7.5-20.3). This was not the case for subjects who lost behavioural performance. The increase was most prominent in frontal electrodes, and correlated with behavioural performance and propofol susceptibility. This effect was positively correlated with high-frequency activity. However, abolishing specific frequency ranges (e.g. alpha or gamma) did not reduce the propofol-induced increase in Lempel-Ziv complexity.

CONCLUSIONS

Brain activity complexity can increase in response to propofol, particularly during low-dose sedation. Propofol-mediated Lempel-Ziv complexity increase was independent of frequency-specific spectral power manipulations, and most prominent in frontal areas. Taken together, these results advance our understanding of brain activity complexity and anaesthetics. They do not support models of consciousness that propose a direct relation between brain activity complexity and states of consciousness.

Etomidate and its Analogs: A Review of Pharmacokinetics and Pharmacodynamics

Etomidate is a hypnotic agent that is used for the induction of anesthesia. It produces its effect by acting as a positive allosteric modulator on the γ-aminobutyric acid type A receptor and thus enhancing the effect of the inhibitory neurotransmitter γ-aminobutyric acid. Etomidate stands out among other anesthetic agents by having a remarkably stable cardiorespiratory profile, producing no cardiovascular or respiratory depression. However, etomidate suppresses the adrenocortical axis by the inhibition of the enzyme 11β-hydroxylase. This makes the drug unsuitable for administration by a prolonged infusion. It also makes the drug unsuitable for administration to critically ill patients. Etomidate has relatively large volumes of distributions and is rapidly metabolized by hepatic esterases into an inactive carboxylic acid through hydrolyzation. Because of the decrease in popularity of etomidate, few modern extensive pharmacokinetic or pharmacodynamic studies exist. Over the last decade, several analogs of etomidate have been developed, with the aim of retaining its stable cardiorespiratory profile, whilst eliminating its suppressive effect on the adrenocortical axis. One of these molecules, ABP-700, was studied in extensive phase I clinical trials. These found that ABP-700 is characterized by small volumes of distribution and rapid clearance. ABP-700 is metabolized similarly to etomidate, by hydrolyzation into an inactive carboxylic acid. Furthermore, ABP-700 showed a rapid onset and offset of clinical effect. One side effect observed with both etomidate and ABP-700 is the occurrence of involuntary muscle movements. The origin of these movements is unclear and warrants further research.

Electroencephalographic dynamics of etomidate-induced loss of consciousness

BACKGROUND

Highly structured electroencephalography (EEG) oscillations can occur in adults during etomidate-induced general anesthesia, but the link between these two phenomena is poorly understood. Therefore, in the present study, we investigated the electroencephalogram dynamics of etomidate-induced loss of consciousness (LOC) in order to understand the neurological mechanism of etomidate-induced LOC.

METHODS

This study is a prospective observational study. Etomidate-induced anesthesia was performed on eligible patients undergoing elective surgery. We analyzed EEG data from 20 patients who received etomidate for the induction of general anesthesia. We used power spectra and coherence methods to process and analyze the EEG data. Our study was based on 4-channel EEG recordings.

RESULTS

Compared with the baseline (awake period), etomidate induced an increase in power in delta, theta, alpha and beta waves during LOC. Compared with the awake period, the delta-wave (1-4 Hz), alpha-wave(8-13 Hz), and theta-wave(4-8 Hz) coherence increased significantly during LOC, while the slow-wave (< 1 Hz) coherence decreased. However, the delta wave (1.0-4.0 Hz) during etomidate-induced LOC was more coherent than during the awake period (1.86-3.17 Hz, two-group test for coherence, p < 0.001).

CONCLUSIONS

The neural circuit mechanism of etomidate-induced LOC is closely related to the induction of oscillation in delta, theta, alpha and beta waves and the enhancement of delta-wave coherence.

TRIAL REGISTRATION

ChiCTR1800017110.

Effects of noxious stimulation on the electroencephalogram during general anaesthesia: a narrative review and approach to analgesic titration

Electroencephalographic (EEG) activity is used to monitor the neurophysiology of the brain, which is a target organ of general anaesthesia. Besides its use in evaluating hypnotic states, neurophysiologic reactions to noxious stimulation can also be observed in the EEG. Recognising and understanding these responses could help optimise intraoperative analgesic management. This review describes three types of changes in the EEG induced by noxious stimulation when the patient is under general anaesthesia: (1) beta arousal, (2) (paradoxical) delta arousal, and (3) alpha dropout. Beta arousal is an increase in EEG power in the beta-frequency band (12-25 Hz) in response to noxious stimulation, especially at lower doses of anaesthesia drugs in the absence of opioids. It is usually indicative of a cortical depolarisation and increased cortical activity. At higher concentrations of anaesthetic drug, and with insufficient opioids, delta arousal (increased power in the delta band [0.5-4 Hz]) and alpha dropout (decreased alpha power [8-12 Hz]) are associated with noxious stimuli. The mechanisms of delta arousal are not well understood, but the midbrain reticular formation seems to play a role. Alpha dropout may indicate a return of thalamocortical communication, from an idling mode to an operational mode. Each of these EEG changes reflect an incomplete modulation of pain signals and can be mitigated by administration of opioid or the use of regional anaesthesia techniques. Future studies should evaluate whether titrating analgesic drugs in response to these EEG signals reduces postoperative pain and influences other postoperative outcomes, including the potential development of chronic pain.

Changes in electroencephalographic power and bicoherence spectra according to depth of dexmedetomidine sedation in patients undergoing spinal anesthesia

Background: Assessment the depth of dexmedetomidine sedation using electroencephalographic (EEG) features can improve the quality of procedural sedation. Previous volunteer studies of dexmedetomidine-induced EEG changes need to be validated, and changes in bicoherence spectra during dexmedetomidine sedation has not been revealed yet. We aimed to investigate the dexmedetomidine-induced EEG change using power spectral and bicoherence analyses in the clinical setting. Patients and Methods: Thirty-six patients undergoing orthopedic surgery under spinal anesthesia were enrolled in this study. Dexmedetomidine sedation was conducted by the stepwise increase in target effect site concentration (Ce) while assessing sedation levels. Bispectral index (BIS) and frontal electroencephalography were recorded continuously, and the performance of BIS and changes in power and bicoherence spectra were analyzed with the data from the F3 electrode. Results: The prediction probability values for detecting different sedation levels were 0.847, 0.841, and 0.844 in BIS, 95% spectral edge frequency, and dexmedetomidine Ce, respectively. As the depth of sedation increased, δ power increased, but high β and γ power decreased significantly (P <0.001). α and spindle power increased significantly under light and moderate sedation (P <0.001 in light vs baseline and deep sedation; P = 0.002 and P <0.001 in moderate sedation vs baseline and deep sedation, respectively). The bicoherence peaks of the δ and α-spindle regions along the diagonal line of the bicoherence matrix emerged during moderate and deep sedation. Peak bicoherence in the δ area showed sedation-dependent increases (29.93%±7.38%, 36.72%±9.70%, 44.88%±12.90%; light, moderate, and deep sedation; P = 0.008 and P <0.001 in light sedation vs moderate and deep sedation, respectively; P = 0.007 in moderate sedation vs deep sedation), whereas peak bicoherence in the α-spindle area did not change (22.92%±4.90%, 24.72%±4.96%, and 26.96%±8.42%, respectively; P=0.053). Conclusions: The increase of δ power and the decrease of high-frequency power were associated with the gradual deepening of dexmedetomidine sedation. The δ bicoherence peak increased with increasing sedation level and can serve as an indicator reflecting dexmedetomidine sedation levels.

Changes in measures of consciousness during anaesthesia of one hemisphere (Wada test)

BACKGROUND

In the Wada test, one hemisphere is selectively anaesthetised by unilateral intracarotid injection of a fast-acting anaesthetic agent. This gives a unique opportunity to observe the functions and physiological activity of one hemisphere while anaesthetising the other, allowing direct comparisons between brain states and hemispheres that are not possible in any other setting.

AIM

To test whether potential measures of consciousness would be affected by selective anaesthesia of one hemisphere, and reliably distinguish the states of the anesthetised and non-anesthetised hemispheres.

METHODS

We analysed EEG data from 7 patients undergoing Wada-tests in preparation for neurosurgery and computed several measures reported to correlate with the state of consciousness: power spectral density, functional connectivity, and measures of signal diversity. These measures were compared between conditions (normal rest vs. unilateral anaesthesia) and hemispheres (injected vs. non-injected), and used with a support vector machine to classify the state and site of injection objectively from individual patient's recordings.

RESULTS

Although brain function, assessed behaviourally, appeared to be substantially altered only on the injected side, we found large bilateral changes in power spectral density for all frequency bands tested, and functional connectivity changed significantly both between and within both hemispheres. Surprisingly, we found no statistically significant differences in the measures of signal diversity between hemispheres or states, for the group of 7 patients, although 4 of the individual patients showed a significant decrease in signal diversity on the injected side. Nevertheless, including signal diversity measures improved the classification results, indicating that these measures carry at least some non-redundant information about the condition and injection site. We propose that several of these results may be explained by conduction of activity, via the corpus callosum, from the injected to the contralateral hemisphere and vice versa, without substantially affecting the function of the receiving hemisphere, thus reflecting what we call "cross-state unreceptiveness".

The influence of induction speed on the frontal (processed) EEG

The intravenous injection of the anaesthetic propofol is clinical routine to induce loss of responsiveness (LOR). However, there are only a few studies investigating the influence of the injection rate on the frontal electroencephalogram (EEG) during LOR. Therefore, we focused on changes of the frontal EEG especially during this period. We included 18 patients which were randomly assigned to a slow or fast induction group and recorded the frontal EEG. Based on this data, we calculated the power spectral density, the band powers and band ratios. To analyse the behaviour of processed EEG parameters we calculated the beta ratio, the spectral entropy, and the spectral edge frequency. Due to the prolonged induction period in the slow injection group we were able to distinguish loss of responsiveness to verbal command (LOvR) from loss of responsiveness to painful stimulus (LOpR) whereas in the fast induction group we could not. At LOpR, we observed a higher relative alpha and beta power in the slow induction group while the relative power in the delta range was lower than in the fast induction group. When concentrating on the slow induction group the increase in relative alpha power pre-LOpR and even before LOvR indicated that frontal EEG patterns, which have been suggested as an indicator of unconsciousness, can develop before LOR. Further, LOvR was best reflected by an increase of the alpha to delta ratio, and LOpR was indicated by a decrease of the beta to alpha ratio. These findings highlight the different spectral properties of the EEG at various levels of responsiveness and underline the influence of the propofol injection rate on the frontal EEG during induction of general anesthesia.

State-Dependent Cortical Unit Activity Reflects Dynamic Brain State Transitions in Anesthesia

Understanding the effects of anesthesia on cortical neuronal spiking and information transfer could help illuminate the neuronal basis of the conscious state. Recent investigations suggest that the brain state identified by local field potential spectrum is not stationary but changes spontaneously at a fixed level of anesthetic concentration. How cortical unit activity changes with dynamically transitioning brain states under anesthesia is unclear. Extracellular unit activity was measured with 64-channel silicon microelectrode arrays in cortical layers 5/6 of the primary visual cortex of chronically instrumented, freely moving male rats (n = 7) during stepwise reduction of the anesthetic desflurane (6%, 4%, 2%, and 0%). Unsupervised machine learning applied to multiunit spike patterns revealed five distinct brain states. A novel desynchronized brain state with increased spike rate variability, sample entropy, and EMG activity occurred in 6% desflurane with 40.0% frequency. The other four brain states reflected graded levels of anesthesia. As anesthesia deepened the spike rate of neurons decreased regardless of their spike rate profile at baseline conscious state. Actively firing neurons with wide-spiking pattern showed increased bursting activity along with increased spike timing variability, unit-to-population correlation, and unit-to-unit transfer entropy, despite the overall decrease in transfer entropy. The narrow-spiking neurons showed similar changes but to a lesser degree. These results suggest that (1) anesthetic effect on spike rate is distinct from sleep, (2) synchronously fragmented spiking pattern is a signature of anesthetic-induced unconsciousness, and (3) the paradoxical, desynchronized brain state in deep anesthesia contends the generally presumed monotonic, dose-dependent anesthetic effect on the brain.SIGNIFICANCE STATEMENT Recent studies suggest that spontaneous changes in brain state occur under anesthesia. However, the spiking behavior of cortical neurons associated with such state changes has not been investigated. We found that local brain states defined by multiunit activity had a nonunitary relationship with the current anesthetic level. A paradoxical brain state displaying asynchronous firing pattern and high EMG activity was found unexpectedly in deep anesthesia. In contrast, the synchronous fragmentation of neuronal spiking appeared to be a robust signature of the state of anesthesia. The findings challenge the assumption of monotonic, anesthetic dose-dependent behavior of cortical neuron populations. They enhance the interpretation of neuroscientific data obtained under anesthesia and the understanding of the neuronal basis of anesthetic-induced state of unconsciousness.

Pharmacokinetics and Pharmacodynamics of Remimazolam (CNS 7056) after Continuous Infusion in Healthy Male Volunteers: Part II. Pharmacodynamics of Electroencephalogram Effects

BACKGROUND

Remimazolam (CNS 7056) is a new ultra-short acting benzodiazepine for IV sedation. This study aimed to investigate the electroencephalogram (EEG) pharmacodynamics of remimazolam infusion.

METHODS

Twenty healthy male volunteers received remimazolam as continuous IV infusion of 5 mg/min for 5 min, 3 mg/min for the next 15 min, and 1 mg/min for further 15 min. Continuous EEG monitoring was performed by a neurophysiologic system with electrodes placed at F3, F4, C3, C4, O1, O2, Cz, and Fp1 (10/20 system) and using the Narcotrend Index. Sedation was assessed clinically by using the Modified Observer's Assessment of Alertness and Sedation scale. Pharmacodynamic models were developed for selected EEG variables and Narcotrend Index.

RESULTS

EEG changes during remimazolam infusion were characterized by an initial increase in beta frequency band and a late increase in delta frequency band. The EEG beta ratio showed a prediction probability of Modified Observer's Assessment of Alertness and Sedation score of 0.79, and could be modeled successfully using a standard sigmoid Emax model. Narcotrend Index showed a prediction probability of Modified Observer's Assessment of Alertness and Sedation score of 0.74. The time course of Narcotrend Index was described by an extended sigmoid Emax model with two sigmoid terms and different plasma-effect equilibration times.

CONCLUSIONS

Beta ratio was identified as a suitable EEG variable for monitoring remimazolam sedation. Narcotrend Index appeared less suitable than the beta ratio for monitoring the sedative effect if remimazolam is administered alone.

Phospholipase C-related inactive protein type-1 deficiency affects anesthetic electroencephalogram activity induced by propofol and etomidate in mice

PURPOSE

The general anesthetics propofol and etomidate mainly exert their anesthetic actions via GABA A receptor (GABA_A-R). The GABA_A-R activity is influenced by phospholipase C-related inactive protein type-1 (PRIP-1), which is related to trafficking and subcellular localization of GABA_A-R. PRIP-1 deficiency attenuates the behavioral reactions to propofol but not etomidate. However, the effect of these anesthetics and of PRIP-1 deficiency on brain activity of CNS are still unclear. In this study, we examined the effects of propofol and etomidate on the electroencephalogram (EEG).

METHODS

The cortical EEG activity was recorded in wild-type (WT) and PRIP-1 knockout (PRIP-1 KO) mice. All recorded EEG data were offline analyzed, and the power spectral density and 95% spectral edge frequency of EEG signals were compared between genotypes before and after injections of anesthetics.

RESULTS

PRIP-1 deficiency induced increases in EEG absolute powers, but did not markedly change the relative spectral powers during waking and sleep states in the absence of anesthesia. Propofol administration induced increases in low-frequency relative EEG activity and decreases in SEF95 values in WT but not in PRIP-1 KO mice. Following etomidate injection, low-frequency EEG power was increased in both genotype groups. At high frequency, the relative power in PRIP-1 KO mice was smaller than that in WT mice.

CONCLUSIONS

The lack of PRIP-1 disrupted the EEG power distribution, but did not affect the depth of anesthesia after etomidate administration. Our analyses suggest that PRIP-1 is differentially involved in anesthetic EEG activity with the regulation of GABA_A-R activity.

Comparison of local spectral modulation, and temporal correlation, of simultaneously recorded EEG/fMRI signals during ketamine and midazolam sedation

RATIONALE AND OBJECTIVES

The identification of biomarkers of drug action can be supported by non-invasive brain imaging techniques, such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), with simultaneous collection plausibly overcoming the limitations of either modality alone. Despite this, few studies have assessed the feasibility and utility of recording simultaneous EEG/fMRI in a drug study.

METHODS

We used simultaneous EEG/fMRI to assess the modulation of neural activity by ketamine and midazolam, in a placebo-controlled, single-blind, three-way cross-over design. Specifically, we analysed the sensitivity and direction of the spectral effects of each modality and the temporal correlations between the modulations of power of the common EEG bands and the blood-oxygen-level-dependent (BOLD) signal.

RESULTS AND CONCLUSIONS

Demonstrating feasibility, local spectral effects were similar to those found in previous non-simultaneous EEG and fMRI studies. Ketamine administration resulted in a widespread reduction of BOLD fractional amplitude of low frequency fluctuations (fALFF) and a diverse pattern of effects in the different EEG bands. Midazolam increased fALFF in occipital, parietal, and temporal areas, and frontal delta and beta EEG power. While EEG spectra were more sensitive to pharmacological modulations than the fALFF bands, there was no clear spatial relationship between the two modalities. Additionally, ketamine modulated the temporal correlation strengths between the theta EEG band and the BOLD signal, whereas midazolam altered temporal correlations with the alpha and beta bands. Taken together, these results demonstrate the utility of simultaneous recording: each modality provides unique insights, and combinatorial analyses elicit more information than separate recordings.

A Computational Study of a Spatiotemporal Mean Field Model Capturing the Emergence of Alpha and Gamma Rhythmic Activity in the Neocortex

In this paper, we analyze the spatiotemporal mean field model developed by Liley et al. in order to advance our understanding of the wide effects of pharmacological agents and anesthetics. Specifically, we use the spatiotemporal mean field model for capturing the electrical activity in the neocortex to computationally study the emergence of α - and γ -band rhythmic activity in the brain. We show that α oscillations in the solutions of the model appear globally across the neocortex, whereas γ oscillations can emerge locally as a result of a bifurcation in the dynamics of the model. We solve the dynamic equations of the model using a finite element solver package and show that our results verify the predictions made by bifurcation analysis.

Identifying causal relationships between EEG activity and intracranial pressure changes in neurocritical care patients

OBJECTIVE

To explore and assess the relationship between electroencephalography (EEG) activity and intracranial pressure (ICP) in patients suffering from traumatic brain injury (TBI) and subarachnoid hemorrhage (SAH) during their stay in an intensive care unit.

APPROACH

We performed an observational prospective cohort study of adult patients suffering from TBI or SAH. Continuous EEG-ECG was performed during ICP monitoring. In every patient, variables derived from the EEG were calculated and the Granger causality (GC) methodology was employed to assess whether, and in which direction, there is any relationship between EEG and ICP.

MAIN RESULTS

One-thousand fifty-five hours of continuous multimodal monitoring were analyzed in 21 patients using the GC test. During 37.88% of the analyzed time, significant GC statistic was found in the direction from the EEG activity to the ICP, with typical lags of 25-50 s between them. When recordings were adjusted by sedation-perfusion and/or bolus-and handling, these percentages hardly changed.

SIGNIFICANCE

Long-lasting, continuous and simultaneous EEG and ICP recordings from TBI and SAH patients provide highly rich and useful information, which has allowed for uncovering a strong relationship between both signals. The use of this relationship could lead to developing a medical device to measure ICP in a non-invasive way.

Anesthesia modifies subthreshold critical slowing down in a stochastic Hodgkin-Huxley-like model with inhibitory synaptic input

The dynamics of a stochastic type-I Hodgkin-Huxley-like point neuron model exposed to inhibitory synaptic noise are investigated as a function of distance from spiking threshold and the inhibitory influence of the general anesthetic agent propofol. The model is biologically motivated and includes the effects of intrinsic ion-channel noise via a stochastic differential equation description as well as inhibitory synaptic noise modeled as multiple Poisson-distributed impulse trains with saturating response functions. The effect of propofol on these synapses is incorporated through this drug's principal influence on fast inhibitory neurotransmission mediated by γ-aminobutyric acid (GABA) type-A receptors via reduction of the synaptic response decay rate. As the neuron model approaches spiking threshold from below, we track membrane voltage fluctuation statistics of numerically simulated stochastic trajectories. We find that for a given distance from spiking threshold, increasing the magnitude of anesthetic-induced inhibition is associated with augmented signatures of critical slowing: fluctuation amplitudes and correlation times grow as spectral power is increasingly focused at 0 Hz. Furthermore, as a function of distance from threshold, anesthesia significantly modifies the power-law exponents for variance and correlation time divergences observable in stochastic trajectories. Compared to the inverse square root power-law scaling of these quantities anticipated for the saddle-node bifurcation of type-I neurons in the absence of anesthesia, increasing anesthetic-induced inhibition results in an observable exponent <-0.5 for variance and >-0.5 for correlation time divergences. However, these behaviors eventually break down as distance from threshold goes to zero with both the variance and correlation time converging to common values independent of anesthesia. Compared to the case of no synaptic input, linearization of an approximating multivariate Ornstein-Uhlenbeck model reveals these effects to be the consequence of an additional slow eigenvalue associated with synaptic activity that competes with those of the underlying point neuron in a manner that depends on distance from spiking threshold.

Effect site concentration of propofol at induction and recovery of anaesthesia - A correlative dose-response study

BACKGROUND AND AIMS

Sound knowledge about effect site concentration (Ce) of propofol aids in smooth induction, maintenance and early recovery. We studied the correlation between Ce of propofol at loss of response to verbal command and recovery concentration using target-controlled infusion (TCI) in Indian patients who underwent spine surgeries.

METHODS

Ninety patients undergoing spine surgeries were included. Total intravenous anaesthesia (TIVA) technique with TCI for propofol using modified Marsh model was used. Entropy and neuromuscular transmission were used. Ce at induction and recovery and the corresponding state entropy (SE) values were noted.

RESULTS

The mean propofol Ce and SE at induction were 2.34 ± 0.24 μg/ml and 52 ± 8, respectively. The mean propofol Ce and SE at recovery were 1.02 ± 0.22 μg/ml and 86.80 ± 2.86, respectively. The Ce at recovery was approximately 50% of the induction value. The correlation coefficient 'r' between Ce at induction and recovery was 0.56. The mean infusion dose of propofol during the maintenance period was 81 ± 14.33 μg/kg/min. The average induction dose of propofol was 1.17 ± 0.2 mg/kg.

CONCLUSION

There is a positive correlation between Ce at induction and recovery. Ce for recovery may have to be set at a lower level during TCI-TIVA and appropriately infusion should be stopped for early recovery. The induction and maintenance doses of propofol are lower than the recommended doses. Data emphasise the need for pharmacokinetic model based on our population characteristics.

Network Properties in Transitions of Consciousness during Propofol-induced Sedation

Reliable electroencephalography (EEG) signatures of transitions between consciousness and unconsciousness under anaesthesia have not yet been identified. Herein we examined network changes using graph theoretical analysis of high-density EEG during patient-titrated propofol-induced sedation. Responsiveness was used as a surrogate for consciousness. We divided the data into five states: baseline, transition into unresponsiveness, unresponsiveness, transition into responsiveness, and recovery. Power spectral analysis showed that delta power increased from responsiveness to unresponsiveness. In unresponsiveness, delta waves propagated from frontal to parietal regions as a traveling wave. Local increases in delta connectivity were evident in parietal but not frontal regions. Graph theory analysis showed that increased local efficiency could differentiate the levels of responsiveness. Interestingly, during transitions of responsive states, increased beta connectivity was noted relative to consciousness and unconsciousness, again with increased local efficiency. Abrupt network changes are evident in the transitions in responsiveness, with increased beta band power/connectivity marking transitions between responsive states, while the delta power/connectivity changes were consistent with the fading of consciousness using its surrogate responsiveness. These results provide novel insights into the neural correlates of these behavioural transitions and EEG signatures for monitoring the levels of consciousness under sedation.

Effect of general anesthesia on neonatal aEEG-A cohort study of patients with non-cardiac congenital anomalies

Introduction

The aim of the current study was to determine the effect of general anesthesia on neonatal brain activity using amplitude-integrated EEG (aEEG).

Methods

A prospective cohort study of neonates (January 2013-December 2015), who underwent major neonatal surgery for non-cardiac congenital anomalies. Anesthesia was administered at the discretion of the anesthetist. aEEG monitoring was started six hours preoperatively until 24 hours after surgery. Analysis of classes of aEEG background patterns, ranging from continuous normal voltage to flat trace in six classes, and quantitative EEG-measures, using spontaneous activity transients (SATs) and interSATintervals (ISI), was performed.

Results

In total, 111 neonates were included (36 preterm/75 full-term), age at time of surgery was (median (range) 2 (0–32) days. During anesthesia depression of brain activity was seen, with background patterns ranging from flat trace to discontinuous normal voltage. In most patients brain activity was two background pattern classes lower during anesthesia. After cessation of anesthesia, recovery to preoperative brain activity occurred within 24 hours in 86% of the preterm and 96% of the term infants. Gestational age and the dose of sevoflurane were significantly associated with SAT-rate (F(2,68) = 9.288, p < 0.001) and ISI- durations during surgery (F(3,71) = 12.96, p < 0.001). Background pattern and quantitative EEG-values were not associated with brain lesions (χ2(4) = 2.086, ns).

Conclusion

aEEG shows a variable reduction of brain activity in response to anesthesia in neonates with noncardiac congenital anomalies, with fast recovery after cessation of anesthesia. This reduction is related to gestational age and the dose of sevoflurane. The aEEG offers the opportunity to monitor the depth of anesthesia in the neonate.

Changes in Alpha Frequency and Power of the Electroencephalogram during Volatile-Based General Anesthesia

Oscillations in the electroencephalogram (EEG) at the alpha frequency (8–12 Hz) are thought to be ubiquitous during surgical anesthesia, but the details of how this oscillation responds to ongoing changes in volatile anesthetic concentration have not been well characterized. It is not known how often alpha oscillations are absent in the clinical context, how sensitively alpha frequency and power respond to changes in anesthetic concentration, and what effect increased age has on alpha frequency. Bipolar EEG was recorded frontally from 305 patients undergoing surgery with sevoflurane or desflurane providing general anesthesia. A new method of detecting the presence of alpha oscillations based on the stability of the rate of change of the peak frequency in the alpha range was developed. Linear concentration-response curves were fitted to assess the sensitivity of alpha power and frequency measures to changing levels of anesthesia. Alpha oscillations were seen to be inexplicably absent in around 4% of patients. Maximal alpha power increased with increasing volatile anesthetic concentrations in half of the patients, and decreased in the remaining patients. Alpha frequency decreased with increasing anesthetic concentrations in near to 90% of patients. Increasing age was associated with decreased sensitivity to volatile anesthesia concentrations, and with decreased alpha frequency, which sometimes transitioned into the theta range (5–7 Hz). While peak alpha frequency shows a consistent slowing to increasing volatile concentrations, the peak power of the oscillation does not, suggesting that frequency might be more informative of depth of anesthesia than traditional power based measures during volatile-based anesthesia. The alpha oscillation becomes slower with increasing age, even when the decreased anesthetic needs of older patients were taken into account.

A Mechanistic Neural Field Theory of How Anesthesia Suppresses Consciousness: Synaptic Drive Dynamics, Bifurcations, Attractors, and Partial State Equipartitioning

With the advances in biochemistry, molecular biology, and neurochemistry there has been impressive progress in understanding the molecular properties of anesthetic agents. However, there has been little focus on how the molecular properties of anesthetic agents lead to the observed macroscopic property that defines the anesthetic state, that is, lack of responsiveness to noxious stimuli. In this paper, we use dynamical system theory to develop a mechanistic mean field model for neural activity to study the abrupt transition from consciousness to unconsciousness as the concentration of the anesthetic agent increases. The proposed synaptic drive firing-rate model predicts the conscious-unconscious transition as the applied anesthetic concentration increases, where excitatory neural activity is characterized by a Poincaré-Andronov-Hopf bifurcation with the awake state transitioning to a stable limit cycle and then subsequently to an asymptotically stable unconscious equilibrium state. Furthermore, we address the more general question of synchronization and partial state equipartitioning of neural activity without mean field assumptions. This is done by focusing on a postulated subset of inhibitory neurons that are not themselves connected to other inhibitory neurons. Finally, several numerical experiments are presented to illustrate the different aspects of the proposed theory.

Noise-induced precursors of state transitions in the stochastic Wilson-cowan model

The Wilson-Cowan neural field equations describe the dynamical behavior of a 1-D continuum of excitatory and inhibitory cortical neural aggregates, using a pair of coupled integro-differential equations. Here we use bifurcation theory and small-noise linear stochastics to study the range of a phase transitions-sudden qualitative changes in the state of a dynamical system emerging from a bifurcation-accessible to the Wilson-Cowan network. Specifically, we examine saddle-node, Hopf, Turing, and Turing-Hopf instabilities. We introduce stochasticity by adding small-amplitude spatio-temporal white noise, and analyze the resulting subthreshold fluctuations using an Ornstein-Uhlenbeck linearization. This analysis predicts divergent changes in correlation and spectral characteristics of neural activity during close approach to bifurcation from below. We validate these theoretical predictions using numerical simulations. The results demonstrate the role of noise in the emergence of critically slowed precursors in both space and time, and suggest that these early-warning signals are a universal feature of a neural system close to bifurcation. In particular, these precursor signals are likely to have neurobiological significance as early warnings of impending state change in the cortex. We support this claim with an analysis of the in vitro local field potentials recorded from slices of mouse-brain tissue. We show that in the period leading up to emergence of spontaneous seizure-like events, the mouse field potentials show a characteristic spectral focusing toward lower frequencies concomitant with a growth in fluctuation variance, consistent with critical slowing near a bifurcation point. This observation of biological criticality has clear implications regarding the feasibility of seizure prediction.

Emergence of spatially heterogeneous burst suppression in a neural field model of electrocortical activity

Burst suppression in the electroencephalogram (EEG) is a well-described phenomenon that occurs during deep anesthesia, as well as in a variety of congenital and acquired brain insults. Classically it is thought of as spatially synchronous, quasi-periodic bursts of high amplitude EEG separated by low amplitude activity. However, its characterization as a “global brain state” has been challenged by recent results obtained with intracranial electrocortigraphy. Not only does it appear that burst suppression activity is highly asynchronous across cortex, but also that it may occur in isolated regions of circumscribed spatial extent. Here we outline a realistic neural field model for burst suppression by adding a slow process of synaptic resource depletion and recovery, which is able to reproduce qualitatively the empirically observed features during general anesthesia at the whole cortex level. Simulations reveal heterogeneous bursting over the model cortex and complex spatiotemporal dynamics during simulated anesthetic action, and provide forward predictions of neuroimaging signals for subsequent empirical comparisons and more detailed characterization. Because burst suppression corresponds to a dynamical end-point of brain activity, theoretically accounting for its spatiotemporal emergence will vitally contribute to efforts aimed at clarifying whether a common physiological trajectory is induced by the actions of general anesthetic agents. We have taken a first step in this direction by showing that a neural field model can qualitatively match recent experimental data that indicate spatial differentiation of burst suppression activity across cortex.

Thalamic δ-subunit containing GABAA receptors promote electrocortical signatures of deep non-REM sleep but do not mediate the effects of etomidate at the thalamus in vivo

Extrasynaptic δ-subunits containing GABAA receptors (δGABAARs) are sensitive targets for several commonly used hypnotic agents and mediate tonic neuronal inhibition. δGABAARs are highly expressed within the thalamus and their activation promotes a switch from tonic to burst firing in vitro. Here we test two hypotheses in vivo. (1) Activation of thalamic δGABAARs will elicit electrocortical signatures consistent with widespread thalamocortical burst firing such as increased delta oscillations (1-4 Hz) and reciprocal changes in spindle-like oscillations (7-14 Hz). (2) These signatures will be recapitulated by the general anesthetic etomidate, if the electrocortical effects of etomidate at the thalamus are mediated by δGABAARs. Microperfusion of the δGABAAR-preferring agonist 4,5,6,7-tetrahydroisoxazolo[5,4-c]pyridin-3-ol (THIP; 10 and 50 μM) into the ventrobasal complex produced significant effects on electrocortical activity in wild-type mice, but not in mice lacking δGABAARs (Gabrd(-/-)), i.e., the effects with THIP were dependent on δGABAARs. THIP (1) increased 1-4 Hz power in wakefulness and nonrapid-eye movement (NREM) sleep; (2) reduced spindle-like oscillations in NREM sleep; and (3) increased the speed of stable transitions into NREM sleep, indicating effects on state-space dynamics. In contrast, microperfusion of etomidate (10 and 30 μM) into the ventrobasal complex produced effects on electrocortical activity that were independent of δGABAARs, i.e., effects occurred in wild-type and Gabrd(-/-) mice. Etomidate (1) decreased 1-4 Hz power, increased 8-12 Hz, and/or 12-30 Hz power in all sleep-wake states; (2) increased spindle-like oscillations; and (3) increased REM sleep expression. These results indicate that thalamic δGABAARs promote electrocortical signatures of deep NREM sleep, but do not mediate the effects of etomidate at the thalamus in vivo.

Multiphasic modification of intrinsic functional connectivity of the rat brain during increasing levels of propofol

The dose-dependent effects of anesthetics on brain functional connectivity are incompletely understood. Resting-state functional magnetic resonance imaging (rsfMRI) is widely used to assess the functional connectivity in humans and animals. Propofol is an anesthetic agent with desirable characteristics for functional neuroimaging in animals but its dose-dependent effects on rsfMRI functional connectivity have not been determined. Here we tested the hypothesis that brain functional connectivity undergoes specific changes in distinct neural networks at anesthetic depths associated with loss of consciousness. We acquired spontaneous blood oxygen level-dependent (BOLD) signals simultaneously with electroencephalographic (EEG) signals from rats under steady-state, intravenously administered propofol at increasing doses from light sedation to deep anesthesia (20, 40, 60, 80, and 100 mg/kg/h IV). Power spectra and burst suppression ratio were calculated from the EEG to verify anesthetic depth. Functional connectivity was determined from the whole brain correlation of BOLD data in regions of interest followed by a segmentation of the correlation maps into anatomically defined regional connectivity. We found that propofol produced multiphasic, dose dependent changes in functional connectivity of various cortical and subcortical networks. Cluster analysis predicted segregation of connectivity into two cortical and two subcortical clusters. In one cortical cluster (somatosensory and parietal), the early reduction in connectivity was followed by transient reversal; in the other cluster (sensory, motor and cingulate/retrosplenial), this rebound was absent. The connectivity of the subcortical cluster (brainstem, hippocampal and caudate) was strongly reduced, whereas that of another (hypothalamus, medial thalamus and n. basalis) did not. Subcortical connectivity increased again in deep anesthesia associated with EEG burst suppression. Regional correlation analysis confirmed the breakdown of connectivity within and between specific cortical and subcortical networks with deepening propofol anesthesia. Cortical connectivity was suppressed before subcortical connectivity at a critical propofol dose associated with loss of consciousness.

Ketamine, Propofol, and the EEG: A Neural Field Analysis of HCN1-Mediated Interactions

Ketamine and propofol are two well-known, powerful anesthetic agents, yet at first sight this appears to be their only commonality. Ketamine is a dissociative anesthetic agent, whose main mechanism of action is considered to be N-methyl-d-aspartate (NMDA) antagonism; whereas propofol is a general anesthetic agent, which is assumed to primarily potentiate currents gated by γ-aminobutyric acid type A (GABA_A) receptors. However, several experimental observations suggest a closer relationship. First, the effect of ketamine on the electroencephalogram (EEG) is markedly changed in the presence of propofol: on its own ketamine increases θ (4–8 Hz) and decreases α (8–13 Hz) oscillations, whereas ketamine induces a significant shift to beta band frequencies (13–30 Hz) in the presence of propofol. Second, both ketamine and propofol cause inhibition of the inward pacemaker current I_h, by binding to the corresponding hyperpolarization-activated cyclic nucleotide-gated potassium channel 1 (HCN1) subunit. The resulting effect is a hyperpolarization of the neuron’s resting membrane potential. Third, the ability of both ketamine and propofol to induce hypnosis is reduced in HCN1-knockout mice. Here we show that one can theoretically understand the observed spectral changes of the EEG based on HCN1-mediated hyperpolarizations alone, without involving the supposed main mechanisms of action of these drugs through NMDA and GABA_A, respectively. On the basis of our successful EEG model we conclude that ketamine and propofol should be antagonistic to each other in their interaction at HCN1 subunits. Such a prediction is in accord with the results of clinical experiment in which it is found that ketamine and propofol interact in an infra-additive manner with respect to the endpoints of hypnosis and immobility.

The anesthetic propofol shifts the frequency of maximum spectral power in EEG during general anesthesia: analytical insights from a linear model

The work introduces a linear neural population model that allows to derive analytically the power spectrum subjected to the concentration of the anesthetic propofol. The analytical study of the power spectrum of the systems activity gives conditions on how the frequency of maximum power in experimental electroencephalographic (EEG) changes dependent on the propofol concentration. In this context, we explain the anesthetic-induced power increase in neural activity by an oscillatory instability and derive conditions under which the power peak shifts to larger frequencies as observed experimentally in EEG. Moreover the work predicts that the power increase only occurs while the frequency of maximum power increases. Numerically simulations of the systems activity complement the analytical results.

The value of spontaneous EEG oscillations in distinguishing patients in vegetative and minimally conscious states

OBJECTIVE

The value of spontaneous electroencephalography (EEG) oscillations in distinguishing patients in vegetative state (VS) and minimally conscious states (MCS) was studied.

METHODS

We quantified dynamic repertoire of EEG oscillations in resting condition with closed eyes in patients in VS and MCS. The exact composition of EEG oscillations was assessed by the probability-classification analysis of short-term EEG spectral patterns.

RESULTS

The probability of delta, theta, and slow-alpha oscillations occurrence was smaller for patients in MCS than for VS. Additionally, only patients in MCS demonstrated fast-alpha oscillation occurrence. Depending on the type and composition of EEG oscillations, the probability of their occurrence was either etiology dependent or independent. The probability of EEG oscillations occurrence differentiated brain injuries with different etiologies.

CONCLUSIONS

Spontaneous EEG oscillations have a potential value in distinguishing patients in VS and MCS.

SIGNIFICANCE

This work may have implications for clinical care, rehabilitative programs, and medical-legal decisions in patients with impaired consciousness states following coma due to acute brain injuries.

HIGHLIGHTS

The probability of delta, theta, and slow-alpha oscillations occurrence was smaller and the probability of fast-alpha oscillations occurrence was higher for patients in MCS than for patients in VS. The probability of EEG oscillations occurrence differentiated brain injuries with different etiologies. Spontaneous EEG has a potential value in distinguishing patients in VS and MCS.

Thalamo-cortical mechanisms underlying changes in amplitude and frequency of human alpha oscillations

Although a large number of studies have been devoted to establishing correlations between changes in amplitude and frequency of EEG alpha oscillations and cognitive processes, it is currently unclear through which physiological mechanisms such changes are brought about. In this study we use a biophysical model of EEG generation to gain a fundamental understanding of the functional changes within the thalamo-cortical system that might underly such alpha responses. The main result of this study is that, although the physiology of the thalamo-cortical system is characterized by a large number of parameters, alpha responses effectively depend on only three variables. Physiologically, these variables determine the resonance properties of feedforward, cortico-thalamo-cortical, and intra-cortical circuits. By examining the effect of modulations of these resonances on the amplitude and frequency of EEG alpha oscillations, it is established that the model can reproduce the variety of experimentally observed alpha responses, as well as the experimental finding that changes in alpha amplitude are typically an order of magnitude larger than changes in alpha frequency. The modeling results are also in line with the fact that alpha responses often correlate linearly with indices characterizing cognitive processes. By investigating the effect of synaptic and intrinsic neuronal parameters, we find that alpha responses reflect changes in cortical activation, which is consistent with the hypothesis that alpha activity serves to selectively inhibit cortical regions during cognitive processing demands. As an example of how these analyses can be applied to specific experimental protocols, we reproduce benzodiazepine-induced alpha responses and clarify the putative underlying thalamo-cortical mechanisms. The findings reported in this study provide a fundamental physiological framework within which alpha responses observed in specific experimental protocols can be understood.

Increased electroencephalographic gamma activity reveals awakening from isoflurane anaesthesia in rats

BACKGROUND

Animal studies often require reliable measures for anaesthetic drug effects. Lately, EEG-based depth of anaesthesia estimation has been widely applied to rat models. This study investigated the reliability of different EEG spectral properties in revealing awakening from isoflurane anaesthesia in rats.

METHODS

Adult Wistar rats with previously implanted frontal epidural electrodes were anaesthetized using isoflurane. The anaesthesia was slowly lightened until awakening, as observed by the first spontaneous movement, after which anaesthesia was induced again by increasing the isoflurane concentration. EEG was recorded during the recovery and induction periods, and the spectrograms and 23 quantitative spectral parameters used in the depth of anaesthesia estimation were calculated from the signals.

RESULTS

The awakening was accompanied by a decrease in EEG activity at frequencies below 25 Hz, while the activity at higher frequencies (25-150 Hz) was increased. Whereas the behaviour of parameters used to measure activity in the lower frequencies was subject to variability between animals, the increase in higher frequency activity was more consistent, resulting in a statistically significant change in the relative gamma power parameters at the moment of awakening.

CONCLUSIONS

The increase in frontal relative gamma activity, especially in the 50-150 Hz frequency band, seems to be the most reliable EEG indicator for the awakening of a rat from isoflurane anaesthesia. A number of other spectral measures can also be used to detect this event. However, the role of gamma frequencies in the performance of these parameters is crucial.

DMN Operational Synchrony Relates to Self-Consciousness: Evidence from Patients in Vegetative and Minimally Conscious States

The default mode network (DMN) has been consistently activated across a wide variety of self-related tasks, leading to a proposal of the DMN’s role in self-related processing. Indeed, there is limited fMRI evidence that the functional connectivity within the DMN may underlie a phenomenon referred to as self-awareness. At the same time, none of the known studies have explicitly investigated neuronal functional interactions among brain areas that comprise the DMN as a function of self-consciousness loss. To fill this gap, EEG operational synchrony analysis [1, 2] was performed in patients with severe brain injuries in vegetative and minimally conscious states to study the strength of DMN operational synchrony as a function of self-consciousness expression. We demonstrated that the strength of DMN EEG operational synchrony was smallest or even absent in patients in vegetative state, intermediate in patients in minimally conscious state and highest in healthy fully self-conscious subjects. At the same time the process of ecoupling of operations performed by neuronal assemblies that comprise the DMN was highest in patients in vegetative state, intermediate in patients in minimally conscious state and minimal in healthy fully self-conscious subjects. The DMN’s frontal EEG operational module had the strongest decrease in operational synchrony strength as a function of selfconsciousness loss, when compared with the DMN’s posterior modules. Based on these results it is suggested that the strength of DMN functional connectivity could mediate the strength of self-consciousness expression. The observed alterations similarly occurred across EEG alpha, beta1 and beta2 frequency oscillations. Presented results suggest that the EEG operational synchrony within DMN may provide an objective and accurate measure for the assessment of signs of self-(un)consciousness in these challenging patient populations. This method therefore, may complement the current diagnostic procedures for patients with severe brain injuries and, hence, the planning of a rational rehabilitation intervention.

The EEG signal: a window on the cortical brain activity

The accurate assessment of the depth of anesthesia, allowing a more accurate adaptation of the doses of hypnotics, is an important end point for the anesthesiologist. It is a particularly crucial issue in pediatric anesthesia, in the context of the recent controversies about the potential neurological consequences of the main anesthetic drugs on the developing brain. The electroencephalogram signal reflects the electrical activity of the neurons in the cerebral cortex. It is thus the key to assessment of the level of hypnosis. Beyond visual analysis, several monitoring devices allow an automated treatment of the electroencephalographic (EEG) signal, combining time and frequency domain analysis. Each of these monitors focuses on a specific combination of characteristics of the signal and provides the clinician with useful information that remains, however, partial. For a comprehensive approach of the EEG-derived indices, the main features of the normal EEG, in adults and children, will be presented in the awake state and during sleep. Age-related modifications accompanying cerebral maturation during infancy and childhood will be detailed. Then, this review will provide an update on how anesthetic drugs, particularly hypnotics, influence the EEG signal, and how the main available monitors analyze these drug-induced modifications. The relationships between pain, memory, and the EEG will be discussed. Finally, this review will focus on some specific EEG features such as the electrical epileptoid activity observed under sevoflurane anesthesia. The EEG signal is the best window we have on cortical brain activity and provides a fair pharmacodynamic feedback of the effects of hypnotics. However, the cortex is only one of several targets of anesthesia. Hypnotics and opiates, have also subcortical primary targets, and the EEG performances in the evaluation or prediction of nociception are poor. Monitoring subcortical structures in combination with the EEG might in the future allow a better evaluation and a more precise adaptation of balanced anesthesia.