Globus pallidus externus drives increase in network-wide alpha power with propofol-induced loss-of-consciousness in humans.

States of consciousness are likely mediated by multiple parallel yet interacting cortico-subcortical recurrent networks. Although the mesocircuit model has implicated the pallidocortical circuit as one such network, this circuit has not been extensively evaluated to identify network-level electrophysiological changes related to loss of consciousness (LOC). We characterize changes in the mesocircuit in awake versus propofol-induced LOC in humans by directly simultaneously recording from sensorimotor cortices (S1/M1) and globus pallidus interna and externa (GPi/GPe) in 12 patients with Parkinson disease undergoing deep brain stimulator implantation. Propofol-induced LOC is associated with increases in local power up to 20 Hz in GPi, 35 Hz in GPe, and 100 Hz in S1/M1. LOC is likewise marked by increased pallidocortical alpha synchrony across all nodes, with increased alpha/low beta Granger causal (GC) flow from GPe to all other nodes. In contrast, LOC is associated with decreased network-wide beta coupling and beta GC from M1 to the rest of the network. Results implicate an important and possibly central role of GPe in mediating LOC-related increases in alpha power, supporting a significant role of the GPe in modulating cortico-subcortical circuits for consciousness. Simultaneous LOC-related suppression of beta synchrony highlights that distinct oscillatory frequencies act independently, conveying unique network activity.

Presumption of insensibility during general anaesthesia.

Whilst the general presumption of the public is that general anaesthesia prevents awareness of any sensory stimuli, Lennertz and colleagues have shown in this issue of the British Journal of Anaesthesia that 11% of young adults were able to respond to auditory commands when neuromuscular blocking drugs were prevented from reaching one arm using the isolated forearm technique. This occurred with anaesthetic regimens that followed usual clinical practice in each of the 10 countries that enrolled patients, and it was significantly more common in women than in men. This high incidence demands attention. Further characterisation of the experience of these patients is essential to our understanding of the state of general anaesthesia.

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.

Propofol-induced loss of consciousness is associated with a decrease in thalamocortical connectivity in humans.

Although the molecular effects of many anaesthetics have been well characterized, a network-level explanation for how these changes lead to loss of consciousness remains unclear. Studies using electroencephalography have characterized changes in neural oscillations in the cortex at specific frequency bands during propofol-induced anaesthesia and modelling work suggests these changes result from changes in thalamocortical functional connectivity. However, it is unclear if the neurophysiological changes seen at the cortex are due to enhanced or disrupted thalamocortical communication. Direct recordings from these sites during anaesthesia that could be used to confirm such models are rare. We recorded local field potentials from the ventral intermediate nucleus of the thalamus and electrocorticography signals from the ipsilateral sensorimotor cortex in 10 patients undergoing deep brain stimulation surgery. Signals were acquired during induction of propofol anaesthesia while subjects were resting. After confirming direct structural connectivity between the thalamus and the cortical recording site, we investigated propofol-associated changes in thalamic and cortical local power as well as thalamocortical functional connectivity, as measured with coherence, debiased weighted phase lag index, and phase amplitude coupling. Propofol anaesthesia resulted in local power increases at α frequencies (8-12 Hz) across both thalamic and cortical areas. At sensorimotor cortices, there was a broadband power increase (12-100 Hz), while the power of this same broad frequency band was suppressed within the thalamus. Despite the increase in local α power both within the thalamus and cortex, thalamocortical coherence and debiased weighted phase lag index in the α/low ß frequencies (8-16 Hz, which was present in the awake state) significantly decreased with propofol administration (P < 0.05, two group test of coherence). Likewise, propofol administration resulted in decreased phase amplitude coupling between the phase of α/low ß in the thalamus and the amplitude of broadband gamma (50-200 Hz) in the cortex (P = 0.031, Wilcoxon signed-rank test). We also report phase amplitude coupling between the phase of slow wave oscillations (0.1-1 Hz) and amplitude of broadband frequencies (8-200 Hz) within the cortex and across thalamocortical connections, during anaesthesia, both following a peak-max pattern. While confirming α-power increases with propofol administration both in thalamus and cortex, we observed decreased thalamocortical connectivity, contradicting models that suggest increasing cortical low frequency power is necessarily related to increased thalamocortical coherence but in support of the theory that propofol-induced loss of consciousness is associated with disrupted thalamocortical communication.

Propofol Anesthesia Increases Long-range Frontoparietal Corticocortical Interaction in the Oculomotor Circuit in Macaque Monkeys.

WHAT WE ALREADY KNOW ABOUT THIS TOPIC: A decrease in frontoparietal functional connectivity has been demonstrated with multiple anesthetic agents, and this decrease has been proposed as a final common functional pathway to produce anesthesia.Two alternative measures of long-range cortical interaction are coherence and phase-amplitude coupling. Although phase-amplitude coupling within frontal cortex changes with propofol administration, the effects of propofol on phase-amplitude coupling between different cortical areas have not previously been reported. WHAT THIS ARTICLE TELLS US THAT IS NEW: Using a previously published monkey electrocorticography data set, it was found that propofol induced coherent slow oscillations in visual and oculomotor networks made up of cortical areas with strong anatomic projections.Frontal eye field within-area phase-amplitude coupling increased.Contrary to expectations from previous functional connectivity studies, interareal phase-amplitude coupling also increased with propofol. BACKGROUND: Frontoparietal functional connectivity decreases with multiple anesthetics using electrophysiology and functional imaging. This decrease has been proposed as a final common functional pathway to produce anesthesia. Two alternative measures of long-range cortical interaction are coherence and phase-amplitude coupling. Although phase-amplitude coupling within frontal cortex changes with propofol administration, the effects of propofol on phase-amplitude coupling between different cortical areas have not previously been reported. Based on phase-amplitude coupling observed within frontal lobe during the anesthetized period, it was hypothesized that between-lead phase-amplitude coupling analysis should decrease between frontal and parietal leads during propofol anesthesia. METHODS: A published monkey electrocorticography data set (N = 2 animals) was used to test for interactions in the cortical oculomotor circuit, which is robustly interconnected in primates, and in the visual system during propofol anesthesia using coherence and interarea phase-amplitude coupling. RESULTS: Propofol induces coherent slow oscillations in visual and oculomotor networks made up of cortical areas with strong anatomic projections. Frontal eye field within-area phase-amplitude coupling increases with a time course consistent with a bolus response to intravenous propofol (modulation index increase of 12.6-fold). Contrary to the hypothesis, interareal phase-amplitude coupling also increases with propofol, with the largest increase in phase-amplitude coupling in frontal eye field low-frequency phase modulating lateral intraparietal area ß-power (27-fold increase) and visual area 2 low-frequency phase altering visual area 1 ß-power (19-fold increase). CONCLUSIONS: Propofol anesthesia induces coherent oscillations and increases certain frontoparietal interactions in oculomotor cortices. Frontal eye field and lateral intraparietal area show increased coherence and phase-amplitude coupling. Visual areas 2 and 1, which have similar anatomic projection patterns, show similar increases in phase-amplitude coupling, suggesting higher order feedback increases in influence during propofol anesthesia relative to wakefulness. This suggests that functional connectivity between frontal and parietal areas is not uniformly decreased by anesthetics.

Propofol-induced Changes in α-ß Sensorimotor Cortical Connectivity.

BACKGROUND: Anesthetics are believed to alter functional connectivity across brain regions. However, network-level analyses of anesthesia, particularly in humans, are sparse. The authors hypothesized that propofol-induced loss of consciousness results in functional disconnection of human sensorimotor cortices underlying the loss of volitional motor responses. METHODS: The authors recorded local field potentials from sensorimotor cortices in patients with Parkinson disease (N = 12) and essential tremor (N = 7) undergoing deep brain stimulation surgery, before and after propofol-induced loss of consciousness. Local spectral power and interregional connectivity (coherence and imaginary coherence) were evaluated separately across conditions for the two populations. RESULTS: Propofol anesthesia caused power increases for frequencies between 2 and 100 Hz across the sensorimotor cortices and a shift of the dominant spectral peak in α and ß frequencies toward lower frequencies (median ± SD peak frequency: 24.5 ± 2.6 Hz to 12.8 ± 2.3 Hz in Parkinson disease; 13.8 ± 2.1 Hz to 12.1 ± 1.0 Hz in essential tremor). Despite local increases in power, sensorimotor cortical coherence was suppressed with propofol in both cohorts, specifically in ß frequencies (18 to 29 Hz) for Parkinson disease and α and ß (10 to 48 Hz) in essential tremor. CONCLUSIONS: The decrease in functional connectivity between sensory and motor cortices, despite an increase in local spectral power, suggests that propofol causes a functional disconnection of cortices with increases in autonomous activity within cortical regions. This pattern occurs across diseases evaluated, suggesting that these may be generalizable effects of propofol in patients with movement disorders and beyond. Sensorimotor network disruption may underlie anesthetic-induced loss of volitional control.

Recovery of consciousness is mediated by a network of discrete metastable activity states.

It is not clear how, after a large perturbation, the brain explores the vast space of potential neuronal activity states to recover those compatible with consciousness. Here, we analyze recovery from pharmacologically induced coma to show that neuronal activity en route to consciousness is confined to a low-dimensional subspace. In this subspace, neuronal activity forms discrete metastable states persistent on the scale of minutes. The network of transitions that links these metastable states is structured such that some states form hubs that connect groups of otherwise disconnected states. Although many paths through the network are possible, to ultimately enter the activity state compatible with consciousness, the brain must first pass through these hubs in an orderly fashion. This organization of metastable states, along with dramatic dimensionality reduction, significantly simplifies the task of sampling the parameter space to recover the state consistent with wakefulness on a physiologically relevant timescale.

Criticality supports cross-frequency cortical-thalamic information transfer during conscious states.

Consciousness is thought to be regulated by bidirectional information transfer between the cortex and thalamus, but the nature of this bidirectional communication - and its possible disruption in unconsciousness - remains poorly understood. Here, we present two main findings elucidating mechanisms of corticothalamic information transfer during conscious states. First, we identify a highly preserved spectral channel of cortical-thalamic communication that is present during conscious states, but which is diminished during the loss of consciousness and enhanced during psychedelic states. Specifically, we show that in humans, mice, and rats, information sent from either the cortex or thalamus via δ/θ/α waves (∼1-13 Hz) is consistently encoded by the other brain region by high γ waves (52-104 Hz); moreover, unconsciousness induced by propofol anesthesia or generalized spike-and-wave seizures diminishes this cross-frequency communication, whereas the psychedelic 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) enhances this low-to-high frequency interregional communication. Second, we leverage numerical simulations and neural electrophysiology recordings from the thalamus and cortex of human patients, rats, and mice to show that these changes in cross-frequency cortical-thalamic information transfer may be mediated by excursions of low-frequency thalamocortical electrodynamics toward/away from edge-of-chaos criticality, or the phase transition from stability to chaos. Overall, our findings link thalamic-cortical communication to consciousness, and further offer a novel, mathematically well-defined framework to explain the disruption to thalamic-cortical information transfer during unconscious states.

A Two-Stream Graph Convolutional Network Based on Brain Connectivity for Anesthetized States Analysis.

Investigating neural mechanisms of anesthesia process and developing efficient anesthetized state detection methods are especially on high demand for clinical consciousness monitoring. Traditional anesthesia monitoring methods are not involved with the topological changes between electrodes covering the prefrontal-parietal cortices, by investigating electrocorticography (ECoG). To fill this gap, a framework based on the two-stream graph convolutional network (GCN) was proposed, i.e., one stream for extracting topological structure features, and the other one for extracting node features. The two-stream graph convolutional network includes GCN Model 1 and GCN Model 2. For GCN Model 1, brain connectivity networks were constructed by using phase lag index (PLI), representing different structure features. A common adjacency matrix was founded through the dual-graph method, the structure features were expressed on nodes. Therefore, the traditional spectral graph convolutional network can be directly applied on the graphs with changing topological structures. On the other hand, the average of the absolute signal amplitudes was calculated as node features, then a fully connected matrix was constructed as the adjacency matrix of these node features, as the input of GCN Model 2. This method learns features of both topological structure and nodes of the graph, and uses a dual-graph approach to enhance the focus on topological structure features. Based on the ECoG signals of monkeys, results show that this method which can distinguish awake state, moderate sedation and deep sedation achieved an accuracy of 92.75% in group-level experiments and mean accuracy of 93.50% in subject-level experiments. Our work verifies the excellence of the graph convolutional network in anesthesia monitoring, the high recognition accuracy also shows that the brain network may carry neurological markers associated with anesthesia.

Brain Connectivity Analysis in Anesthetized and Awake States: an ECoG Study in Monkeys.

Increasingly, studies have shown that changes in brain network topology accompany loss of consciousness such that the functional connectivity of the prefrontal-parietal network differs significantly in anesthetized and awake states. In this work, anesthetized and awake segments of electrocorticography were selected from two monkeys. Using phase lag index, functional connectivity matrices were built in multiple frequency bands. Quantifying topological changes in brain network through graph-theoretic properties revealed significant differences between the awake and anesthetized states. Compared to the awake state, there were distinct increases in overall and Delta prefrontal-frontal connectivity, and decreases in Alpha, Beta1 and Beta2 prefrontal-frontal connectivity during the anesthetized state, which indicate a change in the topology of the small-world network. Using functional connectivity features we achieved a satisfactory classification accuracy (93.68%). Our study demonstrates that functional connectivity features are of sufficient power to distinguish awake versus anesthetized state.Clinical Relevance- This explores the brain network topology in awake and anesthetized states, and provides new ideas for clinical depth of anesthesia monitoring.

Attentional modulation of adaptation in V4.

Adaptation and visual attention are two processes that alter neural responses to luminance contrast. Rapid contrast adaptation changes response size and dynamics at all stages of visual processing, while visual attention has been shown to modulate both contrast gain and response gain in macaque extrastriate visual cortex. Because attention aims to enhance behaviorally relevant sensory responses while adaptation acts to attenuate neural activity, the question we asked is, how does attention alter adaptation? We present here single-unit recordings from V4 of two rhesus macaques performing a cued target detection task. The study was designed to characterize the effects of attention on the size and dynamics of a sequence of responses produced by a series of flashed oriented gratings parametric in luminance contrast. We found that the effect of attention on the response dynamics of V4 neurons is inconsistent with a mechanism that only alters the effective stimulus contrast, or only rescales the gain of the response. Instead, the action of attention modifies contrast gain early in the task, and modifies both response gain and contrast gain later in the task. We also show that responses to attended stimuli are more closely locked to the stimulus cycle than unattended responses, and that attended responses show less of the phase lag produced by adaptation than unattended responses. The phase advance generated by attention of the adapted responses suggests that the attentional gain control operates in some ways like a contrast gain control utilizing a neural measure of contrast to influence dynamics.

Genetic Reporters of Neuronal Activity: c-Fos and G-CaMP6.

The majority of 20th century investigations into anesthetic effects on the nervous system have used electrophysiology. Yet some fundamental limitations to electrophysiologic recordings, including the invasiveness of the technique, the need to place (potentially several) electrodes in every site of interest, and the difficulty of selectively recording from individual cell types, have driven the development of alternative methods for detecting neuronal activation. Two such alternative methods with cellular scale resolution have matured in the last few decades and will be reviewed here: the transcription of immediate early genes, foremost c-fos, and the influx of calcium into neurons as reported by genetically encoded calcium indicators, foremost GCaMP6. Reporters of c-fos allow detection of transcriptional activation even in deep or distant nuclei, without requiring the accurate targeting of multiple electrodes at long distances. The temporal resolution of c-fos is limited due to its dependence upon the detection of transcriptional activation through immunohistochemical assays, though the development of RT-PCR probes has shifted the temporal resolution of the assay when tissues of interest can be isolated. GCaMP6 has several isoforms that trade-off temporal resolution for signal to noise, but the fastest are capable of resolving individual action potential events, provided the microscope used scans quickly enough. GCaMP6 expression can be selectively targeted to neuronal populations of interest, and potentially thousands of neurons can be captured within a single frame, allowing the neuron-by-neuron reporting of circuit dynamics on a scale that is difficult to capture with electrophysiology, as long as the populations are optically accessible.

Metastability of Neuronal Dynamics during General Anesthesia: Time for a Change in Our Assumptions?

There is strong evidence that anesthetics have stereotypical effects on brain state, so that a given anesthetic appears to have a signature in the electroencephalogram (EEG), which may vary with dose. This can be usefully interpreted as the anesthetic determining an attractor in the phase space of the brain. How brain activity shifts between these attractors in time remains understudied, as most studies implicitly assume a one-to-one relationship between drug dose and attractor features by assuming stationarity over the analysis interval and analyzing data segments of several minutes in length. Yet data in rats anesthetized with isoflurane suggests that, at anesthetic levels consistent with surgical anesthesia, brain activity alternates between multiple attractors, often spending on the order of 10 min in one activity pattern before shifting to another. Moreover, the probability of these jumps between attractors changes with anesthetic concentration. This suggests the hypothesis that brain state is metastable during anesthesia: though it appears at equilibrium on short timescales (on the order of seconds to a few minutes), longer intervals show shifting behavior. Compelling evidence for metastability in rats anesthetized with isoflurane is reviewed, but so far only suggestive hints of metastability in brain states exist with other anesthetics or in other species. Explicit testing of metastability during anesthesia will require experiments with longer acquisition intervals and carefully designed analytic approaches; some of the implications of these constraints are reviewed for typical spectral analysis approaches. If metastability exists during anesthesia, it implies degeneracy in the relationship between brain state and effect site concentration, as there is not a one-to-one mapping between the two. This degeneracy could explain some of the reported difficulty in using brain activity monitors to titrate drug dose to prevent awareness during anesthesia and should force a rethinking of the notion of depth of anesthesia as a single dimension. Finally, explicit incorporation of knowledge of the dynamics of the brain during anesthesia could offer better depth of anesthesia monitoring.

A Bayesian statistical analysis of behavioral facilitation associated with deep brain stimulation.

Deep brain stimulation (DBS) is an established therapy for Parkinson's Disease and is being investigated as a treatment for chronic depression, obsessive compulsive disorder and for facilitating functional recovery of patients in minimally conscious states following brain injury. For all of these applications, quantitative assessments of the behavioral effects of DBS are crucial to determine whether the therapy is effective and, if so, how stimulation parameters can be optimized. Behavioral analyses for DBS are challenging because subject performance is typically assessed from only a small set of discrete measurements made on a discrete rating scale, the time course of DBS effects is unknown, and between-subject differences are often large. We demonstrate how Bayesian state-space methods can be used to characterize the relationship between DBS and behavior comparing our approach with logistic regression in two experiments: the effects of DBS on attention of a macaque monkey performing a reaction-time task, and the effects of DBS on motor behavior of a human patient in a minimally conscious state. The state-space analysis can assess the magnitude of DBS behavioral facilitation (positive or negative) at specific time points and has important implications for developing principled strategies to optimize DBS paradigms.