Propofol-induced Unconsciousness Research Articles

Kendall transfer entropy: a novel measure for estimating information transfer in complex systems

Objective. Transfer entropy (TE) has been widely used to infer causal relationships among dynamical systems, especially in neuroscience. Kendall transformation provides a novel quantization method for estimating information-theoretic measures and shows potential advantages for small-sample neural signals. But it has yet to be introduced into the framework of TE estimation, which commonly suffers from the limitation of small sample sizes. This paper aims to introduce the idea of Kendall correlation into TE estimation and verify its effect. Approach. We proposed the Kendall TE (KTE) which combines the improved Kendall transformation and the TE estimation. To confirm its effectiveness, we compared KTE with two common TE estimation techniques: the adaptive partitioning algorithm (D-V partitioning) and the symbolic TE. Their performances were estimated by simulation experiments which included linear, nonlinear, linear + nonlinear models and neural mass models. Moreover, the KTE was also applied to real electroencephalography (EEG) recordings to quantify the directional connectivity between frontal and parietal regions with propofol-induced general anesthesia. Main results. The simulation results showed that the KTE outperformed the other two methods by many measures: (1) identifying the coupling direction under a small sample size; (2) the sensitivity to coupling strength; (3) noise resistance; and (4) the sensitivity to time-dependent coupling changes. For real EEG recordings, the KTE clearly detected the disrupted frontal-to-parietal connectivity in propofol-induced unconsciousness, which is in agreement with previous findings. Significance. We reveal that the proposed KTE method is a robust and powerful tool for estimating TE, and is particularly suitable for small sample sizes. The KTE also provides an innovative form of quantizing continuous time series for information-theoretic measures.

P2X7 Receptor in Microglia Contributes to Propofol-induced Unconsciousness by Regulating Synaptic Plasticity in Mice

Propofol infusion is processed through the wake-sleep cycle in neural connections, and the ionotropic purine type 2X7 receptor (P2X7R) is a nonspecific cation channel implicated in sleep regulation and synaptic plasticity through its regulation of electric activity in the brain. Here, we explored the potential roles of P2X7R of microglia in propofol-induced unconsciousness. Propofol induced loss of the righting reflex in male C57BL/6 wild-type mice and increased spectral power of the slow wave and delta wave of the medial prefrontal cortex (mPFC), all of which were reversed with P2X7R antagonist A-740003 and strengthened with P2X7R agonist Bz-ATP. Propofol increased the P2X7R expression level and P2X7R immunoreactivity with microglia in the mPFC, induced mild synaptic injury and increased GABA release in the mPFC, and these changes were less severe when treated with A-740003 and were more obvious when treated with Bz-ATP. Electrophysiological approaches showed that propofol induced a decreased frequency of sEPSCs and an increased frequency of sIPSCs, A-740003 decrease frequency of sEPSCs and sIPSCs and Bz-ATP increase frequency of sEPSCs and sIPSCs under propofol anesthesia. These findings indicated that P2X7R in microglia regulates synaptic plasticity and may contribute to propofol-mediated unconsciousness.

Different Alterations of Hippocampal and Reticulo-Thalamic GABAergic Parvalbumin-Expressing Interneurons Underlie Different States of Unconsciousness

We traced the changes in GABAergic parvalbumin (PV)-expressing interneurons of the hippocampus and reticulo-thalamic nucleus (RT) as possible underlying mechanisms of the different local cortical and hippocampal electroencephalographic (EEG) microstructures during the non-rapid-eye movement (NREM) sleep compared with anesthesia-induced unconsciousness by two anesthetics with different main mechanisms of action (ketamine/diazepam versus propofol). After 3 h of recording their sleep, the rats were divided into two experimental groups: one half received ketamine/diazepam anesthesia and the other half received propofol anesthesia. We simultaneously recorded the EEG of the motor cortex and hippocampus during sleep and during 1 h of surgical anesthesia. We performed immunohistochemistry and analyzed the PV and postsynaptic density protein 95 (PSD-95) expression. PV suppression in the hippocampus and at RT underlies the global theta amplitude attenuation and hippocampal gamma augmentation that is a unique feature of ketamine-induced versus propofol-induced unconsciousness and NREM sleep. While PV suppression resulted in an increase in hippocampal PSD-95 expression, there was no imbalance between inhibition and excitation during ketamine/diazepam anesthesia compared with propofol anesthesia in RT. This increased excitation could be a consequence of a lower GABA interneuronal activity and an additional mechanism underlying the unique local EEG microstructure in the hippocampus during ketamine/diazepam anesthesia.

Unveiling age-independent spectral markers of propofol-induced loss of consciousness by decomposing the electroencephalographic spectrum into its periodic and aperiodic components.

Induction of general anesthesia with propofol induces radical changes in cortical network organization, leading to unconsciousness. While perioperative frontal electroencephalography (EEG) has been widely implemented in the past decades, validated and age-independent EEG markers for the timepoint of loss of consciousness (LOC) are lacking. Especially the appearance of spatially coherent frontal alpha oscillations (8-12 Hz) marks the transition to unconsciousness.Here we explored whether decomposing the EEG spectrum into its periodic and aperiodic components unveiled markers of LOC and investigated their age-dependency. We further characterized the LOC-associated alpha oscillations by parametrizing the adjusted power over the aperiodic component, the center frequency, and the bandwidth of the peak in the alpha range. In this prospective observational trial, EEG were recorded in a young (18-30 years) and an elderly age-cohort (≥ 70 years) over the transition to propofol-induced unconsciousness. An event marker was set in the EEG recordings at the timepoint of LOC, defined with the suppression of the lid closure reflex. Spectral analysis was conducted with the multitaper method. Aperiodic and periodic components were parametrized with the FOOOF toolbox. Aperiodic parametrization comprised the exponent and the offset. The periodic parametrization consisted in the characterization of the peak in the alpha range with its adjusted power, center frequency and bandwidth. Three time-segments were defined: preLOC (105 - 75 s before LOC), LOC (15 s before to 15 s after LOC), postLOC (190 - 220 s after LOC). Statistical significance was determined with a repeated-measures ANOVA. Loss of consciousness was associated with an increase in the aperiodic exponent (young: p = 0.004, elderly: p = 0.007) and offset (young: p = 0.020, elderly: p = 0.004) as well as an increase in the adjusted power (young: p < 0.001, elderly p = 0.011) and center frequency (young: p = 0.008, elderly: p < 0.001) of the periodic alpha peak. We saw age-related differences in the aperiodic exponent and offset after LOC as well as in the power and bandwidth of the periodic alpha peak during LOC. Decomposing the EEG spectrum over induction of anesthesia into its periodic and aperiodic components unveiled novel age-independent EEG markers of propofol-induced LOC: the aperiodic exponent and offset as well as the center frequency and adjusted power of the power peak in the alpha range.

Claustrum modulates behavioral sensitivity and EEG activity of propofol anesthesia.

The claustrum has long been regarded as a vital center for conscious control. Electrical stimulation or damage to the claustrum can result in decreased awareness or loss of consciousness, suggesting that the claustrum may be a target for the action of general anesthetics. This study aimed to determine the role of the claustrum in propofol anesthesia. We first applied a fiber photometry calcium signal recording system to record the claustral neuronal activity during the entire process of propofol anesthesia. Chemogenetic activation of claustral neurones was then performed to verify their role in anesthesia. Finally, muscimol (GABAa receptor agonist) and gabazine (GABAa receptor antagonist) were microinjected into the claustrum to determine whether their GABAa receptors were involved in modulating propofol anesthesia. EEG and behavioral indicators, such as anesthetic sensitivity and efficacy, were recorded and analyzed. An evident anesthesia-related change in claustrum neuronal activity was suppressed during propofol-induced unconsciousness and restored following recovery from anesthesia. Chemogenetic activation of claustrum neuronsresults in attenuated propofol sensitivity, a shorter anesthesia duration, and an EEG shift toward wakefulness. Manipulation of GABAa receptors in the claustrum showed bidirectional control of propofol sensitivity, as activation decreases anesthesia efficiency while inactivation augments it. Additionally, inhibiting claustrum GABAa receptors increases cortical EEG slow waves. Claustrum neurones and their GABAa receptors are implicated in the modulation of propofol anesthesia in both behavioral and EEG assessments. Our findings create scope to reveal the brain targets of anesthetic action further and add to the existing evidence on the consciousness-modulating role of the claustrum.

Recognition of general anesthesia-induced loss of consciousness based on the spatial pattern of the brain networks

Objective. Unconsciousness is a key feature related to general anesthesia (GA) but is difficult to be evaluated accurately by anesthesiologists clinically. Approach. To tracking the loss of consciousness (LOC) and recovery of consciousness (ROC) under GA, in this study, by investigating functional connectivity of the scalp electroencephalogram, we explore any potential difference in brain networks among anesthesia induction, anesthesia recovery, and the resting state. Main results. The results of this study demonstrated significant differences among the three periods, concerning the corresponding brain networks. In detail, the suppressed default mode network, as well as the prolonged characteristic path length and decreased clustering coefficient, during LOC was found in the alpha band, compared to the Resting and the ROC state. When to further identify the Resting and LOC states, the fused network topologies and properties achieved the highest accuracy of 95%, along with a sensitivity of 93.33% and a specificity of 96.67%. Significance. The findings of this study not only deepen our understanding of propofol-induced unconsciousness but also provide quantitative measurements subserving better anesthesia management.

Cholinergic-Induced Specific Oscillations in the Medial Prefrontal Cortex to Reverse Propofol Anesthesia.

General anesthesia is a drug-induced reversible state comprised of altered states of consciousness, amnesia, analgesia, and immobility. The medial frontal cortex (mPFC) has been discovered to modulate the level of consciousness through cholinergic and glutamatergic pathways. The optogenetic tools combined with in vivo electrophysiological recording were used to study the neural oscillatory modulation mechanisms in mPFC underlying the loss of consciousness (LOC) and emergence. We found that optogenetic activation of both cholinergic and glutamatergic neurons in the basal forebrain (BF) reversed the hypnotic effect of propofol and accelerated the emergence from propofol-induced unconsciousness. The cholinergic light-activation during propofol anesthesia increased the power in the β (12–20 Hz) and low γ (20–30 Hz) bands. Conversely, glutamatergic activation increased the power at less specific broad (1–150 Hz) bands. The cholinergic-induced alteration to specific power bands after LOC had opposite effects to that of propofol. These results suggested that the cholinergic system might act on more specific cortical neural circuits related to propofol anesthesia.

Neural effects of propofol-induced unconsciousness and its reversal using thalamic stimulation.

The specific circuit mechanisms through which anesthetics induce unconsciousness have not been completely characterized. We recorded neural activity from the frontal, parietal, and temporal cortices and thalamus while maintaining unconsciousness in non-human primates (NHPs) with the anesthetic propofol. Unconsciousness was marked by slow frequency (~1 Hz) oscillations in local field potentials, entrainment of local spiking to Up states alternating with Down states of little or no spiking activity, and decreased coherence in frequencies above 4 Hz. Thalamic stimulation 'awakened' anesthetized NHPs and reversed the electrophysiologic features of unconsciousness. Unconsciousness is linked to cortical and thalamic slow frequency synchrony coupled with decreased spiking, and loss of higher-frequency dynamics. This may disrupt cortical communication/integration.

Dopamine D1 Receptor in the Nucleus Accumbens Modulates the Emergence from Propofol Anesthesia in Rat.

It has been reported that systemic activation of D1 receptors promotes emergence from isoflurane-induced unconsciousness, suggesting that the central dopaminergic system is involved in the process of recovering from general anesthesia. The nucleus accumbens (NAc) contains abundant GABAergic medium spiny neurons (MSNs) expressing the D1 receptor (D1R), which plays a key role in sleep-wake behavior. However, the role of NAc D1 receptors in the process of emergence from general anesthesia has not been identified. Here, using real-time in vivo fiber photometry, we found that neuronal activity in the NAc was markedly disinhibited during recovery from propofol anesthesia. Subsequently, microinjection of a D1R selective agonist (chloro-APB hydrobromide) into the NAc notably reduced the time to emerge from propofol anesthesia with a decrease in δ-band power and an increase in β-band power evident in the cortical electroencephalogram. These effects were prevented by pretreatment with a D1R antagonist (SCH-23390). Whole-cell patch clamp recordings were performed to further explore the cellular mechanism underlying the modulation of D1 receptors on MSNs under propofol anesthesia. Our data primarily demonstrated that propofol increased the frequency and prolonged the decay time of spontaneous inhibitory postsynaptic currents (sIPSCs) and miniature IPSCs (mIPSCs) of MSNs expressing D1 receptors. A D1R agonist attenuated the effect of propofol on the frequency of sIPSCs and mIPSCs, and the effects of the agonist were eliminated by preapplication of SCH-23390. Collectively, these results indicate that modulation of the D1 receptor on the activity of NAc MSNs is vital for emergence from propofol-induced unconsciousness.

Differentiating propofol-induced altered states of consciousness using features of EEG microstates

ObjectiveIn this study, we comprehensively studied alternations of EEG microstates in resting state, light, and deep level of propofol-induced unconsciousness. We further investigated the feasibility of using microstate features for differentiating different consciousness levels. Methods60-channel EEG was recorded from 31 male subjects in resting, light, and deep anesthesia states. Microstate analysis was performed on each consciousness levels separately. We first identified the optimal number of microstate templates for each consciousness levels and aligned them based on spatial similarity. Then, we extracted features including duration, coverage, and occurrence. Machine learning models including SVM, LDA and Random Forest were employed to classify different consciousness levels using microstate features. Finally, the cortical source of each microstates was analyzed using standardized low-resolution electromagnetic tomography. ResultsWe found that the optimal number of microstates differed in different consciousness levels. 7 common and 2 anesthesia-specific microstates were identified. M4, M5, M1 and M2 were similar to the canonical microstates A to D. Occurrence of M6 and duration of M1, M5 and M7 monotonically decreased with increasing level of consciousness suppression. All three features of the anesthesia-specific microstate M8 significantly decreased with increasing level of anesthesia. The classifiers using microstate features showed a mean accuracy of 85.6% to classify three consciousness levels. ConclusionEEG microstate features significantly altered during propofol-induced unconsciousness, and can be used to distinguish between consciousness levels. SignificanceMicrostate analysis may be a useful tool in deciphering the neural mechanism of propofol-induced anesthesia and provide useful features for quantifying levels of consciousness.

Largest scale dissociation of brain activity at propofol-induced loss of consciousness.

The brain is a functional unit made up of multilevel connected elements showing a pattern of synchronized activity that varies in different states. The wake-sleep cycle is a major variation of brain functional condition that is ultimately regulated by subcortical arousal- and sleep-promoting cell groups. We analyzed the evolution of functional MRI (fMRI) signal in the whole cortex and in a deep region including most sleep- and wake-regulating subcortical nuclei at loss of consciousness induced by the hypnotic agent propofol. Optimal data were obtained in 21 of the 30 healthy participants examined. A dynamic analysis of fMRI time courses on a time-scale of seconds was conducted to characterize consciousness transition, and functional connectivity maps were generated to detail the anatomy of structures showing different dynamics. Inside the magnet, loss of consciousness was marked by the participants ceasing to move their hands. We observed activity synchronization after loss of consciousness within both the cerebral cortex and subcortical structures. However, the evolution of fMRI signal was dissociated, showing a transient reduction of global cortico-subcortical coupling that was restored during the unconscious state. An exception to cortico-subcortical decoupling was a brain network related to self-awareness (i.e. the default mode network) that remained connected to subcortical brain structures. Propofol-induced unconsciousness is thus characterized by an initial, transitory dissociated synchronization at the largest scale of brain activity. Such cortico-subcortical decoupling and subsequent recoupling may allow the brain to detach from waking activity and reorganize into a functionally distinct state.

Information Integration and Mesoscopic Cortical Connectivity during Propofol Anesthesia.

The neurophysiologic mechanisms of propofol-induced loss of consciousness have been studied in detail at the macro (scalp electroencephalogram) and micro (spiking or local field potential) scales. However, the changes in information integration and cortical connectivity during propofol anesthesia at the mesoscopic level (the cortical scale) are less clear. The authors analyzed electrocorticogram data recorded from surgical patients during propofol-induced unconsciousness (n = 9). A new information measure, genuine permutation cross mutual information, was used to analyze how electrocorticogram cross-electrode coupling changed with electrode-distances in different brain areas (within the frontal, parietal, and temporal regions, as well as between the temporal and parietal regions). The changes in cortical networks during anesthesia-at nodal and global levels-were investigated using clustering coefficient, path length, and nodal efficiency measures. In all cortical regions, and in both wakeful and unconscious states (early and late), the genuine permutation cross mutual information and the percentage of genuine connections decreased with increasing distance, especially up to about 3 cm. The nodal cortical network metrics (the nodal clustering coefficients and nodal efficiency) decreased from wakefulness to unconscious state in the cortical regions we analyzed. In contrast, the global cortical network metrics slightly increased in the early unconscious state (the time span from loss of consciousness to 200 s after loss of consciousness), as compared with wakefulness (normalized average clustering coefficient: 1.05 ± 0.01 vs. 1.06 ± 0.03, P = 0.037; normalized average path length: 1.02 ± 0.01 vs. 1.04 ± 0.01, P = 0.021). The genuine permutation cross mutual information reflected propofol-induced coupling changes measured at a cortical scale. Loss of consciousness was associated with a redistribution of the pattern of information integration; losing efficient global information transmission capacity but increasing local functional segregation in the cortical network.

Dynamics of recovery from anaesthesia-induced unconsciousness across primate neocortex.

How the brain recovers from general anaesthesia is poorly understood. Neurocognitive problems during anaesthesia recovery are associated with an increase in morbidity and mortality in patients. We studied intracortical neuronal dynamics during transitions from propofol-induced unconsciousness into consciousness by directly recording local field potentials and single neuron activity in a functionally and anatomically interconnecting somatosensory (S1, S2) and ventral premotor (PMv) network in primates. Macaque monkeys were trained for a behavioural task designed to determine trial-by-trial alertness and neuronal response to tactile and auditory stimulation. We found that neuronal dynamics were dissociated between S1 and higher-order PMv prior to return of consciousness. The return of consciousness was distinguishable by a distinctive return of interregionally coherent beta oscillations and disruption of the slow-delta oscillations. Clustering analysis demonstrated that these state transitions between wakefulness and unconsciousness were rapid and unstable. In contrast, return of pre-anaesthetic task performance was observed with a gradual increase in the coherent beta oscillations. We also found that recovery end points significantly varied intra-individually across sessions, as compared to a rather consistent loss of consciousness time. Recovery of single neuron multisensory responses appeared to be associated with the time of full performance recovery rather than the length of recovery time. Similar to loss of consciousness, return of consciousness was identified with an abrupt shift of dynamics and the regions were dissociated temporarily during the transition. However, the actual dynamics change during return of consciousness is not simply an inverse of loss of consciousness, suggesting a unique process.

Reorganization of rich-clubs in functional brain networks during propofol-induced unconsciousness and natural sleep.

General anesthesia (GA) provides an invaluable experimental tool to understand the essential neural mechanisms underlying consciousness. Previous neuroimaging studies have shown the functional integration and segregation of brain functional networks during anesthetic-induced alteration of consciousness. However, the organization pattern of hubs in functional brain networks remains unclear. Moreover, comparisons with the well-characterized physiological unconsciousness can help us understand the neural mechanisms of anesthetic-induced unconsciousness. Resting-state functional magnetic resonance imaging was performed during wakefulness, mild propofol-induced sedation (m-PIS), and deep PIS (d-PIS) with clinical unconsciousness on 8 healthy volunteers and wakefulness and natural sleep on 9 age- and sex-matched healthy volunteers. Large-scale functional brain networks of each volunteer were constructed based on 160 regions of interest. Then, rich-club organizations in brain functional networks and nodal properties (nodal strength and efficiency) were assessed and analyzed among the different states and groups. Rich-clubs in the functional brain networks were reorganized during alteration of consciousness induced by propofol. Firstly, rich-club nodes were switched from the posterior cingulate cortex (PCC), angular gyrus, and anterior and middle insula to the inferior parietal lobule (IPL), inferior parietal sulcus (IPS), and cerebellum. When sedation was deepened to unconsciousness, the rich-club nodes were switched to the occipital and angular gyrus. These results suggest that the rich-club nodes were switched among the high-order cognitive function networks (default mode network [DMN] and fronto-parietal network [FPN]), sensory networks (occipital network [ON]), and cerebellum network (CN) from consciousness (wakefulness) to propofol-induced unconsciousness. At the same time, compared with wakefulness, local connections were switched to rich-club connections during propofol-induced unconsciousness, suggesting a strengthening of the overall information commutation of networks. Nodal efficiency of the anterior and middle insula and ventral frontal cortex was significantly decreased. Additionally, from wakefulness to natural sleep, a similar pattern of rich-club reorganization with propofol-induced unconsciousness was observed: rich-club nodes were switched from the DMN (including precuneus and PCC) to the sensorimotor network (SMN, including part of the frontal and temporal gyrus). Compared with natural sleep, nodal efficiency of the insula, frontal gyrus, PCC, and cerebellum significantly decreased during propofol-induced unconsciousness. Our study demonstrated that the rich-club reorganization in functional brain networks is characterized by switching of rich-club nodes between the high-order cognitive and sensory and motor networks during propofol-induced alteration of consciousness and natural sleep. These findings will help understand the common neurological mechanism of pharmacological and physiological unconsciousness.

Remifentanil Alleviates Propofol-Induced Burst Suppression without Affecting Bispectral Index in Female Patients: A Randomized Controlled Trial.

The bispectral index is affected by various factors, such as noxious stimuli and other drugs, such as muscle relaxants. The burst suppression ratio from bispectral index monitoring is correlated with electroencephalographic burst suppression, which is associated with deep anesthesia, metabolic disorders, and brain injury. We assessed patients undergoing total intravenous anesthesia and examined the effects of remifentanil on the bispectral index, burst suppression ratio, and hemodynamic changes immediately after loss of consciousness with propofol. Seventy American Society of Anesthesiologists physical status class I and II Korean female patients scheduled for general anesthesia were administered propofol with an effect-site concentration of 5 μg/mL, using a target-controlled infusion (TCI). After losing consciousness, patients received either saline or remifentanil at an effect-site concentration of 5 ng/mL for 10 min. During this period, we recorded the bispectral index values, including burst suppression ratio, blood pressure, and heart rate. With remifentanil infusion, burst suppression ratios were lower (p < 0.01) but bispectral values were not different. The burst suppression ratio was significantly different at 6, 7, 8, and 10 min after remifentanil infusion (p < 0.05). In female patients with propofol-induced unconsciousness, remifentanil alleviated the burst suppression ratio without affecting the bispectral value.

Changes in Whole Brain Dynamics and Connectivity Patterns during Sevoflurane- and Propofol-induced Unconsciousness Identified by Functional Magnetic Resonance Imaging.

A key feature of the human brain is its capability to adapt flexibly to changing external stimuli. This capability can be eliminated by general anesthesia, a state characterized by unresponsiveness, amnesia, and (most likely) unconsciousness. Previous studies demonstrated decreased connectivity within the thalamus, frontoparietal, and default mode networks during general anesthesia. We hypothesized that these alterations within specific brain networks lead to a change of communication between networks and their temporal dynamics. We conducted a pooled spatial independent component analysis of resting-state functional magnetic resonance imaging data obtained from 16 volunteers during propofol and 14 volunteers during sevoflurane general anesthesia that have been previously published. Similar to previous studies, mean z-scores of the resulting spatial maps served as a measure of the activity within a network. Additionally, correlations of associated time courses served as a measure of the connectivity between networks. To analyze the temporal dynamics of between-network connectivity, we computed the correlation matrices during sliding windows of 1 min and applied k-means clustering to the matrices during both general anesthesia and wakefulness. Within-network activity was decreased in the default mode, attentional, and salience networks during general anesthesia (P < 0.001, range of median changes: -0.34, -0.13). Average between-network connectivity was reduced during general anesthesia (P < 0.001, median change: -0.031). Distinct between-network connectivity patterns for both wakefulness and general anesthesia were observed irrespective of the anesthetic agent (P < 0.001), and there were fewer transitions in between-network connectivity patterns during general anesthesia (P < 0.001, median number of transitions during wakefulness: 4 and during general anesthesia: 0). These results suggest that (1) higher-order brain regions play a crucial role in the generation of specific between-network connectivity patterns and their dynamics, and (2) the capability to interact with external stimuli is represented by complex between-network connectivity patterns.

Propofol-induced unresponsiveness is associated with impaired feedforward connectivity in cortical hierarchy

BackgroundImpaired consciousness has been associated with impaired cortical signal propagation after transcranial magnetic stimulation (TMS). We hypothesised that the reduced current propagation under propofol-induced unresponsiveness is associated with changes in both feedforward and feedback connectivity across the cortical hierarchy. MethodsEight subjects underwent left occipital TMS coupled with high-density EEG recordings during wakefulness and propofol-induced unconsciousness. Spectral analysis was applied to responses recorded from sensors overlying six hierarchical cortical sources involved in visual processing. Dynamic causal modelling (DCM) of induced time–frequency responses and evoked response potentials were used to investigate propofol's effects on connectivity between regions. ResultsSensor space analysis demonstrated that propofol reduced both induced and evoked power after TMS in occipital, parietal, and frontal electrodes. Bayesian model selection supported a DCM with hierarchical feedforward and feedback connections. DCM of induced EEG responses revealed that the primary effect of propofol was impaired feedforward responses in cross-frequency theta/alpha–gamma coupling and within frequency theta coupling (F contrast, family-wise error corrected P<0.05). An exploratory analysis (thresholded at uncorrected P<0.001) also suggested that propofol impaired feedforward and feedback beta band coupling. Post hoc analyses showed impairments in all feedforward connections and one feedback connection from parietal to occipital cortex. DCM of the evoked response potential showed impaired feedforward connectivity between left-sided occipital and parietal cortex (T contrast P=0.004, Bonferroni corrected). ConclusionsPropofol-induced loss of consciousness is associated with impaired hierarchical feedforward connectivity assessed by EEG after occipital TMS.

State Space Oscillator Models for Neural Data Analysis.

Neural oscillations reflect the coordinated activity of neuronal populations across a wide range of temporal and spatial scales, and are thought to play a significant role in mediating many aspects of brain function, including atten- tion, cognition, sensory processing, and consciousness. Brain oscillations are typically analyzed using frequency domain methods such as nonparametric spectral analysis, or time domain methods based on linear bandpass filtering. A typical analysis might seek to estimate the power within an oscillation sitting within a particular frequency band. A common approach to this problem is to estimate the signal power within that band, in frequency domain using the power spectrum, or in time domain by estimating the power or variance in a bandpass filtered signal. A major conceptual flaw in this approach is that neural systems, like many physiological or physical systems, have inherent broad-band 1/P' dynamics, whether or not an oscillation is present. Calculating power-in-band, or power in a bandpass filtered signal, can therefore be misleading, since such calculations do not distinguish between broadband power within the band of interest, and true underlying oscillations. In this paper, we present an approach for analyzing neural oscillations using a combination of linear oscillatory models. We estimate the parameters of these models using an expectation maximization (EM) algorithm, and employ AIC to select the appropriate model and identify the oscillations present in the data. We demonstrate the application of this method to univariate electroencephalogram (EEG) data recorded at quiet rest and during propofol-induced unconsciousness.

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

BackgroundBoth the cerebral cortex and subcortical structures play important roles in consciousness. Some evidence points to general anaesthesia-induced unconsciousness being associated with distinct patterns of superficial cortical electrophysiological oscillations, but how general anaesthetics influence deep brain neural oscillations and interactions between oscillations in humans is poorly understood. MethodsLocal field potentials were recorded in discrete deep brain regions, including anterior cingulate cortex, sensory thalamus, and periaqueductal grey, in humans with implanted deep brain electrodes during induction of unconsciousness with propofol. Power-frequency spectra, phase-amplitude coupling, coherence, and directed functional connectivity analysis were used to characterise local field potentials in the awake and unconscious states. ResultsAn increase in alpha (7–13 Hz) power and decrease in gamma (30–90 Hz) power were observed in both deep cortical (ACC, anterior cingulate cortex) and subcortical (sensory thalamus, periaqueductal grey) areas during propofol-induced unconsciousness. Robust alpha-low gamma (30–60 Hz) phase-amplitude coupling induced by general anaesthesia was observed in the anterior cingulate cortex but not in other regions studied. Moreover, alpha oscillations during unconsciousness were highly coherent within the anterior cingulate cortex, and this rhythm exhibited a bidirectional information flow between left and right anterior cingulate cortex but stronger left-to-right flow. ConclusionPropofol increases alpha oscillations and attenuates gamma oscillations in both cortical and subcortical areas. The alpha-gamma phase-amplitude coupling and the functional connectivity of alpha oscillations in the anterior cingulate cortex could be specific markers for loss of consciousness.

A Prospective Study of Age-dependent Changes in Propofol-induced Electroencephalogram Oscillations in Children.

In adults, frontal electroencephalogram patterns observed during propofol-induced unconsciousness consist of slow oscillations (0.1 to 1 Hz) and coherent alpha oscillations (8 to 13 Hz). Given that the nervous system undergoes significant changes during development, anesthesia-induced electroencephalogram oscillations in children may differ from those observed in adults. Therefore, we investigated age-related changes in frontal electroencephalogram power spectra and coherence during propofol-induced unconsciousness. We analyzed electroencephalogram data recorded during propofol-induced unconsciousness in patients between 0 and 21 yr of age (n = 97), using multitaper spectral and coherence methods. We characterized power and coherence as a function of age using multiple linear regression analysis and within four age groups: 4 months to 1 yr old (n = 4), greater than 1 to 7 yr old (n = 16), greater than 7 to 14 yr old (n = 30), and greater than 14 to 21 yr old (n = 47). Total electroencephalogram power (0.1 to 40 Hz) peaked at approximately 8 yr old and subsequently declined with increasing age. For patients greater than 1 yr old, the propofol-induced electroencephalogram structure was qualitatively similar regardless of age, featuring slow and coherent alpha oscillations. For patients under 1 yr of age, frontal alpha oscillations were not coherent. Neurodevelopmental processes that occur throughout childhood, including thalamocortical development, may underlie age-dependent changes in electroencephalogram power and coherence during anesthesia. These age-dependent anesthesia-induced electroencephalogram oscillations suggest a more principled approach to monitoring brain states in pediatric patients.