Resting state network activation and functional connectivity in the dying brain.

OBJECTIVE: To characterize electrophysiological functional connectivity within both the default mode network (DMN) and the task-positive network (TPN) among a small group of unresponsive hospice patients at the end of life. METHODS: EEG recordings from resting state were analysed to identify brain regions in the DMN and TPN of 30 young, healthy controls, and of 9 hospice patients when they were responsive and of 5 patients when they became unresponsive during the last hours of life. RESULTS: The prevalence of activation and connectivity within the DMN was similar across all participant groups. Overall functional connectivity was higher between brain regions within the DMN than between brain regions within TPN for all participant groups. The number of functional connections within the DMN, however, was greater than those within the TPN among controls and responsive hospice patients but not among unresponsive hospice patients. CONCLUSIONS: Some unresponsive patients may have the functional architecture to support internally-oriented thought at the end of life. Resting state default mode - task positive network anticorrelations may be present among some unresponsive hospice patients. SIGNIFICANCE: Some unresponsive end of life patients may be able to mind-wander. Implications for internally-oriented awareness at the end of life are discussed.

Disrupted neural correlates of anesthesia and sleep reveal early circuit dysfunctions in Alzheimer models.

Dysregulated homeostasis of neural activity has been hypothesized to drive Alzheimer's disease (AD) pathogenesis. AD begins with a decades-long presymptomatic phase, but whether homeostatic mechanisms already begin failing during this silent phase is unknown. We show that before the onset of memory decline and sleep disturbances, familial AD (fAD) model mice display no deficits in CA1 mean firing rate (MFR) during active wakefulness. However, homeostatic down-regulation of CA1 MFR is disrupted during non-rapid eye movement (NREM) sleep and general anesthesia in fAD mouse models. The resultant hyperexcitability is attenuated by the mitochondrial dihydroorotate dehydrogenase (DHODH) enzyme inhibitor, which tunes MFR toward lower set-point values. Ex vivo fAD mutations impair downward MFR homeostasis, resulting in pathological MFR set points in response to anesthetic drug and inhibition blockade. Thus, firing rate dyshomeostasis of hippocampal circuits is masked during active wakefulness but surfaces during low-arousal brain states, representing an early failure of the silent disease stage.

Perioperative Electroencephalogram Spectral Dynamics Related to Postoperative Delirium in Older Patients.

BACKGROUND: Intraoperative electroencephalography (EEG) signatures related to the development of postoperative delirium (POD) in older patients are frequently studied. However, a broad analysis of the EEG dynamics including preoperative, postinduction, intraoperative and postoperative scenarios and its correlation to POD development is still lacking. We explored the relationship between perioperative EEG spectra-derived parameters and POD development, aiming to ascertain the diagnostic utility of these parameters to detect patients developing POD. METHODS: Patients aged ≥65 years undergoing elective surgeries that were expected to last more than 60 minutes were included in this prospective, observational single center study (Biomarker Development for Postoperative Cognitive Impairment [BioCog] study). Frontal EEGs were recorded, starting before induction of anesthesia and lasting until recovery of consciousness. EEG data were analyzed based on raw EEG files and downloaded excel data files. We performed multitaper spectral analyses of relevant EEG epochs and further used multitaper spectral estimate to calculate a corresponding spectral parameter. POD assessments were performed twice daily up to the seventh postoperative day. Our primary aim was to analyze the relation between the perioperative spectral edge frequency (SEF) and the development of POD. RESULTS: Of the 237 included patients, 41 (17%) patients developed POD. The preoperative EEG in POD patients was associated with lower values in both SEF (POD 13.1 ± 4.6 Hz versus no postoperative delirium [NoPOD] 17.4 ± 6.9 Hz; P = .002) and corresponding γ-band power (POD -24.33 ± 2.8 dB versus NoPOD -17.9 ± 4.81 dB), as well as reduced postinduction absolute α-band power (POD -7.37 ± 4.52 dB versus NoPOD -5 ± 5.03 dB). The ratio of SEF from the preoperative to postinduction state (SEF ratio) was ~1 in POD patients, whereas NoPOD patients showed a SEF ratio >1, thus indicating a slowing of EEG with loss of unconscious. Preoperative SEF, preoperative γ-band power, and SEF ratio were independently associated with POD (P = .025; odds ratio [OR] = 0.892, 95% confidence interval [CI], 0.808-0.986; P = .029; OR = 0.568, 95% CI, 0.342-0.944; and P = .009; OR = 0.108, 95% CI, 0.021-0.568, respectively). CONCLUSIONS: Lower preoperative SEF, absence of slowing in EEG while transitioning from preoperative state to unconscious state, and lower EEG power in relevant frequency bands in both these states are related to POD development. These findings may suggest an underlying pathophysiology and might be used as EEG-based marker for early identification of patients at risk to develop POD.

Loss of consciousness reduces the stability of brain hubs and the heterogeneity of brain dynamics.

Low-level states of consciousness are characterized by disruptions of brain activity that sustain arousal and awareness. Yet, how structural, dynamical, local and network brain properties interplay in the different levels of consciousness is unknown. Here, we study fMRI brain dynamics from patients that suffered brain injuries leading to a disorder of consciousness and from healthy subjects undergoing propofol-induced sedation. We show that pathological and pharmacological low-level states of consciousness display less recurrent, less connected and more segregated synchronization patterns than conscious state. We use whole-brain models built upon healthy and injured structural connectivity to interpret these dynamical effects. We found that low-level states of consciousness were associated with reduced network interactions, together with more homogeneous and more structurally constrained local dynamics. Notably, these changes lead the structural hub regions to lose their stability during low-level states of consciousness, thus attenuating the differences between hubs and non-hubs brain dynamics.

Quantitative assessment of the relationship between behavioral and autonomic dynamics during propofol-induced unconsciousness.

During general anesthesia, both behavioral and autonomic changes are caused by the administration of anesthetics such as propofol. Propofol produces unconsciousness by creating highly structured oscillations in brain circuits. The anesthetic also has autonomic effects due to its actions as a vasodilator and myocardial depressant. Understanding how autonomic dynamics change in relation to propofol-induced unconsciousness is an important scientific and clinical question since anesthesiologists often infer changes in level of unconsciousness from changes in autonomic dynamics. Therefore, we present a framework combining physiology-based statistical models that have been developed specifically for heart rate variability and electrodermal activity with a robust statistical tool to compare behavioral and multimodal autonomic changes before, during, and after propofol-induced unconsciousness. We tested this framework on physiological data recorded from nine healthy volunteers during computer-controlled administration of propofol. We studied how autonomic dynamics related to behavioral markers of unconsciousness: 1) overall, 2) during the transitions of loss and recovery of consciousness, and 3) before and after anesthesia as a whole. Our results show a strong relationship between behavioral state of consciousness and autonomic dynamics. All of our prediction models showed areas under the curve greater than 0.75 despite the presence of non-monotonic relationships among the variables during the transition periods. Our analysis highlighted the specific roles played by fast versus slow changes, parasympathetic vs sympathetic activity, heart rate variability vs electrodermal activity, and even pulse rate vs pulse amplitude information within electrodermal activity. Further advancement upon this work can quantify the complex and subject-specific relationship between behavioral changes and autonomic dynamics before, during, and after anesthesia. However, this work demonstrates the potential of a multimodal, physiologically-informed, statistical approach to characterize autonomic dynamics.

Spontaneous Multimodal Neural Transmission Suggests That Adult Spinal Networks Maintain an Intrinsic State of Readiness to Execute Sensorimotor Behaviors.

Spontaneous action potential discharge (spAP) is both ubiquitous and functionally relevant during neural development. spAP remains a prominent feature of supraspinal networks in maturity, even during unconsciousness. Evidence suggests that spAP persists in mature spinal networks during wakefulness, and one function of spAP in this context could be maintenance of a "ready state" to execute behaviors. The extent to which spAP persists in mature spinal networks during unconsciousness remains unclear, and its function(s), if any, are likewise unresolved. Here, we attempt to reconcile some of the questions and contradictions that emerge from the disintegrated picture of adult spinal spAP currently available. We recorded simultaneously from large populations of spinal interneurons in vivo in male rats, characterizing the spatial distribution of spAP in the lumbar enlargement and identifying subgroups of spontaneously active neurons. We find (1) concurrent spAP throughout the dorsoventral extent of the gray matter, with a diverse yet strikingly consistent mixture of neuron types across laminae; (2) the proportion of neurons exhibiting spAP in deeper, sensorimotor integrative regions is comparable to that in more superficial, sensory-dominant regions; (3) firing rate, but not spike train variability, varies systematically with region; and (4) spAP includes multimodal neural transmission consistent with executing a spinally-mediated behavior. These findings suggest that adult spAP may continue to support a state of readiness to execute sensorimotor behaviors even during unconsciousness. Such functionality has implications for our understanding of how perception is translated into action, of experience-dependent modification of behavior, and (mal)adaptative responses to injury or disease.SIGNIFICANCE STATEMENT Neurons often discharge action potentials (APs) seemingly spontaneously, that is, in the absence of ongoing behaviors or overt stimuli. This phenomenon is particularly evident during neural development, where spontaneous AP discharge (spAP) is ubiquitous in the central nervous system and is crucial to establishing connectivity among functionally related groups of neurons. The function(s) of spAP in adult spinal networks, if any, have remained enigmatic, especially during unconsciousness. Here, we report evidence that one such function could be to support an intrinsic state of readiness to execute sensorimotor behaviors. This finding has implications for our understanding of how perception is translated into action, of experience-dependent modification of behavior, and (mal)adaptative responses to injury or disease.

Quantum-like model for unconscious-conscious interaction and emotional coloring of perceptions and other conscious experiences.

Quantum measurement theory is applied to quantum-like modeling of coherent generation of perceptions and emotions and generally for emotional coloring of conscious experiences. In quantum theory, a system should be separated from an observer. The brain performs self-measurements. To model them, we split the brain into two subsystems, unconsciousness and consciousness. They correspond to a system and an observer. The states of perceptions and emotions are described through the tensor product decomposition of the unconscious state space; similarly, there are two classes of observables, for conscious experiencing of perceptions and emotions, respectively. Emotional coloring is coupled to quantum contextuality: emotional observables determine contexts. Such contextualization reduces degeneration of unconscious states. The quantum-like approach should be distinguished from consideration of the genuine quantum physical processes in the brain (cf. Penrose and Hameroff). In our approach the brain is a macroscopic system which information processing can be described by the formalism of quantum theory. The paper is concluded with experimental test of contextual emotional coloring of conscious experiences based on Bell type inequalities which are treated in the contextual framework.

Propofol differentially induces unconsciousness and respiratory depression through distinct interactions between GABAA receptor and GABAergic neuron in corresponding nuclei.

Propofol is the most commonly used intravenous anesthetic worldwide. It can induce loss of consciousness prior to the occurrence of severe respiratory suppression, which is also a pharmacodynamic feature of all general anesthetics. However, the neural mechanisms underlying this natural phenomenon are controversial and highly related to patient safety. In the present study, we demonstrated that the pharmacodynamic effects of propofol (50 and 100 µM) on suppression of consciousness-related excitatory postsynaptic currents in the medial prefrontal cortex (mPFC) and centromedian nucleus of the thalamus (CMT) were lower than those in the kernel respiratory rhythmogenesis nucleus pre-Bötzinger complex (PrBo). Furthermore, we unexpectedly found that the GABAA receptor ß3 subunit is the key target for propofol's action and that it is mutually and exclusively expressed in GABAergic neurons. It is also more abundant in the mPFC and CMT, but mainly co-localized with GABAergic neurons in the PrBo. As a result, the differentiated expression pattern should mediate more neuron suppression through the activation of GABAergic neurons in the mPFC and CMT at low doses of propofol (50 µM). However, PrBo GABAergic neurons were only activated by propofol at a high dose (100 µM). These results highlight the detailed pharmacodynamic effects of propofol on consciousness-related and respiration-related nuclei and provide the distinct interaction mechanism between the ß3 subunit and GABAergic neurons in mediating the suppression of consciousness compared to the inhibition of respiration.

Machine learning of EEG spectra classifies unconsciousness during GABAergic anesthesia.

In current anesthesiology practice, anesthesiologists infer the state of unconsciousness without directly monitoring the brain. Drug- and patient-specific electroencephalographic (EEG) signatures of anesthesia-induced unconsciousness have been identified previously. We applied machine learning approaches to construct classification models for real-time tracking of unconscious state during anesthesia-induced unconsciousness. We used cross-validation to select and train the best performing models using 33,159 2s segments of EEG data recorded from 7 healthy volunteers who received increasing infusions of propofol while responding to stimuli to directly assess unconsciousness. Cross-validated models of unconsciousness performed very well when tested on 13,929 2s EEG segments from 3 left-out volunteers collected under the same conditions (median volunteer AUCs 0.99-0.99). Models showed strong generalization when tested on a cohort of 27 surgical patients receiving solely propofol collected in a separate clinical dataset under different circumstances and using different hardware (median patient AUCs 0.95-0.98), with model predictions corresponding with actions taken by the anesthesiologist during the cases. Performance was also strong for 17 patients receiving sevoflurane (alone or in addition to propofol) (median AUCs 0.88-0.92). These results indicate that EEG spectral features can predict unconsciousness, even when tested on a different anesthetic that acts with a similar neural mechanism. With high performance predictions of unconsciousness, we can accurately monitor anesthetic state, and this approach may be used to engineer infusion pumps to intelligibly respond to patients' neural activity.

Spontaneous neural synchrony links intrinsic spinal sensory and motor networks during unconsciousness.

Non-random functional connectivity during unconsciousness is a defining feature of supraspinal networks. However, its generalizability to intrinsic spinal networks remains incompletely understood. Previously, Barry et al., 2014 used fMRI to reveal bilateral resting state functional connectivity within sensory-dominant and, separately, motor-dominant regions of the spinal cord. Here, we record spike trains from large populations of spinal interneurons in vivo in rats and demonstrate that spontaneous functional connectivity also links sensory- and motor-dominant regions during unconsciousness. The spatiotemporal patterns of connectivity could not be explained by latent afferent activity or by populations of interconnected neurons spiking randomly. We also document connection latencies compatible with mono- and disynaptic interactions and putative excitatory and inhibitory connections. The observed activity is consistent with the hypothesis that salient, experience-dependent patterns of neural transmission introduced during behavior or by injury/disease are reactivated during unconsciousness. Such a spinal replay mechanism could shape circuit-level connectivity and ultimately behavior.

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.

Consciousness among delta waves: a paradox?

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

How hot is the hot zone? Computational modelling clarifies the role of parietal and frontoparietal connectivity during anaesthetic-induced loss of consciousness.

In recent years, specific cortical networks have been proposed to be crucial for sustaining consciousness, including the posterior hot zone and frontoparietal resting state networks (RSN). Here, we computationally evaluate the relative contributions of three RSNs - the default mode network (DMN), the salience network (SAL), and the central executive network (CEN) - to consciousness and its loss during propofol anaesthesia. Specifically, we use dynamic causal modelling (DCM) of 10 min of high-density EEG recordings (N = 10, 4 males) obtained during behavioural responsiveness, unconsciousness and post-anaesthetic recovery to characterise differences in effective connectivity within frontal areas, the posterior 'hot zone', frontoparietal connections, and between-RSN connections. We estimate - for the first time - a large DCM model (LAR) of resting EEG, combining the three RSNs into a rich club of interconnectivity. Consistent with the hot zone theory, our findings demonstrate reductions in inter-RSN connectivity in the parietal cortex. Within the DMN itself, the strongest reductions are in feed-forward frontoparietal and parietal connections at the precuneus node. Within the SAL and CEN, loss of consciousness generates small increases in bidirectional connectivity. Using novel DCM leave-one-out cross-validation, we show that the most consistent out-of-sample predictions of the state of consciousness come from a key set of frontoparietal connections. This finding also generalises to unseen data collected during post-anaesthetic recovery. Our findings provide new, computational evidence for the importance of the posterior hot zone in explaining the loss of consciousness, highlighting also the distinct role of frontoparietal connectivity in underpinning conscious responsiveness, and consequently, suggest a dissociation between the mechanisms most prominently associated with explaining the contrast between conscious awareness and unconsciousness, and those maintaining consciousness.

Trigeminal nerve electrical stimulation: An effective arousal treatment for loss of consciousness.

BACKGROUND: To determine if trigeminal nerve electrical stimulation (TNS) would be an effective arousal treatment for loss of consciousness (LOC), we applied neuroscientific methods to investigate the role of potential brain circuit and neuropeptide pathway in regulating level of consciousness. METHODS: Consciousness behavioral analysis, Electroencephalogram (EEG) recording, Chemogenetics, Microarray analysis, Milliplex MAP rat peptide assay, Chromatin immune-precipitation (ChIP), Dual-luciferase reporter experiment, Western blot, PCR and Fluorescence in situ hybridization (FISH). RESULTS: TNS can markedly activate the neuronal activities of the lateral hypothalamus (LH) and the spinal trigeminal nucleus (Sp5), as well as improve rat consciousness level and EEG activities. Then we proved that LH activation and upregulated neuropeptide hypocretin are beneficial for promotion of consciousness recovery. We then applied gene microarray experiment and found hypocretin might be mediated by a well-known transcription factor Early growth response gene 1 (EGR1), and the results were confirmed by ChIP and Dual-luciferase reporter experiment. CONCLUSION: This study illustrates that TNS is an effective arousal strategy Treatment for LOC state via the activation of Sp5 and LH neurons and upregulation of hypocretin expression.

Comparison of anaesthetic- and seizure-induced states of unconsciousness: a narrative review.

In order to understand general anaesthesia and certain seizures, a fundamental understanding of the neurobiology of unconsciousness is needed. This review article explores similarities in neuronal and network changes during general anaesthesia and seizure-induced unconsciousness. Both seizures and anaesthetics cause disruption in similar anatomical structures that presumably lead to impaired consciousness. Despite differences in behaviour and mechanisms, both of these conditions are associated with disruption of the functionality of subcortical structures that mediate neuronal activity in the frontoparietal cortex. These areas are all likely to be involved in maintaining normal consciousness. An assessment of the similarities in the brain network disruptions with certain seizures and general anaesthesia might provide fresh insights into the mechanisms of the alterations of consciousness seen in these particular unconscious states, allowing for innovative therapies for seizures and the development of anaesthetic approaches targeting specific networks.

No cognitive processing in the unconscious, anesthetic-like, state of sleep.

We review evidence challenging the hypothesis that memories are processed or consolidated in sleep. We argue that the brain is in an unconscious state in sleep, akin to general anesthesia (GA), and hence is incapable of meaningful cognitive processing-the sole purview of waking consciousness. At minimum, the encoding of memories in sleep would require that waking events are faithfully transferred to and reproduced in sleep. Remarkably, however, this has never been demonstrated, as waking experiences are never truly replicated in sleep but rather appear in very altered or distorted forms. General anesthetics (GAs) exert their effects through endogenous sleep-wake control systems and accordingly GA and sleep share several common features: sensory blockade, immobility, amnesia and lack of awareness (unconsciousness). The loss of consciousness in non-REM (NREM) sleep or to GAs is characterized by: (a) delta oscillations throughout the cortex; (b) marked reductions in neural activity (from waking) over widespread regions of the cortex, most pronounced in frontal and parietal cortices; and (c) a significant disruption of the functional connectivity of thalamocortical and corticocortical networks, particularly those involved in "higher order" cognitive functions. Several (experimental) reports in animals and humans have shown that disrupting the activity of the cortex, particularly the orbitofrontal cortex, severely impairs higher order cognitive and executive functions. The profound and widespread deactivation of the cortex in the unconscious states of NREM sleep or GA would be expected to produce an equivalent, or undoubtedly a much greater, disruptive effect on mnemonic and cognitive functions. In conclusion, we contend that the unconscious, severely altered state of the brain in NREM sleep would negate any possibility of cognitive processing in NREM sleep.

Biomechanical comparison of concussions with and without a loss of consciousness in elite American football: implications for prevention.

Loss of consciousness (LOC) associated with concussion is no longer considered an indicator of severity of injury in concussion management protocols. Studies investigating the association between LOC and recovery time or neurophysiological performance have reported ambiguous findings and resulted in a limited understanding of the severity of LOC-inducing head impacts. Concussive injuries with and without LOC from helmet-to-helmet and shoulder collisions and falls in elite American football were reconstructed in laboratory using a hybrid III headform and finite element model to obtain peak linear and rotational acceleration and brain tissue deformation metrics in the cerebral cortex, the cerebral white matter, the corpus callosum, the thalamus and the brainstem. Impact velocity, peak linear and rotational acceleration were significantly greater in the LOC group than the no LOC group. The brain tissue deformation metrics were greater in the LOC group than the no LOC group. The best overall predictor for LOC was impact velocity. Concussions with LOC are characterised by greater magnitudes of brain tissue deformation. This was mainly the result of higher impact velocities in the LOC group providing league decision-makers with an understanding of the importance of managing impact velocity through athlete education and rule enforcement or change.

Foundations of Human Consciousness: Imaging the Twilight Zone.

What happens in the brain when conscious awareness of the surrounding world fades? We manipulated consciousness in two experiments in a group of healthy males and measured brain activity with positron emission tomography. Measurements were made during wakefulness, escalating and constant levels of two anesthetic agents (experiment 1, n = 39), and during sleep-deprived wakefulness and non-rapid eye movement sleep (experiment 2, n = 37). In experiment 1, the subjects were randomized to receive either propofol or dexmedetomidine until unresponsiveness. In both experiments, forced awakenings were applied to achieve rapid recovery from an unresponsive to a responsive state, followed by immediate and detailed interviews of subjective experiences during the preceding unresponsive condition. Unresponsiveness rarely denoted unconsciousness, as the majority of the subjects had internally generated experiences. Unresponsive anesthetic states and verified sleep stages, where a subsequent report of mental content included no signs of awareness of the surrounding world, indicated a disconnected state. Functional brain imaging comparing responsive and connected versus unresponsive and disconnected states of consciousness during constant anesthetic exposure revealed that activity of the thalamus, cingulate cortices, and angular gyri are fundamental for human consciousness. These brain structures were affected independent from the pharmacologic agent, drug concentration, and direction of change in the state of consciousness. Analogous findings were obtained when consciousness was regulated by physiological sleep. State-specific findings were distinct and separable from the overall effects of the interventions, which included widespread depression of brain activity across cortical areas. These findings identify a central core brain network critical for human consciousness.SIGNIFICANCE STATEMENT Trying to understand the biological basis of human consciousness is currently one of the greatest challenges of neuroscience. While the loss and return of consciousness regulated by anesthetic drugs and physiological sleep are used as model systems in experimental studies on consciousness, previous research results have been confounded by drug effects, by confusing behavioral "unresponsiveness" and internally generated consciousness, and by comparing brain activity levels across states that differ in several other respects than only consciousness. Here, we present carefully designed studies that overcome many previous confounders and for the first time reveal the neural mechanisms underlying human consciousness and its disconnection from behavioral responsiveness, both during anesthesia and during normal sleep, and in the same study subjects.

Progress in modelling of brain dynamics during anaesthesia and the role of sleep-wake circuitry.

General anaesthesia is used widely in surgery and during interventional medical procedures, but little is known about the exact neural mechanisms for how unconsciousness arises from administering an anaesthetic drug. Computational modelling of brain dynamics has already provided valuable insights into the neural circuitry involved in generating this state. Current theories for the origin of electroencephalographic (EEG) features in brain activity under GABAergic anaesthetic drugs have been proposed through modelling results. While much attention has been paid to describing alpha and delta oscillations, burst suppression, paradoxical excitation and the possibility of hysteresis during transitions to and from unconscious state, these models have focused only on the role of the thalamocortical system. Recent empirical findings suggest that anaesthetic drugs may act directly on the neural circuitry regulating sleep and wake states and circadian rhythms in the hypothalamus. Coupled with the common behavioural features found in physiological sleep and general anaesthesia, this evidence serves as a foundation for the 'shared circuits hypothesis' which proposes that anaesthetic-induced unconsciousness arises predominantly through modulation of the hypothalamic sleep-wake switch. This paper reviews the key findings from computational models describing brain states during the administration of anaesthetic drugs, with a focus on those enhancing GABAergic inhibition given their widespread use in practice and that almost all models of anaesthesia have focused on these drugs. We draw physiological and behavioural links between brain states during sleep and anaesthesia, and aim to highlight the importance of computational modelling in advancing our understanding of anaesthesia by considering sleep and circadian mechanisms in generating unconsciousness in future work.