Thalamocortical model for a propofol-induced alpha-rhythm associated with loss of consciousness

Dynamic changes in rhythmic and arrhythmic neural signatures in the subthalamic nucleus induced by anaesthesia and tracheal intubation

BACKGROUND

Subcortical structures, including the basal ganglia, have been proposed to be crucial for arousal, consciousness, and behavioural responsiveness. How the basal ganglia contribute to the loss and recovery of consciousness during anaesthesia has, however, not yet been well characterised.

METHODS

Twelve patients with advanced Parkinson's disease, who were undergoing deep brain stimulation (DBS) electrode implantation in the subthalamic nucleus (STN), were included in this study. Local field potentials (LFPs) were recorded from the DBS electrodes and EEG was recorded from the scalp during induction of general anaesthesia (with propofol and sufentanil) and during tracheal intubation. Neural signatures of loss of consciousness and of the expected arousal during intubation were sought in the STN and EEG recordings.

RESULTS

Propofol-sufentanil anaesthesia resulted in power increases in delta, theta, and alpha frequencies, and broadband power decreases in higher frequencies in both STN and frontal cortical areas. This was accompanied by increased STN-frontal cortical coherence only in the alpha frequency band (119 [68]%; P=0.0049). We observed temporal activity changes in STN after tracheal intubation, including power increases in high-beta (22-40 Hz) frequency (98 [123]%; P=0.0064) and changes in the power-law exponent in the power spectra at lower frequencies (2-80 Hz), which were not observed in the frontal cortex. During anaesthesia, the dynamic changes in the high-gamma power in STN LFPs correlated with the power-law exponent in the power spectra at lower frequencies (2-80 Hz).

CONCLUSIONS

Apart from similar activity changes in both STN and cortex associated with anaesthesia-induced unresponsiveness, we observed specific neuronal activity changes in the STN in response to the anaesthesia and tracheal intubation. We also show that the power-law exponent in the power spectra in the STN was modulated by tracheal intubation in anaesthesia. Our results support the hypothesis that subcortical nuclei may play an important role in the loss and return of responsiveness.

A Neurologic Examination for Anesthesiologists: Assessing Arousal Level during Induction, Maintenance, and Emergence

Anesthetics have profound effects on the brain and central nervous system. Vital signs, along with the electroencephalogram and electroencephalogram-based indices, are commonly used to assess the brain states of patients receiving general anesthesia and sedation. Important information about the patient's arousal state during general anesthesia can also be obtained through use of the neurologic examination. This article reviews the main components of the neurologic examination focusing primarily on the brainstem examination. It details the components of the brainstem examination that are most relevant for patient management during induction, maintenance, and emergence from general anesthesia. The examination is easy to apply and provides important complementary information about the patient's arousal level that cannot be discerned from vital signs and electroencephalogram measures.

Differential frontal alpha oscillations and mechanisms underlying loss of consciousness: a comparison between slow and fast propofol infusion rates

Mechanisms underlying loss of consciousness following propofol administration remain incompletely understood. The objective of this study was to compare frontal lobe electroencephalography activity and brainstem reflexes during intravenous induction of general anaesthesia, in patients receiving a typical bolus dose (fast infusion) of propofol compared with a slower infusion rate. We sought to determine whether brainstem suppression ('bottom-up') predominates over loss of cortical function ('top-down'). Sixteen ASA physical status-1 patients were randomly assigned to either a fast or slow propofol infusion group. Loss of consciousness and brainstem reflexes were assessed every 30 s by a neurologist blinded to treatment allocation. We performed a multitaper spectral analysis of all electroencephalography data obtained from each participant. Brainstem reflexes were present in all eight patients in the slow infusion group, while being absent in all patients in the fast infusion group, at the moment of loss of consciousness (p = 0.010). An increase in alpha band power was observed before loss of consciousness only in participants allocated to the slow infusion group. Alpha band power emerged several minutes after the loss of consciousness in participants allocated to the fast infusion group. Our results show a predominance of 'bottom-up' mechanisms during fast infusion rates and 'top-down' mechanisms during slow infusion rates. The underlying mechanisms by which propofol induces loss of consciousness are potentially influenced by the speed of infusion.

Nonlinear dynamics captures brain states at different levels of consciousness in patients anesthetized with propofol

The information processing capability of the brain decreases during unconscious states. Capturing this decrease during anesthesia-induced unconsciousness has been attempted using standard spectral analyses as these correlate relatively well with breakdowns in corticothalamic networks. Much of this work has involved the use of propofol to perturb brain activity, as it is one of the most widely used anesthetics for routine surgical anesthesia. Propofol administration alone produces EEG spectral characteristics similar to most hypnotics; however, inter-individual and drug variation render spectral measures inconsistent. Complexity measures of EEG signals could offer better measures to distinguish brain states, because brain activity exhibits nonlinear behavior at several scales during transitions of consciousness. We tested the potential of complexity analyses from nonlinear dynamics to identify loss and recovery of consciousness at clinically relevant timepoints. Patients undergoing propofol general anesthesia for various surgical procedures were identified as having changes in states of consciousness by the loss and recovery of response to verbal stimuli after induction and upon cessation of anesthesia, respectively. We demonstrate that nonlinear dynamics analyses showed more significant differences between consciousness states than spectral measures. Notably, attractors in conscious and anesthesia-induced unconscious states exhibited significantly different shapes. These shapes have implications for network connectivity, information processing, and the total number of states available to the brain at these different levels. They also reflect some of our general understanding of the network effects of consciousness in a way that spectral measures cannot. Thus, complexity measures could provide a universal means for reliably capturing depth of consciousness based on EEG changes at the beginning and end of anesthesia administration.

Intraoperative Low Alpha Power in the Electroencephalogram Is Associated With Postoperative Subsyndromal Delirium

Background

Postoperative delirium (PD) and subsyndromal delirium (PSSD) are frequent complications in older patients associated with poor long-term outcome. It has been suggested that certain electroencephalogram features may be capable of identifying patients at risk during surgery. Thus, the goal of this study was to characterize intraoperative electroencephalographic markers to identify patients prone to develop PD or PSSD.

Methods

We conducted an exploratory observational study in older patients scheduled for elective major abdominal surgery. Intraoperative 16 channels electroencephalogram was recorded, and PD/PSSD were diagnosed after surgery with the confusion assessment method (CAM). The total power spectra and relative power of alpha band were calculated.

Results

PD was diagnosed in 2 patients (6.7%), and 11 patients (36.7%) developed PSSD. All of them (13 patients, PD/PSSD group) were compared with patients without any alterations in CAM (17 patients, control group). There were no detectable power spectrum differences before anesthesia between both groups of patients. However, PD/PSSD group in comparison with control group had a lower intraoperative absolute alpha power during anesthesia (4.4 ± 3.8 dB vs. 9.6 ± 3.2 dB, p = 0.0004) and a lower relative alpha power (0.09 ± 0.06 vs. 0.21 ± 0.08, p < 0.0001). These differences were independent of the anesthetic dose. Finally, relative alpha power had a good ability to identify patients with CAM alterations in the ROC analysis (area under the curve 0.90 (CI 0.78-1), p < 0.001).

Discussion

In conclusion, a low intraoperative alpha power is a novel electroencephalogram marker to identify patients who will develop alterations in CAM - i.e., with PD or PSSD - after surgery.

Multimodal General Anesthesia: Theory and Practice

Balanced general anesthesia, the most common management strategy used in anesthesia care, entails the administration of different drugs together to create the anesthetic state. Anesthesiologists developed this approach to avoid sole reliance on ether for general anesthesia maintenance. Balanced general anesthesia uses less of each drug than if the drug were administered alone, thereby increasing the likelihood of its desired effects and reducing the likelihood of its side effects. To manage nociception intraoperatively and pain postoperatively, the current practice of balanced general anesthesia relies almost exclusively on opioids. While opioids are the most effective antinociceptive agents, they have undesirable side effects. Moreover, overreliance on opioids has contributed to the opioid epidemic in the United States. Spurred by concern of opioid overuse, balanced general anesthesia strategies are now using more agents to create the anesthetic state. Under these approaches, called “multimodal general anesthesia,” the additional drugs may include agents with specific central nervous system targets such as dexmedetomidine and ones with less specific targets, such as magnesium. It is postulated that use of more agents at smaller doses further maximizes desired effects while minimizing side effects. Although this approach appears to maximize the benefit-to-side effect ratio, no rational strategy has been provided for choosing the drug combinations. Nociception induced by surgery is the primary reason for placing a patient in a state of general anesthesia. Hence, any rational strategy should focus on nociception control intraoperatively and pain control postoperatively. In this Special Article, we review the anatomy and physiology of the nociceptive and arousal circuits, and the mechanisms through which commonly used anesthetics and anesthetic adjuncts act in these systems. We propose a rational strategy for multimodal general anesthesia predicated on choosing a combination of agents that act at different targets in the nociceptive system to control nociception intraoperatively and pain postoperatively. Because these agents also decrease arousal, the doses of hypnotics and/or inhaled ethers needed to control unconsciousness are reduced. Effective use of this strategy requires simultaneous monitoring of antinociception and level of unconsciousness. We illustrate the application of this strategy by summarizing anesthetic management for 4 representative surgeries.

Dopamine D2-receptor Antagonist Droperidol Deepens Sevoflurane Anesthesia

BACKGROUND

Although midbrain dopaminergic pathways are known to contribute to arousal and emergence from anesthesia, few reports exist regarding the anesthetic effects of dopamine D2 receptor antagonism in humans. This study examined the effect of the D2 receptor antagonist droperidol on sevoflurane anesthesia by examining α and slow wave electroencephalogram oscillations.

METHODS

Forty-five patients, age 20 to 60 yr, were enrolled. Frontal electroencephalograms were continuously collected for offline analysis via Bispectral Index monitoring. After induction of anesthesia, end-tidal sevoflurane concentration was deliberately maintained at 1%, and intravenous droperidol (0.05 mg/kg bolus) was administered. Electroencephalogram changes were examined in power spectrum and bicoherence, before and 10 min after droperidol injection, then compared using the Wilcoxon signed-ranks test and/or paired t test.

RESULTS

Droperidol significantly augmented the α-bicoherence peak induced by sevoflurane from 30.3% (24.2%, 42.4%) to 50.8% (41.7%, 55.2%) (median [25th, 75th percentiles]; P < 0.0001), Hodges-Lehman median difference, 15.8% (11.3 to 21.4%) (95% CI). The frequency of the α-bicoherence peak was simultaneously shifted to the lower frequency; from 11.5 (11.0, 13.0) to 10.5 (10.0, 11.0) Hz (median [25th, 75th percentiles], P < 0.0001). Averaged bicoherence in the δ-θ area increased conspicuously from 17.2% (15.6 to 18.7%) to 25.1% (23.0 to 27.3%) (mean [95% CI]; P < 0.0001), difference, 8.0% (6.0 to 9.9%).

CONCLUSIONS

Droperidol augments both α and δ-θ bicoherences while shifting the α-bicoherence peaks to lower frequencies, and enhances the effect of sevoflurane anesthesia on the electroencephalogram via γ-aminobutyric acid-mediated oscillatory network regulation.

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).

Cross-frequency coupling of alpha oscillatory power to the entrainment rhythm of a spatially attended input stream

Neural entrainment and alpha oscillatory power (8-14 Hz) are mechanisms of selective attention. The extent to which these two mechanisms interact, especially in the context of visuospatial attention, is unclear. Here, we show that spatial attention to a delta-frequency, rhythmic visual stimulus in one hemifield results in phase-amplitude coupling between the delta-phase of an entrained frontal source and alpha power generated by ipsilateral visuocortical regions. The driving of ipsilateral alpha power by frontal delta also correlates with task performance. Our analyses suggest that neural entrainment may serve a previously underappreciated role in coordinating macroscale brain networks and that inhibition of processing by alpha power can be coupled to an attended temporal structure. Finally, we note that the observed coupling bolsters one dominant hypothesis of modern cognitive neuroscience, that macroscale brain networks and distributed neural computation are coordinated by oscillatory synchrony and cross-frequency interactions.

Towards a Comprehensive Understanding of Anesthetic Mechanisms of Action: A Decade of Discovery

Significant progress has been made in the 21st century towards a comprehensive understanding of the mechanisms of action of general anesthetics, coincident with progress in structural biology and molecular, cellular, and systems neuroscience. This review summarizes important new findings that include target identification through structural determination of anesthetic binding sites, details of receptors and ion channels involved in neurotransmission, and the critical roles of neuronal networks in anesthetic effects on memory and consciousness. These recent developments provide a comprehensive basis for conceptualizing pharmacological control of amnesia, unconsciousness, and immobility.

Coherence of Visual-Evoked Gamma Oscillations Is Disrupted by Propofol but Preserved Under Equipotent Doses of Isoflurane

Previous research demonstrates that the underlying state of the brain influences how sensory stimuli are processed. Canonically, the state of the brain has been defined by quantifying the spectral characteristics of spontaneous fluctuations in local field potentials (LFP). Here, we utilized isoflurane and propofol anesthesia to parametrically alter the spectral state of the murine brain. With either drug, we produce slow wave activity, with low anesthetic doses, or burst suppression, with higher doses. We find that while spontaneous LFP oscillations were similar, the average visual-evoked potential (VEP) was always smaller in amplitude and shorter in duration under propofol than under comparable doses of isoflurane. This diminished average VEP results from increased trial-to-trial variability in VEPs under propofol. One feature of single trial VEPs that was consistent in all animals was visual-evoked gamma band oscillation (20-60 Hz). This gamma band oscillation was coherent between trials in the early phase (<250 ms) of the visual evoked potential under isoflurane. Inter trial phase coherence (ITPC) of gamma oscillations was dramatically attenuated in the same propofol anesthetized mice despite similar spontaneous oscillations in the LFP. This suggests that while both anesthetics lead to loss of consciousness (LOC), elicit slow oscillations and burst suppression, only the isoflurane permits phase resetting of gamma oscillations by visual stimuli. These results demonstrate that accurate characterization of a brain state must include both spontaneous as well as stimulus-induced perturbations of brain activity.

Neuromonitoring in the elderly

PURPOSE OF REVIEW

To summarize recent recommendations on intraoperative electroencephalogram (EEG) neuromonitoring in the elderly aimed at the prevention of postoperative delirium and long-term neurocognitive decline. We discuss recent perioperative EEG investigations relating to aging and cognitive dysfunction, and their implications on intraoperative EEG neuromonitoring in elderly patients.

RECENT FINDINGS

The incidence of postoperative delirium in elderly can be reduced by monitoring depth of anesthesia, using an index number (0-100) derived from processed frontal EEG readings. The recently published European Society of Anaesthesiology guideline on postoperative delirium in elderly now recommends guiding general anesthesia with such indices (Level A). However, intraoperative EEG signatures are heavily influenced by age, cognitive function, and choice of anesthetic agents. Detailed spectral EEG analysis and research on EEG-based functional connectivity provide new insights into the pathophysiology of neuronal excitability, which is seen in elderly patients with postoperative delirium.

SUMMARY

Anesthesiologists should become acquainted with intraoperative EEG signatures and their relation to age, anesthetic agents, and the risk of postoperative cognitive complications. A working knowledge would allow an optimized and individualized provision of general anesthesia for the elderly.

Clinical signs and electroencephalographic patterns of emergence from sevoflurane anaesthesia in children: An observational study

BACKGROUND

Few studies have systematically described relationships between clinical-behavioural signs, electroencephalographic (EEG) patterns and age during emergence from anaesthesia in young children.

OBJECTIVE

To identify the relationships between end-tidal sevoflurane (ETsevoflurane) concentration, age and frontal EEG spectral properties in predicting recovery of clinical-behavioural signs during emergence from sevoflurane in children 0 to 3 years of age, with and without exposure to nitrous oxide. The hypothesis was that clinical signs occur sequentially during emergence, and that for infants aged more than 3 months, changes in alpha EEG power are correlated with clinical-behavioural signs.

DESIGN

An observational study.

SETTING

A tertiary paediatric teaching hospital from December 2012 to August 2016.

PATIENTS

Ninety-five children aged 0 to 3 years who required surgery below the neck.

OUTCOME MEASURES

Time-course of, and ETsevoflurane concentrations at first gross body movement, first cough, first grimace, dysconjugate eye gaze, frontal (F7/F8) alpha EEG power (8 to 12 Hz), frontal beta EEG power (13 to 30 Hz), surgery-end.

RESULTS

Clinical signs of emergence followed an orderly sequence of events across all ages. Clinical signs occurred over a narrow ETsevoflurane, independent of age [movement: 0.4% (95% confidence interval (CI), 0.3 to 0.4), cough 0.3% (95% CI, 0.3 to 0.4), grimace 0.2% (95% CI, 0 to 0.3); P > 0.5 for age vs. ETsevoflurane]. Dysconjugate eye gaze was observed between ETsevoflurane 1 to 0%. In children more than 3 months old, frontal alpha EEG oscillations were present at ETsevoflurane 2.0% and disappeared at 0.5%. Movement occurred within 5 min of alpha oscillation disappearance in 99% of patients. Nitrous oxide had no effect on the time course or ETsevoflurane at which children showed body movement, grimace or cough.

CONCLUSION

Several clinical signs occur sequentially during emergence, and are independent of exposure to nitrous oxide. Eye position is poorly correlated with other clinical signs or ETsevoflurane. EEG spectral characteristics may aid prediction of clinical-behavioural signs in children more than 3 months.

Phase response theory explains cluster formation in sparsely but strongly connected inhibitory neural networks and effects of jitter due to sparse connectivity

We show how to predict whether a neural network will exhibit global synchrony (a one-cluster state) or a two-cluster state based on the assumption of pulsatile coupling and critically dependent upon the phase response curve (PRC) generated by the appropriate perturbation from a partner cluster. Our results hold for a monotonically increasing (meaning longer delays as the phase increases) PRC, which likely characterizes inhibitory fast-spiking basket and cortical low-threshold-spiking interneurons in response to strong inhibition. Conduction delays stabilize synchrony for this PRC shape, whereas they destroy two-cluster states, the former by avoiding a destabilizing discontinuity and the latter by approaching it. With conduction delays, stronger coupling strength can promote a one-cluster state, so the weak coupling limit is not applicable here. We show how jitter can destabilize global synchrony but not a two-cluster state. Local stability of global synchrony in an all-to-all network does not guarantee that global synchrony can be observed in an appropriately scaled sparsely connected network; the basin of attraction can be inferred from the PRC and must be sufficiently large. Two-cluster synchrony is not obviously different from one-cluster synchrony in the presence of noise and may be the actual substrate for oscillations observed in the local field potential (LFP) and the electroencephalogram (EEG) in situations where global synchrony is not possible. Transitions between cluster states may change the frequency of the rhythms observed in the LFP or EEG. Transitions between cluster states within an inhibitory subnetwork may allow more effective recruitment of pyramidal neurons into the network rhythm. NEW & NOTEWORTHY We show that jitter induced by sparse connectivity can destabilize global synchrony but not a two-cluster state with two smaller clusters firing alternately. On the other hand, conduction delays stabilize synchrony and destroy two-cluster states. These results hold if each cluster exhibits a phase response curve similar to one that characterizes fast-spiking basket and cortical low-threshold-spiking cells for strong inhibition. Either a two-cluster or a one-cluster state might provide the oscillatory substrate for neural computations.

Multimodal assessment of recovery from coma in a rat model of diffuse brainstem tegmentum injury

Despite the association between brainstem lesions and coma, a mechanistic understanding of coma pathogenesis and recovery is lacking. We developed a coma model in the rat mimicking human brainstem coma, which allowed multimodal analysis of a brainstem tegmentum lesion's effects on behavior, cortical electrophysiology, and global brain functional connectivity. After coma induction, we observed a transient period (∼1h) of unresponsiveness accompanied by cortical burst-suppression. Comatose rats then gradually regained behavioral responsiveness concurrent with emergence of delta/theta-predominant cortical rhythms in primary somatosensory cortex. During the acute stage of coma recovery (∼1-8h), longitudinal resting-state functional MRI revealed an increase in functional connectivity between subcortical arousal nuclei in the thalamus, basal forebrain, and basal ganglia and cortical regions implicated in awareness. This rat coma model provides an experimental platform to systematically study network-based mechanisms of coma pathogenesis and recovery, as well as to test targeted therapies aimed at promoting recovery of consciousness after coma.

Role of GABAA receptor subtypes in the behavioural effects of intravenous general anaesthetics

Since the introduction of general anaesthetics into clinical practice, researchers have been mystified as to how these chemically disparate drugs act to produce their dramatic effects on central nervous system function and behaviour. Scientific advances, particularly during the last 25 years, have now begun to reveal the molecular mechanisms underpinning their behavioural effects. For certain i.v. general anaesthetics, such as etomidate and propofol, a persuasive case can now be made that the GABAA receptor, a major inhibitory receptor in the mammalian central nervous system, is an important target. Advances in molecular pharmacology and in genetic manipulation of rodent genes reveal that different subtypes of the GABAA receptor are responsible for mediating particular aspects of the anaesthetic behavioural repertoire. Such studies provide a better understanding of the neuronal circuitry involved in the various anaesthetic-induced behaviours and, in the future, may result in the development of novel therapeutics with a reduced propensity for side-effects.

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.

Mid-Latency Auditory Evoked Potentials Differentially Predict Sedation and Drug Level Under Opioid and Hypnotic Agents

Background: Auditory-evoked brain potentials (AEPs) are widely used to assess depth of the sedative component of general anesthesia. Depth of sedation as induced by hypnotic drugs (e.g., propofol) is characterized by a gradual decline of mid-latency cortical AEPs (10–50 ms). Using the decline of mid-latency AEPs as a reliable index for sedation requires its robustness against confounding pharmaceutical influences, e.g., analgesic opioids such as remifentanil. Critically, in this context the following two questions remained unresolved so far: First, it is unclear whether opioids directly affect mid-latency AEPs. Second, high doses of opioids decrease arousal, but it is unknown whether opioid-induced sedation is reflected by the diminution of mid-latency AEPs. We hypothesized that opioids affect mid-latency AEPs and that these effects rely on different mechanisms compared to hypnotic agents.

Methods: To address both questions, we performed a series of experiments under the participation of healthy human volunteers. We measured AEPs and quantified participants’ sedation state by a standardized rating scale during stepwise increase of different pharmaceutical agents (remifentanil, propofol or placebo).

Results: Our results revealed a decline of mid-latency AEPs during remifentanil medication. This decrease was predicted by drug dose, rather than sedation level. In contrast, attenuation of the mid-latency AEPs during propofol was predicted by sedation level and was not related to hypnotic drug dose. We did not find any drug-induced changes of brainstem AEPs (1–10 ms).

Conclusion: As remifentanil reduced mid-latency AEPs without inducing strong sedation levels, a decrease of this evoked brain component does not constitute an unequivocal index for the depth of sedation. These results challenge the use of mid-latency AEPs as a reliable marker of depth of the sedative component of anesthesia if hypnotic drugs are combined with opioids.

Electroencephalogram dynamics during general anesthesia predict the later incidence and duration of burst-suppression during cardiopulmonary bypass

OBJECTIVE

Electroencephalogram burst-suppression during general anesthesia is associated with post-operative delirium (POD). Whether burst-suppression causes POD or merely reflects susceptibility to POD is unclear. We hypothesized decreased intraoperative alpha (8-12 Hz) and beta (13-33 Hz) power prior to the occurrence of burst-suppression in susceptible patients.

METHODS

We analyzed intraoperative electroencephalogram data of cardiac surgical patients undergoing cardiopulmonary bypass (CPB). We detected the incidence and duration of CPB burst-suppression with an automated burst-suppression detection algorithm. We analyzed EEG data with multitaper spectral estimation methods. We assessed associations between patient characteristics and burst-suppression using Binomial and Zero-inflated Poisson Regression Models.

RESULTS

We found significantly decreased alpha and beta power (7.8-22.95 Hz) in the CPB burst-suppression cohort. The odds ratio for the association between point estimates for alpha and beta power (7.8-22.95 Hz) and the incidence of burst-suppression was 0.88 (95% CI: 0.79-0.98). The incidence rate ratio for the association between point estimates for power between the alpha and beta range and the duration of burst-suppression was 0.89 (95% CI: 0.84-0.93).

CONCLUSION

Decreased intra-operative power within the alpha and beta range was associated with susceptibility to burst-suppression during CPB.

SIGNIFICANCE

This dynamic may be used to develop principled neurophysiological-based approaches to aid the preemptive identification and targeted care of POD vulnerable patients.

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.

Brain network disintegration during sedation is mediated by the complexity of sparsely connected regions

The precise mechanism of anaesthetic action on a neural level remains unclear. Recent approaches suggest that anaesthetics attenuate the complexity of interactions (connectivity) however evidence remains insufficient. We used tools from network and information theory to show that, during propofol-induced sedation, a collection of brain regions displayed decreased complexity in their connectivity patterns, especially so if they were sparsely connected. Strikingly, we found that, despite their low connectivity strengths, these regions exhibited an inordinate role in network integration. Their location and connectivity complexity delineated a specific pattern of sparse interactions mainly involving default mode regions while their connectivity complexity during the awake state also correlated with reaction times during sedation signifying its importance as a reliable indicator of the effects of sedation on individuals. Contrary to established views suggesting sedation affects only richly connected brain regions, we propose that suppressed complexity of sparsely connected regions should be considered a critical feature of any candidate mechanistic description for loss of consciousness.

Influence of propofol on the electroencephalogram default mode network in patients of advanced age

Objective

This study was performed to evaluate the effects of propofol on the electroencephalogram (EEG) default mode network (DMN) in patients of advanced age.

Methods

Fifteen men aged >60 years (mean, 70 years) were selected. Propofol target-controlled infusion was performed under EEG bispectral index monitoring. The propofol target effect-site concentration, blood pressure, heart rate, and distributions and powers of the EEG spectrum were recorded in an awake state and under anesthesia. The EEG included seven bands: delta (0.5–3.5 Hz), theta (4.0–7.0 Hz), alpha-1 (7.5–9.5 Hz), alpha-2 (10–12 Hz), beta-1 (13–23 Hz), beta-2 (24–34 Hz), and gamma (35–45 Hz).

Results

From an awake state to anesthesia, the brain topographic map showed that the energies of delta, theta, alpha-1, alpha-2, and beta-1 were concentrated in the frontoparietal site, and the power increased significantly. The energy distribution of beta-2 was significantly decreased and the power significantly reduced. The energy distribution of gamma in the temporal lobe was also markedly decreased and the power significantly reduced.

Conclusions

This study revealed the changes in the spatial distribution and regional energy of the EEG DMD in men of advanced age from the awake state to the anesthetized state.

Propofol Anesthesia Precludes LFP-Based Functional Mapping of Pallidum during DBS Implantation

BACKGROUND/AIMS

There are reports that microelectrode recording (MER) can be performed under certain anesthetized conditions for functional confirmation of the optimal deep brain stimulation (DBS) target. However, it is generally accepted that anesthesia affects MER. Due to a potential role of local field potentials (LFPs) in DBS functional mapping, we characterized the effect of propofol on globus pallidus interna (GPi) and externa (GPe) LFPs in Parkinson disease (PD) patients.

METHODS

We collected LFPs in 12 awake and anesthetized PD patients undergoing DBS implantation. Spectral power of β (13-35 Hz) and high-frequency oscillations (HFOs: 200-300 Hz) was compared across the pallidum.

RESULTS

Propofol suppressed GPi power by > 20 Hz while increasing power at lower frequencies. A similar power shift was observed in GPe; however, power in the high β range (20-35 Hz) increased with propofol. Before anesthesia both β and HFO activity were significantly greater at the GPi (χ2 = 20.63 and χ2 = 48.81, p < 0.0001). However, during anesthesia, we found no significant difference across the pallidum (χ2 = 0.47, p = 0.79, and χ2 = 4.11, p = 0.12).

CONCLUSION

GPi and GPe are distinguishable using LFP spectral profiles in the awake condition. Propofol obliterates this spectral differentiation. Therefore, LFP spectra cannot be relied upon in the propofol-anesthetized state for functional mapping during DBS implantation.

A transient cortical state with sleep-like sensory responses precedes emergence from general anesthesia in humans

During awake consciousness, the brain intrinsically maintains a dynamical state in which it can coordinate complex responses to sensory input. How the brain reaches this state spontaneously is not known. General anesthesia provides a unique opportunity to examine how the human brain recovers its functional capabilities after profound unconsciousness. We used intracranial electrocorticography and scalp EEG in humans to track neural dynamics during emergence from propofol general anesthesia. We identify a distinct transient brain state that occurs immediately prior to recovery of behavioral responsiveness. This state is characterized by large, spatially distributed, slow sensory-evoked potentials that resemble the K-complexes that are hallmarks of stage two sleep. However, the ongoing spontaneous dynamics in this transitional state differ from sleep. These results identify an asymmetry in the neurophysiology of induction and emergence, as the emerging brain can enter a state with a sleep-like sensory blockade before regaining responsivity to arousing stimuli.

General anesthesia is essential to modern medicine. It allows physicians to temporarily keep people in an unconscious state. When infusions of the anesthetic drug stop, patients gradually recover consciousness and awaken, a process called emergence. Previous studies using recordings of electrical activity in the brain have documented spontaneous changes during anesthesia. In addition, the way the brain responds to sounds or other stimulation is altered. How the brain switches between the anesthetized and awake states is not well understood.

Studying the changes that happen during emergence may help scientists learn how the brain awakens after anesthesia. A key question is whether the changes that occur during emergence are the reverse of what happens when someone is anesthetized, or whether it is a completely different process. Knowing this could help clinicians monitoring patients under anesthesia, and help scientists understand more about how the brain transitions into the awake state.

Now, Lewis et al. show that people go through a sleep-like state right before awakening from anesthesia-induced unconsciousness. In the experiments, recordings were made of the electrical activity in the brains of people emerging from anesthesia. One set of recordings was taken in people with epilepsy, who had electrodes implanted in their brains as part of their treatment. Similar recordings of brain electrical activity during emergence were also made on healthy volunteers using electrodes placed on their scalps. In both groups of people, Lewis et al. documented large changes in electrical activity in the brain’s response to sound in the minutes before emergence.

These patterns of electrical activity during emergence were similar to those seen in patients during a normal stage of sleep (stage 2). Patients who were about to wake up from general anesthesia had suppressed brain activity in response to sounds, such as their name. Moreover, this sleep-like state happened only during emergence, indicating it is a distinct process from going under anesthesia. The experiments also suggest that the brain may use a common process to wake up after sleep or anesthesia. More studies may help scientists understand this process and how to better care for patients who need anesthesia.

Moderate sedation induced by general anaesthetics disrupts audio-spatial feature binding with sustained P3 components in healthy humans

Feature binding is considered to be the basis for conscious stimulus perception, while anaesthetics exert a gradient effect on the loss of consciousness (LOC). By integrating these two streams of research, the present study assessed the effect of two anaesthetic agents (i.e. propofol and midazolam) on audio-spatial feature binding. We also recorded the electrophysiological activity of the frontal channels. Using pharmacokinetic simulation, we determined the effect-site concentration (Ce) of the anaesthetics at loss of response to verbal command and eyelash reflex. We subsequently adjusted Ce to 75%, 50% and 25% of Ce-LOC to achieve deep, moderate and light sedation, respectively. Behavioural results showed that moderate sedation selectively disrupted feature binding. The frontal channels showed a P3 component (350-600 ms peristimulus period) following the presentation of audio-spatial stimuli at baseline and under moderate and light sedations. Critically, the late event-related potential component (600-1000 ms) returned to the pre-activated level (0-350 ms) at baseline and under light sedation but was sustained under moderate sedation. We propose that audio-spatial feature binding may require the presence of a P3 component and its subsequent and sufficient decline, as under anaesthetic-induced moderate sedation the P3 component was sustained and featured binding was impaired.

Propofol-induced Changes in α-β Sensorimotor Cortical Connectivity

BACKGROUND

Anesthetics are believed to alter functional connectivity across brain regions. However, network-level analyses of anesthesia, particularly in humans, are sparse. The authors hypothesized that propofol-induced loss of consciousness results in functional disconnection of human sensorimotor cortices underlying the loss of volitional motor responses.

METHODS

The authors recorded local field potentials from sensorimotor cortices in patients with Parkinson disease (N = 12) and essential tremor (N = 7) undergoing deep brain stimulation surgery, before and after propofol-induced loss of consciousness. Local spectral power and interregional connectivity (coherence and imaginary coherence) were evaluated separately across conditions for the two populations.

RESULTS

Propofol anesthesia caused power increases for frequencies between 2 and 100 Hz across the sensorimotor cortices and a shift of the dominant spectral peak in α and β frequencies toward lower frequencies (median ± SD peak frequency: 24.5 ± 2.6 Hz to 12.8 ± 2.3 Hz in Parkinson disease; 13.8 ± 2.1 Hz to 12.1 ± 1.0 Hz in essential tremor). Despite local increases in power, sensorimotor cortical coherence was suppressed with propofol in both cohorts, specifically in β frequencies (18 to 29 Hz) for Parkinson disease and α and β (10 to 48 Hz) in essential tremor.

CONCLUSIONS

The decrease in functional connectivity between sensory and motor cortices, despite an increase in local spectral power, suggests that propofol causes a functional disconnection of cortices with increases in autonomous activity within cortical regions. This pattern occurs across diseases evaluated, suggesting that these may be generalizable effects of propofol in patients with movement disorders and beyond. Sensorimotor network disruption may underlie anesthetic-induced loss of volitional control.

Age-Dependent Changes in the Propofol-Induced Electroencephalogram in Children With Autism Spectrum Disorder

Patients with autism spectrum disorder (ASD) often require sedation or general anesthesia. ASD is thought to arise from deficits in GABAergic signaling leading to abnormal neurodevelopment. We sought to investigate differences in how ASD patients respond to the GABAergic drug propofol by comparing the propofol-induced electroencephalogram (EEG) of ASD and neurotypical (NT) patients. This investigation was a prospective observational study. Continuous 4-channel frontal EEG was recorded during routine anesthetic care of patients undergoing endoscopic procedures between July 1, 2014 and May 1, 2016. Study patients were defined as those with previously diagnosed ASD by DSM-V criteria, aged 2-30 years old. NT patients were defined as those lacking neurological or psychiatric abnormalities, aged 2-30 years old. The primary outcome was changes in propofol-induced alpha (8-13 Hz) and slow (0.1-1 Hz) oscillation power by age. A post hoc analysis was performed to characterize incidence of burst suppression during propofol anesthesia. The primary risk factor of interest was a prior diagnosis of ASD. Outcomes were compared between ASD and NT patients using Bayesian methods. Compared to NT patients, slow oscillation power was initially higher in ASD patients (17.05 vs. 14.20 dB at 2.33 years), but progressively declined with age (11.56 vs. 13.95 dB at 22.5 years). Frontal alpha power was initially lower in ASD patients (17.65 vs. 18.86 dB at 5.42 years) and continued to decline with age (6.37 vs. 11.89 dB at 22.5 years). The incidence of burst suppression was significantly higher in ASD vs. NT patients (23.0% vs. 12.2%, p < 0.01) despite reduced total propofol dosing in ASD patients. Ultimately, we found that ASD patients respond differently to propofol compared to NT patients. A similar pattern of decreased alpha power and increased sensitivity to burst suppression develops in older NT adults; one interpretation of our data could be that ASD patients undergo a form of accelerated neuronal aging in adolescence. Our results suggest that investigations of the propofol-induced EEG in ASD patients may enable insights into the underlying differences in neural circuitry of ASD and yield safer practices for managing patients with ASD.

Different effects of propofol and dexmedetomidine sedation on electroencephalogram patterns: Wakefulness, moderate sedation, deep sedation and recovery

Sedation induces changes in electroencephalography (EEG) dynamics. However, the distinct EEG dynamic characteristics at comparable sedation levels have not been well studied, resulting in potential interpretation errors in EEG monitoring during sedation. We aimed to analyze the EEG dynamics of dexmedetomidine and propofol at comparable sedation levels and to explore EEG changes with increased sedation levels for each agent. We measured the Bispectral Index (BIS) and 20-channel EEG under dexmedetomidine and propofol sedation from wakefulness, moderate sedation, and deep sedation to recovery in healthy volunteers (n = 10) in a randomized, 2-day, crossover study. Observer's Assessment of Alertness and Sedation (OAA/S) score was used to assess sedation levels. Despite similar changes in increased delta oscillations, multiple differences in the EEG spatiotemporal dynamics were observed between these two agents. During moderate sedation, both dexmedetomidine and propofol induced increased spindle power; however, dexmedetomidine decreased the global alpha/beta/gamma power, whereas propofol decreased the alpha power in the occipital area and increased the global spindle/beta/gamma power. During deep sedation, dexmedetomidine was associated with increased fronto-central spindle power and decreased global alpha/beta/gamma power, but propofol was associated with increased theta/alpha/spindle/beta power, which was maximized in the frontal area. The transition of topographic alpha/spindle/beta power distribution from moderate sedation to deep sedation completely differed between these two agents. Our study demonstrated that there was a distinct hierarchy of EEG changes with increased sedation depths by propofol and dexmedetomidine. Differences in EEG dynamics at the same sedation level might account for differences in the BIS value and reflect the different sedation mechanisms. EEG-based clinical sedation monitoring should consider the effect of drug types on EEG dynamics.

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.

Long-range temporal correlations in the brain distinguish conscious wakefulness from induced unconsciousness

Rhythmic neuronal synchronization across large-scale networks is thought to play a key role in the regulation of conscious states. Changes in neuronal oscillation amplitude across states of consciousness have been widely reported, but little is known about possible changes in the temporal dynamics of these oscillations. The temporal structure of brain oscillations may provide novel insights into the neural mechanisms underlying consciousness. To address this question, we examined long-range temporal correlations (LRTC) of EEG oscillation amplitudes recorded during both wakefulness and anesthetic-induced unconsciousness. Importantly, the time-varying EEG oscillation envelopes were assessed over the course of a sevoflurane sedation protocol during which the participants alternated between states of consciousness and unconsciousness. Both spectral power and LRTC in oscillation amplitude were computed across multiple frequency bands. State-dependent differences in these features were assessed using non-parametric tests and supervised machine learning. We found that periods of unconsciousness were associated with increases in LRTC in beta (15-30Hz) amplitude over frontocentral channels and with a suppression of alpha (8-13Hz) amplitude over occipitoparietal electrodes. Moreover, classifiers trained to predict states of consciousness on single epochs demonstrated that the combination of beta LRTC with alpha amplitude provided the highest classification accuracy (above 80%). These results suggest that loss of consciousness is accompanied by an augmentation of temporal persistence in neuronal oscillation amplitude, which may reflect an increase in regularity and a decrease in network repertoire compared to the brain's activity during resting-state consciousness.

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.

Spectral and phase-amplitude coupling signatures in human deep brain oscillations during propofol-induced anaesthesia

BACKGROUND

Both the cerebral cortex and subcortical structures play important roles in consciousness. Some evidence points to general anaesthesia-induced unconsciousness being associated with distinct patterns of superficial cortical electrophysiological oscillations, but how general anaesthetics influence deep brain neural oscillations and interactions between oscillations in humans is poorly understood.

METHODS

Local field potentials were recorded in discrete deep brain regions, including anterior cingulate cortex, sensory thalamus, and periaqueductal grey, in humans with implanted deep brain electrodes during induction of unconsciousness with propofol. Power-frequency spectra, phase-amplitude coupling, coherence, and directed functional connectivity analysis were used to characterise local field potentials in the awake and unconscious states.

RESULTS

An increase in alpha (7-13 Hz) power and decrease in gamma (30-90 Hz) power were observed in both deep cortical (ACC, anterior cingulate cortex) and subcortical (sensory thalamus, periaqueductal grey) areas during propofol-induced unconsciousness. Robust alpha-low gamma (30-60 Hz) phase-amplitude coupling induced by general anaesthesia was observed in the anterior cingulate cortex but not in other regions studied. Moreover, alpha oscillations during unconsciousness were highly coherent within the anterior cingulate cortex, and this rhythm exhibited a bidirectional information flow between left and right anterior cingulate cortex but stronger left-to-right flow.

CONCLUSION

Propofol increases alpha oscillations and attenuates gamma oscillations in both cortical and subcortical areas. The alpha-gamma phase-amplitude coupling and the functional connectivity of alpha oscillations in the anterior cingulate cortex could be specific markers for loss of consciousness.

Sample entropy analysis for the estimating depth of anaesthesia through human EEG signal at different levels of unconsciousness during surgeries

Estimating the depth of anaesthesia (DoA) in operations has always been a challenging issue due to the underlying complexity of the brain mechanisms. Electroencephalogram (EEG) signals are undoubtedly the most widely used signals for measuring DoA. In this paper, a novel EEG-based index is proposed to evaluate DoA for 24 patients receiving general anaesthesia with different levels of unconsciousness. Sample Entropy (SampEn) algorithm was utilised in order to acquire the chaotic features of the signals. After calculating the SampEn from the EEG signals, Random Forest was utilised for developing learning regression models with Bispectral index (BIS) as the target. Correlation coefficient, mean absolute error, and area under the curve (AUC) were used to verify the perioperative performance of the proposed method. Validation comparisons with typical nonstationary signal analysis methods (i.e., recurrence analysis and permutation entropy) and regression methods (i.e., neural network and support vector machine) were conducted. To further verify the accuracy and validity of the proposed methodology, the data is divided into four unconsciousness-level groups on the basis of BIS levels. Subsequently, analysis of variance (ANOVA) was applied to the corresponding index (i.e., regression output). Results indicate that the correlation coefficient improved to 0.72 ± 0.09 after filtering and to 0.90 ± 0.05 after regression from the initial values of 0.51 ± 0.17. Similarly, the final mean absolute error dramatically declined to 5.22 ± 2.12. In addition, the ultimate AUC increased to 0.98 ± 0.02, and the ANOVA analysis indicates that each of the four groups of different anaesthetic levels demonstrated significant difference from the nearest levels. Furthermore, the Random Forest output was extensively linear in relation to BIS, thus with better DoA prediction accuracy. In conclusion, the proposed method provides a concrete basis for monitoring patients’ anaesthetic level during surgeries.

Emergence EEG pattern classification in sevoflurane anesthesia

OBJECTIVE

Significant spectral electroencephalogram (EEG) pattern characteristics exist in individual patients during the re-establishment of consciousness after general anesthesia. However, these EEG patterns cannot be quantitatively identified using commercially available depth of anesthesia (DoA) monitors. This study proposes an effective classification method and indices to classify these patterns among patients.

APPROACH

Four types of emergence EEG patterns were identified based on the EEG data set from 52 patients undergoing sevoflurane general anesthesia from two hospitals. Then, the relative power spectrum density (RPSD) of five frequency sub-bands of clinical interest (delta, theta, alpha, beta and gamma) were selected for emergence state analysis. Finally, a genetic algorithm support vector machine (GA-SVM) was used to identify the emergence EEG patterns. The performance was reported in terms of sensitivity (SE), specificity (SP) and accuracy (AC).

MAIN RESULTS

The combination of the mean and mode of RPSD in the delta and alpha band (P (delta)/P (alpha) performed the best in the GA-SVM classification. The AC indices obtained by GA-SVM across the four patterns were 90.64  ±  7.61, 81.79  ±  5.84, 82.14  ±  7.99 and 72.86  ±  11.11 respectively. Furthermore, the emergence time of the patients with EEG emergence patterns I and III increased as the patients' age increased. However, for patients with EEG emergence pattern IV, the emergence time positively correlates with the patients' age when they are under 50, and negatively correlates with it when they are over 50.

SIGNIFICANCE

The mean and mode of P (delta)/P (alpha) is a useful index to classify the different emergence EEG patterns. In addition, these patterns may correlate with an underlying neural substrate which is related to the patients' age. Highlights ► Four emergence EEG patterns were found in γ-amino-butyric acid (GABA)-ergic anesthetic drugs. ► A genetic algorithm combined with a support vector machine (GA-SVM) was proposed to identify the emergence EEG patterns. ► The relative power spectrum density (RPSD) was used as a feature to classify the emergence EEG patterns and good accuracy was achieved. ► The statistics shows that the emergence EEG patterns are age-related and may have value in assessing postoperative brain states.

Time rescaling reproduces EEG behavior during transition from propofol anesthesia-induced unconsciousness to consciousness

General anesthesia (GA) is a reversible manipulation of consciousness whose mechanism is mysterious at the level of neural networks leaving space for several competing hypotheses. We recorded electrocorticography (ECoG) signals in patients who underwent intracranial monitoring during awake surgery for the treatment of cerebral tumors in functional areas of the brain. Therefore, we recorded the transition from unconsciousness to consciousness directly on the brain surface. Using frequency resolved interferometry; we studied the intermediate ECoG frequencies (4-40 Hz). In the theoretical study, we used a computational Jansen and Rit neuron model to simulate recovery of consciousness (ROC). During ROC, we found that f increased by a factor equal to 1.62 ± 0.09, and δf varied by the same factor (1.61 ± 0.09) suggesting the existence of a scaling factor. We accelerated the time course of an unconscious EEG trace by an approximate factor 1.6 and we showed that the resulting EEG trace match the conscious state. Using the theoretical model, we successfully reproduced this behavior. We show that the recovery of consciousness corresponds to a transition in the frequency (f, δf) space, which is exactly reproduced by a simple time rescaling. These findings may perhaps be applied to other altered consciousness states.

On the Physiological Modulation and Potential Mechanisms Underlying Parieto-Occipital Alpha Oscillations

The parieto-occipital alpha (8–13 Hz) rhythm is by far the strongest spectral fingerprint in the human brain. Almost 90 years later, its physiological origin is still far from clear. In this Research Topic I review human pharmacological studies using electroencephalography (EEG) and magnetoencephalography (MEG) that investigated the physiological mechanisms behind posterior alpha. Based on results from classical and recent experimental studies, I find a wide spectrum of drugs that modulate parieto-occipital alpha power. Alpha frequency is rarely affected, but this might be due to the range of drug dosages employed. Animal and human pharmacological findings suggest that both GABA enhancers and NMDA blockers systematically decrease posterior alpha power. Surprisingly, most of the theoretical frameworks do not seem to embrace these empirical findings and the debate on the functional role of alpha oscillations has been polarized between the inhibition vs. active poles hypotheses. Here, I speculate that the functional role of alpha might depend on physiological excitation as much as on physiological inhibition. This is supported by animal and human pharmacological work showing that GABAergic, glutamatergic, cholinergic, and serotonergic receptors in the thalamus and the cortex play a key role in the regulation of alpha power and frequency. This myriad of physiological modulations fit with the view that the alpha rhythm is a complex rhythm with multiple sources supported by both thalamo-cortical and cortico-cortical loops. Finally, I briefly discuss how future research combining experimental measurements derived from theoretical predictions based of biophysically realistic computational models will be crucial to the reconciliation of these disparate findings.

DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community.

Computational Neuroscience: Mathematical and Statistical Perspectives

Mathematical and statistical models have played important roles in neuroscience, especially by describing the electrical activity of neurons recorded individually, or collectively across large networks. As the field moves forward rapidly, new challenges are emerging. For maximal effectiveness, those working to advance computational neuroscience will need to appreciate and exploit the complementary strengths of mechanistic theory and the statistical paradigm.

Actions of Propofol on Neurons in the Cerebral Cortex

Propofol is primarily a hypnotic, and is widely used for induction and maintenance of anesthesia, as well as for sedation in various medical procedures. The exact mechanisms of its action are not well understood, although its neural mechanisms have been explored in in vivo and in vitro experiments. Accumulating evidence indicates that one of the major targets of propofol is the cerebral cortex. The principal effect of propofol is considered to be the potentiation of GABA_A receptor-mediated inhibitory synaptic currents, but propofol has additional roles in modulating ion channels, including voltage-gated Na⁺ channels and several K⁺ channels. We focus on the pharmacological actions of propofol on cerebrocortical neurons, particularly at the cellular and synaptic levels.

Timescales of Intrinsic BOLD Signal Dynamics and Functional Connectivity in Pharmacologic and Neuropathologic States of Unconsciousness

Environmental events are processed on multiple timescales via hierarchical organization of temporal receptive windows (TRWs) in the brain. The dependence of neural timescales and TRWs on altered states of consciousness is unclear. States of reduced consciousness are marked by a shift toward slowing of neural dynamics (<1 Hz) in EEG/ECoG signals. We hypothesize that such prolongation of intrinsic timescales are also seen in blood-oxygen-level-dependent (BOLD) signals. To test this hypothesis, we measured the timescales of intrinsic BOLD signals using mean frequency (MF) and temporal autocorrelation (AC) in healthy volunteers (n = 23; male/female 14/9) during graded sedation with propofol. We further examined the relationship between the intrinsic timescales (local/voxel level) and its regional connectivity (across neighboring voxels; regional homogeneity, ReHo), global (whole-brain level) functional connectivity (GFC), and topographical similarity (Topo). Additional results were obtained from patients undergoing deep general anesthesia (n = 12; male/female: 5/7) and in patients with disorders of consciousness (DOC) (n = 21; male/female: 14/7). We found that MF, AC, and ReHo increased, whereas GFC and Topo decreased, during propofol sedation. The local alterations occur before changes of distant connectivity. Conversely, all of these parameters decreased in deep anesthesia and in patients with DOC. We conclude that propofol synchronizes local neuronal interactions and prolongs the timescales of intrinsic BOLD signals. These effects may impede communication among distant brain regions. Furthermore, the intrinsic timescales exhibit distinct dynamic signatures in sedation, deep anesthesia, and DOC. These results improve our understanding of the neural mechanisms of unconsciousness in pharmacologic and neuropathologic states.

SIGNIFICANCE STATEMENT Information processing in the brain occurs through a hierarchy of temporal receptive windows (TRWs) in multiple timescales. Anesthetic drugs induce a reversible suppression of consciousness and thus offer a unique opportunity to investigate the state dependence of neural timescales. Here, we demonstrate for the first time that sedation with propofol is accompanied by the prolongation of the timescales of intrinsic BOLD signals presumably reflecting enlarged TRWs. We show that this is accomplished by an increase of local and regional signal synchronization, effects that may disrupt information exchange among distant brain regions. Furthermore, we show that the timescales of intrinsic BOLD signals exhibit distinct dynamic signatures in sedation, deep anesthesia, and disorders of consciousness.

Pharmacodynamic modeling of propofol-induced general anesthesia in young adults

Target controlled infusion (TCI) of intraveneous anesthetics can assist clinical practitioners to provide improved care for General Anesthesia (GA). Pharmacokinetic/Pharmacodynamic (PK/PD) models help in relating the anesthetic drug infusion to observed brain activity inferred from electroencephalogram (EEG) signals. The parameters in popular population PK/PD models for propofol-induced GA (Marsh and Schnider models) are either verified based on proprietary functions of the EEG signal which are difficult to correlate with the neurophysiological models of anesthesia, or the marker itself needs to be estimated simultaneously with the PD model. Both these factors make these existing paradigms challenging to apply in real-time context where a patient-specific tuning of parameters is desired. In this work, we propose a simpler EEG marker from frequency domain description of EEG and develop two corresponding PK/PD modeling approaches which differ in whether they use existing population-level PK models (approach 1) or not (approach 2). We use a simple deterministic parameter estimation approach to identify the unknown PK/PD model parameters from an existing human EEG data-set. We infer that both approaches 1 and 2 yield similar and reasonably good fits to the marker data. This work can be useful in developing patient-specific TCI strategies to induce GA.

Thalamocortical control of propofol phase-amplitude coupling

The anesthetic propofol elicits many different spectral properties on the EEG, including alpha oscillations (8-12 Hz), Slow Wave Oscillations (SWO, 0.1-1.5 Hz), and dose-dependent phase-amplitude coupling (PAC) between alpha and SWO. Propofol is known to increase GABAA inhibition and decrease H-current strength, but how it generates these rhythms and their interactions is still unknown. To investigate both generation of the alpha rhythm and its PAC to SWO, we simulate a Hodgkin-Huxley network model of a hyperpolarized thalamus and corticothalamic inputs. We find, for the first time, that the model thalamic network is capable of independently generating the sustained alpha seen in propofol, which may then be relayed to cortex and expressed on the EEG. This dose-dependent sustained alpha critically relies on propofol GABAA potentiation to alter the intrinsic spindling mechanisms of the thalamus. Furthermore, the H-current conductance and background excitation of these thalamic cells must be within specific ranges to exhibit any intrinsic oscillations, including sustained alpha. We also find that, under corticothalamic SWO UP and DOWN states, thalamocortical output can exhibit maximum alpha power at either the peak or trough of this SWO; this implies the thalamus may be the source of propofol-induced PAC. Hyperpolarization level is the main determinant of whether the thalamus exhibits trough-max PAC, which is associated with lower propofol dose, or peak-max PAC, associated with higher dose. These findings suggest: the thalamus generates a novel rhythm under GABAA potentiation such as under propofol, its hyperpolarization may determine whether a patient experiences trough-max or peak-max PAC, and the thalamus is a critical component of propofol-induced cortical spectral phenomena. Changes to the thalamus may be a critical part of how propofol accomplishes its effects, including unconsciousness.

Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG

Subcortical structures play a critical role in brain function. However, options for assessing electrophysiological activity in these structures are limited. Electromagnetic fields generated by neuronal activity in subcortical structures can be recorded noninvasively, using magnetoencephalography (MEG) and electroencephalography (EEG). However, these subcortical signals are much weaker than those generated by cortical activity. In addition, we show here that it is difficult to resolve subcortical sources because distributed cortical activity can explain the MEG and EEG patterns generated by deep sources. We then demonstrate that if the cortical activity is spatially sparse, both cortical and subcortical sources can be resolved with M/EEG. Building on this insight, we develop a hierarchical sparse inverse solution for M/EEG. We assess the performance of this algorithm on realistic simulations and auditory evoked response data, and show that thalamic and brainstem sources can be correctly estimated in the presence of cortical activity. Our work provides alternative perspectives and tools for characterizing electrophysiological activity in subcortical structures in the human brain.

Spatio-temporal dynamics of multimodal EEG-fNIRS signals in the loss and recovery of consciousness under sedation using midazolam and propofol

On sedation motivated by the clinical needs for safety and reliability, recent studies have attempted to identify brain-specific signatures for tracking patient transition into and out of consciousness, but the differences in neurophysiological effects between 1) the sedative types and 2) the presence/absence of surgical stimulations still remain unclear. Here we used multimodal electroencephalography–functional near-infrared spectroscopy (EEG–fNIRS) measurements to observe electrical and hemodynamic responses during sedation simultaneously. Forty healthy volunteers were instructed to push the button to administer sedatives in response to auditory stimuli every 9–11 s. To generally illustrate brain activity at repetitive transition points at the loss of consciousness (LOC) and the recovery of consciousness (ROC), patient-controlled sedation was performed using two different sedatives (midazolam (MDZ) and propofol (PPF)) under two surgical conditions. Once consciousness was lost via sedatives, we observed gradually increasing EEG power at lower frequencies (<15 Hz) and decreasing power at higher frequencies (>15 Hz), as well as spatially increased EEG powers in the delta and lower alpha bands, and particularly also in the upper alpha rhythm, at the frontal and parieto-occipital areas over time. During ROC from unconsciousness, these spatio-temporal changes were reversed. Interestingly, the level of consciousness was switched on/off at significantly higher effect-site concentrations of sedatives in the brain according to the use of surgical stimuli, but the spatio-temporal EEG patterns were similar, regardless of the sedative used. We also observed sudden phase shifts in fronto-parietal connectivity at the LOC and the ROC as critical points. fNIRS measurement also revealed mild hemodynamic fluctuations. Compared with general anesthesia, our results provide insights into critical hallmarks of sedative-induced (un)consciousness, which have similar spatio-temporal EEG-fNIRS patterns regardless of the stage and the sedative used.

Inferring oscillatory modulation in neural spike trains

Oscillations are observed at various frequency bands in continuous-valued neural recordings like the electroencephalogram (EEG) and local field potential (LFP) in bulk brain matter, and analysis of spike-field coherence reveals that spiking of single neurons often occurs at certain phases of the global oscillation. Oscillatory modulation has been examined in relation to continuous-valued oscillatory signals, and independently from the spike train alone, but behavior or stimulus triggered firing-rate modulation, spiking sparseness, presence of slow modulation not locked to stimuli and irregular oscillations with large variability in oscillatory periods, present challenges to searching for temporal structures present in the spike train. In order to study oscillatory modulation in real data collected under a variety of experimental conditions, we describe a flexible point-process framework we call the Latent Oscillatory Spike Train (LOST) model to decompose the instantaneous firing rate in biologically and behaviorally relevant factors: spiking refractoriness, event-locked firing rate non-stationarity, and trial-to-trial variability accounted for by baseline offset and a stochastic oscillatory modulation. We also extend the LOST model to accommodate changes in the modulatory structure over the duration of the experiment, and thereby discover trial-to-trial variability in the spike-field coherence of a rat primary motor cortical neuron to the LFP theta rhythm. Because LOST incorporates a latent stochastic auto-regressive term, LOST is able to detect oscillations when the firing rate is low, the modulation is weak, and when the modulating oscillation has a broad spectral peak.

Oscillatory modulation of neural activity in the brain is widely observed under conditions associated with a variety of cognitive tasks and mental states. Within individual neurons, oscillations may be uncovered in the moment-to-moment variation in neural firing rate. This, however, is often challenging because many factors may affect fluctuations in neural firing rate and, in addition, neurons fire irregular sets of action potentials, or spike trains, due to an unknown combination of meaningful signals and extraneous noise. We have devised a statistical Latent Oscillatory Spike Train (LOST) model with accompanying model-fitting technology, that is able to detect subtle oscillations in spike trains by taking into account both spiking noise and temporal variation in the oscillation itself. The method couples two techniques developed for other purposes in the literature on Bayesian analysis. Using data simulated from theoretical neurons and real data recorded from cortical motor neurons, we demonstrate the method’s ability to track changes in the modulatory structure of the oscillation across experimental trials.