EEG slow-wave coherence changes in propofol-induced general anesthesia: experiment and theory

Regulating the activity of GABAergic neurons in the ventral pallidum alters the general anesthesia effect of propofol

The full mechanism of action of propofol, a commonly administered intravenous anesthetic drug in clinical practice, remains elusive. The focus of this study was the role of GABAergic neurons which are the main neuron group in the ventral pallidum (VP) closely associated with anesthetic effects in propofol anesthesia. The activity of VP GABAergic neurons following propofol anesthesia in Vgat-Cre mice was observed via detecting c-Fos immunoreactivity by immunofluorescence and western blotting. Subsequently, chemogenetic techniques were employed in Vgat-Cre mice to regulate the activity of VP GABAergic neurons. The role of VP GABAergic neurons in generating the effects of general anesthesia induced by intravenous propofol was further explored through behavioral tests of the righting reflex. The results revealed that c-Fos expression in VP GABAergic neurons in Vgat-Cre mice dramatically decreased after propofol injection. Further studies demonstrated that chemogenetic activation of VP GABAergic neurons during propofol anesthesia shortened the duration of anesthesia and promoted wakefulness. Conversely, the inhibition of VP GABAergic neurons extended the duration of anesthesia and facilitated the effects of anesthesia. The results obtained in this study suggested that regulating the activity of GABAergic neurons in the ventral pallidum altered the effect of propofol on general anesthesia.

EEG Changes during Propofol Anesthesia Induction in Vegetative State Patients Undergoing Spinal Cord Stimulation Implantation Surgery

OBJECTIVE

To compare the EEG changes in vegetative state (VS) patients and non-craniotomy, non-vegetative state (NVS) patients during general anesthesia with low-dose propofol and to find whether it affects the arousal rate of VS patients.

METHODS

Seven vegetative state patients (VS group: five with traumatic brain injury, two with ischemic-hypoxic VS) and five non-craniotomy, non-vegetative state patients (NVS group) treated in the Department of Neurosurgery, Peking University International Hospital from January to May 2022 were selected. All patients were induced with 0.5 mg/kg propofol, and the Bispectral Index (BIS) changes within 5 min after administration were observed. Raw EEG signals and perioperative EEG signals were collected and analyzed using EEGLAB in the MATLAB software environment, time-frequency spectrums were calculated, and EEG changes were analyzed using power spectrums.

RESULTS

There was no significant difference in the general data before surgery between the two groups (p > 0.05); the BIS reduction in the VS group was significantly greater than that in the NVS group at 1 min, 2 min, 3 min, 4 min, and 5 min after 0.5 mg/kg propofol induction (p < 0.05). Time-frequency spectrum analysis showed the following: prominent α band energy around 10 Hz and decreased high-frequency energy in the NVS group, decreased high-frequency energy and main energy concentrated below 10 Hz in traumatic brain injury VS patients, higher energy in the 10-20 Hz band in ischemic-hypoxic VS patients. The power spectrum showed that the brain electrical energy of the NVS group was weakened R5 min after anesthesia induction compared with 5 min before induction, mainly concentrated in the small wave peak after 10 Hz, i.e., the α band peak; the energy of traumatic brain injury VS patients was weakened after anesthesia induction, but no α band peak appeared; and in ischemic-hypoxic VS patients, there was no significant change in low-frequency energy after anesthesia induction, high-frequency energy was significantly weakened, and a clear α band peak appeared slightly after 10 Hz. Three months after the operation, follow-up visits were made to the VS group patients who had undergone SCS surgery. One patient with traumatic brain injury VS was diagnosed with MCS-, one patient with ischemic-hypoxic VS had increased their CRS-R score by 1 point, and the remaining five patients had no change in their CRS scores.

CONCLUSIONS

Low doses of propofol cause great differences in the EEG of different types of VS patients, which may be the unique response of damaged nerve cell residual function to propofol, and these weak responses may also be the basis of brain recovery.

Perioperative Brain Function Monitoring with Electroencephalography in Horses Anesthetized with Multimodal Balanced Anesthetic Protocol Subjected to Surgeries

Simple Summary

This study aimed to investigate the use of electroencephalography (EEG) and EEG-derived (processed) indices for detecting brain activity changes perioperatively in 12 anesthetized adult horses subjected to various surgery. Frontal electrodes together with Sedline/Root monitor were used on these horses from soon after anesthesia induction and continued until the horse first attempted to stand in recovery. The EEG waves were characterized by low-frequency high amplitude alpha, theta, and alpha waves during the isoflurane maintenance and surgery, which is commonly observed in profound anesthesia. The processed EEG indices including Patient State Index, Burst Suppression Ratio, and 95% Spectral Edge Frequency changed significantly between the stages (induction, surgery, and recovery) of anesthesia. Collectively, the presence of the slow EEG wave activities and the presence of burst suppression implies that these horses were profoundly unconscious during the anesthesia. We concluded that the use of EEG in conjunction with traditional cardiorespiratory monitoring provides clinically relevant information about perioperative brain state changes in the anesthetized horses.

Abstract

This study aimed to investigate the use of electroencephalography (EEG) for detecting brain activity changes perioperatively in anesthetized horses subjected to surgery. Twelve adult horses undergoing various surgeries were evaluated after premedication with xylazine and butorphanol, induction with ketamine, midazolam, and guaifenesin, and maintenance with isoflurane. The frontal EEG electrodes were placed after the horse was intubated and mechanically ventilated. The EEG data were collected continuously from Stage (S)1—transition from induction to isoflurane maintenance, S2—during surgery, S3—early recovery before xylazine sedation (0.2 mg kg IV), and S4—recovery after xylazine sedation. The Patient State Index (PSI), (Burst) Suppression Ratio (SR), and 95% Spectral Edge Frequency (SEF₉₅) were compared across the stages. The PSI was lowest in S2 (20.8 ± 2.6) and increased to 30.0 ± 27.7 (p = 0.005) in S3. The SR increased from S1 (5.5 ± 10.7%) to S3 (32.7 ± 33.8%, p = 0.0001). The spectral power analysis showed that S3 had a significantly higher content of delta wave activity (0.1–4 Hz) in the EEG and lower relative power in the 3 Hz to 15 Hz range when compared to S1 and S2. A similar result was observed in S4, but the lower power was in a narrower range, from 3 Hz to 7 Hz, which indicate profound central nervous system depression potentiated by xylazine, despite the cessation of isoflurane anesthesia. We concluded that the use of EEG provides clinically relevant information about perioperative brain state changes of the isoflurane-anesthetized horse.

Consciousness is supported by near-critical slow cortical electrodynamics

Mounting evidence suggests that during conscious states, the electrodynamics of the cortex are poised near a critical point or phase transition and that this near-critical behavior supports the vast flow of information through cortical networks during conscious states. Here, we empirically identify a mathematically specific critical point near which waking cortical oscillatory dynamics operate, which is known as the edge-of-chaos critical point, or the boundary between stability and chaos. We do so by applying the recently developed modified 0-1 chaos test to electrocorticography (ECoG) and magnetoencephalography (MEG) recordings from the cortices of humans and macaques across normal waking, generalized seizure, anesthesia, and psychedelic states. Our evidence suggests that cortical information processing is disrupted during unconscious states because of a transition of low-frequency cortical electric oscillations away from this critical point; conversely, we show that psychedelics may increase the information richness of cortical activity by tuning low-frequency cortical oscillations closer to this critical point. Finally, we analyze clinical electroencephalography (EEG) recordings from patients with disorders of consciousness (DOC) and show that assessing the proximity of slow cortical oscillatory electrodynamics to the edge-of-chaos critical point may be useful as an index of consciousness in the clinical setting.

Effects of propofol on sleep architecture and sleep-wake systems in rats

Previous studies have shown that the synchronization of electroencephalogram (EEG) signals is found during propofol-induced general anesthesia, which is similar to that of slow-wave sleep (SWS). However, a complete understanding is lacking in terms of the characteristics of EEG changes in rats after propofol administration and whether propofol acts through natural sleep circuits. Here, we examined the characteristics of EEG patterns induced by intraperitoneal injection of propofol in rats. We found that high (10 mg/kg) and medium (5 mg/kg) doses of propofol induced a cortical EEG of low-frequency, high-amplitude activity with rare electromyographic activity and markedly shortened sleep latency. The high dose of propofol increased deep slow-wave sleep (SWS2) to 4 h, as well as the number of large SWS2 bouts (>480 s), their mean duration and the peak of the power density curve in the delta range of 0.75-3.25 Hz. After the medium dose of propofol, the total number of wakefulness, light slow-wave sleep (SWS1) and SWS2 episodes increased, whereas the mean duration of wakefulness decreased. The high dose of propofol significantly increased c-fos expression in the ventrolateral preoptic nucleus (VLPO) sleep center and decreased the number of c-fos-immunoreactive neurons in wake-related systems including the tuberomammillary nucleus (TMN), perifornical nucleus (PeF), lateral hypothalamic nucleus (LH), ventrolateral periaqueductal gray (vPAG) and supramammillary region (SuM). These results indicated that the high dose of propofol produced high-quality sleep by increasing SWS2, whereas the medium dose produced fragmented and low-quality sleep by disrupting the continuity of wakefulness. Furthermore, sleep-promoting effects of propofol are correlated with activation of the VLPO cluster and inhibition of the TMN, PeF, LH, vPAG and SuM.

Contributions of synaptic and astrocyte physiology to the anaesthetised encephalogram revealed using a computational model

BACKGROUND

General anaesthesia is known to enhance inhibitory synaptic transmission to produce characteristic effects on the EEG and reduction in brain metabolism secondary to reduced neuronal activity. Evidence suggests that anaesthesia might have a direct effect on synaptic metabolic processes, and this relates to anaesthesia sensitivity. We explored elements of synaptic transmission looking for possible contributions to the anaesthetised EEG and how it may modulate anaesthesia sensitivity.

METHODS

We developed a Hodgkin-Huxley-type neural network computer simulation capable of mimicking anaesthetic prolongation of gamma-aminobutyric acid (GABA)ergic inhibitory postsynaptic potentials (IPSPs), and capable of altering postsynaptic ion homeostasis and neurotransmitter recycling. We examined their interactions on simulated electrocorticography (sECoG), and compared these with published anaesthesia EEG spectra.

RESULTS

The sECoG spectra from the model were comparable with published normal awake EEG spectra. Prolongation of IPSP duration in the model caused inhibition of high frequencies and saturation of low frequencies with a peak in keeping with current evidence. IPSP prolongation alone was unable to reproduce alpha rhythms or the generalised increase in EEG power found with anaesthesia. Adding inhibition of postsynaptic ion homeostasis to IPSP prolongation helped retain alpha rhythms, increased sECoG power, and antagonised the slow-wave saturation peak in a dose-dependent fashion that appeared dependent on the postsynaptic membrane potential, providing a plausible mechanism for how metabolic changes can modulate anaesthesia sensitivity.

CONCLUSIONS

Our model suggests how metabolic processes can modulate anaesthesia and produce non-receptor dependent drug sensitivity.

Consciousness among delta waves: a paradox?

A common observation in EEG research is that consciousness vanishes with the appearance of delta (1 - 4 Hz) waves, particularly when those waves are high amplitude. High amplitude delta oscillations are very frequently observed in states of diminished consciousness, including slow wave sleep, anaesthesia, generalised epileptic seizures, and disorders of consciousness such as coma and vegetative state. This strong correlation between loss of consciousness and high amplitude delta oscillations is thought to stem from the widespread cortical deactivation that occurs during the "down states" or troughs of these slow oscillations. Recently, however, many studies have reported the presence of prominent delta activity during conscious states, which casts doubt on the hypothesis that high amplitude delta oscillations are an indicator of unconsciousness. These studies include work in Angelman syndrome, epilepsy, behavioural responsiveness during propofol anaesthesia, postoperative delirium, and states of dissociation from the environment such as dreaming and powerful psychedelic states. The foregoing studies complement an older, yet largely unacknowledged, body of literature that has documented awake, conscious patients with high amplitude delta oscillations in clinical reports from Rett syndrome, Lennox-Gastaut syndrome, schizophrenia, mitochondrial diseases, hepatic encephalopathy, and nonconvulsive status epilepticus. At the same time, a largely parallel body of recent work has reported convincing evidence that the complexity or entropy of EEG and magnetoencephalogram or MEG signals strongly relates to an individual's level of consciousness. Having reviewed this literature, we discuss plausible mechanisms that would resolve the seeming contradiction between high amplitude delta oscillations and consciousness. We also consider implications concerning theories of consciousness, such as integrated information theory and the entropic brain hypothesis. Finally, we conclude that false inferences of unconscious states can be best avoided by examining measures of electrophysiological complexity in addition to spectral power.

The Raw and Processed Electroencephalogram as a Monitoring and Diagnostic Tool

In this narrative review, different aspects of electroencephalogram (EEG) monitoring during anesthesia are approached, with a special focus on cardiothoracic and vascular anesthesia, from the basic principles to more sophisticated diagnosis and monitoring utilities. The available processed EEG-derived indexes of the depth of the hypnotic component of anesthesia have well-defined limitations and usefulness. They prevent intraoperative awareness with recall in specific patient populations and under a specific anesthetic regimen. They prevent intraoperative overdose, and they shorten recovery times. They also help to avoid lengthy intraoperative periods of suppression activity, which are known to be deleterious in terms of outcome. Other than those available indexes, the huge amount of information contained in the EEG currently is being used only partially. Several other areas of interest regarding EEG during anesthesia have emerged in terms of anesthesia mechanisms elucidation, nociception monitoring, and diagnosis or prevention of brain insults.

Case Studies Using the Electroencephalogram to Monitor Anesthesia-Induced Brain States in Children

For this child, at this particular moment, how much anesthesia should I give? Determining the drug requirements of a specific patient is a fundamental problem in medicine. Our current approach uses population-based pharmacological models to establish dosing. However, individual patients, and children in particular, may respond to drugs differently. In anesthesiology, we have the advantage that we can monitor our patients in real time and titrate drugs to the desired effect. Examples include blood pressure management or muscle relaxation. Although the brain is the primary site of action for sedative-hypnotic drugs, the brain is not routinely monitored during general anesthesia or sedation, a fact that would surprise many patients. One reason for this is that, until recently, physiologically principled approaches for anesthetic brain monitoring have not been articulated. In the past few years, our knowledge of anesthetic brain mechanisms has developed rapidly. We now know that anesthetic drug effects are clearly visible in the electroencephalogram (EEG) of adults and reflect underlying anesthetic pharmacology and brain mechanisms. Most recently, similar effects have been characterized in children. In this article, we describe how EEG monitoring could be used to guide anesthetic management in pediatric patients. We review previous evidence and present multiple case studies showing how drug-specific and dose-dependent EEG signatures seen in adults are visible in children and infants, including those with neurological disorders. We propose that the EEG can be used in the anesthetic care of children to enable anesthesiologists to better assess the drug requirements of individual patients in real time and improve patient safety and experience.

The value of intra-operative electrographic biomarkers for tailoring during epilepsy surgery: from group-level to patient-level analysis

Signal analysis biomarkers, in an intra-operative setting, may be complementary tools to guide and tailor the resection in drug-resistant focal epilepsy patients. Effective assessment of biomarker performances are needed to evaluate their clinical usefulness and translation. We defined a realistic ground-truth scenario and compared the effectiveness of different biomarkers alone and combined to localize epileptogenic tissue during surgery. We investigated the performances of univariate, bivariate and multivariate signal biomarkers applied to 1 min inter-ictal intra-operative electrocorticography to discriminate between epileptogenic and non-epileptogenic locations in 47 drug-resistant people with epilepsy (temporal and extra-temporal) who had been seizure-free one year after the operation. The best result using a single biomarker was obtained using the phase-amplitude coupling measure for which the epileptogenic tissue was localized in 17 out of 47 patients. Combining the whole set of biomarkers provided an improvement of the performances: 27 out of 47 patients. Repeating the analysis only on the temporal-lobe resections we detected the epileptogenic tissue in 29 out of 30 combining all the biomarkers. We suggest that the assessment of biomarker performances on a ground-truth scenario is required to have a proper estimate on how biomarkers translate into clinical use. Phase-amplitude coupling seems the best performing single biomarker and combining biomarkers improves localization of epileptogenic tissue. Performance achieved is not adequate as a tool in the operation theater yet, but it can improve the understanding of pathophysiological process.

Cortical functional connectivity indexes arousal state during sleep and anesthesia

Disruption of cortical connectivity likely contributes to loss of consciousness (LOC) during both sleep and general anesthesia, but the degree of overlap in the underlying mechanisms is unclear. Both sleep and anesthesia comprise states of varying levels of arousal and consciousness, including states of largely maintained conscious experience (sleep: N1, REM; anesthesia: sedated but responsive) as well as states of substantially reduced conscious experience (sleep: N2/N3; anesthesia: unresponsive). Here, we tested the hypotheses that (1) cortical connectivity will exhibit clear changes when transitioning into states of reduced consciousness, and (2) these changes will be similar for arousal states of comparable levels of consciousness during sleep and anesthesia. Using intracranial recordings from five adult neurosurgical patients, we compared resting state cortical functional connectivity (as measured by weighted phase lag index, wPLI) in the same subjects across arousal states during natural sleep [wake (WS), N1, N2, N3, REM] and propofol anesthesia [pre-drug wake (WA), sedated/responsive (S), and unresponsive (U)]. Analysis of alpha-band connectivity indicated a transition boundary distinguishing states of maintained and reduced conscious experience in both sleep and anesthesia. In wake states WS and WA, alpha-band wPLI within the temporal lobe was dominant. This pattern was largely unchanged in N1, REM, and S. Transitions into states of reduced consciousness N2, N3, and U were characterized by dramatic changes in connectivity, with dominant connections shifting to prefrontal cortex. Secondary analyses indicated similarities in reorganization of cortical connectivity in sleep and anesthesia. Shifts from temporal to frontal cortical connectivity may reflect impaired sensory processing in states of reduced consciousness. The data indicate that functional connectivity can serve as a biomarker of arousal state and suggest common mechanisms of LOC in sleep and anesthesia.

Phospholipase C-related inactive protein type-1 deficiency affects anesthetic electroencephalogram activity induced by propofol and etomidate in mice

PURPOSE

The general anesthetics propofol and etomidate mainly exert their anesthetic actions via GABA A receptor (GABA_A-R). The GABA_A-R activity is influenced by phospholipase C-related inactive protein type-1 (PRIP-1), which is related to trafficking and subcellular localization of GABA_A-R. PRIP-1 deficiency attenuates the behavioral reactions to propofol but not etomidate. However, the effect of these anesthetics and of PRIP-1 deficiency on brain activity of CNS are still unclear. In this study, we examined the effects of propofol and etomidate on the electroencephalogram (EEG).

METHODS

The cortical EEG activity was recorded in wild-type (WT) and PRIP-1 knockout (PRIP-1 KO) mice. All recorded EEG data were offline analyzed, and the power spectral density and 95% spectral edge frequency of EEG signals were compared between genotypes before and after injections of anesthetics.

RESULTS

PRIP-1 deficiency induced increases in EEG absolute powers, but did not markedly change the relative spectral powers during waking and sleep states in the absence of anesthesia. Propofol administration induced increases in low-frequency relative EEG activity and decreases in SEF95 values in WT but not in PRIP-1 KO mice. Following etomidate injection, low-frequency EEG power was increased in both genotype groups. At high frequency, the relative power in PRIP-1 KO mice was smaller than that in WT mice.

CONCLUSIONS

The lack of PRIP-1 disrupted the EEG power distribution, but did not affect the depth of anesthesia after etomidate administration. Our analyses suggest that PRIP-1 is differentially involved in anesthetic EEG activity with the regulation of GABA_A-R activity.

Attenuation of high-frequency (30-200 Hz) thalamocortical EEG rhythms as correlate of anaesthetic action: evidence from dexmedetomidine

Background

Gamma (30-80 Hz) and high-gamma (80-200 Hz) thalamocortical EEG rhythms are involved in conscious processes and are attenuated by isoflurane and propofol. To explore the hypothesis that this attenuation is a correlate of anaesthetic action, we characterized the effect dexmedetomidine, a selective adrenergic α-2 agonist with lesser hypnotic potency, on these rhythms.

Methods

We recorded local field potentials from barrel cortex and ventroposteromedial thalamic nucleus in ten previously instrumented rats to measure spectral power (30-50 Hz, 51-75 Hz, 76-125 Hz, 126-200 Hz bands) during baseline, at four dexmedetomidine plasma concentrations obtained by i.v. target-controlled infusion (1.86, 3.75, 5.63 and 7.50 ng ml -1 ), and during recovery. Thalamocortical coherence over 0.3-200 Hz was also measured.

Results

Loss of righting reflex (LORR) occurred with 5.63 ng ml -1 . Dexmedetomidine produced a linear concentration-dependent attenuation of cortical ( P <0.04) and thalamic ( P  ≤ 0.0051) log power in all bands. Slopes for cortex and thalamus were similar. The slope for dexmedetomidine on thalamic power in the 76-200 Hz range was less than half that of the other agents ( P <0.003). LORR was associated with an increase in delta band (0.3-4.0 Hz) thalamocortical coherence ( P <0.001). Increased low-frequency coherence also occurred with propofol and isoflurane.

Conclusions

Dexmedetomidine attenuates high-frequency thalamocortical rhythms, but to a lesser degree than isoflurane and propofol. The main differences between dexmedetomidine and the other anaesthetics involved thalamic rhythms, further substantiating the link between impaired thalamic function and anaesthesia. Increased delta coherence likely reflects cyclic hyperpolarization of thalamocortical networks and may be a marker for loss of consciousness.

Potential EEG biomarkers of sedation doses in intensive care patients unveiled by using a machine learning approach

OBJECTIVE

Sedation of neurocritically ill patients is one of the most challenging situation in ICUs. Quantitative knowledge on the sedation effect on brain activity in that complex scenario could help to uncover new markers for sedation assessment. Hence, we aim to evaluate the existence of changes of diverse EEG-derived measures in deeply-sedated (RASS-Richmond agitation-sedation scale  -4 and  -5) neurocritically ill patients, and also whether sedation doses are related with those eventual changes.

APPROACH

We performed an observational prospective cohort study in the intensive care unit of the Hospital de la Princesa. Twenty-six adult patients suffered from traumatic brain injury and subarachnoid hemorrhage were included in the present study. Long-term continuous electroencephalographic (EEG) recordings (2141 h) and hourly annotated information were used to determine the relationship between intravenous sedation infusion doses and network and spectral EEG measures. To do that, two different strategies were followed: assessment of the statistical dependence between both variables using the Spearman correlation rank and by performing an automatic classification method based on a machine learning algorithm.

MAIN RESULTS

More than 60% of patients presented a correlation greater than 0.5 in at least one of the calculated EEG measures with the sedation dose. The automatic classification method presented an accuracy of 84.3% in discriminating between different sedation doses. In both cases the nodes' degree was the most relevant measurement.

SIGNIFICANCE

The results presented here provide evidences of brain activity changes during deep sedation linked to sedation doses. Particularly, the capability of network EEG-derived measures in discriminating between different sedation doses could be the framework for the development of accurate methods for sedation levels assessment.

Symbolic time series analysis of fNIRS signals in brain development assessment

OBJECTIVE

Assessing an infant's brain development remains a challenge for neuroscientists and pediatricians despite great technological advances. As a non-invasive neuroimaging tool, functional near-infrared spectroscopy (fNIRS) has great advantages in monitoring an infant's brain activity. To explore the dynamic features of hemodynamic changes in infants, in-pattern exponent (IPE), anti-pattern exponent (APE), as well as permutation cross-mutual information (PCMI) based on symbolic dynamics are proposed to measure the phase differences and coupling strength in oxyhemoglobin (HbO) and deoxyhemoglobin (Hb) signals from fNIRS.

APPROACH

First, simulated sinusoidal oscillation signals and four coupled nonlinear systems were employed for performance assessments. Hilbert transform based measurements of hemoglobin phase oxygenation and deoxygenation (hPod) and phase-locking index of hPod (hPodL) were calculated for comparison. Then, the IPE, APE and PCMI indices from resting state fNIRS data of preterm, term infants and adults were calculated to estimate the phase difference and coupling of HbO and Hb. All indices' performance was assessed by the degree of monotonicity (DoM). The box plots and coefficients of variation (CV) were employed to assess the measurements and robustness in the results.

MAIN RESULTS

In the simulation analysis, IPE and APE can distinguish the phase difference of two sinusoidal oscillation signals. Both hPodL and PCMI can track the strength of two coupled nonlinear systems. Compared to hPodL, the PCMI had higher DoM indices in measuring the coupling of two nonlinear systems. In the fNIRS data analysis, similar to hPod, the IPE and APE can distinguish preterm, term infants, and adults in 0.01-0.05 Hz, 0.05-0.1 Hz, and 0.01-0.1 Hz frequency bands, respectively. PCMI more effectively distinguished the term and preterm infants than hPodL in the 0.05-0.1 Hz frequency band. As symbolic time series measures, the IPE and APE were able to detect the brain developmental changes in subjects of different ages. PCMI can assess the resting-state HbO and Hb coupling changes across different developmental ages, which may reflect the metabolic and neurovascular development.

SIGNIFICANCE

The symbolic-based methodologies are promising measures for fNIRS in estimating the brain development, especially in assessing newborns' brain developmental status.

Network Properties in Transitions of Consciousness during Propofol-induced Sedation

Reliable electroencephalography (EEG) signatures of transitions between consciousness and unconsciousness under anaesthesia have not yet been identified. Herein we examined network changes using graph theoretical analysis of high-density EEG during patient-titrated propofol-induced sedation. Responsiveness was used as a surrogate for consciousness. We divided the data into five states: baseline, transition into unresponsiveness, unresponsiveness, transition into responsiveness, and recovery. Power spectral analysis showed that delta power increased from responsiveness to unresponsiveness. In unresponsiveness, delta waves propagated from frontal to parietal regions as a traveling wave. Local increases in delta connectivity were evident in parietal but not frontal regions. Graph theory analysis showed that increased local efficiency could differentiate the levels of responsiveness. Interestingly, during transitions of responsive states, increased beta connectivity was noted relative to consciousness and unconsciousness, again with increased local efficiency. Abrupt network changes are evident in the transitions in responsiveness, with increased beta band power/connectivity marking transitions between responsive states, while the delta power/connectivity changes were consistent with the fading of consciousness using its surrogate responsiveness. These results provide novel insights into the neural correlates of these behavioural transitions and EEG signatures for monitoring the levels of consciousness under sedation.

Statistical mechanics of consciousness: Maximization of information content of network is associated with conscious awareness

It is said that complexity lies between order and disorder. In the case of brain activity and physiology in general, complexity issues are being considered with increased emphasis. We sought to identify features of brain organization that are optimal for sensory processing, and that may guide the emergence of cognition and consciousness, by analyzing neurophysiological recordings in conscious and unconscious states. We find a surprisingly simple result: Normal wakeful states are characterized by the greatest number of possible configurations of interactions between brain networks, representing highest entropy values. Therefore, the information content is larger in the network associated to conscious states, suggesting that consciousness could be the result of an optimization of information processing. These findings help to guide in a more formal sense inquiry into how consciousness arises from the organization of matter.

Clinical Electroencephalography for Anesthesiologists: Part I: Background and Basic Signatures

The widely used electroencephalogram-based indices for depth-of-anesthesia monitoring assume that the same index value defines the same level of unconsciousness for all anesthetics. In contrast, we show that different anesthetics act at different molecular targets and neural circuits to produce distinct brain states that are readily visible in the electroencephalogram. We present a two-part review to educate anesthesiologists on use of the unprocessed electroencephalogram and its spectrogram to track the brain states of patients receiving anesthesia care. Here in part I, we review the biophysics of the electroencephalogram and the neurophysiology of the electroencephalogram signatures of three intravenous anesthetics: propofol, dexmedetomidine, and ketamine, and four inhaled anesthetics: sevoflurane, isoflurane, desflurane, and nitrous oxide. Later in part II, we discuss patient management using these electroencephalogram signatures. Use of these electroencephalogram signatures suggests a neurophysiologically based paradigm for brain state monitoring of patients receiving anesthesia care.

Percolation Model of Sensory Transmission and Loss of Consciousness Under General Anesthesia

Neurons communicate with each other dynamically; how such communications lead to consciousness remains unclear. Here, we present a theoretical model to understand the dynamic nature of sensory activity and information integration in a hierarchical network, in which edges are stochastically defined by a single parameter p representing the percolation probability of information transmission. We validate the model by comparing the transmitted and original signal distributions, and we show that a basic version of this model can reproduce key spectral features clinically observed in electroencephalographic recordings of transitions from conscious to unconscious brain activities during general anesthesia. As p decreases, a steep divergence of the transmitted signal from the original was observed, along with a loss of signal synchrony and a sharp increase in information entropy in a critical manner; this resembles the precipitous loss of consciousness during anesthesia. The model offers mechanistic insights into the emergence of information integration from a stochastic process, laying the foundation for understanding the origin of cognition.