Disconnecting Consciousness: Is There a Common Anesthetic End Point?

Regional entropy of functional imaging signals varies differently in sensory and cognitive systems during propofol-modulated loss and return of behavioral responsiveness

The level and richness of consciousness depend on information integration in the brain. Altered interregional functional interactions may indicate disrupted information integration during anesthetic-induced unconsciousness. How anesthetics modulate the amount of information in various brain regions has received less attention. Here, we propose a novel approach to quantify regional information content in the brain by the entropy of the principal components of regional blood oxygen-dependent imaging signals during graded propofol sedation. Fifteen healthy individuals underwent resting-state scans in wakeful baseline, light sedation (conscious), deep sedation (unconscious), and recovery (conscious). Light sedation characterized by lethargic behavioral responses was associated with global reduction of entropy in the brain. Deep sedation with completely suppressed overt responsiveness was associated with further reductions of entropy in sensory (primary and higher sensory plus orbital prefrontal cortices) but not high-order cognitive (dorsal and medial prefrontal, cingulate, parietotemporal cortices and hippocampal areas) systems. Upon recovery of responsiveness, entropy was restored in the sensory but not in high-order cognitive systems. These findings provide novel evidence for a reduction of information content of the brain as a potential systems-level mechanism of reduced consciousness during propofol anesthesia. The differential changes of entropy in the sensory and high-order cognitive systems associated with losing and regaining overt responsiveness are consistent with the notion of "disconnected consciousness", in which a complete sensory-motor disconnection from the environment occurs with preserved internal mentation.

Propofol Sedation Alters Perceptual and Cognitive Functions in Healthy Volunteers as Revealed by Functional Magnetic Resonance Imaging

BACKGROUND

Elucidating networks underlying conscious perception is important to understanding the mechanisms of anesthesia and consciousness. Previous studies have observed changes associated with loss of consciousness primarily using resting paradigms. The authors focused on the effects of sedation on specific cognitive systems using task-based functional magnetic resonance imaging. The authors hypothesized deepening sedation would degrade semantic more than perceptual discrimination.

METHODS

Discrimination of pure tones and familiar names were studied in 13 volunteers during wakefulness and propofol sedation targeted to light and deep sedation. Contrasts highlighted specific cognitive systems: auditory/motor (tones vs. fixation), phonology (unfamiliar names vs. tones), and semantics (familiar vs. unfamiliar names), and were performed across sedation conditions, followed by region of interest analysis on representative regions.

RESULTS

During light sedation, the spatial extent of auditory/motor activation was similar, becoming restricted to the superior temporal gyrus during deep sedation. Region of interest analysis revealed significant activation in the superior temporal gyrus during light (t [17] = 9.71, P < 0.001) and deep sedation (t [19] = 3.73, P = 0.001). Spatial extent of the phonologic contrast decreased progressively with sedation, with significant activation in the inferior frontal gyrus maintained during light sedation (t [35] = 5.17, P < 0.001), which didn't meet criteria for significance in deep sedation (t [38] = 2.57, P = 0.014). The semantic contrast showed a similar pattern, with activation in the angular gyrus during light sedation (t [16] = 4.76, P = 0.002), which disappeared in deep sedation (t [18] = 0.35, P = 0.731).

CONCLUSIONS

Results illustrate broad impairment in cognitive cortex during sedation, with activation in primary sensory cortex beyond loss of consciousness. These results agree with clinical experience: a dose-dependent reduction of higher cognitive functions during light sedation, despite partial preservation of sensory processes through deep sedation.

Combined Monitoring-Brain Function Monitoring and Cerebral Oximetry

Peri-operative brain function monitoring is still seen by most clinicians as complex, difficult to interpret and is therefore adopted very slowly. Current available technology mainly focusses on either a processed parameter based on the electroencephalogram to titrate anesthetics and central acting agents or on cerebral oximetry, a wider term to obtain information on the cerebral oxygen balance. There is still a lack of technological offerings that allow to monitor both entities in one device. However, there is scientific evidence that it is possible to combine measurements in an algorithmic approach that allows to better manage brain function in the surgical setting. Such integrated solutions should be made available to clinicians as they are likely to optimize patient care dependent on a sound health technology assessment.

Inhibitory actions of general anesthetics on hippocampal CA1 neurons modified by activation of amygdala circuitry are demonstrated on the novel amygdala-hippocampal slice preparation

In order to examine effects of general anesthetics on hippocampal synaptic transmission in the absence and presence of amygdala circuitry activation, we have developed a unique amygdala-hippocampal slice preparation in which projections between amygdala and hippocampal CA1 are conserved. Stimulating electrodes were placed in radiatum stratum (Rad) to stimulate CA1, and in amygdala-hippocampal area (AH) to simulate amygdala inputs to hippocampus. Two sets of extracellular recording microelectrodes were positioned in cell bodies and dendrites of CA1 to record population spikes (PSs) and excitatory post-synaptic potentials (EPSPs), respectively. Intravenous anesthetics did not elicit consistent effects on PS and EPSP following a test stimulus on Rad. A pre-pulse of AH in addition to a test-pulse on Rad produced significant reduction of PS amplitude without a change in EPSP. Pre-treatment with tetanus-pulse on AH reversed the anesthetic-induced reduction of PS. The results suggest that inhibitory actions of general anesthetics in CA1 can be modified by activation of amygdala, suggesting that preoperative anxiety and fear could modify anesthetic actions. The modification was more prominent in the presence of intravenous anesthetics than with volatile agents.

Recreational use of GHB is associated with alterations of resting state functional connectivity of the central executive and default mode networks

Gamma-hydroxybutyrate acid (GHB) is a recreational drug with a high addictive potential. Severe side effects such as GHB-induced coma are common and linked to increased emergency room attendances. Task-based functional-imaging studies have revealed an association between the regular use of GHB and multiple GHB-induced comas, and altered neurocognitive function. However the effects of multiple GHB-induced comas and regular GHB-use on intrinsic brain connectivity during rest remain unknown. The study population consisted of 23 GHB-users with ≥4 GHB-induced comas (GHB-Coma), 22 GHB-users who never experienced a GHB-induced coma (GHB-NoComa) and 24 polydrug users who never used GHB (No-GHB). Resting-state scans were collected to assess resting-state functional-connectivity within and between the default mode network (DMN), the bilateral central executive network (CEN) and the salience network (SN). The GHB-NoComa group showed decreased rsFC of the right CEN with a region in the anterior cingulate cortex (pFWE  = 0.048) and decreased rsFC between the right CEN and the DMN (pFWE  = 0.048) when compared with the No-GHB group. These results suggest that regular GHB-use is associated with decreased rsFC within the right CEN and between the right CEN and the DMN. The presence of multiple GHB-induced comas is not associated with (additional) alterations in rsFC.

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 &lt; 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 &lt; 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.

Evaluating Approximations and Heuristic Measures of Integrated Information

Integrated information theory (IIT) proposes a measure of integrated information, termed Phi (Φ), to capture the level of consciousness of a physical system in a given state. Unfortunately, calculating Φ itself is currently possible only for very small model systems and far from computable for the kinds of system typically associated with consciousness (brains). Here, we considered several proposed heuristic measures and computational approximations, some of which can be applied to larger systems, and tested if they correlate well with Φ. While these measures and approximations capture intuitions underlying IIT and some have had success in practical applications, it has not been shown that they actually quantify the type of integrated information specified by the latest version of IIT and, thus, whether they can be used to test the theory. In this study, we evaluated these approximations and heuristic measures considering how well they estimated the Φ values of model systems and not on the basis of practical or clinical considerations. To do this, we simulated networks consisting of 3–6 binary linear threshold nodes randomly connected with excitatory and inhibitory connections. For each system, we then constructed the system’s state transition probability matrix (TPM) and generated observed data over time from all possible initial conditions. We then calculated Φ, approximations to Φ, and measures based on state differentiation, coalition entropy, state uniqueness, and integrated information. Our findings suggest that Φ can be approximated closely in small binary systems by using one or more of the readily available approximations (r > 0.95) but without major reductions in computational demands. Furthermore, the maximum value of Φ across states (a state-independent quantity) correlated strongly with measures of signal complexity (LZ, r_s = 0.722), decoder-based integrated information (Φ*, r_s = 0.816), and state differentiation (D1, r_s = 0.827). These measures could allow for the efficient estimation of a system’s capacity for high Φ or function as accurate predictors of low- (but not high-)Φ systems. While it is uncertain whether the results extend to larger systems or systems with other dynamics, we stress the importance that measures aimed at being practical alternatives to Φ be, at a minimum, rigorously tested in an environment where the ground truth can be established.

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.

Consciousness as a Physical Process Caused by the Organization of Energy in the Brain

To explain consciousness as a physical process we must acknowledge the role of energy in the brain. Energetic activity is fundamental to all physical processes and causally drives biological behavior. Recent neuroscientific evidence can be interpreted in a way that suggests consciousness is a product of the organization of energetic activity in the brain. The nature of energy itself, though, remains largely mysterious, and we do not fully understand how it contributes to brain function or consciousness. According to the principle outlined here, energy, along with forces and work, can be described as actualized differences of motion and tension. By observing physical systems, we can infer there is something it is like to undergo actualized difference from the intrinsic perspective of the system. Consciousness occurs because there is something it is like, intrinsically, to undergo a certain organization of actualized differences in the brain.

The Effect of Common Signals on Power, Coherence and Granger Causality: Theoretical Review, Simulations, and Empirical Analysis of Fruit Fly LFPs Data

When analyzing neural data it is important to consider the limitations of the particular experimental setup. An enduring issue in the context of electrophysiology is the presence of common signals. For example a non-silent reference electrode adds a common signal across all recorded data and this adversely affects functional and effective connectivity analysis. To address the common signals problem, a number of methods have been proposed, but relatively few detailed investigations have been carried out. As a result, our understanding of how common signals affect neural connectivity estimation is incomplete. For example, little is known about recording preparations involving high spatial-resolution electrodes, used in linear array recordings. We address this gap through a combination of theoretical review, simulations, and empirical analysis of local field potentials recorded from the brains of fruit flies. We demonstrate how a framework that jointly analyzes power, coherence, and quantities based on Granger causality reveals the presence of common signals. We further show that subtracting spatially adjacent signals (bipolar derivations) largely removes the effects of the common signals. However, in some special cases this operation itself introduces a common signal. We also show that Granger causality is adversely affected by common signals and that a quantity referred to as “instantaneous interaction” is increased in the presence of common signals. The theoretical review, simulation, and empirical analysis we present can readily be adapted by others to investigate the nature of the common signals in their data. Our contributions improve our understanding of how common signals affect power, coherence, and Granger causality and will help reduce the misinterpretation of functional and effective connectivity analysis.

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.

Design and Evaluation of a Real Time Physiological Signals Acquisition System Implemented in Multi-Operating Rooms for Anesthesia

With critical importance of medical healthcare, there exist urgent needs for in-depth medical studies that can access and analyze specific physiological signals to provide theoretical support for practical clinical care. As a consequence, obtaining the valuable medical data with minimal cost and impacts on hospital work comes as the first concern of researchers. Anesthesia plays a widely recognized role in surgeries, which attracts people to undertake relevant research. In this paper, a real-time physiological medical signal data acquisition system (PMSDA) for the multi-operating room applications is proposed with high universality of the hospital practical settings and research requirements. By utilizing a wireless communication approach, it provides an easily accessible network platform for collection of physiological medical signals such as photoplethysmogram (PPG), electrocardiograph (ECG) and electroencephalogram (EEG) during the surgery. In addition, the raw data is stored on a server for safe backup and further analysis of depth of anesthesia (DoA). Results show that the PMSDA exhibits robust, high quality performance and efficiently reduces costs compared to previously manual methods and allows seamless integration into hospital environment, independent of its routine work. Overall, it provides a pragmatic and flexible surgery-data acquisition system model with low impact and resource cost applicable to research in critical and practical medical circumstances.

Isoflurane Impairs Low-Frequency Feedback but Leaves High-Frequency Feedforward Connectivity Intact in the Fly Brain

Hierarchically organized brains communicate through feedforward (FF) and feedback (FB) pathways. In mammals, FF and FB are mediated by higher and lower frequencies during wakefulness. FB is preferentially impaired by general anesthetics in multiple mammalian species. This suggests FB serves critical functions in waking brains. The brain of Drosophila melanogaster (fruit fly) is also hierarchically organized, but the presence of FB in these brains is not established. Here, we studied FB in the fly brain, by simultaneously recording local field potentials (LFPs) from low-order peripheral structures and higher-order central structures. We analyzed the data using Granger causality (GC), the first application of this analysis technique to recordings from the insect brain. Our analysis revealed that low frequencies (0.1–5 Hz) mediated FB from the center to the periphery, while higher frequencies (10–45 Hz) mediated FF in the opposite direction. Further, isoflurane anesthesia preferentially reduced FB. Our results imply that the spectral characteristics of FF and FB may be a signature of hierarchically organized brains that is conserved from insects to mammals. We speculate that general anesthetics may induce unresponsiveness across species by targeting the mechanisms that support FB.

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.

Distinguishing Anesthetized from Awake State in Patients: A New Approach Using One Second Segments of Raw EEG

Objective: The objective of this study was to test whether properties of 1-s segments of spontaneous scalp EEG activity can be used to automatically distinguish the awake state from the anesthetized state in patients undergoing general propofol anesthesia.

Methods: Twenty five channel EEG was recorded from 10 patients undergoing general intravenous propofol anesthesia with remifentanil during anterior cervical discectomy and fusion. From this, we extracted properties of the EEG by applying the Directed Transfer Function (DTF) directly to every 1-s segment of the raw EEG signal. The extracted properties were used to develop a data-driven classification algorithm to categorize patients as “anesthetized” or “awake” for every 1-s segment of raw EEG.

Results: The properties of the EEG signal were significantly different in the awake and anesthetized states for at least 8 of the 25 channels (p < 0.05, Bonferroni corrected Wilcoxon rank-sum tests). Using these differences, our algorithms achieved classification accuracies of 95.9%.

Conclusion: Properties of the DTF calculated from 1-s segments of raw EEG can be used to reliably classify whether the patients undergoing general anesthesia with propofol and remifentanil were awake or anesthetized.

Significance: This method may be useful for developing automatic real-time monitors of anesthesia.

Quantitative vascular neuroimaging of the rat brain using superparamagnetic nanoparticles: New insights on vascular organization and brain function

A method called Quantitative Ultra-Short Time-to-Echo Contrast Enhanced (QUTE-CE) Magnetic Resonance Imaging (MRI) which utilizes superparamagnetic iron oxide nanoparticles (SPIONs) as a contrast agent to yield positive contrast angiograms with high clarity and definition is applied to the whole live rat brain. QUTE-CE MRI intensity data are particularly well suited for measuring quantitative cerebral blood volume (qCBV). A global map of qCBV in the awake resting-state with unprecedented detail was created via application of a 3D MRI rat brain atlas with 173 segmented and annotated brain areas. From this map we identified two distributed, integrated neural circuits showing the highest capillary densities in the brain. One is the neural circuitry involved with the primary senses of smell, hearing and vision and the other is the neural circuitry of memory. Under isoflurane anesthesia, these same circuits showed significant decreases in qCBV suggesting a role in consciousness. Neural circuits in the brainstem associated with the reticular activating system and the maintenance of respiration, body temperature and cardiovascular function showed an increase in qCBV with anesthesia. During awake CO2 challenge, 84 regions showed significant increases relative to an awake baseline state. This CO2 response provides a measure of cerebral vascular reactivity and regional perfusion reserve with the highest response measured in the somatosensory cortex. These results demonstrate the utility of QUTE-CE MRI for qCBV analysis and offer a new perspective on brain function and vascular organization.

Investigation of Slow-wave Activity Saturation during Surgical Anesthesia Reveals a Signature of Neural Inertia in Humans

BACKGROUND

Previously, we showed experimentally that saturation of slow-wave activity provides a potentially individualized neurophysiologic endpoint for perception loss during anesthesia. Furthermore, it is clear that induction and emergence from anesthesia are not symmetrically reversible processes. The observed hysteresis is potentially underpinned by a neural inertia mechanism as proposed in animal studies.

METHODS

In an advanced secondary analysis of 393 individual electroencephalographic data sets, we used slow-wave activity dose-response relationships to parameterize slow-wave activity saturation during induction and emergence from surgical anesthesia. We determined whether neural inertia exists in humans by comparing slow-wave activity dose responses on induction and emergence.

RESULTS

Slow-wave activity saturation occurs for different anesthetics and when opioids and muscle relaxants are used during surgery. There was wide interpatient variability in the hypnotic concentrations required to achieve slow-wave activity saturation. Age negatively correlated with power at slow-wave activity saturation. On emergence, we observed abrupt decreases in slow-wave activity dose responses coincident with recovery of behavioral responsiveness in ~33% individuals. These patients are more likely to have lower power at slow-wave activity saturation, be older, and suffer from short-term confusion on emergence.

CONCLUSIONS

Slow-wave activity saturation during surgical anesthesia implies that large variability in dosing is required to achieve a targeted potential loss of perception in individual patients. A signature for neural inertia in humans is the maintenance of slow-wave activity even in the presence of very-low hypnotic concentrations during emergence from anesthesia.

Location of the Mesopontine Neurons Responsible for Maintenance of Anesthetic Loss of Consciousness

The transition from wakefulness to general anesthesia is widely attributed to suppressive actions of anesthetic molecules distributed by the systemic circulation to the cerebral cortex (for amnesia and loss of consciousness) and to the spinal cord (for atonia and antinociception). An alternative hypothesis proposes that anesthetics act on one or more brainstem or diencephalic nuclei, with suppression of cortex and spinal cord mediated by dedicated axonal pathways. Previously, we documented induction of an anesthesia-like state in rats by microinjection of small amounts of GABAA-receptor agonists into an upper brainstem region named the mesopontine tegmental anesthesia area (MPTA). Correspondingly, lesioning this area rendered animals resistant to systemically delivered anesthetics. Here, using rats of both sexes, we applied a modified microinjection method that permitted localization of the anesthetic-sensitive neurons with much improved spatial resolution. Microinjected at the MPTA hotspot identified, exposure of 1900 or fewer neurons to muscimol was sufficient to sustain whole-body general anesthesia; microinjection as little as 0.5 mm off-target did not. The GABAergic anesthetics pentobarbital and propofol were also effective. The GABA-sensitive cell cluster is centered on a tegmental (reticular) field traversed by fibers of the superior cerebellar peduncle. It has no specific nuclear designation and has not previously been implicated in brain-state transitions.SIGNIFICANCE STATEMENT General anesthesia permits pain-free surgery. Furthermore, because anesthetic agents have the unique ability to reversibly switch the brain from wakefulness to a state of unconsciousness, knowing how and where they work is a potential route to unraveling the neural mechanisms that underlie awareness itself. Using a novel method, we have located a small, and apparently one of a kind, cluster of neurons in the mesopontine tegmentum that are capable of effecting brain-state switching when exposed to GABAA-receptor agonists. This action appears to be mediated by a network of dedicated axonal pathways that project directly and/or indirectly to nearby arousal nuclei of the brainstem and to more distant targets in the forebrain and spinal cord.

Network Efficiency and Posterior Alpha Patterns Are Markers of Recovery from General Anesthesia: A High-Density Electroencephalography Study in Healthy Volunteers

Recent studies have investigated local oscillations, long-range connectivity, and global network patterns to identify neural changes associated with anesthetic-induced unconsciousness. These studies typically employ anesthetic protocols that either just cross the threshold of unconsciousness, or induce deep unconsciousness for a brief period of time-neither of which models general anesthesia for major surgery. To study neural patterns of unconsciousness and recovery in a clinically-relevant context, we used a realistic anesthetic regimen to induce and maintain unconsciousness in eight healthy participants for 3 h. High-density electroencephalogram (EEG) was acquired throughout and for another 3 h after emergence. Seven epochs of 5-min eyes-closed resting states were extracted from the data at baseline as well as 30, 60, 90, 120, 150, and 180-min post-emergence. Additionally, 5-min epochs were extracted during induction, unconsciousness, and immediately prior to recovery of consciousness, for a total of 10 analysis epochs. The EEG data in each epoch were analyzed using source-localized spectral analysis, phase-lag index, and graph theoretical techniques. Posterior alpha power was significantly depressed during unconsciousness, and gradually approached baseline levels over the 3 h recovery period. Phase-lag index did not distinguish between states of consciousness or stages of recovery. Network efficiency was significantly depressed and network clustering coefficient was significantly increased during unconsciousness; these graph theoretical measures returned to baseline during the 3 h recovery period. Posterior alpha power may be a potential biomarker for normal recovery of functional brain networks after general anesthesia.

Bottom-Up and Top-Down Mechanisms of General Anesthetics Modulate Different Dimensions of Consciousness

There has been controversy regarding the precise mechanisms of anesthetic-induced unconsciousness, with two salient approaches that have emerged within systems neuroscience. One prominent approach is the “bottom up” paradigm, which argues that anesthetics suppress consciousness by modulating sleep-wake nuclei and neural circuits in the brainstem and diencephalon that have evolved to control arousal states. Another approach is the “top-down” paradigm, which argues that anesthetics suppress consciousness by modulating the cortical and thalamocortical circuits involved in the integration of neural information. In this article, we synthesize these approaches by mapping bottom-up and top-down mechanisms of general anesthetics to two distinct but inter-related dimensions of consciousness: level and content. We show how this explains certain empirical observations regarding the diversity of anesthetic drug effects. We conclude with a more nuanced discussion of how levels and contents of consciousness interact to generate subjective experience and what this implies for the mechanisms of anesthetic-induced unconsciousness.

Propofol, Sevoflurane, and Ketamine Induce a Reversible Increase in Delta-Gamma and Theta-Gamma Phase-Amplitude Coupling in Frontal Cortex of Rat

Studies from human and non-human species have demonstrated a breakdown of functional corticocortical connectivity during general anesthesia induced by anesthetics with diverse molecular, neurophysiological, and pharmacological profiles. Recent studies have demonstrated that changes in long-range neural communication, and by corollary, functional connectivity, might be influenced by cross-frequency coupling (CFC) between the phase of slow oscillations and the amplitude of local fast oscillations. Phase-amplitude coupling (PAC) between slow oscillations and alpha rhythm during general anesthesia reveal distinct patterns depending on the anesthetic. In this study, we analyzed the effect of three clinically used anesthetics (propofol: n = 6, sevoflurane: n = 10, and ketamine: n = 8) with distinct molecular mechanisms on changes in PAC in the frontal cortex of rat. The loss of righting reflex was used as a surrogate for unconsciousness. PAC was calculated using the modulation index (MI) algorithm between delta (1–4 Hz), theta (4–10 Hz), low gamma (25–55 Hz), and high gamma (65–125 Hz) bands. A linear mixed model with fixed effects was used for statistical comparisons between waking, anesthetized, and post-anesthesia recovery epochs. All three anesthetics increased the coupling between delta and low gamma (p < 0.0001) as well as between theta and low gamma (p < 0.0001) oscillations, which returned to baseline waking levels during the post-anesthetic recovery period. In addition, a reversible reduction in high gamma power (p < 0.0001) was a consistent change during anesthesia induced by all three agents. The changes in delta-high gamma and theta-high gamma PAC as well as power spectral changes in delta, theta, and low gamma bandwidths did not show a uniform response across the three anesthetics. These results encourage the study of alternative PAC patterns as drug-invariant markers of general anesthesia in humans.

Accelerated Recovery of Consciousness after General Anesthesia Is Associated with Increased Functional Brain Connectivity in the High-Gamma Bandwidth

Recent data from our laboratory demonstrate that high-frequency gamma connectivity across the cortex is present during consciousness and depressed during unconsciousness. However, these data were derived from static and well-defined states of arousal rather than during transitions that would suggest functional relevance. We also recently found that subanesthetic ketamine administered during isoflurane anesthesia accelerates recovery upon discontinuation of the primary anesthetic and increases gamma power during emergence. In the current study we re-analyzed electroencephalogram (EEG) data to test the hypothesis that functional cortical connectivity between anterior and posterior cortical regions would be increased during accelerated recovery induced by ketamine when compared to saline-treated controls. Rodents were instrumented with intracranial EEG electrodes and general anesthesia was induced with isoflurane anesthesia. After 37.5 min of continuous isoflurane anesthesia, a subanesthetic dose of ketamine (25 mg/kg intraperitoneal) was administered, with evidence of a 44% reduction in emergence time. In this study, we analyzed gamma and theta coherence (measure of undirected functional connectivity) and normalized symbolic transfer entropy (measure of directed functional connectivity) between frontal and parietal cortices during various levels of consciousness, with a focus on emergence from isoflurane anesthesia. During accelerated emergence in the ketamine-treated group, there was increased frontal-parietal coherence {p = 0.005, 0.05-0.23 [95% confidence interval (CI)]} and normalized symbolic transfer entropy [frontal to parietal: p < 0.001, 0.010-0.026 (95% CI); parietal to frontal: p < 0.001, 0.009-0.025 (95% CI)] in high-frequency gamma bandwidth as compared with the saline-treated group. Surrogates of cortical information exchange in high-frequency gamma are increased in association with accelerated recovery from anesthesia. This finding adds evidence suggesting a functional significance of high-gamma information transfer in consciousness.

Functional connectivity and network analysis during hypoactive delirium and recovery from anesthesia

OBJECTIVE

To gain insight in the underlying mechanism of reduced levels of consciousness due to hypoactive delirium versus recovery from anesthesia, we studied functional connectivity and network topology using electroencephalography (EEG).

METHODS

EEG recordings were performed in age and sex-matched patients with hypoactive delirium (n=18), patients recovering from anesthesia (n=20), and non-delirious control patients (n=20), all after cardiac surgery. Functional and directed connectivity were studied with phase lag index and directed phase transfer entropy. Network topology was characterized using the minimum spanning tree (MST). A random forest classifier was calculated based on all measures to obtain discriminative ability between the three groups.

RESULTS

Non-delirious control subjects showed a back-to-front information flow, which was lost during hypoactive delirium (p=0.01) and recovery from anesthesia (p<0.01). The recovery from anesthesia group had more integrated network in the delta band compared to non-delirious controls. In contrast, hypoactive delirium showed a less integrated network in the alpha band. High accuracy for discrimination between hypoactive delirious patients and controls (86%) and recovery from anesthesia and controls (95%) were found. Accuracy for discrimination between hypoactive delirium and recovery from anesthesia was 73%.

CONCLUSION

Loss of functional and directed connectivity were observed in both hypoactive delirium and recovery from anesthesia, which might be related to the reduced level of consciousness in both states. These states could be distinguished in topology, which was a less integrated network during hypoactive delirium.

SIGNIFICANCE

Functional and directed connectivity are similarly disturbed during a reduced level of consciousness due to hypoactive delirium and sedatives, however topology was differently affected.

Repertoire of mesoscopic cortical activity is not reduced during anesthesia

Consciousness has been linked to the repertoire of brain states at various spatiotemporal scales. Anesthesia is thought to modify consciousness by altering information integration in cortical and thalamocortical circuits. At a mesoscopic scale, neuronal populations in the cortex form synchronized ensembles whose characteristics are presumably state-dependent but this has not been rigorously tested. In this study, spontaneous neuronal activity was recorded with 64-contact microelectrode arrays in primary visual cortex of chronically instrumented, unrestrained rats under stepwise decreasing levels of desflurane anesthesia (8%, 6%, 4%, and 2% inhaled concentrations) and wakefulness (0% concentration). Negative phases of the local field potentials formed compact, spatially contiguous activity patterns (CAPs) that were not due to chance. The number of CAPs was 120% higher in wakefulness and deep anesthesia associated with burst-suppression than at intermediate levels of consciousness. The frequency distribution of CAP sizes followed a power-law with slope -1.5 in relatively deep anesthesia (8-6%) but deviated from that at the lighter levels. Temporal variance and entropy of CAP sizes were lowest in wakefulness (76% and 24% lower at 0% than at 8% desflurane, respectively) but changed little during recovery of consciousness. CAPs categorized by K-means clustering were conserved at all anesthesia levels and wakefulness, although their proportion changed in a state-dependent manner. These observations yield new knowledge about the dynamic landscape of ongoing population activity in sensory cortex at graded levels of anesthesia. The repertoire of population activity and self-organized criticality at the mesoscopic scale do not appear to contribute to anesthetic suppression of consciousness, which may instead depend on large-scale effects, more subtle dynamic properties, or changes outside of primary sensory cortex.

Propofol attenuates low-frequency fluctuations of resting-state fMRI BOLD signal in the anterior frontal cortex upon loss of consciousness

Recent studies indicate that spontaneous low-frequency fluctuations (LFFs) of resting-state functional magnetic resonance imaging (rs-fMRI) blood oxygen level-dependent (BOLD) signals are driven by the slow (<0.1Hz) modulation of ongoing neuronal activity synchronized locally and across remote brain regions. How regional LFFs of the BOLD fMRI signal are altered during anesthetic-induced alteration of consciousness is not well understood. Using rs-fMRI in 15 healthy participants, we show that during administration of propofol to achieve loss of behavioral responsiveness indexing unconsciousness, the fractional amplitude of LFF (fALFF index) was reduced in comparison to wakeful baseline in the anterior frontal regions, temporal pole, hippocampus, parahippocampal gyrus, and amygdala. Such changes were absent in large areas of the motor, parietal, and sensory cortices. During light sedation characterized by the preservation of overt responsiveness and therefore consciousness, fALFF was reduced in the subcortical areas, temporal pole, medial orbital frontal cortex, cingulate cortex, and cerebellum. Between light sedation and deep sedation, fALFF was reduced primarily in the medial and dorsolateral frontal areas. The preferential reduction of LFFs in the anterior frontal regions is consistent with frontal to sensory-motor cortical disconnection and may contribute to the suppression of consciousness during general anesthesia.