Reconfiguration of network hub structure after propofol-induced unconsciousness

Common functional mechanisms underlying dynamic brain network changes across five general anesthetics: A rat fMRI study

BACKGROUND

Reversible loss of consciousness is the primary therapeutic endpoint of general anesthesia; however, the drug-invariant mechanisms underlying anesthetic-induced unconsciousness are still unclear. This study aimed to investigate the static, dynamic, topological and organizational changes in functional brain network induced by five clinically-used general anesthetics in the rat brain.

METHOD

Male Sprague-Dawley rats (n = 57) were randomly allocated to received propofol, isoflurane, ketamine, dexmedetomidine, or combined isoflurane plus dexmedetomidine anesthesia. Resting-state functional magnetic resonance images were acquired under general anesthesia and analyzed for changes in dynamic functional brain networks compared to the awake state.

RESULTS

Different general anesthetics induced distinct patterns of functional connectivity inhibition within brain-wide networks, resulting in multi-level network reorganization primarily by impairing the functional connectivity of cortico-subcortical networks as well as by reducing information transmission capacity, intrinsic connectivity, and network architecture stability of subcortical regions. Conversely, functional connectivity and topological properties were preserved within cortico-cortical networks, albeit with fewer dynamic fluctuations under general anesthesia.

CONCLUSIONS

Our findings highlighted the effects of different general anesthetics on functional brain network reorganization, which might shed light on the drug-invariant mechanism of anesthetic-induced unconsciousness.

Dynamical changes of interaction across functional brain communities during propofol-induced sedation

It is crucial to understand how anesthetics disrupt information transmission within the whole-brain network and its hub structure to gain insight into the network-level mechanisms underlying propofol-induced sedation. However, the influence of propofol on functional integration, segregation, and community structure of whole-brain networks were still unclear. We recruited 12 healthy subjects and acquired resting-state functional magnetic resonance imaging data during 5 different propofol-induced effect-site concentrations (CEs): 0, 0.5, 1.0, 1.5, and 2.0 μg/ml. We constructed whole-brain functional networks for each subject under different conditions and identify community structures. Subsequently, we calculated the global and local topological properties of whole-brain network to investigate the alterations in functional integration and segregation with deepening propofol sedation. Additionally, we assessed the alteration of key nodes within the whole-brain community structure at each effect-site concentrations level. We found that global participation was significantly increased at high effect-site concentrations, which was mediated by bilateral postcentral gyrus. Meanwhile, connector hubs appeared and were located in posterior cingulate cortex and precentral gyrus at high effect-site concentrations. Finally, nodal participation coefficients of connector hubs were closely associated to the level of sedation. These findings provide valuable insights into the relationship between increasing propofol dosage and enhanced functional interaction within the whole-brain networks.

Changes in information integration and brain networks during propofol-, dexmedetomidine-, and ketamine-induced unresponsiveness

BACKGROUND

Information integration and network science are important theories for quantifying consciousness. However, whether these theories propose drug- or conscious state-related changes in EEG during anaesthesia-induced unresponsiveness remains unknown.

METHODS

A total of 72 participants were randomised to receive i.v. infusion of propofol, dexmedetomidine, or ketamine at a constant infusion rate until loss of responsiveness. High-density EEG was recorded during the consciousness transition from the eye-closed baseline to the unresponsiveness state and then to the recovery of the responsiveness state. Permutation cross mutual information (PCMI) and PCMI-based brain networks in broadband (0.1-45 Hz) and sub-band frequencies were used to analyse drug- and state-related EEG signature changes.

RESULTS

PCMI and brain networks exhibited state-related changes in certain brain regions and frequency bands. The within-area PCMI of the frontal, parietal, and occipital regions, and the between-area PCMI of the parietal-occipital region (median [inter-quartile ranges]), baseline vs unresponsive were as follows: 0.54 (0.46-0.58) vs 0.46 (0.40-0.50), 0.58 (0.52-0.60) vs 0.48 (0.44-0.53), 0.54 (0.49-0.59) vs 0.47 (0.42-0.52) decreased during anaesthesia for three drugs (P<0.05). Alpha PCMI in the frontal region, and gamma PCMI in the posterior area significantly decreased in the unresponsive state (P<0.05). The frontal, parietal, and occipital nodal clustering coefficients and parietal nodal efficiency decreased in the unresponsive state (P<0.05). The increased normalised path length in delta, theta, and gamma bands indicated impaired global integration (P<0.05).

CONCLUSIONS

The three anaesthetics caused changes in information integration patterns and network functions. Thus, it is possible to build a quantifying framework for anaesthesia-induced conscious state changes on the EEG scale using PCMI and network science.

Atypical instantaneous spatio-temporal patterns of neural dynamics in Alzheimer's disease

Cognitive functions produced by large-scale neural integrations are the most representative 'emergence phenomena' in complex systems. A novel approach focusing on the instantaneous phase difference of brain oscillations across brain regions has succeeded in detecting moment-to-moment dynamic functional connectivity. However, it is restricted to pairwise observations of two brain regions, contrary to large-scale spatial neural integration in the whole-brain. In this study, we introduce a microstate analysis to capture whole-brain instantaneous phase distributions instead of pairwise differences. Upon applying this method to electroencephalography signals of Alzheimer's disease (AD), which is characterised by progressive cognitive decline, the AD-specific state transition among the four states defined as the leading phase location due to the loss of brain regional interactions could be promptly characterised. In conclusion, our synthetic analysis approach, focusing on the microstate and instantaneous phase, enables the capture of the instantaneous spatiotemporal neural dynamics of brain activity and characterises its pathological conditions.

The EEG complexity, information integration and brain network changes in minimally conscious state patients during general anesthesia

Objective.General anesthesia (GA) can induce reversible loss of consciousness. Nonetheless, the electroencephalography (EEG) characteristics of patients with minimally consciousness state (MCS) during GA are seldom observed.Approach.We recorded EEG data from nine MCS patients during GA. We used the permutation Lempel-Ziv complexity (PLZC), permutation fluctuation complexity (PFC) to quantify the type I and II complexities. Additionally, we used permutation cross mutual information (PCMI) and PCMI-based brain network to investigate functional connectivity and brain networks in sensor and source spaces.Main results.Compared to the preoperative resting state, during the maintenance of surgical anesthesia state, PLZC decreased (p< 0.001), PFC increased (p< 0.001) and PCMI decreased (p< 0.001) in sensor space. The results for these metrics in source space are consistent with sensor space. Additionally, node network indicators nodal clustering coefficient (NCC) (p< 0.001) and nodal efficiency (NE) (p< 0.001) decreased in these two spaces. Global network indicators normalized average path length (Lave/Lr) (p< 0.01) and modularity (Q) (p< 0.05) only decreased in sensor space, while the normalized average clustering coefficient (Cave/Cr) and small-world index (σ) did not change significantly. Moreover, the dominance of hub nodes is reduced in frontal regions in these two spaces. After recovery of consciousness, PFC decreased in the two spaces, while PLZC, PCMI increased. NCC, NE, and frontal region hub node dominance increased only in the sensor space. These indicators did not return to preoperative levels. In contrast, global network indicatorsLave/LrandQwere not significantly different from the preoperative resting state in sensor space.Significance.GA alters the complexity of the EEG, decreases information integration, and is accompanied by a reconfiguration of brain networks in MCS patients. The PLZC, PFC, PCMI and PCMI-based brain network metrics can effectively differentiate the state of consciousness of MCS patients during GA.

EEG spectral slope: A reliable indicator for continuous evaluation of consciousness levels during propofol anesthesia

The level of consciousness undergoes continuous alterations during anesthesia. Prior to the onset of propofol-induced complete unconsciousness, degraded levels of behavioral responsiveness can be observed. However, a reliable index to monitor altered consciousness levels during anesthesia has not been sufficiently investigated. In this study, we obtained 60-channel EEG data from 24 healthy participants during an ultra-slow propofol infusion protocol starting with an initial concentration of 1 μg/ml and a stepwise increase of 0.2 μg/ml in concentration. Consecutive auditory stimuli were delivered every 5 to 6 s, and the response time to the stimuli was used to assess the responsiveness levels. We calculated the spectral slope in a time-resolved manner by extracting 5-second EEG segments at each auditory stimulus and estimated their correlation with the corresponding response time. Our results demonstrated that during slow propofol infusion, the response time to external stimuli increased, while the EEG spectral slope, fitted at 15-45 Hz, became steeper, and a significant negative correlation was observed between them. Moreover, the spectral slope further steepened at deeper anesthetic levels and became flatter during anesthesia recovery. We verified these findings using an external dataset. Additionally, we found that the spectral slope of frontal electrodes over the prefrontal lobe had the best performance in predicting the response time. Overall, this study used a time-resolved analysis to suggest that the EEG spectral slope could reliably track continuously altered consciousness levels during propofol anesthesia. Furthermore, the frontal spectral slope may be a promising index for clinical monitoring of anesthesia depth.

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.

Evaluating brain spectral and connectivity differences between silent mind-wandering and trance states

Trance is an altered state of consciousness characterized by alterations in cognition. In general, trance states induce mental silence (i.e., cognitive thought reduction), and mental silence can induce trance states. Conversely, mind-wandering is the mind's propensity to stray its attention away from the task at hand and toward content irrelevant to the current moment, and its main component is inner speech. Building on the previous literature on mental silence and trance states and incorporating inverse source reconstruction advances, the study's objectives were to evaluate differences between trance and mind-wandering states using: (1) electroencephalography (EEG) power spectra at the electrode level, (2) power spectra at the area level (source reconstructed signal), and (3) EEG functional connectivity between these areas (i.e., how they interact). The relationship between subjective trance depths ratings and whole-brain connectivity during trance was also evaluated. Spectral analyses revealed increased delta and theta power in the frontal region and increased gamma in the centro-parietal region during mind-wandering, whereas trance showed increased beta and gamma power in the frontal region. Power spectra at the area level and pairwise comparisons of the connectivity between these areas demonstrated no significant difference between the two states. However, subjective trance depth ratings were inversely correlated with whole-brain connectivity in all frequency bands (i.e., deeper trance is associated with less large-scale connectivity). Trance allows one to enter mentally silent states and explore their neurophenomenological processes. Limitations and future directions are discussed.

Emerging functional connectivity patterns during sevoflurane anaesthesia in the developing human brain

BACKGROUND

Spectral-based EEG is used to monitor anaesthetic state during surgical procedures in adults. Spectral EEG features that can resemble the patterns seen in adults emerge in children after the age of 10 months and cannot distinguish wakefulness and anaesthesia in the youngest children. There is a need to explore alternative EEG measures. We hypothesise that functional connectivity is one of the measures that can help distinguish between consciousness states in children.

METHODS

An EEG data set of children undergoing sevoflurane general anaesthesia (age 0-3 yr) was reanalysed using debiased weighted phase lag index as a measure of functional connectivity in wakefulness (n=38) and anaesthesia (n=73). Network topology measures were compared between states in 0- to 6-, 6- to 10-, and >10-month-old children.

RESULTS

Functional connectivity was reduced in anaesthesia vs wakefulness in delta band (n=cluster of 17 significant connections; P=0.013; 58% connections surviving thresholding in wakefulness and 49% in anaesthesia). Network density and node degree were lower in anaesthesia even in the youngest children (0.57 in wakefulness; 0.48 in anaesthesia; t [9]=3.39; P=0.029; G=0.98; confidence interval [CI] [0.25-1.77]). Modularity was higher in anaesthesia (0-6 months: 0.16 in wakefulness and 0.19 in anaesthesia, t [9]=-2.95, P=0.04, G=-0.85, CI [-1.60 to -0.16]; >10 months: 0.16 vs 0.21, t [13]=-6.45, P<0.001, G=-1.62, CI [-2.49 to -0.85]) and decreased with age (ρ [73]=-0.456; P<0.001).

CONCLUSIONS

Anaesthesia modulates functional connectivity. Increased segregation into a more modular structure in anaesthesia decreases with age as adult-like features develop. These findings advance our understanding of the network architecture underlying the effects of anaesthesia on the developing brain.

Functional brain network and trail making test changes following major surgery and postoperative delirium: a prospective, multicentre, observational cohort study

BACKGROUND

Delirium is a frequent complication after surgery in older adults and is associated with an increased risk of long-term cognitive impairment and dementia. Disturbances in functional brain networks were previously reported during delirium. We hypothesised that alterations in functional brain networks persist after remission of postoperative delirium and that functional brain network alterations are associated with long-term cognitive impairment.

METHODS

In this prospective, multicentre, observational cohort study, we included older patients who underwent clinical assessments (including the Trail Making Test B [TMT-B]) and resting-state functional MRI (rs-fMRI) before and 3 months after elective surgery. Delirium was assessed on the first seven postoperative days.

RESULTS

Of the 554 enrolled patients, 246 remained after strict motion correction, of whom 38 (16%) developed postoperative delirium. The rs-fMRI functional connectivity strength increased 3 months after surgery in the total study population (β=0.006; 95% confidence interval [CI]: 0.001-0.011; P=0.013), but it decreased after postoperative delirium (β=-0.015; 95% CI: -0.028 to 0.002; P=0.023). No difference in TMT-B scores was found at follow-up between patients with and without postoperative delirium. Patients with decreased functional connectivity strength declined in TMT-B scores compared with those who did not (β=11.04; 95% CI: 0.85-21.2; P=0.034).

CONCLUSIONS

Postoperative delirium was associated with decreased brain functional connectivity strength after 3 months, suggesting that delirium has a long-lasting impact on brain networks. The decreased connectivity strength was associated with significant cognitive deterioration after major surgery.

CLINICAL TRIAL REGISTRATION

NCT02265263.

Deep brain stimulation improves electroencephalogram functional connectivity of patients with minimally conscious state

AIM

Deep brain stimulation (DBS) is a potential neuromodulatory therapy that enhances recovery from disorders of consciousness, especially minimally conscious state (MCS). This study measured the effects of DBS on the brain and explored the underlying mechanisms of DBS on MCS.

METHODS

Nine patients with MCS were recruited for this study. The neuromodulation effects of 100 Hz DBS were explored via cross-control experiments. Coma Recovery Scale-Revised (CRS-R) and EEG were recorded, and corresponding functional connectivity and network parameters were calculated.

RESULTS

Our results showed that 100 Hz DBS could improve the functional connectivity of the whole, local and local-local brain regions, while no significant change in EEG functional connectivity was observed in sham DBS. The whole brain's network parameters (clustering coefficient, path length, and small world characteristic) were significantly improved. In addition, a significant increase in the CRS-R and functional connectivity of three MCS patients who received 100 Hz DBS for 6 months were observed.

CONCLUSION

This study showed that DBS improved EEG functional connectivity and brain networks, indicating that the long-term use of DBS could improve the level of consciousness of MCS patients.

Effect of sedatives or anesthetics on the measurement of resting brain function in common marmosets

Common marmosets are promising laboratory animals for the study of higher brain functions. Although there are many opportunities to use sedatives and anesthetics in resting brain function measurements in marmosets, their effects on the resting-state network remain unclear. In this study, the effects of sedatives or anesthetics such as midazolam, dexmedetomidine, co-administration of isoflurane and dexmedetomidine, propofol, alfaxalone, isoflurane, and sevoflurane on the resting brain function in common marmosets were evaluated using independent component analysis, dual regression analysis, and graph-theoretic analysis; and the sedatives or anesthetics suitable for the evaluation of resting brain function were investigated. The results show that network preservation tendency under light sedative with midazolam and dexmedetomidine is similar regardless of the type of target receptor. Moreover, alfaxalone, isoflurane, and sevoflurane have similar effects on resting state brain function, but only propofol exhibits different tendencies, as resting brain function is more preserved than it is following the administration of the other anesthetics. Co-administration of isoflurane and dexmedetomidine shows middle effect between sedatives and anesthetics.

Paradoxical markers of conscious levels: Effects of propofol on patients in disorders of consciousness

Human consciousness is widely understood to be underpinned by rich and diverse functional networks, whose breakdown results in unconsciousness. Candidate neural correlates of anesthetic-induced unconsciousness include: (1) disrupted frontoparietal functional connectivity; (2) disrupted brain network hubs; and (3) reduced spatiotemporal complexity. However, emerging counterexamples have revealed that these markers may appear outside of the state they are associated with, challenging both their inclusion as markers of conscious level, and the theories of consciousness that rely on their evidence. In this study, we present a case series of three individuals in disorders of consciousness (DOC) who exhibit paradoxical brain responses to exposure to anesthesia. High-density electroencephalographic data were recorded from three patients with unresponsive wakefulness syndrome (UWS) while they underwent a protocol of propofol anesthesia with a targeted effect site concentration of 2 μg/ml. Network hubs and directionality of functional connectivity in the alpha frequency band (8–13 Hz), were estimated using the weighted phase lag index (wPLI) and directed phase lag index (dPLI). The spatiotemporal signal complexity was estimated using three types of Lempel-Ziv complexity (LZC). Our results illustrate that exposure to propofol anesthesia can paradoxically result in: (1) increased frontoparietal feedback-dominant connectivity; (2) posterior network hubs; and (3) increased spatiotemporal complexity. The case examples presented in this paper challenge the role of functional connectivity and spatiotemporal complexity in theories of consciousness and for the clinical evaluation of levels of human consciousness.

Selective corticocortical connectivity suppression during propofol-induced anesthesia in healthy volunteers

We comprehensively studied directional feedback and feedforward connectivity to explore potential connectivity changes that underlie propofol-induced deep sedation. We further investigated the corticocortical connectivity patterns within and between hemispheres. Sixty-channel electroencephalographic data were collected from 19 healthy volunteers in a resting wakefulness state and propofol-induced deep unconsciousness state defined by a bispectral index value of 40. A source analysis was employed to locate cortical activity. The Desikan-Killiany atlas was used to partition cortices, and directional functional connectivity was assessed by normalized symbolic transfer entropy between higher-order (prefrontal and frontal) and lower-order (auditory, sensorimotor and visual) cortices and between hot-spot frontal and parietal cortices. We found that propofol significantly suppressed feedforward connectivity from the left parietal to right frontal cortex and bidirectional connectivity between the left frontal and left parietal cortex, between the frontal and auditory cortex, and between the frontal and sensorimotor cortex. However, there were no significant changes in either feedforward or feedback connectivity between the prefrontal and all the lower-order cortices and between the frontal and visual cortices or in feedback connectivity from the frontal to parietal cortex. Propofol anesthetic selectively decreased the unidirectional interaction between higher-order frontoparietal cortices and bidirectional interactions between the higher-order frontal cortex and lower-order auditory and sensorimotor cortices, which indicated that both feedback and feedforward connectivity were suppressed under propofol-induced deep sedation. Our findings provide critical insights into the connectivity changes underlying the top-down mechanism of propofol anesthesia at deep sedation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-021-09775-x.

Cortical Complexity and Connectivity during Isoflurane-induced General Anesthesia: A Rat Study

OBJECTIVE

The investigation of neurophysiologic mechanisms of anesthetic drug-induced loss of consciousness (LOC) by using the entropy, complexity, and information integration theories at the mesoscopic level has been a hot topic in recent years. However, systematic research is still lacking.

APPROACH

We analyzed electrocorticography (ECoG) data recorded from nine rats during isoflurane-induced unconsciousness. To characterize the complexity and connectivity changes, we investigated ECoG power, symbolic dynamic-based entropy (i.e., permutation entropy (PE)), complexity (i.e., permutation Lempel-Ziv complexity (PLZC)), information integration (i.e., permutation cross mutual information (PCMI)), and PCMI-based cortical brain networks in the frontal, parietal, and occipital cortical regions.

MAIN RESULTS

Firstly, LOC was accompanied by a raised power in the ECoG beta (12-30 Hz) but a decreased power in the high gamma (55-95 Hz) frequency band in all three brain regions. Secondly, PE and PLZC showed similar change trends in the lower frequency band (0.1-45 Hz), declining after LOC (p<0.05) and increasing after recovery of consciousness (p<0.001). Thirdly, intra-frontal and inter-frontal-parietal PCMI declined after LOC, in both lower (0.1-45Hz) and higher frequency bands (55-95Hz) (p<0.001). Finally, the local network parameters of the nodal clustering coefficient and nodal efficiency in the frontal region decreased after LOC, in both the lower and higher frequency bands (p<0.05). Moreover, global network parameters of the normalized average clustering coefficient and small world index increased slightly after LOC in the lower frequency band. However, this increase was not statistically significant.

SIGNIFICANCE

The PE, PLZC, PCMI and PCMI-based brain networks are effective metrics for qualifying the effects of isoflurane.

Constrained Functional Connectivity Dynamics in Pediatric Surgical Patients Undergoing General Anesthesia

BACKGROUND

Functional connectivity in cortical networks is thought to be important for consciousness and can be disrupted during the anesthetized state. Recent work in adults has revealed dynamic connectivity patterns during stable general anesthesia but whether similar connectivity state transitions occur in the developing brain remains undetermined. We tested the hypothesis that anesthetic-induced unconsciousness is associated with disruption of functional connectivity in the developing brain and that, like adults, there are dynamic shifts in connectivity patterns during the stable maintenance phase of general anesthesia.

METHODS

This was a preplanned analysis of a previously reported single-center, prospective, cross-sectional study of healthy (ASA I or II) children aged 8-16 years undergoing surgery with general anesthesia (n=50) at Michigan Medicine. Whole scalp (16-channel), wireless electroencephalographic data were collected from the preoperative period through the recovery of consciousness. Functional connectivity was measured using weighted phase lag index and discrete connectivity states were classified using cluster analysis.

RESULTS

Changes in functional connectivity were associated with anesthetic state transitions across multiple regions and frequency bands. An increase in prefrontal-frontal alpha (median[25th, 75th]; baseline 0.070[0.049, 0.101] vs. maintenance 0.474[0.286, 0.606], p<0.001) and theta connectivity (0.038[0.029, 0.048] vs 0.399[0.254, 0.488], p<0.001), and decrease in parietal-occipital alpha connectivity (0.171[0.145, 0.243] vs. 0.089[0.055, 0.132], p<0.001) were among those with the greatest effect size. Contrary to our hypothesis, connectivity patterns during the maintenance phase of general anesthesia were dominated by stable theta and alpha prefrontal-frontal and alpha frontal-parietal connectivity, and exhibited high between-cluster similarity (r = 0.75 to 0.87).

CONCLUSIONS

Changes in functional connectivity are associated with anesthetic state transitions but, unlike adults, connectivity patterns are constrained during general anesthesia in late childhood and early adolescence.

Reorganization of rich clubs in functional brain networks of dementia with Lewy bodies and Alzheimer's disease

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DLB and AD had the different functional reorganization patterns.

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Rich club nodes increased in frontal-parietal network in patients with DLB.

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The rich club nodes in temporal lobe decreased and those in cerebellum increased for AD.

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Compared with HC, rich club connectivity was enhanced in the DLB and AD groups.

The purpose of this study was to reveal the patterns of reorganization of rich club organization in brain functional networks in dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD). The study found that the rich club node shifts from sensory/somatomotor network to fronto-parietal network in DLB. For AD, the rich club nodes switch between the temporal lobe with obvious structural atrophy and the frontal lobe, parietal lobe and cerebellum with relatively preserved structure and function. In addition, compared with healthy controls, rich club connectivity was enhanced in the DLB and AD groups. The connection strength of DLB patients was related to cognitive assessment. In conclusion, we revealed the different functional reorganization patterns of DLB and AD. The conversion and redistribution of rich club members may play a causal role in disease-specific outcomes. It may be used as a potential biomarker to provide more accurate prevention and treatment strategies.

Brain Responses to Propofol in Advance of Recovery From Coma and Disorders of Consciousness: A Preliminary Study

RATIONALE

Predicting recovery of consciousness in unresponsive, brain-injured individuals has crucial implications for clinical decision-making. Propofol induces distinctive brain network reconfiguration in the healthy brain as it loses consciousness. In patients with disorders of consciousness, the brain network's reconfiguration to propofol may reveal the patient's underlying capacity for consciousness.

OBJECTIVE

To design and test a new metric for the prognostication of consciousness recovery in disorders of consciousness.

METHODS

Using a within-subject design, we conducted an anesthetic protocol with concomitant high-density EEG in 12 patients in a disorder of consciousness following a brain injury. We quantified the reconfiguration of EEG network hubs and directed functional connectivity before, during, and after propofol exposure, and obtained an index of propofol-induced network reconfiguration: the Adaptive Reconfiguration Index. We compared the index of patients who recovered consciousness 3 months post-EEG (n = 3) to that of patients who did not recover or remained in a chronic disorder of consciousness (n = 7), and conducted a logistic regression to assess prognostic accuracy.

MEASUREMENTS AND MAIN RESULTS

The Adaptive Reconfiguration Index was significantly higher in patients who later recovered full consciousness (U-value=21, p=0.008), and able to discriminate with 100% accuracy whether the patient recovered consciousness.

CONCLUSIONS

The Adaptive Reconfiguration Index of patients who recovered from a disorder of consciousness at 3-month follow-up was linearly separable from that of patients who did not recover or remained in a chronic disorder of consciousness, on the single-subject level. EEG and propofol can be administered at the bedside with few contraindications, affording the Adaptive Reconfiguration Index tremendous translational potential as a prognostic measure of consciousness recovery in acute clinical settings.

Neurophysiologic Complexity in Children Increases with Developmental Age and Is Reduced by General Anesthesia

BACKGROUND

Neurophysiologic complexity in the cortex has been shown to reflect changes in the level of consciousness in adults but remains incompletely understood in the developing brain. This study aimed to address changes in cortical complexity related to age and anesthetic state transitions. This study tested the hypotheses that cortical complexity would (1) increase with developmental age and (2) decrease during general anesthesia.

METHODS

This was a single-center, prospective, cross-sectional study of healthy (American Society of Anesthesiologists physical status I or II) children (n = 50) of age 8 to 16 undergoing surgery with general anesthesia at Michigan Medicine. This age range was chosen because it reflects a period of substantial brain network maturation. Whole scalp (16-channel), wireless electroencephalographic data were collected from the preoperative period through the recovery of consciousness. Cortical complexity was measured using the Lempel-Ziv algorithm and analyzed during the baseline, premedication, maintenance of general anesthesia, and clinical recovery periods. The effect of spectral power on Lempel-Ziv complexity was analyzed by comparing the original complexity value with those of surrogate time series generated through phase randomization that preserves power spectrum.

RESULTS

Baseline spatiotemporal Lempel-Ziv complexity increased with age (yr; slope [95% CI], 0.010 [0.004, 0.016]; P < 0.001); when normalized to account for spectral power, there was no significant age effect on cortical complexity (0.001 [-0.004, 0.005]; P = 0.737). General anesthesia was associated with a significant decrease in spatiotemporal complexity (median [25th, 75th]; baseline, 0.660 [0.620, 0.690] vs. maintenance, 0.459 [0.402, 0.527]; P < 0.001), and spatiotemporal complexity exceeded baseline levels during postoperative recovery (0.704 [0.642, 0.745]; P = 0.009). When normalized, there was a similar reduction in complexity during general anesthesia (baseline, 0.913 [0.887, 0.923] vs. maintenance 0.851 [0.823, 0.877]; P < 0.001), but complexity remained significantly reduced during recovery (0.873 [0.840, 0.902], P < 0.001).

CONCLUSIONS

Cortical complexity increased with developmental age and decreased during general anesthesia. This association remained significant when controlling for spectral changes during anesthetic-induced perturbations in consciousness but not with developmental age.

EDITOR’S PERSPECTIVE

Brain Functional Connectivity as Biomarker for Propofol-Induced Alterations of Consciousness

Understanding neural correlates of consciousness and its alterations poses a grand challenge for modern neuroscience. Even though recent years of research have shown many conceptual and empirical advances, the evolution of a system that can track anesthesia-induced loss of consciousness is hindered by the lack of reliable markers. The work presented herein estimates the functional connectivity (FC) between 21 scalp electroencephalogram (EEG) recordings to evaluate its utility in characterizing changes in brain networks during propofol sedation. The sedation dataset in the University of Cambridge data repository was used for analyses. FC was estimated using the debiased estimator of the squared Weighted Phase Lag Index (dWPLI2). Spectral FC networks before, during, and after sedation was considered for 5 EEG sub-bands. Results demonstrated significantly higher alpha band FC during baseline, mild and moderate sedation, and recovery stages. A striking association between frontal brain activity and propofol-sedation was also noticed. Furthermore, inhibition of frontal to parietal and frontal to occipital connections were observed as characteristic features of propofol-induced alterations in consciousness. A random subspace ensemble framework using logistic model tree as the base classifier, and 18 functional connections as features, yielded a cross-validation accuracy of 98.75% in discriminating baseline, mild and moderate sedation, and recovery stages. These findings validate that EEG-based FC can reliably distinguish altered conscious states associated with anaesthesia.

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.

Consciousness and complexity: a consilience of evidence

Over the last years, a surge of empirical studies converged on complexity-related measures as reliable markers of consciousness across many different conditions, such as sleep, anesthesia, hallucinatory states, coma, and related disorders. Most of these measures were independently proposed by researchers endorsing disparate frameworks and employing different methods and techniques. Since this body of evidence has not been systematically reviewed and coherently organized so far, this positive trend has remained somewhat below the radar. The aim of this paper is to make this consilience of evidence in the science of consciousness explicit. We start with a systematic assessment of the growing literature on complexity-related measures and identify their common denominator, tracing it back to core theoretical principles and predictions put forward more than 20 years ago. In doing this, we highlight a consistent trajectory spanning two decades of consciousness research and provide a provisional taxonomy of the present literature. Finally, we consider all of the above as a positive ground to approach new questions and devise future experiments that may help consolidate and further develop a promising field where empirical research on consciousness appears to have, so far, naturally converged.

Differential classification of states of consciousness using envelope- and phase-based functional connectivity

The development of sophisticated computational tools to quantify changes in the brain's oscillatory dynamics across states of consciousness have included both envelope- and phase-based measures of functional connectivity (FC), but there are very few direct comparisons of these techniques using the same dataset. The goal of this study was to compare an envelope-based (i.e. Amplitude Envelope Correlation, AEC) and a phase-based (i.e. weighted Phase Lag Index, wPLI) measure of FC in their classification of states of consciousness. Nine healthy participants underwent a three-hour experimental anesthetic protocol with propofol induction and isoflurane maintenance, in which five minutes of 128-channel electroencephalography were recorded before, during, and after anesthetic-induced unconsciousness, at the following time points: Baseline; light sedation with propofol (Light Sedation); deep unconsciousness following three hours of surgical levels of anesthesia with isoflurane (Unconscious); five minutes prior to the recovery of consciousness (Pre-ROC); and three hours following the recovery of consciousness (Recovery). Support vector machine classification was applied to the source-localized EEG in the alpha (8-13 Hz) frequency band in order to investigate the ability of AEC and wPLI (separately and together) to discriminate i) the four states from Baseline; ii) Unconscious ("deep" unconsciousness) vs. Pre-ROC ("light" unconsciousness); and iii) responsiveness (Baseline, Light Sedation, Recovery) vs. unresponsiveness (Unconscious, Pre-ROC). AEC and wPLI yielded different patterns of global connectivity across states of consciousness, with AEC showing the strongest network connectivity during the Unconscious epoch, and wPLI showing the strongest connectivity during full consciousness (i.e., Baseline and Recovery). Both measures also demonstrated differential predictive contributions across participants and used different brain regions for classification. AEC showed higher classification accuracy overall, particularly for distinguishing anesthetic-induced unconsciousness from Baseline (83.7 ± 0.8%). AEC also showed stronger classification accuracy than wPLI when distinguishing Unconscious from Pre-ROC (i.e., "deep" from "light" unconsciousness) (AEC: 66.3 ± 1.2%; wPLI: 56.2 ± 1.3%), and when distinguishing between responsiveness and unresponsiveness (AEC: 76.0 ± 1.3%; wPLI: 63.6 ± 1.8%). Classification accuracy was not improved compared to AEC when both AEC and wPLI were combined. This analysis of source-localized EEG data demonstrates that envelope- and phase-based FC provide different information about states of consciousness but that, on a group level, AEC is better able to detect relative alterations in brain FC across levels of anesthetic-induced unconsciousness compared to wPLI.

Analyzing the Loss and the Recovery of Consciousness: Functional Connectivity Patterns and Changes in Heart Rate Variability During Propofol-Induced Anesthesia

The analysis of the central and the autonomic nervous systems (CNS, ANS) activities during general anesthesia (GA) provides fundamental information for the study of neural processes that support alterations of the consciousness level. In the present pilot study, we analyzed EEG signals and the heart rate (HR) variability (HRV) in a sample of 11 patients undergoing spinal surgery to investigate their CNS and ANS activities during GA obtained with propofol administration. Data were analyzed during different stages of GA: baseline, the first period of anesthetic induction, the period before the loss of consciousness, the first period after propofol discontinuation, and the period before the recovery of consciousness (ROC). In EEG spectral analysis, we found a decrease in posterior alpha and beta power in all cortical areas observed, except the occipital ones, and an increase in delta power, mainly during the induction phase. In EEG connectivity analysis, we found a significant increase of local efficiency index in alpha and delta bands between baseline and loss of consciousness as well as between baseline and ROC in delta band only and a significant reduction of the characteristic path length in alpha band between the baseline and ROC. Moreover, connectivity results showed that in the alpha band there was mainly a progressive increase in the number and in the strength of incoming connections in the frontal region, while in the beta band the parietal region showed mainly a significant increase in the number and in the strength of outcoming connections values. The HRV analysis showed that the induction of anesthesia with propofol was associated with a progressive decrease in complexity and a consequent increase in the regularity indexes and that the anesthetic procedure determined bradycardia which was accompanied by an increase in cardiac sympathetic modulation and a decrease in cardiac parasympathetic modulation during the induction. Overall, the results of this pilot study showed as propofol-induced anesthesia caused modifications on EEG signal, leading to a "rebalance" between long and short-range cortical connections, and had a direct effect on the cardiac system. Our data suggest interesting perspectives for the interactions between the central and autonomic nervous systems for the modulation of the consciousness level.

Molecular Diversity of Anesthetic Actions Is Evident in Electroencephalogram Effects in Humans and Animals

Anesthetic agents cause unique electroencephalogram (EEG) activity resulting from actions on their diverse molecular targets. Typically to produce balanced anesthesia in the clinical setting, several anesthetic and adjuvant agents are combined. This creates challenges for the clinical use of intraoperative EEG monitoring, because computational approaches are mostly limited to spectral analyses and different agents and combinations produce different EEG responses. Thus, testing of many combinations of agents is needed to generate accurate, protocol independent analyses. Additionally, most studies to develop new computational approaches take place in young, healthy adults and electrophysiological responses to anesthetics vary widely at the extremes of age, due to physiological brain differences. Below, we discuss the challenges associated with EEG biomarker identification for anesthetic depth based on the diversity of molecular targets. We suggest that by focusing on the generalized effects of anesthetic agents on network activity, we can create paths for improved universal analyses.

Protocol for the Prognostication of Consciousness Recovery Following a Brain Injury

Individuals who have suffered a severe brain injury typically require extensive hospitalization in intensive care units (ICUs), where critical treatment decisions are made to maximize their likelihood of recovering consciousness and cognitive function. These treatment decisions can be difficult when the neurological assessment of the patient is limited by unreliable behavioral responses. Reliable objective and quantifiable markers are lacking and there is both (1) a poor understanding of the mechanisms underlying the brain's ability to reconstitute consciousness and cognition after an injury and (2) the absence of a reliable and clinically feasible method of tracking cognitive recovery in ICU survivors. Our goal is to develop and validate a clinically relevant EEG paradigm that can inform the prognosis of unresponsive, brain-injured patients in the ICU. This protocol describes a study to develop a point-of-care system intended to accurately predict outcomes of unresponsive, brain-injured patients in the ICU. We will recruit 200 continuously-sedated brain-injured patients across five ICUs. Between 24 h and 7 days post-ICU admission, high-density EEG will be recorded from behaviorally unresponsive patients before, during and after a brief cessation of pharmacological sedation. Once patients have reached the waking stage, they will be asked to complete an abridged Cambridge Brain Sciences battery, a web-based series of neurocognitive tests. The test series will be repeated every day during acute admission (ICU, ward), or as often as possible given the constraints of ICU and ward care. Following discharge, patients will continue to complete the same test series on weekly, and then monthly basis, for up to 12 months following injury. Functional outcomes will also be assessed up to 12 months post-injury. We anticipate our findings will lead to an increased ability to identify patients, as soon as possible after their brain injury, who are most likely to survive, and to make accurate predictions about their long-term cognitive and functional outcome. In addition to providing critically needed support for clinical decision-making, this study has the potential to transform our understanding of key functional EEG networks associated with consciousness and cognition.

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.

Brain network motif topography may predict emergence from disorders of consciousness: a case series

Neuroimaging methods have improved the accuracy of diagnosis in patients with disorders of consciousness (DOC), but novel, clinically translatable methods for prognosticating this population are still needed. In this case series, we explored the association between topographic and global brain network properties and prognosis in patients with DOC. We recorded high-density electroencephalograms in three patients with acute or chronic DOC, two of whom also underwent an anesthetic protocol. In these two cases, we compared functional network motifs, network hubs and power topography (i.e. topographic network properties), as well as relative power and graph theoretical measures (i.e. global network properties), at baseline, during exposure to anesthesia and after recovery from anesthesia. We also compared these properties to a group of healthy, conscious controls. At baseline, the topographic distribution of nodes participating in alpha motifs resembled conscious controls in patients who later recovered consciousness and high relative power in the delta band was associated with a negative outcome. Strikingly, the reorganization of network motifs, network hubs and power topography under anesthesia followed by their return to a baseline patterns upon recovery from anesthesia, was associated with recovery of consciousness. Our findings suggest that topographic network properties measured at the single-electrode level might provide more prognostic information than global network properties that are averaged across the brain network. In addition, we propose that the brain network's capacity to reorganize in response to a perturbation is a precursor to the recovery of consciousness in DOC patients.

Influence of pre-anesthesia dynamic frontal-parietal communication on individual susceptibility to propofol

OBJECTIVE

We investigated whether pre-anesthesia dynamic frontal-parietal functional connectivity was correlated with the observed interindividual differences in propofol susceptibility.

METHODS

Three resting-state EEG datasets were used in the study (N = 29, N = 21 and N = 20). We estimated the pre-anesthesia strength and fluctuations of frontal-parietal functional connectivity by using sliding-window analysis. Propofol served as the sole anesthetic drug, and it was administered by using a target-controlled infusion system. Individual susceptibility to propofol was assessed by the induction time, from infusion onset until a bispectral index value of 60 was reached, for subjects in dataset-1 and dataset-2, and susceptibility was assessed by behavioral data for subjects in the external dataset.

RESULTS

We observed in the three datasets that subjects with high susceptibility to propofol had lower pre-anesthesia strength and lower fluctuation of frontal-parietal functional connectivity than the low-susceptibility group at alpha band. Moreover, the induction time was significantly correlated with the estimated pre-anesthesia frontal-parietal functional connectivity measures. We also validated the robustness of these findings by using different window lengths in sliding-window analysis.

CONCLUSIONS

Subjects with weaker pre-anesthesia dynamic frontal-parietal communication are more likely to be anesthetized.

SIGNIFICANCE

These observations suggest that the titration procedure for propofol should consider the pre-anesthesia brain functional state.

Alpha band frontal connectivity is a state-specific electroencephalographic correlate of unresponsiveness during exposure to dexmedetomidine and propofol

BACKGROUND

Coherent alpha electroencephalogram (EEG) rhythms in the frontal cortex have been correlated with the hypnotic effects of propofol and dexmedetomidine, but less is known about frontal connectivity as a state-specific correlate of unresponsiveness as compared with long-range connectivity. We aimed to distinguish dose- and state-dependent effects of dexmedetomidine and propofol on EEG connectivity.

METHODS

Forty-seven healthy males received either dexmedetomidine (n=23) or propofol (n=24) as target-controlled infusion with stepwise increments until loss of responsiveness (LOR). We attempted to arouse participants during constant dosing (return of responsiveness [ROR]), and the target concentration was then increased 50% to achieve presumed loss of consciousness. We collected 64-channel EEG data and prefrontal-frontal and anterior-posterior functional connectivity in the alpha band (8-14 Hz) was measured using coherence and weighted phase lag index (wPLI). Directed connectivity was measured with directed phase lag index (dPLI).

RESULTS

Prefrontal-frontal EEG-based connectivity discriminated the states at the different drug concentrations. At ROR, prefrontal-frontal connectivity reversed to the level observed before LOR, indicating that connectivity changes were related to unresponsiveness rather than drug concentration. Unresponsiveness was associated with emergence of frontal-to-prefrontal dominance (dPLI: -0.13 to -0.40) in contrast to baseline (dPLI: 0.01-0.02). Coherence, wPLI, and dPLI had similar capability to discriminate the states that differed in terms of responsiveness and drug concentration. In contrast, anterior-posterior connectivity in the alpha band did not differentiate LOR and ROR.

CONCLUSIONS

Local prefrontal-frontal EEG-based connectivity reflects unresponsiveness induced by propofol or dexmedetomidine, suggesting its utility in monitoring the anaesthetised state with these agents.

CLINICAL TRIAL REGISTRATION

NCT01889004.

fMRI network correlates of predisposing risk factors for delirium: A cross-sectional study

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Predisposing risk is not associated with delirium-related fMRI characteristics.

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Older age within an elderly cohort is related to higher functional connectivity strength.

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This relation is in opposite direction than hypothesized.

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The onset of delirium may reflect new functional network impairments.

Delirium, the clinical expression of acute encephalopathy, is a common neuropsychiatric syndrome that is related to poor outcomes, such as long-term cognitive impairment. Disturbances of functional brain networks are hypothesized to predispose for delirium. The aim of this study in non-delirious elderly individuals was to investigate whether predisposing risk factors for delirium are associated with fMRI network characteristics that have been observed during delirium. As predisposing risk factors, we studied age, alcohol misuse, cognitive impairment, depression, functional impairment, history of transient ischemic attack or stroke, and physical status. In this multicenter study, we included 554 subjects and analyzed resting-state fMRI data from 222 elderly subjects (63% male, age range: 65–85 year) after rigorous motion correction. Functional network characteristics were analyzed and based on the minimum spanning tree (MST). Global functional connectivity strength, network efficiency (MST diameter) and network integration (MST leaf fraction) were analyzed, as these measures were altered during delirium in previous studies. Linear regression analyses were used to investigate the relation between predisposing delirium risk factors and delirium-related fMRI characteristics, adjusted for confounding and multiple testing. Predisposing risk factors for delirium were not associated with delirium-related fMRI network characteristics. Older age within our elderly cohort was related to global functional connectivity strength (β = 0.182, p < 0.05), but in the opposite direction than hypothesized. Delirium-related functional network impairments can therefore not be considered as the common mechanism for predisposition for delirium.

The neurophysiology of ketamine: an integrative review

The drug ketamine has been extensively studied due to its use in anaesthesia, as a model of psychosis and, most recently, its antidepressant properties. Understanding the physiology of ketamine is complex due to its rich pharmacology with multiple potential sites at clinically relevant doses. In this review of the neurophysiology of ketamine, we focus on the acute effects of ketamine in the resting brain. We ascend through spatial scales starting with a complete review of the pharmacology of ketamine and then cover its effects on in vitro and in vivo electrophysiology. We then summarise and critically evaluate studies using EEG/MEG and neuroimaging measures (MRI and PET), integrating across scales where possible. While a complicated and, at times, confusing picture of ketamine’s effects are revealed, we stress that much of this might be caused by use of different species, doses, and analytical methodologies and suggest strategies that future work could use to answer these problems.

The (Un)Conscious Mouse as a Model for Human Brain Functions: Key Principles of Anesthesia and Their Impact on Translational Neuroimaging

In recent years, technical and procedural advances have brought functional magnetic resonance imaging (fMRI) to the field of murine neuroscience. Due to its unique capacity to measure functional activity non-invasively, across the entire brain, fMRI allows for the direct comparison of large-scale murine and human brain functions. This opens an avenue for bidirectional translational strategies to address fundamental questions ranging from neurological disorders to the nature of consciousness. The key challenges of murine fMRI are: (1) to generate and maintain functional brain states that approximate those of calm and relaxed human volunteers, while (2) preserving neurovascular coupling and physiological baseline conditions. Low-dose anesthetic protocols are commonly applied in murine functional brain studies to prevent stress and facilitate a calm and relaxed condition among animals. Yet, current mono-anesthesia has been shown to impair neural transmission and hemodynamic integrity. By linking the current state of murine electrophysiology, Ca2+ imaging and fMRI of anesthetic effects to findings from human studies, this systematic review proposes general principles to design, apply and monitor anesthetic protocols in a more sophisticated way. The further development of balanced multimodal anesthesia, combining two or more drugs with complementary modes of action helps to shape and maintain specific brain states and relevant aspects of murine physiology. Functional connectivity and its dynamic repertoire as assessed by fMRI can be used to make inferences about cortical states and provide additional information about whole-brain functional dynamics. Based on this, a simple and comprehensive functional neurosignature pattern can be determined for use in defining brain states and anesthetic depth in rest and in response to stimuli. Such a signature can be evaluated and shared between labs to indicate the brain state of a mouse during experiments, an important step toward translating findings across species.

Dynamic Cortical Connectivity during General Anesthesia in Surgical Patients

BACKGROUND

Functional connectivity across the cortex has been posited to be important for consciousness and anesthesia, but functional connectivity patterns during the course of surgery and general anesthesia are unknown. The authors tested the hypothesis that disrupted cortical connectivity patterns would correlate with surgical anesthesia.

METHODS

Surgical patients (n = 53) were recruited for study participation. Whole-scalp (16-channel) wireless electroencephalographic data were prospectively collected throughout the perioperative period. Functional connectivity was assessed using weighted phase lag index. During anesthetic maintenance, the temporal dynamics of connectivity states were characterized via Markov chain analysis, and state transition probabilities were quantified.

RESULTS

Compared to baseline (weighted phase lag index, 0.163, ± 0.091), alpha frontal-parietal connectivity was not significantly different across the remaining anesthetic and perioperative epochs, ranging from 0.100 (± 0.041) to 0.218 (± 0.136) (P > 0.05 for all time periods). In contrast, there were significant increases in alpha prefrontal-frontal connectivity (peak = 0.201 [0.154, 0.248]; P < 0.001), theta prefrontal-frontal connectivity (peak = 0.137 [0.091, 0.182]; P < 0.001), and theta frontal-parietal connectivity (peak = 0.128 [0.084, 0.173]; P < 0.001) during anesthetic maintenance. Additionally, shifts occurred between states of high prefrontal-frontal connectivity (alpha, beta) with suppressed frontal-parietal connectivity, and high frontal-parietal connectivity (alpha, theta) with reduced prefrontal-frontal connectivity. These shifts occurred in a nonrandom manner (P < 0.05 compared to random transitions), suggesting structured transitions of connectivity during general anesthesia.

CONCLUSIONS

Functional connectivity patterns dynamically shift during surgery and general anesthesia but do so in a structured way. Thus, a single measure of functional connectivity will likely not be a reliable correlate of surgical anesthesia.

Information Integration and Mesoscopic Cortical Connectivity during Propofol Anesthesia

Background

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.

Methods

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.

Results

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).

Conclusions

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.

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What We Already Know about This Topic

What This Article Tells Us That Is New

Predisposition for delirium and EEG characteristics

OBJECTIVE

Delirium is associated with increased electroencephalography (EEG) delta activity, decreased connectivity strength and decreased network integration. To improve our understanding of development of delirium, we studied whether non-delirious individuals with a predisposition for delirium also show these EEG abnormalities.

METHODS

Elderly subjects (N = 206) underwent resting-state EEG measurements and were assessed on predisposing delirium risk factors, i.e. older age, alcohol misuse, cognitive impairment, depression, functional impairment, history of stroke and physical status. Delirium-related EEG characteristics of interest were relative delta power, alpha connectivity strength (phase lag index) and network integration (minimum spanning tree leaf fraction). Linear regression analyses were used to investigate the relation between predisposing delirium risk factors and EEG characteristics that are associated with delirium, adjusting for confounding and multiple testing.

RESULTS

Functional impairment was related to a decrease in connectivity strength (adjusted R² = 0.071, β = 0.201, p < 0.05). None of the other risk factors had significant influence on EEG delta power, connectivity strength or network integration.

CONCLUSIONS

Functional impairment seems to be associated with decreased alpha connectivity strength. Other predisposing risk factors for delirium had no effect on the studied EEG characteristics.

SIGNIFICANCE

Predisposition for delirium is not consistently related to EEG characteristics that can be found during delirium.

Analysis of brain connectivity during nitrous oxide sedation using graph theory

Nitrous oxide, the least potent inhalation anesthetic, is widely used for conscious sedation. Recently, it has been reported that the occurrence of anesthetic-induced loss of consciousness decreases the interconnection between brain regions, resulting in brain network changes. However, few studies have investigated these changes in conscious sedation using nitrous oxide. Therefore, the present study aimed to use graph theory to analyze changes in brain networks during nitrous oxide sedation. Participants were 20 healthy volunteers (10 men and 10 women, 20–40 years old) with no history of systemic disease. We acquired electroencephalogram (EEG) recordings of 32 channels during baseline, nitrous oxide inhalation sedation, and recovery. EEG epochs from the baseline and the sedation state (50% nitrous oxide) were extracted and analyzed with the network connection parameters of graph theory. Analysis of 1/f dynamics, revealed a steeper slope while in the sedation state than during the baseline. Network connectivity parameters showed significant differences between the baseline and sedation state, in delta, alpha1, alpha2, and beta2 frequency bands. The most pronounced differences in functional distance during nitrous oxide sedation were observed in the alpha1 and alpha2 frequency bands. Change in 1/f dynamics indicates that changes in brain network systems occur during nitrous oxide administration. Changes in network parameters imply that nitrous oxide interferes with the efficiency of information integration in the frequency bands important for cognitive processes and attention tasks. Alteration of brain network during nitrous oxide administration may be associated to the sedative mechanism of nitrous oxide.

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.

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

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

EEG Feature Analysis for Detecting the Fluctuation of Consciousness Level during Propofol Anesthesia

Various EEG features have been proposed for differentiating the consciousness and unconsciousness states during general anesthesia. However, their performance for detecting the fluctuation of consciousness level remains unclear. In this work, we recorded 60-channels EEG data during propofol anesthesia, and extracted 110 EEG features that were shown to be sensitive to the change of consciousness level. Then, we used classification model to evaluate the performance of these features in distinguishing the response state fluctuating around the point of loss of behavioral responsiveness (LOBR) to external stimuli. We found that EEG features, including delta power, SynchFastSlow, and the topographical ratio of alpha power, were efficient in distinguishing the stable change in consciousness level with an accuracy of 95.8%, however, these features performed poorly in distinguishing the response state around the point of LOBR with an accuracy of 66.9%. Using EEG features selected specifically for detecting consciousness fluctuation, approximately 10% improvement in accuracy was obtained. Our results suggested that the EEG features that were sensitive to the stable change of consciousness level and fluctuation of consciousness level were largely different. EEG features including theta band power and functional connectivity are more relevant to the fluctuation of consciousness level.

Delirium screening in the intensive care unit using emerging QEEG techniques: A pilot study

Delirium is an under-diagnosed yet frequently occurring clinical complication with potentially serious consequences for intensive care unit (ICU) patients. Diagnosis is currently reactive and based upon qualitative assessment of the patient's cognitive status by ICU staff. Here, we conducted a preliminary investigation into whether emerging quantitative electroencephalography (QEEG) analysis techniques can accurately discriminate between delirious and non-delirious patients in an ICU setting. Resting EEG recordings from 5 ICU patients in a state of delirium and 5 age matched control patients were analyzed using autoregressive spectral estimation for quantification of EEG power and renormalized partial directed coherence for analysis of directed functional connectivity. Delirious subjects exhibited pronounced EEG slowing as well as severe general loss of directed functional connectivity between recording sites. Distinction between groups based on these parameters was surprisingly clear given the low sample size employed. Furthermore, by targeting the electrode positions where effects were most apparent it was possible to clearly segregate patients using only 3 scalp electrodes. These findings indicate that quantitative diagnosis and monitoring of delirium is not only possible using emerging QEEG methods but is also accomplishable using very low-density electrode systems.

Evaluation of long-term consumption of omeprazole disadvantages: a network analysis

AIM

Evaluation of deregulated genes after long-term consuming of omeprazole via network analysis.

BACKGROUND

Proton pump inhibitors (PPIs) are used to inhibit gastric high rate of acid secretion in patients. Omeprazole as a PPI is a common drug in this regard. Evaluation of long-term consumption of omeprazole is studied in the present study via its effects on the gene expression of "human coronary artery endothelial cells".

METHODS

Net effect of the presence of omeprazole on gene expression profiles of "human coronary artery endothelial cells" was evaluated through data from gene expression omnibus (GEO). Results of protein-protein interaction (PPI) network analysis were assessed via biological process examination to find the critical deregulated genes after long-term consumption of omeprazole.

RESULTS

"Negative regulation of muscle cell apoptotic process", "negative regulation of DNA binding", "telencephalon cell migration", "forebrain cell migration" "response to cadmium ion", "cell-cell recognition", "positive regulation of protein targeting to mitochondrion", and "central nervous system neuron development" were the clusters of biological processes that were associated to the long -term presence of omeprazole. The final critical deregulated genes were JAK2, PTK2, and NRG1.

CONCLUSION

It can be concluded that cell cycle, proliferation, and apoptosis and several essential biological processes are affected and nervous system is a possible target related to the long-term consumption of omeprazole.

Resting State EEG Characteristics During Sedation With Midazolam or Propofol in Older Subjects

Background. Despite widespread application, little is known about the neurophysiological effects of light sedation with midazolam or propofol, particularly in older subjects. The aim of this study was to assess the effects of light sedation with midazolam or propofol on a variety of EEG measures in older subjects. Methods. In patients (≥60 years without neuropsychiatric disease such as delirium), 2 EEG recordings were performed, before and after administration of either midazolam (n = 22) or propofol (n = 26) to facilitate an endoscopic procedure. Power spectrum, functional connectivity, and network topology based on the minimum spanning tree (MST) were compared within subjects. Results. Midazolam and propofol administration resulted in Richmond Agitation and Sedation Scale levels between 0 and -4 and between -2 and -4, respectively. Both agents altered the power spectra with increased delta (0.5-4 Hz) and decreased alpha (8-13 Hz) power. Only propofol was found to significantly reduce functional connectivity. In the beta frequency band, the MST was more integrated during midazolam sedation. Propofol sedation resulted in a less integrated network in the alpha frequency band. Conclusion. Despite the different levels of light sedation with midazolam and propofol, similar changes in power were found. Functional connectivity and network topology showed differences between midazolam and propofol sedation. Future research should establish if these differences are caused by the different levels of sedation or the mechanism of action of these agents.

Nonlinear dynamics captures brain states at different levels of consciousness in patients anesthetized with propofol

The information processing capability of the brain decreases during unconscious states. Capturing this decrease during anesthesia-induced unconsciousness has been attempted using standard spectral analyses as these correlate relatively well with breakdowns in corticothalamic networks. Much of this work has involved the use of propofol to perturb brain activity, as it is one of the most widely used anesthetics for routine surgical anesthesia. Propofol administration alone produces EEG spectral characteristics similar to most hypnotics; however, inter-individual and drug variation render spectral measures inconsistent. Complexity measures of EEG signals could offer better measures to distinguish brain states, because brain activity exhibits nonlinear behavior at several scales during transitions of consciousness. We tested the potential of complexity analyses from nonlinear dynamics to identify loss and recovery of consciousness at clinically relevant timepoints. Patients undergoing propofol general anesthesia for various surgical procedures were identified as having changes in states of consciousness by the loss and recovery of response to verbal stimuli after induction and upon cessation of anesthesia, respectively. We demonstrate that nonlinear dynamics analyses showed more significant differences between consciousness states than spectral measures. Notably, attractors in conscious and anesthesia-induced unconscious states exhibited significantly different shapes. These shapes have implications for network connectivity, information processing, and the total number of states available to the brain at these different levels. They also reflect some of our general understanding of the network effects of consciousness in a way that spectral measures cannot. Thus, complexity measures could provide a universal means for reliably capturing depth of consciousness based on EEG changes at the beginning and end of anesthesia administration.

General Anesthesia: A Probe to Explore Consciousness

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

Assessment of phase-lag entropy, a new measure of electroencephalographic signals, for propofol-induced sedation

Background

Phase-lag entropy (PLE) was recently described as a measurement of temporal pattern diversity in the phase relationship between two electroencephalographic signals from prefrontal and frontal montages. This study was performed to evaluate the performance of PLE for assessing the depth of sedation.

Methods

Thirty adult patients undergoing upper limb surgery with a brachial plexus block were administered propofol by target-controlled infusion. The depth of sedation was assessed using the Observer’s Assessment of Alertness/Sedation (OAA/S) scale. The effect-site concentration (Ce) of propofol was initially started at 0.5 μg/ml and was increased in increments of 0.2 μg/ml until an OAA/S score of 1 was reached. Three minutes after the target Ce was reached, the PLE, bispectral index (BIS), and level of sedation were assessed. Correlations between the OAA/S score and PLE or BIS were determined. The prediction probabilities (P_k) of PLE and BIS were also analyzed.

Results

The PLE values were closely correlated with the OAA/S scores (Spearman’s Rho = 0.755; P < 0.001) to an extent comparable with the correlation between the BIS and OAA/S score (Spearman’s Rho = 0.788; P < 0.001). The P_k values of PLE and BIS were 0.731 and 0.718, respectively.

Conclusions

PLE is a new and reliable consciousness monitoring system for assessing the depth of sedation induced by propofol, which is comparable with the BIS.