Brain network disintegration during sedation is mediated by the complexity of sparsely connected regions

Modeling cortical synaptic effects of anesthesia and their cholinergic reversal

General anesthetics work through a variety of molecular mechanisms while resulting in the common end point of sedation and loss of consciousness. Generally, the administration of common anesthetics induces reduction in synaptic excitation while promoting synaptic inhibition. Exogenous modulation of the anesthetics' synaptic effects can help determine the neuronal pathways involved in anesthesia. For example, both animal and human studies have shown that exogenously induced increases in acetylcholine in the brain can elicit wakeful-like behavior despite the continued presence of the anesthetic. However, the underlying mechanisms of anesthesia reversal at the cellular level have not been investigated. Here we apply a computational model of a network of excitatory and inhibitory neurons to simulate the network-wide effects of anesthesia, due to changes in synaptic inhibition and excitation, and their reversal by cholinergic activation through muscarinic receptors. We use a differential evolution algorithm to fit model parameters to match measures of spiking activity, neuronal connectivity, and network dynamics recorded in the visual cortex of rodents during anesthesia with desflurane in vivo. We find that facilitating muscarinic receptor effects of acetylcholine on top of anesthetic-induced synaptic changes predicts the reversal of anesthetic suppression of neurons' spiking activity, functional connectivity, as well as pairwise and population interactions. Thus, our model predicts a specific neuronal mechanism for the cholinergic reversal of anesthesia consistent with experimental behavioral observations.

From temporal to spatial topography: hierarchy of neural dynamics in higher- and lower-order networks shapes their complexity

The brain shows a topographical hierarchy along the lines of lower- and higher-order networks. The exact temporal dynamics characterization of this lower-higher-order topography at rest and its impact on task states remains unclear, though. Using 2 functional magnetic resonance imaging data sets, we investigate lower- and higher-order networks in terms of the signal compressibility, operationalized by Lempel-Ziv complexity (LZC). As we assume that this degree of complexity is related to the slow-fast frequency balance, we also compute the median frequency (MF), an estimation of frequency distribution. We demonstrate (i) topographical differences at rest between higher- and lower-order networks, showing lower LZC and MF in the former; (ii) task-related and task-specific changes in LZC and MF in both lower- and higher-order networks; (iii) hierarchical relationship between LZC and MF, as MF at rest correlates with LZC rest-task change along the lines of lower- and higher-order networks; and (iv) causal and nonlinear relation between LZC at rest and LZC during task, with MF at rest acting as mediator. Together, results show that the topographical hierarchy of lower- and higher-order networks converges with their temporal hierarchy, with these neural dynamics at rest shaping their range of complexity during task states in a nonlinear way.

Electroencephalogram-Based Complexity Measures as Predictors of Post-operative Neurocognitive Dysfunction

Physiologic signals such as the electroencephalogram (EEG) demonstrate irregular behaviors due to the interaction of multiple control processes operating over different time scales. The complexity of this behavior can be quantified using multi-scale entropy (MSE). High physiologic complexity denotes health, and a loss of complexity can predict adverse outcomes. Since postoperative delirium is particularly hard to predict, we investigated whether the complexity of preoperative and intraoperative frontal EEG signals could predict postoperative delirium and its endophenotype, inattention. To calculate MSE, the sample entropy of EEG recordings was computed at different time scales, then plotted against scale; complexity is the total area under the curve. MSE of frontal EEG recordings was computed in 50 patients ≥ age 60 before and during surgery. Average MSE was higher intra-operatively than pre-operatively (p = 0.0003). However, intraoperative EEG MSE was lower than preoperative MSE at smaller scales, but higher at larger scales (interaction p < 0.001), creating a crossover point where, by definition, preoperative, and intraoperative MSE curves met. Overall, EEG complexity was not associated with delirium or attention. In 42/50 patients with single crossover points, the scale at which the intraoperative and preoperative entropy curves crossed showed an inverse relationship with delirium-severity score change (Spearman ρ = -0.31, p = 0.054). Thus, average EEG complexity increases intra-operatively in older adults, but is scale dependent. The scale at which preoperative and intraoperative complexity is equal (i.e., the crossover point) may predict delirium. Future studies should assess whether the crossover point represents changes in neural control mechanisms that predispose patients to postoperative delirium.

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.

Mechanisms Underlying Disorders of Consciousness: Bridging Gaps to Move Toward an Integrated Translational Science

AIM

In order to successfully detect, classify, prognosticate, and develop targeted therapies for patients with disorders of consciousness (DOC), it is crucial to improve our mechanistic understanding of how severe brain injuries result in these disorders.

METHODS

To address this need, the Curing Coma Campaign convened a Mechanisms Sub-Group of the Coma Science Work Group (CSWG), aiming to identify the most pressing knowledge gaps and the most promising approaches to bridge them.

RESULTS

We identified a key conceptual gap in the need to differentiate the neural mechanisms of consciousness per se, from those underpinning connectedness to the environment and behavioral responsiveness. Further, we characterised three fundamental gaps in DOC research: (1) a lack of mechanistic integration between structural brain damage and abnormal brain function in DOC; (2) a lack of translational bridges between micro- and macro-scale neural phenomena; and (3) an incomplete exploration of possible synergies between data-driven and theory-driven approaches.

CONCLUSION

In this white paper, we discuss research priorities that would enable us to begin to close these knowledge gaps. We propose that a fundamental step towards this goal will be to combine translational, multi-scale, and multimodal data, with new biomarkers, theory-driven approaches, and computational models, to produce an integrated account of neural mechanisms in DOC. Importantly, we envision that reciprocal interaction between domains will establish a "virtuous cycle," leading towards a critical vantage point of integrated knowledge that will enable the advancement of the scientific understanding of DOC and consequently, an improvement of clinical practice.

Cell-type-specific imaging of neurotransmission reveals a disrupted excitatory-inhibitory cortical network in isoflurane anaesthesia

BACKGROUND

Despite the fundamental clinical significance of general anaesthesia, the cortical mechanism underlying anaesthetic-induced loss of consciousness (aLOC) remains elusive.

METHODS

Here, we measured the dynamics of two major cortical neurotransmitters, gamma-aminobutyric acid (GABA) and glutamate, through in vivo two-photon imaging and genetically encoded neurotransmitter sensors in a cell type-specific manner in the primary visual (V1) cortex.

FINDINGS

We found a general decrease in cortical GABA transmission during aLOC. However, the glutamate transmission varies among different cortical cell types, where in it is almost preserved on pyramidal cells and is significantly reduced on inhibitory interneurons. Cortical interneurons expressing vasoactive intestinal peptide (VIP) and parvalbumin (PV) specialize in disinhibitory and inhibitory effects, respectively. During aLOC, VIP neuronal activity was delayed, and PV neuronal activity was dramatically inhibited and highly synchronized.

INTERPRETATION

These data reveal that aLOC resembles a cortical state with a disrupted excitatory-inhibitory network and suggest that a functional inhibitory network is indispensable in the maintenance of consciousness.

FUNDING

This work was supported by the grants of the National Natural Science Foundation of China (grant nos. 81620108012 and 82030038 to H.D. and grant nos. 31922029, 61890951, and 61890950 to J.H.).

Detection of Electrophysiological Activity of Amygdala during Anesthesia Using Stereo-EEG: A Preliminary Research in Anesthetized Epileptic Patients

Recent studies of anesthesia mechanisms have focused on neuronal network and functional connectivity. The stereo-electroencephalography (SEEG) recordings provide appropriate temporal and spatial resolution to study whole-brain dynamics; however, the feasibility to detect subcortical signals during anesthesia still needs to be studied with clinical evidence. Here, we focus on the amygdala to investigate if SEEG can be used to detect cortical and subcortical electrophysiological activity in anesthetized epileptic patients. Therefore, we present direct evidence in humans that SEEG indeed can be used to record cortical and subcortical electrophysiological activity during anesthesia. The study was carried out in propofol-anesthetized five epileptic patients. The electrophysiology activity of the amygdala and other cortical areas from anesthesia to the recovery of consciousness was investigated using stereo-EEG (SEEG). Results indicated that with the decrease of propofol concentration, power spectral density (PSD) in the delta band of the amygdala significantly decreased. When it was close to recovery, the correlation between the amygdala and ipsilateral temporal lobe significantly decreased followed by a considerable increase when awake. The findings of the current study suggest SEEG as an effective tool for providing direct evidence of the anesthesia mechanism.

Reorganisation of Brain Hubs across Altered States of Consciousness

Patterns of functional interactions across distributed brain regions are suggested to provide a scaffold for the conscious processing of information, with marked topological alterations observed in loss of consciousness. However, establishing a firm link between macro-scale brain network organisation and conscious cognition requires direct investigations into neuropsychologically-relevant architectural modifications across systematic reductions in consciousness. Here we assessed both global and regional disturbances to brain graphs in a group of healthy participants across baseline resting state fMRI as well as two distinct levels of propofol-induced sedation. We found a persistent modular architecture, yet significant reorganisation of brain hubs that formed parts of a wider rich-club collective. Furthermore, the reduction in the strength of rich-club connectivity was significantly associated with the participants’ performance in a semantic judgment task, indicating the importance of this higher-order topological feature for conscious cognition. These results highlight a remarkable interplay between global and regional properties of brain functional interactions in supporting conscious cognition that is relevant to our understanding of clinical disorders of consciousness.

Fractal dimension of cortical functional connectivity networks & severity of disorders of consciousness

Recent evidence suggests that the quantity and quality of conscious experience may be a function of the complexity of activity in the brain and that consciousness emerges in a critical zone between low and high-entropy states. We propose fractal shapes as a measure of proximity to this critical point, as fractal dimension encodes information about complexity beyond simple entropy or randomness, and fractal structures are known to emerge in systems nearing a critical point. To validate this, we tested several measures of fractal dimension on the brain activity from healthy volunteers and patients with disorders of consciousness of varying severity. We used a Compact Box Burning algorithm to compute the fractal dimension of cortical functional connectivity networks as well as computing the fractal dimension of the associated adjacency matrices using a 2D box-counting algorithm. To test whether brain activity is fractal in time as well as space, we used the Higuchi temporal fractal dimension on BOLD time-series. We found significant decreases in the fractal dimension between healthy volunteers (n = 15), patients in a minimally conscious state (n = 10), and patients in a vegetative state (n = 8), regardless of the mechanism of injury. We also found significant decreases in adjacency matrix fractal dimension and Higuchi temporal fractal dimension, which correlated with decreasing level of consciousness. These results suggest that cortical functional connectivity networks display fractal character and that this is associated with level of consciousness in a clinically relevant population, with higher fractal dimensions (i.e. more complex) networks being associated with higher levels of consciousness. This supports the hypothesis that level of consciousness and system complexity are positively associated, and is consistent with previous EEG, MEG, and fMRI studies.

Consciousness & Brain Functional Complexity in Propofol Anaesthesia

The brain is possibly the most complex system known to mankind, and its complexity has been called upon to explain the emergence of consciousness. However, complexity has been defined in many ways by multiple different fields: here, we investigate measures of algorithmic and process complexity in both the temporal and topological domains, testing them on functional MRI BOLD signal data obtained from individuals undergoing various levels of sedation with the anaesthetic agent propofol, replicating our results in two separate datasets. We demonstrate that the various measures are differently able to discriminate between levels of sedation, with temporal measures showing higher sensitivity. Further, we show that all measures are strongly related to a single underlying construct explaining most of the variance, as assessed by Principal Component Analysis, which we interpret as a measure of “overall complexity” of our data. This overall complexity was also able to discriminate between levels of sedation and serum concentrations of propofol, supporting the hypothesis that consciousness is related to complexity - independent of how the latter is measured.

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.

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.

Future of paediatric sedation: towards a unified goal of improving practice

This review offers a perspective on the future of paediatric sedation. This future will require continued evaluation of adverse events, their risk factors, and predictors. As the introduction of new sedatives with paediatric applications will remain limited, the potential role of mainstay sedatives administered by new routes, for new indications, and with new delivery techniques, should be considered. The role of non-pharmacological strategies for anxiolysis, along with the application of non-mainstay physiologic monitoring, may aid in the improvement of targeted sedation delivery. Understanding the mechanism and location of action of the different sedatives will remain an important focus. Important developments in paediatric sedation will require that large scale studies with global data contribution be conducted in order to support changes in sedation practice, improve the patient experience, and make sedation safer.