Neurophysiologic Correlates of Ketamine Sedation and Anesthesia: A High-density Electroencephalography Study in Healthy Volunteers

Electroencephalographic slow wave dynamics and loss of behavioural responsiveness induced by ketamine in human volunteers

BACKGROUND

Previous work on the electroencephalographic (EEG) effects of anaesthetic doses of ketamine has identified a characteristic signature of increased high frequency (beta-gamma) and theta waves alternating with episodic slow waves. It is unclear which EEG parameter is optimal for pharmacokinetic-pharmacodynamic modelling of the hypnotic actions of ketamine, or which EEG parameter is most closely linked to loss of behavioural responsiveness.

METHODS

We re-analysed previously published 128-channel scalp EEG data from 15 subjects who had received a 1.5 mg kg^-1 bolus i.v. dose of ketamine. We applied standard sigmoid pharmacokinetic-pharmacodynamic models to the drug-induced changes in slow wave activity, theta, and beta-gamma EEG power; and examined the morphology of the slow waves in the time domain for Fz, F3, T3, P3, and Pz average-referenced channels.

RESULTS

Hypnotic doses of ketamine i.v. induced medio-frontal EEG slow waves, and loss of behavioural response when the estimated brain concentration was 1.64 (0.17) μg ml^-1. Recovery of responsiveness occurred at 1.06 (0.21) μg.ml^-1 after slow wave activity had markedly diminished. Pharmacokinetic-pharmacodynamic modelling fitted best to the slow wave activity and theta power (almost half the beta-gamma channels could not be modelled). Slow wave effect-site equilibration half-time (23 [4] s), and offset, was faster than for theta (47 [22] s).

CONCLUSIONS

Changes in EEG slow wave activity after a hypnotic dose of ketamine could be fitted by a standard sigmoid dose-response model. Their onset, but not their offset, was consistently associated with loss of behavioural response in our small study group.

General Anesthesia: A Probe to Explore Consciousness

General anesthesia reversibly alters consciousness, without shutting down the brain globally. Depending on the anesthetic agent and dose, it may produce different consciousness states including a complete absence of subjective experience (unconsciousness), a conscious experience without perception of the environment (disconnected consciousness, like during dreaming), or episodes of oriented consciousness with awareness of the environment (connected consciousness). Each consciousness state may potentially be followed by explicit or implicit memories after the procedure. In this respect, anesthesia can be considered as a proxy to explore consciousness. During the recent years, progress in the exploration of brain function has allowed a better understanding of the neural correlates of consciousness, and of their alterations during anesthesia. Several changes in functional and effective between-region brain connectivity, consciousness network topology, and spatio-temporal dynamics of between-region interactions have been evidenced during anesthesia. Despite a set of effects that are common to many anesthetic agents, it is still uneasy to draw a comprehensive picture of the precise cascades during general anesthesia. Several questions remain unsolved, including the exact identification of the neural substrate of consciousness and its components, the detection of specific consciousness states in unresponsive patients and their associated memory processes, the processing of sensory information during anesthesia, the pharmacodynamic interactions between anesthetic agents, the direction-dependent hysteresis phenomenon during the transitions between consciousness states, the mechanisms of cognitive alterations that follow an anesthetic procedure, the identification of an eventual unitary mechanism of anesthesia-induced alteration of consciousness, the relationship between network effects and the biochemical or sleep-wake cycle targets of anesthetic agents, as well as the vast between-studies variations in dose and administration mode, leading to difficulties in between-studies comparisons. In this narrative review, we draw the picture of the current state of knowledge in anesthesia-induced unconsciousness, from insights gathered on propofol, halogenated vapors, ketamine, dexmedetomidine, benzodiazepines and xenon. We also describe how anesthesia can help understanding consciousness, we develop the above-mentioned unresolved questions, and propose tracks for future research.

Anesthetics Have Different Effects on the Electrocorticographic Spectra of Wild-type and Mitochondrial Mutant Mice

WHAT WE ALREADY KNOW ABOUT THIS TOPIC

WHAT THIS ARTICLE TELLS US THAT IS NEW: BACKGROUND:: Knockout of the mitochondrial protein Ndufs4 (Ndufs4[KO]) in mice causes hypersensitivity to volatile anesthetics but resistance to ketamine. The authors hypothesized that electrocorticographic changes underlying the responses of Ndufs4(KO) to volatile anesthetics and to ketamine would be similar in mutant and control mice.

METHODS

Electrocorticographic recordings at equipotent volatile anesthetic concentrations were compared between genotypes. In separate studies, control and cell type-specific Ndufs4(KO) mice were anesthetized with intraperitoneal ketamine to determine their ED50s.

RESULTS

Ndufs4 (KO) did not differ from controls in baseline electrocorticography (N = 5). Compared to baseline, controls exposed to isoflurane (EC50) lost power (expressed as mean baseline [µV/Hz]; mean isoflurane [µV/Hz]) in delta (2.45; 0.50), theta (1.41; 0.16), alpha (0.23; 0.05), beta (0.066; 0.016), and gamma (0.020; 0.005) frequency bands (N = 5). Compared to baseline, at their isoflurane EC50, Ndufs4(KO) maintained power in delta (1.08; 1.38), theta (0.36; 0.26), and alpha (0.09; 0.069) frequency bands but decreased in beta (0.041; 0.023) and gamma (0.020; 0.0068) frequency bands (N = 5). Similar results were seen for both genotypes in halothane. Vesicular glutamate transporter 2 (VGLUT2)-specific Ndufs4(KO) mice were markedly resistant to ketamine (ED50; 125 mg/kg) compared to control mice (ED50; 75 mg/kg; N = 6). At their respective ED95s for ketamine, mutant (N = 5) electrocorticography spectra showed a decrease in power in the beta (0.040; 0.020) and gamma (0.035; 0.015) frequency bands not seen in controls (N = 7).

CONCLUSIONS

Significant differences exist between the electrocorticographies of mutant and control mice at equipotent doses for volatile anesthetics and ketamine. The energetic state specifically of excitatory neurons determines the behavioral response to ketamine.

Auditory Steady State Response; nature and utility as a translational science tool

The auditory steady-state response (ASSR) has been used to detect auditory processing deficits in patients with psychiatric disorders. However, the methodology of ASSR recording from the brain surface has not been standardized in preclinical studies, limiting its use as a translational biomarker. The sites of maximal ASSR in humans are the vertex and/or middle frontal area, although it has been suggested that the auditory cortex is the source of the ASSR. We constructed and validated novel methods for ASSR recording using a switchable pedestal which allows ASSR recording alternatively from temporal or parietal cortex with a wide range of frequencies in freely moving rats. We further evaluated ASSR as a translational tool by assessing the effect of ketamine. The ASSR measured at parietal cortex did not show clear event-related spectral perturbation (ERSP) or inter-trial coherence (ITC) in any frequency bands or a change with ketamine. In contrast, the ASSR at temporal cortex showed clear ERSP and ITC where 40 Hz was maximal in both gamma-band frequencies. Ketamine exerted a biphasic effect in ERSP at gamma bands. These findings suggest that temporal cortex recording with a wide frequency range is a robust methodology to detect ASSR, potentially enabling application as a translational biomarker in psychiatric and developmental disorders.

Understanding the Effects of General Anesthetics on Cortical Network Activity Using Ex Vivo Preparations

General anesthetics have been used to ablate consciousness during surgery for more than 150 yr. Despite significant advances in our understanding of their molecular-level pharmacologic effects, comparatively little is known about how anesthetics alter brain dynamics to cause unconsciousness. Consequently, while anesthesia practice is now routine and safe, there are many vagaries that remain unexplained. In this paper, the authors review the evidence that cortical network activity is particularly sensitive to general anesthetics, and suggest that disruption to communication in, and/or among, cortical brain regions is a common mechanism of anesthesia that ultimately produces loss of consciousness. The authors review data from acute brain slices and organotypic cultures showing that anesthetics with differing molecular mechanisms of action share in common the ability to impair neurophysiologic communication. While many questions remain, together, ex vivo and in vivo investigations suggest that a unified understanding of both clinical anesthesia and the neural basis of consciousness is attainable.

Dynamic Cortical Connectivity during General Anesthesia in Healthy Volunteers

Editor’s Perspective

What We Already Know about This Topic

What This Article Tells Us That Is New

Background

Recent studies of anesthetic-induced unconsciousness in healthy volunteers have focused on functional brain connectivity patterns, but the protocols rarely parallel the depth and duration of surgical anesthesia. Furthermore, it is unknown whether there is a single functional connectivity pattern that correlates with general anesthesia for the duration of prolonged anesthetic exposure.

Methods

The authors analyzed electroencephalographic data in 30 healthy participants who underwent induction of anesthesia with propofol followed by 3 h of isoflurane anesthesia at age-adjusted 1.3 minimum alveolar concentration. Functional connectivity was assessed by frequency-resolved weighted phase lag index between frontal and parietal channels and between prefrontal and frontal channels, which were classified into a discrete set of states through k-means cluster analysis. Temporal dynamics were evaluated by the occurrence rate and dwell time distribution for each state as well as the transition probabilities between states.

Results

Burst suppression was present, with mean suppression ratio reducing from 44.8 ± 32.3% to 14.0 ± 20.2% (mean ± SD) during isoflurane anesthesia (P < 0.001). Aside from burst suppression, eight connectivity states were classified by optimizing the reproducibility of clustering solutions, with each characterized by distinct properties. The temporal progression of dominant states revealed a successive shifting trajectory from the state associated with alpha frontal-parietal connectivity to those associated with delta and alpha prefrontal-frontal connectivity during induction, which was reversed during emergence. Cortical connectivity was dynamic during maintenance period, and it was more probable to remain in the same state (82.0 ± 8.3%) than to switch to a different state (P < 0.001). However, transitions to other states were structured, i.e., occurred more frequently than expected by chance.

Conclusions

Anesthesia-induced alterations of functional connectivity are dynamic despite the stable and prolonged administration of isoflurane, in the absence of any noxious stimuli. Changes in connectivity over time will likely yield more information as a marker or mechanism of surgical anesthesia than any single pattern.

Cortical dynamics during psychedelic and anesthetized states induced by ketamine

Ketamine is a unique drug that has psychedelic and anesthetic properties in a dose-dependent manner. Recent studies have shown that ketamine anesthesia appears to maintain the spatiotemporal complexity of cortical activation evoked by transcranial magnetic stimulation, while a psychedelic dose of ketamine is associated with increased spontaneous magnetoencephalographic signal diversity. However, a systematic investigation of the dose-dependent effects of ketamine on cortical complexity using the same modality is required. Furthermore, it is unknown whether the complexity level stabilizes or fluctuates over time for the duration of ketamine exposure. Here we investigated the spatiotemporal complexity of spontaneous high-density scalp electroencephalography (EEG) signals in healthy volunteers during alterations of consciousness induced by both subanesthetic and anesthetic doses of ketamine. Given the fast transient spectral dynamics, especially during the gamma-burst pattern after loss of consciousness, we employed a method based on Hidden Markov modeling to classify the EEG signals into a discrete set of brain states that correlated with different behavioral states. We characterized the spatiotemporal complexity specific for each brain state as measured through the Lempel-Ziv complexity algorithm. After controlling for signal diversity due to spectral changes, we found that the subanesthetic dose of ketamine is associated with an elevated complexity level relative to baseline, while the brain activity following an anesthetic dose of ketamine is characterized by alternating low and high complexity levels until stabilizing at a high level comparable to that during baseline. Thus, spatiotemporal complexity associated with ketamine-induced state transitions has features of general anesthesia, normal consciousness, and altered states of consciousness. These results improve our understanding of the complex pharmacological, neurophysiological, and phenomenological properties of ketamine.

Analysis of 17 948 pediatric patients undergoing procedural sedation with a combination of intranasal dexmedetomidine and ketamine

BACKGROUND

Intranasal procedural sedation using dexmedetomidine is well described in the literature. The combination of intranasal dexmedetomidine and ketamine is a novel approach for which there are little data on the rate of successful sedation or adverse events.

OBJECTIVES

The aim of this study is to evaluate the rate of successful sedation and adverse events of intranasal procedural sedation using a combination of dexmedetomidine and ketamine for diagnostic examination in children.

METHODS

This was a retrospective study and data were collected after ethics approval. A total of 17 948 pediatric patients (7718 females, 10 230 males) in a tertiary hospital in China were evaluated. Patients received a combination of 2 μg kg^-1 of dexmedetomidine and 1 mg kg^-1 of ketamine intranasally for procedural sedation. The level of sedation and recovery was assessed by the Modified Observer Assessment of Alertness/Sedation scale and the Modified Aldrete Score.

RESULTS

The rate of intranasal sedation success was 93% (16691/17948), intranasal sedation rescue was 1.8% (322/17948), and intranasal sedation failure was 5.2% (935/17948). Sedation success was defined as successful completed the diagnostic examination and obtained adequate diagnostic-quality images and reports. Intranasal sedation success, rescue and failure were respectively defined as sedation success with intranasal a single dose, additional bolus dose and the need for intravenous (IV) medications/inhalation agents. Median sedation time was 62 min (interquartile range: 55-70 min), median time for onset of sedation was 15 min (interquartile range: 15-20 min), and median sedation recovery time was 45 min (interquartile range: 38-53 min). Incidence of adverse events was low (0.58%; 105/17948), with major and minor adverse event being reported in 0.02% (4/17948) and 0.56% (101/17948) patients, respectively. Postoperative nausea and vomiting was the most common (0.3%; 53/17948) minor adverse event.

CONCLUSION

Procedural sedation using a combination of intranasal dexmedetomidine and ketamine is associated with acceptable effectiveness and low rates of adverse events.

Measuring depth of anaesthesia using changes in directional connectivity: a comparison with auditory middle latency response and estimated bispectral index during propofol anaesthesia

General anaesthesia is associated with changes in connectivity between different regions of the brain, the assessment of which has the potential to provide a novel marker of anaesthetic effect. We propose an index that quantifies the strength and direction of information flow in electroencephalographic signals collected across the scalp, assess its performance in discriminating 'wakefulness' from 'anaesthesia', and compare it with estimated bispectral index and the auditory middle latency response. We used a step-wise slow induction of anaesthesia in 10 patients to assess graded changes in electroencephalographic directional connectivity at propofol effect-site concentrations of 2 μg.ml^-1 , 3 μg.ml^-1 and 4 μg.ml^-1 . For each stable effect-site concentration, connectivity was estimated from multichannel electroencephalograms using directed coherence, together with middle latency response and estimated bispectral index. We used a linear support vector machine classifier to compare the performance of the different electroencephalographic features in discriminating wakefulness from anaesthesia. We found a significant reduction in the strength of long-range connectivity (interelectrode distance > 10 cm) (p < 0.008), and a reversal of information flow from markedly postero-frontal to fronto-posterior (p < 0.006) between wakefulness and a propofol effect-site concentration of 2 μg.ml^-1 . This then remained relatively constant as effect-site concentration increased, consistent with a step change in directed coherence with anaesthesia. This contrasted with the gradual change with increasing anaesthetic dose observed for estimated bispectral index and middle latency response. Directed coherence performed best in discriminating wakefulness from anaesthesia with an accuracy of 95%, indicating the potential of this new method (on its own or combined with others) for monitoring adequacy of anaesthesia.

Role of Network Science in the Study of Anesthetic State Transitions

The heterogeneity of molecular mechanisms, target neural circuits, and neurophysiologic effects of general anesthetics makes it difficult to develop a reliable and drug-invariant index of general anesthesia. No single brain region or mechanism has been identified as the neural correlate of consciousness, suggesting that consciousness might emerge through complex interactions of spatially and temporally distributed brain functions. The goal of this review article is to introduce the basic concepts of networks and explain why the application of network science to general anesthesia could be a pathway to discover a fundamental mechanism of anesthetic-induced unconsciousness. This article reviews data suggesting that reduced network efficiency, constrained network repertoires, and changes in cortical dynamics create inhospitable conditions for information processing and transfer, which lead to unconsciousness. This review proposes that network science is not just a useful tool but a necessary theoretical framework and method to uncover common principles of anesthetic-induced unconsciousness.

Mechanisms of hysteresis in human brain networks during transitions of consciousness and unconsciousness: Theoretical principles and empirical evidence

Hysteresis, the discrepancy in forward and reverse pathways of state transitions, is observed during changing levels of consciousness. Identifying the underlying mechanism of hysteresis phenomena in the brain will enhance the ability to understand, monitor, and control state transitions related to consciousness. We hypothesized that hysteresis in brain networks shares the same underlying mechanism of hysteresis as other biological and non-biological networks. In particular, we hypothesized that the principle of explosive synchronization, which can mediate abrupt state transitions, would be critical to explaining hysteresis in the brain during conscious state transitions. We analyzed high-density electroencephalogram (EEG) that was acquired in healthy human volunteers during conscious state transitions induced by the general anesthetics sevoflurane or ketamine. We developed a novel method to monitor the temporal evolution of EEG networks in a parameter space, which consists of the strength and topography of EEG-based networks. Furthermore, we studied conditions of explosive synchronization in anatomically informed human brain network models. We identified hysteresis in the trajectory of functional brain networks during state transitions. The model study and empirical data analysis explained various hysteresis phenomena during the loss and recovery of consciousness in a principled way: (1) more potent anesthetics induce a larger hysteresis; (2) a larger range of EEG frequencies facilitates transitions into unconsciousness and impedes the return of consciousness; (3) hysteresis of connectivity is larger than that of EEG power; and (4) the structure and strength of functional brain networks reconfigure differently during the loss vs. recovery of consciousness. We conclude that the hysteresis phenomena observed during the loss and recovery of consciousness are generic network features. Furthermore, the state transitions are grounded in the same principle as state transitions in complex non-biological networks, especially during perturbation. These findings suggest the possibility of predicting and modulating hysteresis of conscious state transitions in large-scale brain networks.

Hysteresis, characterized by distinct forward and reverse phase transitions, is ubiquitous in nature. For example, there are distinct temperatures for water freezing and ice melting. Similarly, it has been found that state transitions related to consciousness exhibit hysteresis. In particular, the concentration of general anesthetics required to achieve loss of consciousness is significantly higher than the concentration at which consciousness is regained. However, it is unknown whether this is trivially reducible to the pharmacology of these drugs or if it is something related to brain function itself. In this study, we took a novel, network-based approach and hypothesized that the hysteresis observed during anesthetic state transitions shares the same underlying mechanism as that observed in non-biological networks. Our computational modeling, analytic study, and high-density human EEG analysis suggest that various hysteresis phenomena during loss and recovery of consciousness can be explained in principled ways by generic network features. Identifying these network mechanisms of hysteresis in the brain also provides a unified framework for understanding the radically different conscious state transitions associated with sleep, anesthesia, and disorders of consciousness.

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.

Subanaesthetic ketamine and altered states of consciousness in humans

BACKGROUND

Despite its designation as a 'dissociative anaesthetic,' the dissociative and psychoactive effects of ketamine remain incompletely understood. The goal of this study was to characterise the subjective experiences and accompanying EEG changes with subanaesthetic doses of ketamine.

METHODS

High-density EEG was recorded in 15 human volunteers before, during, and after subanaesthetic ketamine infusion (0.5 mg kg^-1 over 40 min), with self-reported measures of altered states of consciousness obtained after ketamine exposure. Sensor- and source-level EEG changes were analysed with a focus on spectral power and regional changes.

RESULTS

Ketamine-induced altered states were characterised predominantly by dissociative experiences such as disembodiment and ego transcendence; sensory disturbances were also common. Ketamine broadly decreased low-frequency power, with mean reductions largest at alpha (8-12 Hz) in parietal (-0.94 dB, P<0.001) and occipital (-1.8 dB, P<0.001) channel clusters. Significant decreases in alpha were identified in the precuneus and temporal-parietal junction.

CONCLUSIONS

Ketamine induces altered states of consciousness during periods of reduced alpha power in the precuneus and temporal-parietal junction. Modulation of these temporal-parietal loci are candidate mechanisms of the psychoactive effects of ketamine, given that this region is involved in multisensory integration, body representation, and consciousness.

Gamma band oscillations in the early phase of psychosis: A systematic review

Abnormal gamma oscillations, measured by electroencephalography (EEG), have been associated with chronic psychotic disorders, but their prevalence in the early phase of psychosis is less clear. We sought to address this by systematically reviewing the relevant literature. We searched for EEG studies of gamma band oscillations in subjects at high risk for psychosis and in patients with first episode psychosis. The following measures of gamma oscillations were extracted: resting power, evoked power, induced power, connectivity and peak frequency. Forty-five studies with a total of 3099 participants were included. There were potential sources of bias in the study designs and potential artefacts. Although there were few consistent findings, several studies reported decreased evoked or induced power in both high risk subjects and first episode patients. Studies using larger samples with serial EEG measurements, and designs that minimise artefacts that occur at the gamma frequency may advance work in this area.

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.

Neural Correlates of Unconsciousness in Large-Scale Brain Networks

The biological basis of consciousness is one of the most challenging and fundamental questions in 21st century science. A related pursuit aims to identify the neural correlates and causes of unconsciousness. We review current trends in the investigation of physiological, pharmacological, and pathological states of unconsciousness at the level of large-scale functional brain networks. We focus on the roles of brain connectivity, repertoire, graph-theoretical techniques, and neural dynamics in understanding the functional brain disconnections and reduced complexity that appear to characterize these states. Persistent questions in the field, such as distinguishing true correlates, linking neural scales, and understanding differential recovery patterns, are also addressed.

Estimating the Integrated Information Measure Phi from High-Density Electroencephalography during States of Consciousness in Humans

The integrated information theory (IIT) proposes a quantitative measure, denoted as Φ, of the amount of integrated information in a physical system, which is postulated to have an identity relationship with consciousness. IIT predicts that the value of Φ estimated from brain activities represents the level of consciousness across phylogeny and functional states. Practical limitations, such as the explosive computational demands required to estimate Φ for real systems, have hindered its application to the brain and raised questions about the utility of IIT in general. To achieve practical relevance for studying the human brain, it will be beneficial to establish the reliable estimation of Φ from multichannel electroencephalogram (EEG) and define the relationship of Φ to EEG properties conventionally used to define states of consciousness. In this study, we introduce a practical method to estimate Φ from high-density (128-channel) EEG and determine the contribution of each channel to Φ. We examine the correlation of power, frequency, functional connectivity, and modularity of EEG with regional Φ in various states of consciousness as modulated by diverse anesthetics. We find that our approximation of Φ alone is insufficient to discriminate certain states of anesthesia. However, a multi-dimensional parameter space extended by four parameters related to Φ and EEG connectivity is able to differentiate all states of consciousness. The association of Φ with EEG connectivity during clinically defined anesthetic states represents a new practical approach to the application of IIT, which may be used to characterize various physiological (sleep), pharmacological (anesthesia), and pathological (coma) states of consciousness in the human brain.