Electroencephalographic Variation during End Maintenance and Emergence from Surgical Anesthesia

The re-establishment of conscious awareness after discontinuing general anesthesia has often been assumed to be the inverse of loss of consciousness. This is despite the obvious asymmetry in the initiation and termination of natural sleep. In order to characterize the restoration of consciousness after surgery, we recorded frontal electroencephalograph (EEG) from 100 patients in the operating room during maintenance and emergence from general anesthesia. We have defined, for the first time, 4 steady-state patterns of anesthetic maintenance based on the relative EEG power in the slow-wave (<14 Hz) frequency bands that dominate sleep and anesthesia. Unlike single-drug experiments performed in healthy volunteers, we found that surgical patients exhibited greater electroencephalographic heterogeneity while re-establishing conscious awareness after drug discontinuation. Moreover, these emergence patterns could be broadly grouped according to the duration and rapidity of transitions amongst these slow-wave dominated brain states that precede awakening. Most patients progressed gradually from a pattern characterized by strong peaks of delta (0.5–4 Hz) and alpha/spindle (8–14 Hz) power (‘Slow-Wave Anesthesia’) to a state marked by low delta-spindle power (‘Non Slow-Wave Anesthesia’) before awakening. However, 31% of patients transitioned abruptly from Slow-Wave Anesthesia to waking; they were also more likely to express pain in the post-operative period. Our results, based on sleep-staging classification, provide the first systematized nomenclature for tracking brain states under general anesthesia from maintenance to emergence, and suggest that these transitions may correlate with post-operative outcomes such as pain.     

Gap junctions modulate seizures in a mean-field model of general anesthesia for the cortex

During slow-wave sleep, general anesthesia, and generalized seizures, there is an absence of consciousness. These states are characterized by low-frequency large-amplitude traveling waves in scalp electroencephalogram. Therefore the oscillatory state might be an indication of failure to form coherent neuronal assemblies necessary for consciousness. A generalized seizure event is a pathological brain state that is the clearest manifestation of waves of synchronized neuronal activity. Since gap junctions provide a direct electrical connection between adjoining neurons, thus enhancing synchronous behavior, reducing gap-junction conductance should suppress seizures; however there is no clear experimental evidence for this. Here we report theoretical predictions for a physiologically-based cortical model that describes the general anesthetic phase transition from consciousness to coma, and includes both chemical synaptic and direct electrotonic synapses. The model dynamics exhibits both Hopf (temporal) and Turing (spatial) instabilities; the Hopf instability corresponds to the slow (≲8 Hz) oscillatory states similar to those seen in slow-wave sleep, general anesthesia, and seizures. We argue that a delicately balanced interplay between Hopf and Turing modes provides a canonical mechanism for the default non-cognitive rest state of the brain. We show that the Turing mode, set by gap-junction diffusion, is generally protective against entering oscillatory modes; and that weakening the Turing mode by reducing gap conduction can release an uncontrolled Hopf oscillation and hence an increased propensity for seizure and simultaneously an increased sensitivity to GABAergic anesthesia.     

Large-Scale Information Flow in Conscious and Unconscious States: an ECoG Study in Monkeys

Consciousness is an emergent property of the complex brain network. In order to understand how consciousness is constructed, neural interactions within this network must be elucidated. Previous studies have shown that specific neural interactions between the thalamus and frontoparietal cortices; frontal and parietal cortices; and parietal and temporal cortices are correlated with levels of consciousness. However, due to technical limitations, the network underlying consciousness has not been investigated in terms of large-scale interactions with high temporal and spectral resolution. In this study, we recorded neural activity with dense electrocorticogram (ECoG) arrays and used the spectral Granger causality to generate a more comprehensive network that relates to consciousness in monkeys. We found that neural interactions were significantly different between conscious and unconscious states in all combinations of cortical region pairs. Furthermore, the difference in neural interactions between conscious and unconscious states could be represented in 4 frequency-specific large-scale networks with unique interaction patterns: 2 networks were related to consciousness and showed peaks in alpha and beta bands, while the other 2 networks were related to unconsciousness and showed peaks in theta and gamma bands. Moreover, networks in the unconscious state were shared amongst 3 different unconscious conditions, which were induced either by ketamine and medetomidine, propofol, or sleep. Our results provide a novel picture that the difference between conscious and unconscious states is characterized by a switch in frequency-specific modes of large-scale communications across the entire cortex, rather than the cessation of interactions between specific cortical regions.     

Measures of entropy and complexity in altered states of consciousness

Quantification of complexity in neurophysiological signals has been studied using different methods, especially those from information or dynamical system theory. These studies have revealed a dependence on different states of consciousness, and in particular that wakefulness is characterized by a greater complexity of brain signals, perhaps due to the necessity for the brain to handle varied sensorimotor information. Thus, these frameworks are very useful in attempts to quantify cognitive states. We set out to analyze different types of signals obtained from scalp electroencephalography (EEG), intracranial EEG and magnetoencephalography recording in subjects during different states of consciousness: resting wakefulness, different sleep stages and epileptic seizures. The signals were analyzed using a statistical (permutation entropy) and a deterministic (permutation Lempel–Ziv complexity) analytical method. The results are presented in complexity versus entropy graphs, showing that the values of entropy and complexity of the signals tend to be greatest when the subjects are in fully alert states, falling in states with loss of awareness or consciousness. These findings were robust for all three types of recordings. We propose that the investigation of the structure of cognition using the frameworks of complexity will reveal mechanistic aspects of brain dynamics associated not only with altered states of consciousness but also with normal and pathological conditions.     

The reorganization of the electrical activity of the human brain during the depression of consciousness (comatose states)

To study the problem of consciousness an original structural-functional approach has been applied with the use of possibilities of spectral-coherent EEG analysis in evaluation of human brain functional state together with the specificity of the cerebral coma having local focal belonging. It is revealed that the most informative signs for characteristics of consciousness state are peculiarities of reconstruction of intercentral relations of the electrical brain processes: decrease of mean levels of the EEG coherence at progressive development of coma; staged approach to relative norm at regressive course of comatose state and recovery of consciousness; their stability on the low level at prolonged coma; increase in low or high (above optimum) frequencies band at neighbouring with coma states of consciousness. It may be considered that one of the necessary conditions of normal state of consciousness is preservation of the optimum level of correlation of electrical brain activity alongside with frequency-regional specificity of the EEG coherence spectrum. Any deviation from the optimum is unfavourable condition for normal course of cerebral reactions because of the disturbance of intercentral connections mosaic necessary for their realization.     

How deep is the rift between conscious states in sleep and wakefulness? Spontaneous experience over the sleep–wake cycle

Whether we are awake or asleep is believed to mark a sharp divide between the types of conscious states we undergo in either behavioural state. Consciousness in sleep is often equated with dreaming and thought to be characteristically different from waking consciousness. Conversely, recent research shows that we spend a substantial amount of our waking lives mind wandering, or lost in spontaneous thoughts. Dreaming has been described as intensified mind wandering, suggesting that there is a continuum of spontaneous experience that reaches from waking into sleep. This challenges how we conceive of the behavioural states of sleep and wakefulness in relation to conscious states. I propose a conceptual framework that distinguishes different subtypes of spontaneous thoughts and experiences independently of their occurrence in sleep or waking. I apply this framework to selected findings from dream and mind-wandering research. I argue that to assess the relationship between spontaneous thoughts and experiences and the behavioural states of sleep and wakefulness, we need to look beyond dreams to consider kinds of sleep-related experience that qualify as dreamless. I conclude that if we consider the entire range of spontaneous thoughts and experiences, there appears to be variation in subtypes both within as well as across behavioural states. Whether we are sleeping or waking does not appear to strongly constrain which subtypes of spontaneous thoughts and experiences we undergo in those states. This challenges the conventional and coarse-grained distinction between sleep and waking and their putative relation to conscious states.This article is part of the theme issue ‘Offline perception: voluntary and spontaneous perceptual experiences without matching external stimulation’.     

Spontaneous Sleep-Like Brain State Alternations and Breathing Characteristics in Urethane Anesthetized Mice

Brain state alternations resembling those of sleep spontaneously occur in rats under urethane anesthesia and they are closely linked with sleep-like respiratory changes. Although rats are a common model for both sleep and respiratory physiology, we sought to determine if similar brain state and respiratory changes occur in mice under urethane. We made local field potential recordings from the hippocampus and measured respiratory activity by means of EMG recordings in intercostal, genioglossus, and abdominal muscles. Similar to results in adult rats, urethane anesthetized mice displayed quasi-periodic spontaneous forebrain state alternations between deactivated patterns resembling slow wave sleep (SWS) and activated patterns resembling rapid eye movement (REM) sleep. These alternations were associated with an increase in breathing rate, respiratory variability, a depression of inspiratory related activity in genioglossus muscle and an increase in expiratory-related abdominal muscle activity when comparing deactivated (SWS-like) to activated (REM-like) states. These results demonstrate that urethane anesthesia consistently induces sleep-like brain state alternations and correlated changes in respiratory activity across different rodent species. They open up the powerful possibility of utilizing transgenic mouse technology for the advancement and translation of knowledge regarding sleep cycle alternations and their impact on respiration.     

A Conserved Behavioral State Barrier Impedes Transitions between Anesthetic-Induced Unconsciousness and Wakefulness: Evidence for Neural Inertia

One major unanswered question in neuroscience is how the brain transitions between conscious and unconscious states. General anesthetics offer a controllable means to study these transitions. Induction of anesthesia is commonly attributed to drug-induced global modulation of neuronal function, while emergence from anesthesia has been thought to occur passively, paralleling elimination of the anesthetic from its sites in the central nervous system (CNS). If this were true, then CNS anesthetic concentrations on induction and emergence would be indistinguishable. By generating anesthetic dose-response data in both insects and mammals, we demonstrate that the forward and reverse paths through which anesthetic-induced unconsciousness arises and dissipates are not identical. Instead they exhibit hysteresis that is not fully explained by pharmacokinetics as previously thought. Single gene mutations that affect sleep-wake states are shown to collapse or widen anesthetic hysteresis without obvious confounding effects on volatile anesthetic uptake, distribution, or metabolism. We propose a fundamental and biologically conserved concept of neural inertia, a tendency of the CNS to resist behavioral state transitions between conscious and unconscious states. We demonstrate that such a barrier separates wakeful and anesthetized states for multiple anesthetics in both flies and mice, and argue that it contributes to the hysteresis observed when the brain transitions between conscious and unconscious states.     

A psychophysiological approach toward the problem of consciousness

Psychophysiological analysis of the relationship between the level of consciousness and the brain activation permitted an identification of three levels of consciousness at the transition from wakefulness to sleep. A change in the intensity and quality of involuntarily mental processes served as an index of the level of consciousness according to subjects' self-reports. It was found that a certain EEG profile corresponds to each level of consciousness under study. Data obtained showed that the lowest level of activation corresponds to a state in which a subject notes an inhibition of "internal speech", "failure of thoughts". At this case the dynamics of the EEG high frequency rhythm changes which is possibly related to the mechanism of transmission of cognitive information.     

The remote roots of consciousness in fruit‐fly selective attention?

A mechanistic study of consciousness need not be confined to human complexity. Other animals also display key behaviors and responses that have long been intimately tied to the measure of consciousness in humans. Among them are some very well-defined and measurable endpoints: selective attention, sleep and general anesthesia. That these three variables associated with changes in consciousness might exist even in a fruit-fly does not necessarily imply that a fly is "conscious", but it does suggest that some of the problems central to the field of consciousness studies could be investigated in a model organism such as Drosophila melanogaster. Demonstrating suppression of unattended stimuli, which is central to attention studies in humans, is now possible in Drosophila by measuring neural correlates of visual selection. By combining such studies with an eventual understanding of suppression in other arousal states in the fly, such as sleep and general anesthesia, we might be unraveling mechanisms relevant to consciousness as well.     

Differential effects of propofol and ketamine on critical brain dynamics

Whether the brain operates at a critical “tipping” point is a long standing scientific question, with evidence from both cellular and systems-scale studies suggesting that the brain does sit in, or near, a critical regime. Neuroimaging studies of humans in altered states of consciousness have prompted the suggestion that maintenance of critical dynamics is necessary for the emergence of consciousness and complex cognition, and that reduced or disorganized consciousness may be associated with deviations from criticality. Unfortunately, many of the cellular-level studies reporting signs of criticality were performed in non-conscious systems (in vitro neuronal cultures) or unconscious animals (e.g. anaesthetized rats). Here we attempted to address this knowledge gap by exploring critical brain dynamics in invasive ECoG recordings from multiple sessions with a single macaque as the animal transitioned from consciousness to unconsciousness under different anaesthetics (ketamine and propofol). We use a previously-validated test of criticality: avalanche dynamics to assess the differences in brain dynamics between normal consciousness and both drug-states. Propofol and ketamine were selected due to their differential effects on consciousness (ketamine, but not propofol, is known to induce an unusual state known as “dissociative anaesthesia”). Our analyses indicate that propofol dramatically restricted the size and duration of avalanches, while ketamine allowed for more awake-like dynamics to persist. In addition, propofol, but not ketamine, triggered a large reduction in the complexity of brain dynamics. All states, however, showed some signs of persistent criticality when testing for exponent relations and universal shape-collapse. Further, maintenance of critical brain dynamics may be important for regulation and control of conscious awareness.     

Preferential inhibition of frontal-to-parietal feedback connectivity is a neurophysiologic correlate of general anesthesia in surgical patients

Background

The precise mechanism and optimal measure of anesthetic-induced unconsciousness has yet to be elucidated. Preferential inhibition of feedback connectivity from frontal to parietal brain networks is one potential neurophysiologic correlate, but has only been demonstrated in animals or under limited conditions in healthy volunteers.

Methods and Findings

We recruited eighteen patients presenting for surgery under general anesthesia; electroencephalography of the frontal and parietal regions was acquired during (i) baseline consciousness, (ii) anesthetic induction with propofol or sevoflurane, (iii) general anesthesia, (iv) recovery of consciousness, and (v) post-recovery states. We used two measures of effective connectivity, evolutional map approach and symbolic transfer entropy, to analyze causal interactions of the frontal and parietal regions. The dominant feedback connectivity of the baseline conscious state was inhibited after anesthetic induction and during general anesthesia, resulting in reduced asymmetry of feedback and feedforward connections in the frontoparietal network. Dominant feedback connectivity returned when patients recovered from anesthesia. Both analytic techniques and both classes of anesthetics demonstrated similar results in this heterogeneous population of surgical patients.

Conclusions

The disruption of dominant feedback connectivity in the frontoparietal network is a common neurophysiologic correlate of general anesthesia across two anesthetic classes and two analytic measures. This study represents a key translational step from the underlying cognitive neuroscience of consciousness to more sophisticated monitoring of anesthetic effects in human surgical patients.     

The in vivo neurochemistry of the brain during general anesthesia

Anesthesia describes a complex state composed of immobility, amnesia, hypnosis (sleep or loss of consciousness), analgesia, and muscle relaxation. Bottom-up approaches explain anesthesia by an interaction of the anesthetic with receptor proteins in the brain, whereas top-down approaches consider predominantly cortical and thalamic network activity and connectivity. Both approaches have a number of explanatory gaps and as yet no unifying view has emerged. In addition to a direct interaction with primary target receptor proteins, general anesthetics have massive effects on neurotransmitter activity in the brain. They can change basal transmitter levels by interacting with neuronal activity, transmitter synthesis, release, reuptake and metabolism. By that way, they can affect a great number of neurotransmitter systems and receptors. Here, we review how different general anesthetics affect extracellular activity of neurotransmitters in the brain during induction, maintenance, and emergence from anesthesia and which functional consequences this may have. Commonalities and differences between different groups of anesthetics in their action on neurotransmitter activity are discussed. We also review how general anesthetics affect the response dynamics of the neurotransmitter systems after sensory stimulation. More than 30 years of research have now yielded a complex picture of the effects of general anesthetics on brain neurotransmitter basal activity and response dynamics. It is suggested that analyzing the effects on neurotransmitter activity is the logical next step after protein interactions in a bottom-up analysis of anesthetic action in the brain on the way to a unifying view of anesthesia.     

Possible Levels of Animal Consciousness with Reference to Grey Parrots (Psittacus erithacus)

Researchers often study nonhuman abilities by assuming theirsubjects form representations about perceived stimuli and thenprocess such information; why then would consciousness be required,and, if required, at what level? Arguments about nonhuman consciousnessrange from claims of levels comparable to humans to refutationof any need to study such phenomena. We suggest that (a) speciesexhibit different levels attuned to their ecological niches,and (b) animals, within their maximum possible level, exhibitdifferent extents of awareness appropriate to particular situations,much like humans (presumably conscious) who often act withoutconscious awareness of factors controlling their behavior. Wepropose that, to engage in complex information processing, animalslikely exhibit perceptual consciousness sensu Natsoulas (1978),i.e., are aware of what is being processed. We discuss theseissues and provide examples suggesting perceptual consciousness.     

Neuronal Avalanches Differ from Wakefulness to Deep Sleep – Evidence from Intracranial Depth Recordings in Humans

Neuronal activity differs between wakefulness and sleep states. In contrast, an attractor state, called self-organized critical (SOC), was proposed to govern brain dynamics because it allows for optimal information coding. But is the human brain SOC for each vigilance state despite the variations in neuronal dynamics? We characterized neuronal avalanches – spatiotemporal waves of enhanced activity - from dense intracranial depth recordings in humans. We showed that avalanche distributions closely follow a power law – the hallmark feature of SOC - for each vigilance state. However, avalanches clearly differ with vigilance states: slow wave sleep (SWS) shows large avalanches, wakefulness intermediate, and rapid eye movement (REM) sleep small ones. Our SOC model, together with the data, suggested first that the differences are mediated by global but tiny changes in synaptic strength, and second, that the changes with vigilance states reflect small deviations from criticality to the subcritical regime, implying that the human brain does not operate at criticality proper but close to SOC. Independent of criticality, the analysis confirms that SWS shows increased correlations between cortical areas, and reveals that REM sleep shows more fragmented cortical dynamics.     

Temporal dynamics of distinct CA1 cell populations during unconscious state induced by ketamine

Ketamine is a widely used dissociative anesthetic which can induce some psychotic-like symptoms and memory deficits in some patients during the post-operative period. To understand its effects on neural population dynamics in the brain, we employed large-scale in vivo ensemble recording techniques to monitor the activity patterns of simultaneously recorded hippocampal CA1 pyramidal cells and various interneurons during several conscious and unconscious states such as awake rest, running, slow wave sleep, and ketamine-induced anesthesia. Our analyses reveal that ketamine induces distinct oscillatory dynamics not only in pyramidal cells but also in at least seven different types of CA1 interneurons including putative basket cells, chandelier cells, bistratified cells, and O-LM cells. These emergent unique oscillatory dynamics may very well reflect the intrinsic temporal relationships within the CA1 circuit. It is conceivable that systematic characterization of network dynamics may eventually lead to better understanding of how ketamine induces unconsciousness and consequently alters the conscious mind.     

EEG-based automatic classification of 'awake' versus 'anesthetized' state in general anesthesia using Granger Causality

Background

General anesthesia is a reversible state of unconsciousness and depression of reflexes to afferent stimuli induced by administration of a “cocktail” of chemical agents. The multi-component nature of general anesthesia complicates the identification of the precise mechanisms by which anesthetics disrupt consciousness. Devices that monitor the depth of anesthesia are an important aide for the anesthetist. This paper investigates the use of effective connectivity measures from human electrical brain activity as a means of discriminating between ‘awake’ and ‘anesthetized’ state during induction and recovery of consciousness under general anesthesia.

Methodology/Principal Findings

Granger Causality (GC), a linear measure of effective connectivity, is utilized in automated classification of ‘awake’ versus ‘anesthetized’ state using Linear Discriminant Analysis and Support Vector Machines (with linear and non-linear kernel). Based on our investigations, the most characteristic change of GC observed between the two states is the sharp increase of GC from frontal to posterior regions when the subject was anesthetized, and reversal at recovery of consciousness. Features derived from the GC estimates resulted in classification of ‘awake’ and ‘anesthetized’ states in 21 patients with maximum average accuracies of 0.98 and 0.95, during loss and recovery of consciousness respectively. The differences in linear and non-linear classification are not statistically significant, implying that GC features are linearly separable, eliminating the need for a complex and computationally expensive non-linear classifier. In addition, the observed GC patterns are particularly interesting in terms of a physiological interpretation of the disruption of consciousness by anesthetics. Bidirectional interaction or strong unidirectional interaction in the presence of a common input as captured by GC are most likely related to mechanisms of information flow in cortical circuits.

Conclusions/Significance

GC-based features could be utilized effectively in a device for monitoring depth of anesthesia during surgery.     

Improving the clinical assessment of consciousness with advances in electrophysiological and neuroimaging techniques

In clinical neurology, a comprehensive understanding of consciousness has been regarded as an abstract concept - best left to philosophers. However, times are changing and the need to clinically assess consciousness is increasingly becoming a real-world, practical challenge. Current methods for evaluating altered levels of consciousness are highly reliant on either behavioural measures or anatomical imaging. While these methods have some utility, estimates of misdiagnosis are worrisome (as high as 43%) - clearly this is a major clinical problem. The solution must involve objective, physiologically based measures that do not rely on behaviour. This paper reviews recent advances in physiologically based measures that enable better evaluation of consciousness states (coma, vegetative state, minimally conscious state, and locked in syndrome). Based on the evidence to-date, electroencephalographic and neuroimaging based assessments of consciousness provide valuable information for evaluation of residual function, formation of differential diagnoses, and estimation of prognosis.     

The effects of barbiturates upon the hemodynamic responses to intravenous methionine-enkephalin in dogs: modulation by the GABA complex

In conscious animals, the intravenous administration of enkephalins increases heart rate (HR) and mean systemic arterial blood pressure (MAP); however, when given during barbiturate anesthesia, enkephalins reduce HR and MAP. We have investigated the potential role of the gamma-aminobutyric acid (GABA) complex (consisting of chloride-ion channel and binding sites for GABA, benzodiazepine, and barbiturate/picrotoxin) as the site of modulation of enkephalin responses by certain anesthetic agents in our chronically instrumented dog model. In our model, methionine-enkephalin (Met5-ENK) (35 micrograms/kg intravenously) increased HR and MAP, but following induction of general anesthesia with barbiturate (pentobarbital) or of sedation with benzodiazepine (diazepam), Met5-ENK produced vasodepressor responses despite differing levels of consciousness in the treated animals. Subsequent administration of picrotoxin restored pressor responses to Met5-ENK in the barbiturate-treated dogs, but not in those treated with benzodiazepine; picrotoxin did not alter the level of consciousness. Picrotoxin had no effect upon Met5-ENK responses in the conscious state. In contrast, alpha-chloralose, a convulsive anesthetic agent which does not appear to alter GABA complex activity, blunted but did not reverse pressor responses to Met5-ENK, despite causing a level of anesthesia similar to that produced by barbiturate. The observed pressor response to Met5-ENK during alpha-chloralose anesthesia was totally inhibited by naloxone, indicating that this response was still mediated by opiate receptors. Our data are compatible with modulation of enkephalin responses by GABA complex activity. Systemic enkephalins may generate afferent signals which may subsequently undergo GABA complex processing; the state of activation of the GABA complex may then determine whether systemic enkephalin signals are translated as vasopressor or vasodepressor responses.