Dynamics of recovery from anaesthesia-induced unconsciousness across primate neocortex

Combining quantified EEG with clinical measures to better predict outcomes of acute disorders of consciousness

OBJECTIVE

To explore the application of the neuronal recovery model (i.e., the ABCD model derived from EEG power spectral analysis) in forecasting outcomes for patients with acute disorders of consciousness (DOC).

METHODS

Patients with acute DOC were enrolled, and clinical assessments, including the Glasgow Coma Scale (GCS), Full Outline of UnResponsiveness (FOUR), and Coma Recovery Scale-Revised (CRS-R) scores, along with electroencephalography (EEG), were documented on the first day post-enrollment. The ABCD model, derived from EEG power spectral data reflecting frequency bands, categorized brain activity into four distinct groups (A, B, C, D). Outcome prognoses were evaluated using the Glasgow Outcome Scale-Extended (GOSE) six months after enrollment. Statistical analyses were performed to assess the correlation between the ABCD model and clinical assessments, and to investigate the predictive value of EEG and clinical assessments for the long-term prognosis.

RESULTS

A total of 93 patients with acute DOC were included; the median age was 64 years (interquartile range 52, 72), of which 52 patients had favorable outcomes. Significant correlations were observed between the ABCD model and both the FOUR and CRS-R scores. The CRS-R and ABCD model demonstrated relatively good predictive value for six-month prognoses, with Area Under the Curve (AUC) values of 0.695 and 0.678, respectively (P < 0.05). Furthermore, the combination of the CRS-R score and ABCD model exhibited the highest predictive value with an AUC of 0.746.

CONCLUSIONS

The ABCD model effectively predicted the prognosis of patients with acute DOC in combination with CRS-R.

Spatiospectral dynamics of electroencephalography patterns during propofol-induced alterations of consciousness states

Altered consciousness induced by anesthetics is characterized by distinct spatial and spectral neural dynamics that are readily apparent in the human electroencephalogram. Despite considerable study, we remain uncertain which brain regions and neural oscillations are involved, as well as how they are impacted when consciousness is disrupted. The experimental data was obtained from the open-access dataset, which contains pre-processed EEG data recorded from 20 healthy participants during propofol sedation. Using unsupervised machine learning methods (i.e., non-negative matrix factorization, NMF), we investigated the spatiospectral dynamic evolution of brain activity from awake to sedation and back induced by propofol in healthy research volunteers. Our methods yielded six dynamical patterns that continuously reflect the neural activity changes in specific brain regions and frequency bands under propofol sedation. Temporal dynamic analyses showed that differences in alpha oscillation patterns were less pronounced in response group than drowsy group, with hemispheric asymmetry in posterior occipital lobe over the course of the sedation procedure. We designed an index 'hemispheric lateralization modulation of alpha [HLM(α)]' to measure asymmetry during awake state and predicting individual variability in propofol-induced alterations of consciousness states, obtaining prediction AUC of 0.8462. We present an alpha modulation index which characterizes how these patterns track the transition from awake to sedation as a function of increasing dosage. Our study reveals dynamics indices that track the evolution of neurophysiological of propofol on brain circuits. Analyzing the spatiospectral dynamics influenced by propofol provides valuable understanding of the mechanisms of these agents and strategies for monitoring and precisely controlling the level of consciousness in patients under sedation and general anesthesia.

Regulation of states of consciousness by supramammillary nucleus glutamatergic neurones during sevoflurane anaesthesia in mice

BACKGROUND

The supramammillary nucleus (SuM), located in the caudal hypothalamus, includes wake-promoting glutamatergic neurones. Their potential role in regulating states of consciousness during general anaesthesia remains unknown.

METHODS

We used in vivo fibre photometry, c-Fos staining, chemogenetic and optogenetic manipulations, and electroencephalography/electromyography to explore the roles of glutamatergic SuM neurones (SuMVglut2 neurones) at different phases of sevoflurane anaesthesia. Rabies-mediated retrograde and anterograde tract tracing were used to investigate the monosynaptic glutamatergic inputs from the medial septum (MS) to SuM. Their roles in sevoflurane anaesthesia were investigated by in vivo fibre photometry and optogenetic manipulations.

RESULTS

The population activity of SuMVglut2 neurones decreased at loss of consciousness but increased during recovery of consciousness under sevoflurane anaesthesia. Their activity also decreased during suppression but increased during bursts in sevoflurane-induced burst-suppression oscillations. Activating SuMVglut2 neurones chemogenetically or optogenetically decreased sensitivity to sevoflurane, induced behavioural arousal and cortical activation during continuous steady-state anaesthesia, and stable burst-suppression oscillations under sevoflurane. In contrast, chemogenetic or optogenetic inhibition of SuMVglut2 neurones increased sensitivity to sevoflurane or intensified cortical inhibition during sevoflurane anaesthesia. Retrograde and anterograde tracing verified monosynaptic projections from MSVglut2 neurones to SuMVglut2 neurones. The activity of MSVglut2 SuM terminals increased during loss of consciousness but recovered during recovery of consciousness. Optogenetic activation or inhibition of MSVglut2 SuM terminals induced cortical activation or inhibition, respectively, during sevoflurane anaesthesia.

CONCLUSIONS

Activation of SuMVglut2 neurones or the glutamatergic septo-supramammillary circuit induces behavioural arousal and cortical activation during sevoflurane anaesthesia.

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.

Preclinical and translational models for delirium: Recommendations for future research from the NIDUS delirium network

Delirium is a common, morbid, and costly syndrome that is closely linked to Alzheimer's disease (AD) and AD-related dementias (ADRD) as a risk factor and outcome. Human studies of delirium have advanced our knowledge of delirium incidence and prevalence, risk factors, biomarkers, outcomes, prevention, and management. However, understanding of delirium neurobiology remains limited. Preclinical and translational models for delirium, while challenging to develop, could advance our knowledge of delirium neurobiology and inform the development of new prevention and treatment approaches. We discuss the use of preclinical and translational animal models in delirium, focusing on (1) a review of current animal models, (2) challenges and strategies for replicating elements of human delirium in animals, and (3) the utility of biofluid, neurophysiology, and neuroimaging translational markers in animals. We conclude with recommendations for the development and validation of preclinical and translational models for delirium, with the goal of advancing awareness in this important field.

Weakly Correlated Local Cortical State Switches under Anesthesia Lead to Strongly Correlated Global States

During recovery from anesthesia, brain activity switches abruptly between a small set of discrete states. Surprisingly, this switching also occurs under constant doses of anesthesia, even in the absence of stimuli. These metastable states and the transitions between them are thought to form a "scaffold" that ultimately guides the brain back to wakefulness. The processes that constrain cortical activity patterns to these states and govern how states are coordinated between different cortical regions are unknown. If state transitions were driven by subcortical modulation, different cortical sites should exhibit near-synchronous state transitions. Conversely, spatiotemporal heterogeneity would suggest that state transitions are coordinated through corticocortical interactions. To differentiate between these hypotheses, we quantified synchrony of brain states in male rats exposed to a fixed isoflurane concentration. States were defined from spectra of local field potentials recorded across layers of visual and motor cortices. A transition synchrony measure shows that most state transitions are highly localized. Furthermore, while most pairs of cortical sites exhibit statistically significant coupling of both states and state transition times, coupling strength is typically weak. States and state transitions in the thalamic input layer (L4) are particularly decoupled from those in supragranular and infragranular layers. This suggests that state transitions are not imposed on the cortex by broadly projecting modulatory systems. Although each pairwise interaction is typically weak, we show that the multitude of such weak interactions is sufficient to confine global activity to a small number of discrete states.SIGNIFICANCE STATEMENT The brain consistently recovers to wakefulness after anesthesia, but this process is poorly understood. Previous work revealed that, during recovery from anesthesia, corticothalamic activity falls into one of several discrete patterns. The neuronal mechanisms constraining the cortex to just a few discrete states remain unknown. Global states could be coordinated by fluctuations in subcortical nuclei that project broadly to the cortex. Alternatively, these states may emerge from interactions within the cortex itself. Here, we provide evidence for the latter possibility by demonstrating that most pairs of cortical sites exhibit weak coupling. We thereby lay groundwork for future investigations of the specific cellular and network mechanisms of corticocortical activity state coupling.

Asymmetric neural dynamics characterize loss and recovery of consciousness

Anesthetics are known to disrupt neural interactions in cortical and subcortical brain circuits. While the effect of anesthetic drugs on consciousness is reversible, the neural mechanism mediating induction and recovery may be different. Insight into these distinct mechanisms can be gained from a systematic comparison of neural dynamics during slow induction of and emergence from anesthesia. To this end, we used functional magnetic resonance imaging (fMRI) data obtained in healthy volunteers before, during, and after the administration of propofol at incrementally adjusted target concentrations. We analyzed functional connectivity of corticocortical and subcorticocortical networks and the temporal autocorrelation of fMRI signal as an index of neural processing timescales. We found that en route to unconsciousness, temporal autocorrelation across the entire brain gradually increased, whereas functional connectivity gradually decreased. In contrast, regaining consciousness was associated with an abrupt restoration of cortical but not subcortical temporal autocorrelation and an abrupt boost of subcorticocortical functional connectivity. Pharmacokinetic effects could not account for the difference in neural dynamics between induction and emergence. We conclude that the induction and recovery phases of anesthesia follow asymmetric neural dynamics. A rapid increase in the speed of cortical neural processing and subcorticocortical neural interactions may be a mechanism that reboots consciousness.

Objective and graded calibration of recovery of consciousness in experimental models

PURPOSE OF REVIEW

Experimental preclinical models of recovery of consciousness (ROC) and anesthesia emergence are crucial for understanding the neuronal circuits restoring arousal during coma emergence. Such models can also potentially help to better understand how events during coma emergence facilitate or hinder recovery from brain injury. Here we provide an overview of current methods used to assess ROC/level of arousal in animal models. This exposes the need for objective approaches to calibrate arousal levels. We outline how correlation of measured behaviors and their reestablishment at multiple stages with cellular, local and broader neuronal networks, gives a fuller understanding of ROC.

RECENT FINDINGS

Animals emerging from diverse coma-like states share a dynamic process of cortical and behavioral recovery that reveals distinct states consistently sequenced from low-to-high arousal level and trackable in nonhuman primates and rodents. Neuronal activity modulation of layer V-pyramidal neurons and neuronal aggregates within the brainstem and thalamic nuclei play critical roles at specific stages to promote restoration of a conscious state.

SUMMARY

A comprehensive, graded calibration of cortical, physiological, and behavioral changes in animal models is undoubtedly needed to establish an integrative framework. This approach reveals the contribution of local and systemic neuronal circuits to the underlying mechanisms for recovering consciousness.

Explaining anaesthetic hysteresis with effect-site equilibration

BACKGROUND

Anaesthetic induction occurs at higher plasma drug concentrations than emergence in animal studies. Some studies find evidence for such anaesthetic hysteresis in humans, whereas others do not. Traditional thinking attributes hysteresis to drug equilibration between plasma and the effect site. Indeed, a key difference between human studies showing anaesthetic hysteresis and those that do not is in how effect-site equilibration was modelled. However, the effect-site is a theoretical compartment in which drug concentration cannot be measured experimentally. Thus, it is not clear whether drug equilibration models with experimentally intractable compartments are sufficiently constrained to unequivocally establish evidence for the presence or absence of anaesthetic hysteresis.

METHODS

We constructed several models. One lacked hysteresis beyond effect-site equilibration. In another, neuronal dynamics contributed to hysteresis. We attempted to distinguish between these two systems using drug equilibration models.

RESULTS

Our modelling studies showed that one can always construct an effect-site equilibration model such that hysteresis collapses. So long as the concentration in the effect-site cannot be measured directly, the correct effect-site equilibration model and the one that erroneously collapses hysteresis are experimentally indistinguishable. We also found that hysteresis can naturally arise even in a simple network of neurones independently of drug equilibration.

CONCLUSIONS

Effect-site equilibration models can readily collapse hysteresis. However, this does not imply that hysteresis is solely attributable to the kinetics of drug equilibration.

Neural signatures of α2-Adrenergic agonist-induced unconsciousness and awakening by antagonist

How the brain dynamics change during anesthetic-induced altered states of consciousness is not completely understood. The α2-adrenergic agonists are unique. They generate unconsciousness selectively through α2-adrenergic receptors and related circuits. We studied intracortical neuronal dynamics during transitions of loss of consciousness (LOC) with the α2-adrenergic agonist dexmedetomidine and return of consciousness (ROC) in a functionally interconnecting somatosensory and ventral premotor network in non-human primates. LOC, ROC and full task performance recovery were all associated with distinct neural changes. The early recovery demonstrated characteristic intermediate dynamics distinguished by sustained high spindle activities. Awakening by the α2-adrenergic antagonist completely eliminated this intermediate state and instantaneously restored awake dynamics and the top task performance while the anesthetic was still being infused. The results suggest that instantaneous functional recovery is possible following anesthetic-induced unconsciousness and the intermediate recovery state is not a necessary path for the brain recovery.