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

Pigs as a translational animal model for the study of peak alpha frequency

The most characteristic feature of the human electroencephalogram is the peak alpha frequency (PAF). While PAF has been proposed as a biomarker in several diseases and disorders, the disease mechanisms modulating PAF, as well as its physiological substrates, remain elusive. This has partly been due to challenges related to experimental manipulation and invasive procedures in human neuroscience, as well as the scarcity of animal models where PAF is consistently present in resting-state. With the potential inclusion of PAF in clinical screening and decision-making, advancing the mechanistic understanding of PAF is warranted. In this paper, we propose the female Danish Landrace pig as a suitable animal model to probe the mechanisms of PAF and its feature as a biomarker. We show that somatosensory alpha oscillations are present in anesthetized pigs using electrocorticography and intracortical electrodes located at the sensorimotor cortex. This was evident when looking at the time-domain as well as the spectral morphology of spontaneous recordings. We applied the FOOOF-algorithm to extract the spectral characteristics and implemented a robustness threshold for any periodic component. Using this conservative threshold, PAF was present in 18/20 pigs with a normal distribution of the peak frequency between 8-12 Hz, producing similar findings to human recordings. We show that PAF was present in 69.6 % of epochs of approximately six-minute-long resting-state recordings. In sum, we propose that the pig is a suitable candidate for investigating the neural mechanisms of PAF as a biomarker for disease and disorders such as pain, neuropsychiatric disorders, and response to pharmacotherapy.

Xenon anaesthesia is associated with a reduction in frontal electroencephalogram peak alpha frequency

Background

Administration of conventional anaesthetic agents is associated with changes in electroencephalogram (EEG) oscillatory dynamics, including a reduction in the peak alpha frequency. Computational models of neurones can reproduce such phenomena and are valuable tools for investigating their underlying mechanisms. We hypothesised that EEG data acquired during xenon anaesthesia in humans would show similar changes in peak alpha frequency and that computational neuronal models of recognised cellular actions of xenon would be consistent with the observed changes.

Methods

EEG recordings were obtained for 11 participants from a randomised controlled trial of xenon anaesthesia and for 21 participants from a volunteer study of xenon administration. The frontal peak alpha frequency was calculated for both cohorts at awake baseline and during xenon administration. In silico simulations with two computational models of neurones were performed to investigate how xenon antagonism of hyperpolarisation-activated cyclic nucleotide-gated channel 2 (HCN2) and glutamatergic excitatory neurotransmission would influence peak alpha frequency.

Results

Compared with awake baseline, frontal peak alpha frequency was significantly lower during xenon administration in the randomised controlled trial cohort, median (inter-quartile range) frequency 7.73 Hz (7.27-8.08 Hz) vs 8.81 Hz (8.35-9.03 Hz), P=0.012, and the volunteer cohort, 8.69 Hz (8.34-8.98 Hz) vs 9.41 Hz (9.11-9.92 Hz), P=0.001. In silico simulations with both computational models suggest that antagonism of HCN2 and glutamatergic excitatory neurotransmission are associated with a reduction in peak alpha frequency.

Conclusions

Xenon administration is associated with a reduction of peak alpha frequency in the frontal EEG. In silico simulations utilising two computational models of neurones suggest that these changes are consistent with antagonism of HCN2 and glutamatergic excitatory neurotransmission.

Clinical trial registration

The Australian New Zealand Clinical Trials Registry: ANZCTR number 12618000916246.

Decrease of the peak heights of EEG bicoherence indicated insufficiency of analgesia during surgery under general anesthesia

BACKGROUND

Studies show that the two peak heights of electroencephalographic bicoherence (pBIC-high, pBIC-low) decrease after incision and are restored by fentanyl administration. We investigated whether pBICs are good indicators for adequacy of analgesia during surgery.

METHODS

After local ethical committee approval, we enrolled 50 patients (27-65 years, ASA-PS I or II) who were scheduled elective surgery. Besides standard anesthesia monitors, to assess pBICs, we used a BIS monitor and freeware Bispectrum Analyzer for A2000. Fentanyl 5 µg/kg was completely administered before incision, and anesthesia was maintained with sevoflurane. After skin incision, when the peak of pBIC-high or pBIC-low decreased by 10% in absolute value (named LT10-high and LT10-low groups in order) or when either peak decreased to below 20% (BL20-high and BL20-low groups), an additional 1 g/kg of fentanyl was administered to examine its effect on the peak that showed a decrease.

RESULTS

The mean values and standard deviation for pBIC-high 5 min before fentanyl administration, at the time of fentanyl administration, and 5 min after fentanyl administration for LT10-high group were 39.8% (10.9%), 26.9% (10.5%), and 35.7% (12.5%). And those for pBIC-low for LT10-low group were 39.5% (6.0%), 26.8% (6.4%) and 35.0% (7.0%). Those for pBIC-high for BL20-high group were 26.3% (5.6%), 16.5% (2.6%), and 25.7% (7.0%). And those for pBIC-low for BL20-low group were 26.7% (4.8%), 17.4% (1.8%) and 26.9% (5.7%), respectively. Meanwhile, at these trigger points, hemodynamic parameters didn't show significant changes.

CONCLUSION

Superior to standard anesthesia monitoring, pBICs are better indicators of analgesia during surgery.

TRIAL REGISTRY

Clinical trial Number and registry URL: UMIN ID: UMIN000042843 https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno  = R000048907.

Lower alpha frequency of intraoperative frontal EEG is associated with postoperative delirium: A secondary propensity-matched analysis

BACKGROUND

Postoperative delirium (POD) is a serious complication of surgery, especially in the elderly patient population. It has been proposed that decreasing the amount of anesthetics by titrating to an EEG index will lower POD rate, but clear evidence is missing. A strong age-dependent negative correlation has been reported between the peak oscillatory frequency of alpha waves and end-tidal anesthetic concentration, with older patients generating slower alpha frequencies. We hypothesized, that slower alpha oscillations are associated with a higher rate of POD.

METHOD

Retrospective analysis of patients` data from a prospective observational study in cardiac surgical patients approved by the Bernese Ethics committee. Frontal EEG was recorded during Isoflurane effect-site concentrations of 0.7 to 0.8 and peak alpha frequency was measured at highest power between 6 and 17 Hz. Delirium was assessed by chart review. Demographic and clinical characteristics were compared between POD and non-POD groups. Selection bias was addressed using nearest neighbor propensity score matching (PSM) for best balance. This incorporated 18 variables, whereas patients with missing variable information or without an alpha oscillation were excluded.

RESULT

Of the 1072 patients in the original study, 828 were included, 73 with POD, 755 without. PSM allowed 328 patients into the final analysis, 67 with, 261 without POD. Before PSM, 8 variables were significantly different between POD and non-POD groups, none thereafter. Mean peak alpha frequency was significantly lower in the POD in contrast to non-POD group before and after matching (7.9 vs 8.9 Hz, 7.9 vs 8.8 Hz respectively, SD 1.3, p < 0.001).

CONCLUSION

Intraoperative slower frontal peak alpha frequency is independently associated with POD after cardiac surgery and may be a simple intraoperative neurophysiological marker of a vulnerable brain for POD. Further studies are needed to investigate if there is a causal link between alpha frequency and POD.

Effect of Repeated Exposure to Sevoflurane on Electroencephalographic Alpha Oscillation in Pediatric Patients Undergoing Radiation Therapy: A Prospective Observational Study

BACKGROUND

Pharmacological tolerance is defined as a decrease in the effect of a drug over time, or the need to increase the dose to achieve the same effect. It has not been established whether repeated exposure to sevoflurane induces tolerance in children.

METHODS

We conducted an observational study in children younger than 6 years of age scheduled for multiple radiotherapy sessions with sevoflurane anesthesia. To evaluate the development of sevoflurane tolerance, we analyzed changes in electroencephalographic spectral power at induction, across sessions. We fitted individual and group-level linear regression models to evaluate the correlation between the outcomes and sessions. In addition, a linear mixed-effect model was used to evaluate the association between radiotherapy sessions and outcomes.

RESULTS

Eighteen children were included and the median number of radiotherapy sessions per child was 28 (interquartile range: 10 to 33). There was no correlation between induction time and radiotherapy sessions. At the group level, the linear mixed-effect model showed, in a subgroup of patients, that alpha relative power and spectral edge frequency 95 were inversely correlated with the number of anesthesia sessions. Nonetheless, this subgroup did not differ from the other subjects in terms of age, sex, or the total number of radiotherapy sessions.

CONCLUSIONS

Our results suggest that children undergoing repeated anesthesia exposure for radiotherapy do not develop tolerance to sevoflurane. However, we found that a group of patients exhibited a reduction in the alpha relative power as a function of anesthetic exposure. These results may have implications that justify further studies.

Cognitive function mediates the relationship between age and anaesthesia-induced oscillatory-specific alpha power

Cognitive decline is common among older individuals, and although the underlying brain mechanisms are not entirely understood, researchers have suggested using EEG frontal alpha activity during general anaesthesia as a potential biomarker for cognitive decline. This is because frontal alpha activity associated with GABAergic general anaesthetics has been linked to cognitive function. However, oscillatory-specific alpha power has also been linked with chronological age. We hypothesize that cognitive function mediates the association between chronological age and (oscillatory-specific) alpha power. We analysed data from 380 participants (aged over 60) with baseline screening assessments and intraoperative EEG. We utilized the telephonic Montreal Cognitive Assessment to assess cognitive function. We computed total band power, oscillatory-specific alpha power, and aperiodics to measure anaesthesia-induced alpha activity. To test our mediation hypotheses, we employed structural equation modelling. Pairwise correlations between age, cognitive function and alpha activity were significant. Cognitive function mediated the association between age and classical alpha power [age → cognitive function → classical alpha; β = -0.0168 (95% confidence interval: -0.0313 to -0.00521); P = 0.0016] as well as the association between age and oscillatory-specific alpha power [age → cognitive function → oscillatory-specific alpha power; β = -0.00711 (95% confidence interval: -0.0154 to -0.000842); P = 0.028]. However, cognitive function did not mediate the association between age and aperiodic activity (1/f slope, P = 0.43; offset, P = 0.0996). This study is expected to provide valuable insights for anaesthesiologists, enabling them to make informed inferences about a patient's age and cognitive function from an analysis of anaesthetic-induced EEG signals in the operating room. To ensure generalizability, further studies across different populations are needed.

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.

EDITOR’S PERSPECTIVE

The medial septum controls hippocampal supra-theta oscillations

Hippocampal theta oscillations orchestrate faster beta-to-gamma oscillations facilitating the segmentation of neural representations during navigation and episodic memory. Supra-theta rhythms of hippocampal CA1 are coordinated by local interactions as well as inputs from the entorhinal cortex (EC) and CA3 inputs. However, theta-nested gamma-band activity in the medial septum (MS) suggests that the MS may control supra-theta CA1 oscillations. To address this, we performed multi-electrode recordings of MS and CA1 activity in rodents and found that MS neuron firing showed strong phase-coupling to theta-nested supra-theta episodes and predicted changes in CA1 beta-to-gamma oscillations on a cycle-by-cycle basis. Unique coupling patterns of anatomically defined MS cell types suggested that indirect MS-to-CA1 pathways via the EC and CA3 mediate distinct CA1 gamma-band oscillations. Optogenetic activation of MS parvalbumin-expressing neurons elicited theta-nested beta-to-gamma oscillations in CA1. Thus, the MS orchestrates hippocampal network activity at multiple temporal scales to mediate memory encoding and retrieval.

Intra-operative electroencephalogram frontal alpha-band spectral analysis and postoperative delirium in cardiac surgery: A prospective cohort study

BACKGROUND

Postoperative delirium (POD) remains a frequent complication after cardiac surgery, with pre-operative cognitive status being one of the main predisposing factors. However, performing complete pre-operative neuropsychological testing is challenging. The magnitude of frontal electroencephalographic (EEG) α oscillations during general anaesthesia has been related to pre-operative cognition and could constitute a functional marker for brain vulnerability.

OBJECTIVE

We hypothesised that features of intra-operative α-band activity could predict the occurrence of POD.

DESIGN

Single-centre prospective observational study.

SETTING

University hospital, from 15 May 2019 to 15 December 2021.

PATIENTS

Adult patients undergoing elective cardiac surgery.

MAIN OUTCOME MEASURES

Pre-operative cognitive status was assessed by neuropsychological tests and scored as a global z score. A 5-min EEG recording was obtained 30 min after induction of anaesthesia. Anaesthesia was maintained with sevoflurane. Power and peak frequency in the α-band were extracted from the frequency spectra. POD was assessed using the Confusion Assessment Method for Intensive Care Unit, the Confusion Assessment Method and a chart review.

RESULTS

Sixty-five (29.5%) of 220 patients developed POD. Delirious patients were significantly older with median [IQR] ages of 74 [64 to 79] years vs. 67 [59 to 74] years; P  < 0.001) and had lower pre-operative cognitive z scores (-0.52 ± 1.14 vs. 0.21 ± 0.84; P  < 0.001). Mean α power (-14.03 ± 4.61 dB vs. -11.59 ± 3.37 dB; P  < 0.001) and maximum α power (-11.36 ± 5.28 dB vs. -8.85 ± 3.90 dB; P  < 0.001) were significantly lower in delirious patients. Intra-operative mean α power was significantly associated with the probability of developing POD (adjusted odds ratio, 0.88; 95% confidence interval (CI), 0.81 to 0.96; P  = 0.007), independently of age and only whenever cognitive status was not considered.

CONCLUSION

A lower intra-operative frontal α-band power is associated with a higher incidence of POD after cardiac surgery. Intra-operative measures of α power could constitute a means of identifying patients at risk of this complication.

TRIAL REGISTRATION

NCT03706989.

Depth of anaesthesia monitoring: time to reject the index?

Depth of anaesthesia monitors can fail to detect consciousness under anaesthesia, primarily because they rely on the frontal EEG, which does not arise from a neural correlate of consciousness. A study published in a previous issue of the British Journal of Anaesthesia showed that indices produced by the different commercial monitors can give highly discordant results when analysing changes in the frontal EEG. Anaesthetists could benefit from routinely assessing the raw EEG and its spectrogram, rather than relying solely on an index produced by a depth of anaesthesia monitor.

A Real-Time Neurophysiologic Stress Test for the Aging Brain: Novel Perioperative and ICU Applications of EEG in Older Surgical Patients

As of 2022, individuals age 65 and older represent approximately 10% of the global population [1], and older adults make up more than one third of anesthesia and surgical cases in developed countries [2, 3]. With approximately > 234 million major surgical procedures performed annually worldwide [4], this suggests that > 70 million surgeries are performed on older adults across the globe each year. The most common postoperative complications seen in these older surgical patients are perioperative neurocognitive disorders including postoperative delirium, which are associated with an increased risk for mortality [5], greater economic burden [6, 7], and greater risk for developing long-term cognitive decline [8] such as Alzheimer's disease and/or related dementias (ADRD). Thus, anesthesia, surgery, and postoperative hospitalization have been viewed as a biological "stress test" for the aging brain, in which postoperative delirium indicates a failed stress test and consequent risk for later cognitive decline (see Fig. 3). Further, it has been hypothesized that interventions that prevent postoperative delirium might reduce the risk of long-term cognitive decline. Recent advances suggest that rather than waiting for the development of postoperative delirium to indicate whether a patient "passed" or "failed" this stress test, the status of the brain can be monitored in real-time via electroencephalography (EEG) in the perioperative period. Beyond the traditional intraoperative use of EEG monitoring for anesthetic titration, perioperative EEG may be a viable tool for identifying waveforms indicative of reduced brain integrity and potential risk for postoperative delirium and long-term cognitive decline. In principle, research incorporating routine perioperative EEG monitoring may provide insight into neuronal patterns of dysfunction associated with risk of postoperative delirium, long-term cognitive decline, or even specific types of aging-related neurodegenerative disease pathology. This research would accelerate our understanding of which waveforms or neuronal patterns necessitate diagnostic workup and intervention in the perioperative period, which could potentially reduce postoperative delirium and/or dementia risk. Thus, here we present recommendations for the use of perioperative EEG as a "predictor" of delirium and perioperative cognitive decline in older surgical patients.

Quantitative relationship between anteriorization of alpha oscillations and level of general anesthesia

A typical electroencephalogram (EEG) change induced by general anesthesia is anteriorization-disappearance of occipital alpha oscillations followed by the development of frontal alpha oscillations. Investigating the quantitative relationship between such a specific EEG change and the level of anesthesia has academic and clinical importance. We quantified the degree of anteriorization and investigated its detailed relationship with the level of anesthesia. We acquired 21-electrode EEG data and bispectral index (BIS) values of 50 patients undergoing surgery from before anesthesia induction until after patient arousal. For each epoch of a 10.24-s window with 1-s offsets, we calculated frontal alpha power [Formula: see text], occipital alpha power [Formula: see text], and their difference [Formula: see text] to quantify anteriorization. We calculated Spearman's rank correlation coefficients between these values and the BIS value. We used locally weighted regression to estimate [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] at each BIS value. Thirty-six patients (26 females and 10 males aged 24-85 years) were analyzed. The 95% confidence intervals for the mean of Fisher transformations of Spearman's rank correlation coefficients between [Formula: see text], [Formula: see text], and [Formula: see text] and BIS value were [- 0.68, - 0.26], [0.02, 0.62], and [- 1.11, - 0.91], respectively. The change in [Formula: see text] and [Formula: see text] with BIS value showed different patterns by the type of anesthetic agent, whereas that in [Formula: see text] was more consistent with smaller individual variance. Anteriorization, quantified by the difference between frontal and occipital alpha powers, continuously developed in conjunction with general anesthesia. Quantifying anteriorization may provide an objective indicator of the level of anesthesia.

EEG responses to standardised noxious stimulation during clinical anaesthesia: a pilot study

Background

During clinical anaesthesia, the administration of analgesics mostly relies on empirical knowledge and observation of the patient's reactions to noxious stimuli. Previous studies in healthy volunteers under controlled conditions revealed EEG activity in response to standardised nociceptive stimuli even at high doses of remifentanil and propofol. This pilot study aims to investigate the feasibility of using these standardised nociceptive stimuli in routine clinical practice.

Methods

We studied 17 patients undergoing orthopaedic trauma surgery under general anaesthesia. We evaluated if the EEG could track standardised noxious phase-locked electrical stimulation and tetanic stimulation, a time-locked surrogate for incisional pain, before, during, and after the induction of general anaesthesia. Subsequently, we analysed the effect of tetanic stimulation on the surgical pleth index as a peripheral, vegetative, nociceptive marker.

Results

We found that the phase-locked evoked potentials after noxious electrical stimulation vanished after the administration of propofol, but not at low concentrations of remifentanil. After noxious tetanic stimulation under general anaesthesia, there were no consistent spectral changes in the EEG, but the vegetative response in the surgical pleth index was statistically significant (Hedges' g effect size 0.32 [95% confidence interval 0.12-0.77], P=0.035).

Conclusion

Our standardised nociceptive stimuli are not optimised for obtaining consistent EEG responses in patients during clinical anaesthesia. To validate and sufficiently reproduce EEG-based standardised stimulation as a marker for nociception in clinical anaesthesia, other pain models or stimulation settings might be required to transfer preclinical studies into clinical practice.

Clinical trial registration

DRKS00017829.

Spectral EEG correlations from the different phases of general anesthesia

Introduction

Electroencephalography (EEG) signals contain transient oscillation patterns commonly used to classify brain states in responses to action, sleep, coma or anesthesia.

Methods

Using a time-frequency analysis of the EEG, we search for possible causal correlations between the successive phases of general anesthesia. We hypothesize that it could be possible to anticipate recovery patterns from the induction or maintenance phases. For that goal, we track the maximum power of the α-band and follow its time course.

Results and discussion

We quantify the frequency shift of the α-band during the recovery phase and the associated duration. Using Pearson coefficient and Bayes factor, we report non-significant linear correlation between the α-band frequency and duration shifts during recovery and the presence of the δ or the α rhythms during the maintenance phase. We also found no correlations between the α-band emergence trajectory and the total duration of the flat EEG epochs (iso-electric suppressions) induced by a propofol bolus injected during induction. Finally, we quantify the instability of the α-band using the mathematical total variation that measures possible deviations from a flat line. To conclude, the present correlative analysis shows that EEG dynamics extracted from the initial and maintenance phases of general anesthesia cannot anticipate both the emergence trajectory and the extubation time.

Effect of combined use of cerebral oximetry and electroencephalogram monitoring on the incidence of perioperative neurocognitive disorders in adult cardiac and non-cardiac surgery: A systematic review of randomized and non-randomized trials

Background: There is insufficient evidence to recommend using either intraoperative cerebral oximetry or (processed) electroencephalogram (EEG) alone for preventing perioperative neurocognitive disorders (PNDs). Objective: To evaluate the effectiveness of combined use of cerebral oximetry and electroencephalogram-guided anesthesia on the incidence of PNDs in adult patients undergoing cardiac and non-cardiac interventions. Methods: A PICOS - based systematic review of English articles using Pubmed and Embase (from inception to August 2022) was performed. There were no exclusion criteria regarding the type of the study. Abstract proceedings and new study protocols or ongoing studies were not included. Review articles were analyzed in search of eligible references. All possible terms that were illustrative of PNDs were used. Results: Among the 63 full manuscripts that were analyzed in detail, 15 met the inclusion criteria. We found 2 retrospective, 8 prospective observational and 5 randomized controlled trials of which 1 did not evaluate the use of neuromonitoring in the randomization process. The definition and the methods used to diagnose PNDs were very heterogeneous. Only 8 studies used an algorithm to avoid/treat cerebral oxygen desaturation and/or to treat EEG abnormalities. Overall, there was a tendency towards less PNDs in studies where such an algorithm was used. Conclusions: Our results suggest that integrating information obtained from cerebral oximetry and an EEG monitor may reduce the incidence of PNDs whenever an adapted algorithm is used to improve brain function.

Raspberry Pi-Based Data Archival System for Electroencephalogram Signals From the SedLine Root Device

BACKGROUND

The retrospective analysis of electroencephalogram (EEG) signals acquired from patients under general anesthesia is crucial in understanding the patient's unconscious brain's state. However, the creation of such database is often tedious and cumbersome and involves human labor. Hence, we developed a Raspberry Pi-based system for archiving EEG signals recorded from patients under anesthesia in operating rooms (ORs) with minimal human involvement.

METHODS

Using this system, we archived patient EEG signals from over 500 unique surgeries at the Emory University Orthopaedics and Spine Hospital, Atlanta, for about 18 months. For this, we developed a software package that runs on a Raspberry Pi and archives patient EEG signals from a SedLine Root EEG Monitor (Masimo) to a secure Health Insurance Portability and Accountability Act (HIPAA) compliant cloud storage. The OR number corresponding to each surgery was archived along with the EEG signal to facilitate retrospective EEG analysis. We retrospectively processed the archived EEG signals and performed signal quality checks. We also proposed a formula to compute the proportion of true EEG signal and calculated the corresponding statistics. Further, we curated and interleaved patient medical record information with the corresponding EEG signals.

RESULTS

We retrospectively processed the EEG signals to demonstrate a statistically significant negative correlation between the relative alpha power (8-12 Hz) of the EEG signal captured under anesthesia and the patient's age.

CONCLUSIONS

Our system is a standalone EEG archiver developed using low cost and readily available hardware. We demonstrated that one could create a large-scale EEG database with minimal human involvement. Moreover, we showed that the captured EEG signal is of good quality for retrospective analysis and combined the EEG signal with the patient medical records. This project's software has been released under an open-source license to enable others to use and contribute.

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.

The First Derivative of the Electroencephalogram Facilitates Tracking of Electroencephalographic Alpha Band Activity During General Anesthesia

BACKGROUND

Intraoperative neuromonitoring can help to navigate anesthesia. Pronounced alpha oscillations in the frontal electroencephalogram (EEG) appear to predict favorable perioperative neurocognitive outcomes and may also provide a measure of intraoperative antinociception. Monitoring the presence and strength of these alpha oscillations can be challenging, especially in elderly patients, because the EEG in these patients may be dominated by oscillations in other frequencies. Hence, the information regarding alpha oscillatory activity may be hidden and hard to visualize on a screen. Therefore, we developed an effective approach to improve the detection and presentation of alpha activity in the perioperative setting.

METHODS

We analyzed EEG records of 180 patients with a median age of 60 years (range, 18-90 years) undergoing noncardiac, nonneurologic surgery under general anesthesia with propofol induction and sevoflurane maintenance. We calculated the power spectral density (PSD) for the unprocessed EEG as well as for the time-discrete first derivative of the EEG (diffPSD) from 10-second epochs. Based on these data, we estimated the power-law coefficient κ of the PSD and diffPSD, as the EEG coarsely follows a 1/fκ distribution when displayed in double logarithmic coordinates. In addition, we calculated the alpha (7.8-12.1 Hz) to delta (0.4-4.3 Hz) ratio from the PSD as well as diffPSD.

RESULTS

The median κ was 0.899 [first and third quartile: 0.786, 0.986] for the unaltered PSD, and κ = -0.092 [-0.202, -0.013] for the diffPSD, corresponding to an almost horizontal PSD of the differentiated EEG. The alpha-to-delta ratio of the diffPSD was strongly increased (median ratio = -8.0 dB [-10.5, -4.7 dB] for the unaltered PSD versus 30.1 dB [26.1, 33.8 dB] for the diffPSD). A strong narrowband oscillatory alpha power component (>20% of total alpha power) was detected in 23% using PSD, but in 96% of the diffPSD.

CONCLUSIONS

We demonstrated that the calculation of the diffPSD from the time-discrete derivative of the intraoperative frontal EEG is a straightforward approach to improve the detection of alpha activity by eliminating the broadband background noise. This improvement in alpha peak detection and visualization could facilitate the guidance of general anesthesia and improve patient outcome.

[The quantitative EEG in electroencephalogram-based brain monitoring during general anesthesia]

The electroencephalogram (EEG) is increasingly being used in the clinical routine of anesthesia in German-speaking countries. In over 90% of patients the frontal EEG changes somewhat predictably in response to administration of the normally used anesthetic agents (propofol and volatile gasses). An adequate depth of anesthesia and appropriate concentrations of anesthetics in the brain generate mostly frontal oscillations between 8 and 12 Hz as well as slow delta waves between 0.5 and 4 Hz. The frontal EEG channel is well-suited for avoidance of insufficient depth of anesthesia and excessive administration of anesthetics. This article explains the clinical interpretation of the most important EEG patterns and the biophysical background. Also discussed are important limitations and pitfalls for the clinical routine, which the anesthetist should know in order to utilize the EEG as an admittedly incomplete but clinically extremely important parameter for the level of consciousness.

Monitoring anesthesia using simultaneous functional Near Infrared Spectroscopy and Electroencephalography

OBJECTIVE

This study aims to understand the neural and hemodynamic responses during general anesthesia in order to develop a comprehensive multimodal anesthesia depth monitor using simultaneous functional Near Infrared Spectroscopy (fNIRS) and Electroencephalogram (EEG).

METHODS

37 adults and 17 children were monitored with simultaneous fNIRS and EEG, during the complete general anesthesia process. The coupling of fNIRS signals with neuronal signals (EEG) was calculated. Measures of complexity (sample entropy) and phase difference were also quantified from fNIRS signals to identify unique fNIRS based biomarkers of general anesthesia.

RESULTS

A significant decrease in the complexity and power of fNIRS signals characterize the anesthesia maintenance phase. Furthermore, responses to anesthesia vary between adults and children in terms of neurovascular coupling and frontal EEG alpha power.

CONCLUSIONS

This study shows that fNIRS signals could reliably quantify the underlying neuronal activity under general anesthesia and clearly distinguish the different phases throughout the procedure in adults and children (with less accuracy).

SIGNIFICANCE

A multimodal approach incorporating the specific differences between age groups, provides a reliable measure of anesthesia depth.

Continuing professional development module : An updated introduction to electroencephalogram-based brain monitoring during intended general anesthesia

The electroencephalogram (EEG) provides a reliable reflection of the brain's electrical state, so it can reassure us that the anesthetic agents are actually reaching the patient's brain, and are having the desired effect. In most patients, the EEG changes somewhat predictably in response to propofol and volatile agents, so a frontal EEG channel can guide avoidance of insufficient and excessive administration of general anesthesia. Persistent alpha-spindles (around 10 Hz) phase-amplitude coupled with slow delta waves (around 1 Hz) are commonly seen during an "appropriate hypnotic state of general anesthesia". Such patterns can be appreciated from the EEG waveform or from the spectrogram (a colour-coded display of how the power in the various EEG frequencies changes with time). Nevertheless, there are exceptions to this. For example, administration of ketamine and nitrous oxide is generally not associated with the aforementioned alpha-spindle coupled with delta wave pattern. Also, some patients, including older adults and those with neurodegenerative disorders, are less predisposed to generate a strong electroencephalographic "alpha-spindle" pattern during general anesthesia. There might also be some rare instances when the frontal EEG shows a pattern suggestive of general anesthesia, while the patient has some awareness and is able to follow simple commands, albeit this is typically without obvious distress or memory formation. Thus, the frontal EEG alone, as currently analyzed, is an imperfect but clinically useful mirror, and more scientific insights will be needed before we can claim to have a reliable readout of brain "function" during general anesthesia.

Low Frontal Alpha Power Is Associated With the Propensity for Burst Suppression: An Electroencephalogram Phenotype for a "Vulnerable Brain"

BACKGROUND

A number of recent studies have reported an association between intraoperative burst suppression and postoperative delirium. These studies suggest that anesthesia-induced burst suppression may be an indicator of underlying brain vulnerability. A prominent feature of electroencephalogram (EEG) under propofol and sevoflurane anesthesia is the frontal alpha oscillation. This frontal alpha oscillation is known to decline significantly during aging and is generated by prefrontal brain regions that are particularly prone to age-related neurodegeneration. Given that burst suppression and frontal alpha oscillations are both associated with brain vulnerability, we hypothesized that anesthesia-induced frontal alpha power could also be associated with burst suppression.

METHODS

We analyzed EEG data from a previously reported cohort in which 155 patients received propofol (n = 60) or sevoflurane (n = 95) as the primary anesthetic. We computed the EEG spectrum during stable anesthetic maintenance and identified whether or not burst suppression occurred during the anesthetic. We characterized the relationship between burst suppression and alpha power using logistic regression. We proposed 5 different models consisting of different combinations of potential contributing factors associated with burst suppression: (1) a Base Model consisting of alpha power; (2) an Extended Mechanistic Model consisting of alpha power, age, and drug dosing information; (3) a Clinical Confounding Factors Model consisting of alpha power, hypotension, and other confounds; (4) a Simplified Model consisting only of alpha power and propofol bolus administration; and (5) a Full Model consisting of all of these variables to control for as much confounding as possible.

RESULTS

All models show a consistent significant association between alpha power and burst suppression while adjusting for different sets of covariates, all with consistent effect size estimates. Using the Simplified Model, we found that for each decibel decrease in alpha power, the odds of experiencing burst suppression increased by 1.33-fold.

CONCLUSIONS

In this study, we show how a decrease in anesthesia-induced frontal alpha power is associated with an increased propensity for burst suppression, in a manner that captures individualized information above and beyond a patient's chronological age. Lower frontal alpha band power is strongly associated with higher propensity for burst suppression and, therefore, potentially higher risk of postoperative neurocognitive disorders. We hypothesize that low frontal alpha power and increased propensity for burst suppression together characterize a "vulnerable brain" phenotype under anesthesia that could be mechanistically linked to brain metabolism, cognition, and brain aging.

Association of Sleep Electroencephalography-Based Brain Age Index With Dementia

IMPORTANCE

Dementia is an increasing cause of disability and loss of independence in the elderly population yet remains largely underdiagnosed. A biomarker for dementia that can identify individuals with or at risk for developing dementia may help close this diagnostic gap.

OBJECTIVE

To investigate the association between a sleep electroencephalography-based brain age index (BAI), the difference between chronological age and brain age estimated using the sleep electroencephalogram, and dementia.

DESIGN, SETTING, AND PARTICIPANTS

In this retrospective cross-sectional study of 9834 polysomnograms, BAI was computed among individuals with previously determined dementia, mild cognitive impairment (MCI), or cognitive symptoms but no diagnosis of MCI or dementia, and among healthy individuals without dementia from August 22, 2008, to June 4, 2018. Data were analyzed from November 15, 2018, to June 24, 2020.

EXPOSURE

Dementia, MCI, and dementia-related symptoms, such as cognitive change and memory impairment.

MAIN OUTCOMES AND MEASURES

The outcome measures were the trend in BAI when moving from groups ranging from healthy, to symptomatic, to MCI, to dementia and pairwise comparisons of BAI among these groups.

FINDINGS

A total of 5144 sleep studies were included in BAI examinations. Patients in these studies had a median (interquartile range) age of 54 (43-65) years, and 3026 (59%) were men. The patients included 88 with dementia, 44 with MCI, 1075 who were symptomatic, and 2336 without dementia. There was a monotonic increase in mean (SE) BAI from the nondementia group to the dementia group (nondementia: 0.20 [0.42]; symptomatic: 0.58 [0.41]; MCI: 1.65 [1.20]; dementia: 4.18 [1.02]; P < .001).

CONCLUSIONS AND RELEVANCE

These findings suggest that a sleep-state electroencephalography-based BAI shows promise as a biomarker associated with progressive brain processes that ultimately result in dementia.

Double standard: why electrocardiogram is standard care while electroencephalogram is not?

PURPOSE OF REVIEW

Major adverse cardiovascular and cerebrovascular events (MACCE) significantly affect the surgical outcomes. Electrocardiogram (ECG) has been a standard intraoperative monitor for 30 years. Electroencephalogram (EEG) can provide valuable information about the anesthetized state and guide anesthesia management during surgery. Whether EEG should be a standard intraoperative monitor is discussed in this review.

RECENT FINDINGS

Deep anesthesia has been associated with postoperative delirium, especially in elderly patients. Intraoperative EEG monitoring has been demonstrated to reduce total anesthesia drug use during general anesthesia and postoperative delirium.

SUMMARY

Unlike ECG monitoring, the EEG under general anesthesia has not been designated as a standard monitor by anesthesiologist societies around the world. The processed EEG technology has been commercially available for more than 25 years and EEG technology has significantly facilitated its intraoperative use. It is time to consider EEG as a standard anesthesia monitor during surgery.

Spectral and Entropic Features Are Altered by Age in the Electroencephalogram in Patients under Sevoflurane Anesthesia

BACKGROUND

Preexisting factors such as age and cognitive performance can influence the electroencephalogram (EEG) during general anesthesia. Specifically, spectral EEG power is lower in elderly, compared to younger, subjects. Here, the authors investigate age-related changes in EEG architecture in patients undergoing general anesthesia through a detailed examination of spectral and entropic measures.

METHODS

The authors retrospectively studied 180 frontal EEG recordings from patients undergoing general anesthesia, induced with propofol/fentanyl and maintained by sevoflurane at the Waikato Hospital in Hamilton, New Zealand. The authors calculated power spectral density and normalized power spectral density, the entropic measures approximate and permutation entropy, as well as the beta ratio and spectral entropy as exemplary parameters used in current monitoring systems from segments of EEG obtained before the onset of surgery (i.e., with no noxious stimulation).

RESULTS

The oldest quartile of patients had significantly lower 1/f characteristics (P < 0.001; area under the receiver operating characteristics curve, 0.84 [0.76 0.92]), indicative of a more uniform distribution of spectral power. Analysis of the normalized power spectral density revealed no significant impact of age on relative alpha (P = 0.693; area under the receiver operating characteristics curve, 0.52 [0.41 0.63]) and a significant but weak effect on relative beta power (P = 0.041; area under the receiver operating characteristics curve, 0.62 [0.52 0.73]). Using entropic parameters, the authors found a significant age-related change toward a more irregular and unpredictable EEG (permutation entropy: P < 0.001, area under the receiver operating characteristics curve, 0.81 [0.71 0.90]; approximate entropy: P < 0.001; area under the receiver operating characteristics curve, 0.76 [0.66 0.85]). With approximate entropy, the authors could also detect an age-induced change in alpha-band activity (P = 0.002; area under the receiver operating characteristics curve, 0.69 [0.60 78]).

CONCLUSIONS

Like the sleep literature, spectral and entropic EEG features under general anesthesia change with age revealing a shift toward a faster, more irregular, oscillatory composition of the EEG in older patients. Age-related changes in neurophysiological activity may underlie these findings however the contribution of age-related changes in filtering properties or the signal to noise ratio must also be considered. Regardless, most current EEG technology used to guide anesthetic management focus on spectral features, and improvements to these devices might involve integration of entropic features of the raw EEG.

Electroencephalogram Suppression Despite Extremely Low-Dose Anesthetic During Cardiac Surgery: A Case Report

A prominent feature of electroencephalogram (EEG) under general anesthesia is anteriorization of α waves. We report the case of a 63-year-old man anesthetized for coronary artery bypass grafting in whom the NeuroSENSE-processed EEG monitor recorded only δ waves in the absence of α frequencies, along with high EEG suppression despite extremely low doses of anesthetics during the whole procedure. The patient fully recovered from anesthesia 2 hours after the procedure and showed neither awareness nor neurological complications. This atypical EEG pattern under low concentration of anesthetics may be an intraoperative marker of a specific brain phenotype.

Influence of midazolam premedication on intraoperative EEG signatures in elderly patients

OBJECTIVE

To investigate the influence of midazolam premedication on the EEG-spectrum before and during general anesthesia in elderly patients.

METHODS

Patients aged ≥65 years, undergoing elective surgery were included in this prospective observational study. A continuous pre- and intraoperative frontal EEG was recorded in patients who received premedication with midazolam (Mid, n = 15) and patients who did not (noMid, n = 30). Absolute power within the delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), and beta (12-25 Hz) frequency-bands was analyzed in EEG-sections before (pre-induction), and after induction of anesthesia with propofol (post-induction), as well as during general anesthesia with either propofol or volatile-anesthetics (intra-operative).

RESULTS

Pre-induction, α-power of Mid patients was lower compared with noMid-patients (α-power: Mid: -10.75 dB vs. noMid: -9.20 dB; p = 0.036). After induction of anesthesia Mid-patients displayed a stronger increase of frontal α-power resulting in higher absolute α-power at post-induction state, (α-power: Mid -3.56 dB vs. noMid: -6.69 dB; p = 0.004), which remained higher intraoperatively (α-power: Mid: -2.12 dB vs. noMid: -6.10 dB; p = 0.024).

CONCLUSION

Midazolam premedication alters the intraoperative EEG-spectrum in elderly patients.

SIGNIFICANCE

This finding provides further evidence for the role of GABAergic activation in the induction of elevated, frontal α-power during general anesthesia.

TRIAL REGISTRY NUMBER

NCT02265263. 23 September 2014. Principal investigator: Prof. Dr. med. Claudia Spies. (https://clinicaltrials.gov/ct2/show/NCT02265263).

The Human Default Consciousness and Its Disruption: Insights From an EEG Study of Buddhist Jhāna Meditation

The “neural correlates of consciousness” (NCC) is a familiar topic in neuroscience, overlapping with research on the brain’s “default mode network.” Task-based studies of NCC by their nature recruit one part of the cortical network to study another, and are therefore both limited and compromised in what they can reveal about consciousness itself. The form of consciousness explored in such research, we term the human default consciousness (DCs), our everyday waking consciousness. In contrast, studies of anesthesia, coma, deep sleep, or some extreme pathological states such as epilepsy, reveal very different cortical activity; all of which states are essentially involuntary, and generally regarded as “unconscious.” An exception to involuntary disruption of consciousness is Buddhist jhāna meditation, whose implicit aim is to intentionally withdraw from the default consciousness, to an inward-directed state of stillness referred to as jhāna consciousness, as a basis to develop insight. The default consciousness is sensorily-based, where information about, and our experience of, the outer world is evaluated against personal and organic needs and forms the basis of our ongoing self-experience. This view conforms both to Buddhist models, and to the emerging work on active inference and minimization of free energy in determining the network balance of the human default consciousness. This paper is a preliminary report on the first detailed EEG study of jhāna meditation, with findings radically different to studies of more familiar, less focused forms of meditation. While remaining highly alert and “present” in their subjective experience, a high proportion of subjects display “spindle” activity in their EEG, superficially similar to sleep spindles of stage 2 nREM sleep, while more-experienced subjects display high voltage slow-waves reminiscent, but significantly different, to the slow waves of deeper stage 4 nREM sleep, or even high-voltage delta coma. Some others show brief posterior spike-wave bursts, again similar, but with significant differences, to absence epilepsy. Some subjects also develop the ability to consciously evoke clonic seizure-like activity at will, under full control. We suggest that the remarkable nature of these observations reflects a profound disruption of the human DCs when the personal element is progressively withdrawn.

Analyzing Electroencephalography (EEG) Waves Provides a Reliable Tool to Assess the Depth of Sevoflurane Anesthesia in Pediatric Patients

BACKGROUND Studies have reported that BIS is unreliable in children because its algorithm provides misleading information about the actual depth of anesthesia. Raw EEG analysis provides direct neurophysiologic measurement of cerebral activity. The relationship between age and EEG has rarely been reported, thus the aim of the present study was to compare raw electroencephalography (EEG) among different age groups of surgical patients under general anesthesia with 1.0 MAC sevoflurane. MATERIAL AND METHODS We enrolled 135 patients aged 0-80 years old (ASA physical status I or II) undergoing surgery, who were divided into 6 groups: 1-12 months old (group 1), 1-3 years old (group 2), 3-6 years old (group 3), 6-18 years old (group 4), 18-65 years old (group 5), and 65-80 years old (group 6). Different raw EEG waves (alpha, delta, and theta) were compared for all subjects. RESULTS The BIS values in groups 1 to 6 were 52.2±12.7, 55.0±8.0, 44.5±7.3, 43.8±7.3, 44.2±6.2, and 49.1±6.2 respectively. Compared with groups 1 and 2 (52.2±12.7, 55.0±8.0), BIS values of groups 3, 4, and 5 (44.5±7.3, 43.8±7.3, 44.2±6.2, respectively) were lower (P<0.05). Theta frequency was observed in the 6 groups. The EEG frequencies in groups 1 to 6 were 6.0 (5.5-6.0), 6.0 (5.5-6.0), 6.0 (5.5-6.0), 6.0 (6.0-7.0), 6.3 (6.0-7.0), and 6.0 (5.1-6.0), respectively. Compared with group 6, EEG frequencies in groups 4 and 5 were higher (P<0.05). BIS value was significantly correlated with EEG frequency (R²=0.063, P<0.01). CONCLUSIONS Analyzing raw EEG waves provides more accurate judgement of depth of anesthesia, especially in pediatric cases in which monitors often provide misleading values.

The effect of sevoflurane and isoflurane anesthesia on single unit and local field potentials

Volatile general anesthetics are used commonly in adults and children, yet their mechanisms of action are complex and the changes in single unit firing and synaptic activity that underlie the broad decreases in neuronal activity induced by these drugs have not been well characterized. Capturing such changes throughout the anesthesia process is important for comparing the effects of different anesthetics and gaining a better understanding of their mechanisms of action and their impact on different brain regions. Using chronically implanted electrodes in the rabbit somatosensory cortex, we compared the effects of two common general anesthetics, isoflurane, and sevoflurane, on cortical neurons. Single unit activity and local field potentials (LFP) were recorded continuously before and during anesthetic delivery at 1 MAC, as well as during recovery. Our findings show that although isoflurane and sevoflurane belong to the same class of volatile general anesthetics, their effects upon cortical single units and LFP were quite different. Overall, the suppression of neuronal firing was greater and more uniform under sevoflurane. Moreover, the changes in LFP frequency bands suggest that effect of anesthesia upon beta oscillations does not necessarily depend on the level of single unit activity, but rather on the changes in GABA/glutamate neurotransmission induced by each drug.

Modulation of frontal EEG alpha oscillations during maintenance and emergence phases of general anaesthesia to improve early neurocognitive recovery in older patients: protocol for a randomised controlled trial

BACKGROUND

Postoperative delirium may manifest in the immediate post-anaesthesia care period. Such episodes appear to be predictive of further episodes of inpatient delirium and associated adverse outcomes. Frontal electroencephalogram (EEG) findings of suppression patterns and low proprietary index values have been associated with postoperative delirium and poor outcomes. However, the efficacy of titrating anaesthesia to proprietary index targets for preventing delirium remains contentious. We aim to assess the efficacy of two strategies which we hypothesise could prevent post-anaesthesia care unit (PACU) delirium by maximising the alpha oscillation observed in frontal EEG channels during the maintenance and emergence phases of anaesthesia.

METHODS

This is a 2 × 2 factorial, double-blind, stratified, randomised control trial of 600 patients. Eligible patients are those aged 60 years or over who are undergoing non-cardiac, non-intracranial, volatile-based anaesthesia of expected duration of more than 2 h. Patients will be stratified by pre-operative cognitive status, surgery type and site. For the maintenance phase of anaesthesia, patients will be randomised (1:1) to an alpha power-maximisation anaesthesia titration strategy versus standard care avoiding suppression patterns in the EEG. For the emergence phase of anaesthesia, patients will be randomised (1:1) to early cessation of volatile anaesthesia and emergence from an intravenous infusion of propofol versus standard emergence from volatile anaesthesia only. The primary study outcomes are the power of the frontal alpha oscillation during the maintenance and emergence phases of anaesthesia. Our main clinical outcome of interest is PACU delirium.

DISCUSSION

This is a largely exploratory study; the extent to which EEG signatures can be modified by titration of pharmacological agents is not known. The underlying concept is maximisation of anaesthetic efficacy by individualised drug titration to a clearly defined EEG feature. The interventions are already clinically used strategies in anaesthetic practice, but have not been formally evaluated. The addition of propofol during the emergence phase of volatile-based general anaesthesia is known to reduce emergence delirium in children; however, the efficacy of this strategy in older patients is not known.

TRIAL REGISTRATION

Australian and New Zealand Clinical Trial Registry, ID: 12617001354370 . Registered on 27/09/2017.

Cognitive Impairment Is Associated with Absolute Intraoperative Frontal α-Band Power but Not with Baseline α-Band Power: A Pilot Study

BACKGROUND

Cognitive abilities decline with aging, leading to a higher risk for the development of postoperative delirium or postoperative neurocognitive disorders after general anesthesia. Since frontal α-band power is known to be highly correlated with cognitive function in general, we hypothesized that preoperative cognitive impairment is associated with lower baseline and intraoperative frontal α-band power in older adults.

METHODS

Patients aged ≥65 years undergoing elective surgery were included in this prospective observational study. Cognitive function was assessed on the day before surgery using six age-sensitive cognitive tests. Scores on those tests were entered into a principal component analysis to calculate a composite "g score" of global cognitive ability. Patient groups were dichotomized into a lower cognitive group (LC) reaching the lower 1/3 of "g scores" and a normal cognitive group (NC) consisting of the upper 2/3 of "g scores." Continuous pre- and intraoperative frontal electroencephalograms (EEGs) were recorded. EEG spectra were analyzed at baseline, before start of anesthesia medication, and during a stable intraoperative period. Significant differences in band power between the NC and LC groups were computed by using a frequency domain (δ 0.5-3 Hz, θ 4-7 Hz, α 8-12 Hz, β 13-30 Hz)-based bootstrapping algorithm.

RESULTS

Of 38 included patients (mean age 72 years), 24 patients were in the NC group, and 14 patients had lower cognitive abilities (LC). Intraoperative α-band power was significantly reduced in the LC group compared to the NC group (NC -1.6 [-4.48/1.17] dB vs. LC -6.0 [-9.02/-2.64] dB), and intraoperative α-band power was positively correlated with "g score" (Spearman correlation: r = 0.381; p = 0.018). Baseline EEG power did not show any associations with "g."

CONCLUSIONS

Preoperative cognitive impairment in older adults is associated with intraoperative absolute frontal α-band power, but not baseline α-band power.

Towards a better understanding of anesthesia emergence mechanisms: Research and clinical implications

Emergence from anesthesia (AE) is the ending stage of anesthesia featuring the transition from unconsciousness to complete wakefulness and recovery of consciousness (RoC). A wide range of undesirable complications, including coughing, respiratory/cardiovascular events, and mental status changes such as emergence delirium, and delayed RoC, may occur during this critical phase. In general anesthesia processes, induction and AE represent a neurobiological example of "hysteresis". Indeed, AE mechanisms should not be simply considered as reverse events of those occurring in the induction phase. Anesthesia-induced loss of consciousness (LoC) and AE until RoC are quite distinct phenomena with, in part, a distinct neurobiology. Althoughanaesthetics produce LoC mostly by affecting cortical connectivity, arousal processes at the end of anesthesia are triggered by structures deep in the brain, rather than being induced within the neocortex. This work aimed to provide an overview on AE processes research, in terms of mechanisms, and EEG findings. Because most of the research in this field concerns preclinical investigations, translational suggestions and research perspectives are proposed. However, little is known about the relationship between AE neurobiology, and potential complications occurring during the emergence, and after the RoC. Thus, another scope of this review is to underline why a better understanding of AE mechanisms could have significant clinical implications, such as improving the patients' quality of recovery, and avoiding early and late postoperative complications.

Suppression of underlying neuronal fluctuations mediates EEG slowing during general anaesthesia

The physiological mechanisms by which anaesthetic drugs modulate oscillatory brain activity remain poorly understood. Combining human data, mathematical and computational analysis of both spiking and mean-field models, we investigated the spectral dynamics of encephalographic (EEG) beta-alpha oscillations, observed in human patients undergoing general anaesthesia. The effect of anaesthetics can be modelled as a reduction of neural fluctuation intensity, and/or an increase in inhibitory synaptic gain in the thalamo-cortical circuit. Unlike previous work, which suggested the primary importance of gamma-amino-butryic-acid (GABA) augmentation in causing a shift to low EEG frequencies, our analysis demonstrates that a non-linear transition, triggered by a simple decrease in neural fluctuation intensity, is sufficient to explain the clinically-observed appearance - and subsequent slowing - of the beta-alpha narrowband EEG peak. In our model, increased synaptic inhibition alone, did not correlate with the clinically-observed encephalographic spectral changes, but did cause the anaesthetic-induced decrease in neuronal firing rate. Taken together, our results show that such a non-linear transition results in functional fragmentation of cortical and thalamic populations; highly correlated intra-population dynamics triggered by anaesthesia decouple and isolate neural populations. Our results are able to parsimoniously unify and replicate the observed anaesthetic effects on both the EEG spectra and inter-regional connectivity, and further highlight the importance of neural activity fluctuations in the genesis of altered brain states.

Electroencephalographic markers of brain development during sevoflurane anaesthesia in children up to 3 years old

BACKGROUND

General anaesthetics generate spatially defined brain oscillations in the EEG that relate fundamentally to neural-circuit architecture. Few studies detailing the neural-circuit activity of general anaesthesia in children have been described. The study aim was to identify age-related changes in EEG characteristics that mirror different stages of early human brain development during sevoflurane anaesthesia.

METHODS

Multichannel EEG recordings were performed in 91 children aged 0-3 yr undergoing elective surgery. We mapped spatial power and coherence over the frontal, parietal, temporal, and occipital cortices during maintenance anaesthesia.

RESULTS

During sevoflurane exposure: (i) slow-delta (0.1-4 Hz) oscillations were present in all ages, (ii) theta (4-8 Hz) and alpha (8-12 Hz) oscillations emerge by ∼4 months, (iii) alpha oscillations increased in power from 4 to 10 months, (iv) frontal alpha-oscillation predominance emerged at ∼6 months, (v) frontal slow oscillations were coherent from birth until 6 months, and (vi) frontal alpha oscillations became coherent ∼10 months and persisted in older ages.

CONCLUSIONS

Key developmental milestones in the maturation of the thalamo-cortical circuitry likely generate changes in EEG patterns in infants undergoing sevoflurane general anaesthesia. Characterisation of anaesthesia-induced EEG oscillations in children demonstrates the importance of developing age-dependent strategies to monitor properly the brain states of children receiving general anaesthesia. These data have the potential to guide future studies investigating neurodevelopmental pathologies involving altered excitatory-inhibitory balance, such as epilepsy or Rett syndrome.