Chaos analysis of EEG during isoflurane-induced loss of righting in rats

Chaotic nature of the electroencephalogram during shallow and deep anesthesia: From analysis of the Lyapunov exponent

In conscious states, the electrodynamics of the cortex are reported to work near a critical point or phase transition of chaotic dynamics, known as the edge-of-chaos, representing a boundary between stability and chaos. Transitions away from this boundary disrupt cortical information processing and induce a loss of consciousness. The entropy of the electroencephalogram (EEG) is known to decrease as the level of anesthesia deepens. However, whether the chaotic dynamics of electroencephalographic activity shift from this boundary to the side of stability or the side of chaotic enhancement during anesthesia-induced loss of consciousness remains poorly understood. We investigated the chaotic properties of EEGs at two different depths of clinical anesthesia using the maximum Lyapunov exponent, which is mathematically regarded as a formal measure of chaotic nature, using the Rosenstein algorithm. In 14 adult patients, 12 s of electroencephalographic signals were selected during two depths of clinical anesthesia (sevoflurane concentration 2% as relatively deep anesthesia, sevoflurane concentration 0.6% as relatively shallow anesthesia). Lyapunov exponents, correlation dimensions and approximate entropy were calculated from these electroencephalographic signals. As a result, maximum Lyapunov exponent was generally positive during sevoflurane anesthesia, and both maximum Lyapunov exponents and correlation dimensions were significantly greater during deep anesthesia than during shallow anesthesia despite reductions in approximate entropy. The chaotic nature of the EEG might be increased at clinically deeper inhalational anesthesia, despite the decrease in randomness as reflected in the decreased entropy, suggesting a shift to the side of chaotic enhancement under anesthesia.

Consciousness and inward electromagnetic field interactions

Electromagnetic field (EMF) theories of mind/brain integration have been proposed to explain brain function for over seventy years. Interest in this theory continues to this day because it explains mind-brain integration and it offers a simple solution to the “binding problem” of our unified conscious experience. Thus, it addresses at least in part the “hard problem” of consciousness. EMFs are easily measured and many corelates have been noted for field activity; associated with loss and recovery of consciousness, sensory perceptions, and behavior. Unfortunately, the theory was challenged early on by experiments that were thought to have ruled out a role of EMFs in brain activity, and the field of neuroscience has since marginalized EMF theories. Here I explain why early evidence against EMFs contributing to consciousness was misinterpreted and offer an alternative view to help direct future research.

Vowel speech recognition from rat electroencephalography using long short-term memory neural network

Over the years, considerable research has been conducted to investigate the mechanisms of speech perception and recognition. Electroencephalography (EEG) is a powerful tool for identifying brain activity; therefore, it has been widely used to determine the neural basis of speech recognition. In particular, for the classification of speech recognition, deep learning-based approaches are in the spotlight because they can automatically learn and extract representative features through end-to-end learning. This study aimed to identify particular components that are potentially related to phoneme representation in the rat brain and to discriminate brain activity for each vowel stimulus on a single-trial basis using a bidirectional long short-term memory (BiLSTM) network and classical machine learning methods. Nineteen male Sprague-Dawley rats subjected to microelectrode implantation surgery to record EEG signals from the bilateral anterior auditory fields were used. Five different vowel speech stimuli were chosen, /a/, /e/, /i/, /o/, and /u/, which have highly different formant frequencies. EEG recorded under randomly given vowel stimuli was minimally preprocessed and normalized by a z-score transformation to be used as input for the classification of speech recognition. The BiLSTM network showed the best performance among the classifiers by achieving an overall accuracy, f1-score, and Cohen’s κ values of 75.18%, 0.75, and 0.68, respectively, using a 10-fold cross-validation approach. These results indicate that LSTM layers can effectively model sequential data, such as EEG; hence, informative features can be derived through BiLSTM trained with end-to-end learning without any additional hand-crafted feature extraction methods.

A review of methods used to kill laboratory rodents: issues and opportunities

Rodents are the most widely used species for scientific purposes. A critical pre-requisite of their use, based on utilitarian ethical reasoning, is the provision of a humane death when necessary for scientific or welfare grounds. Focussing on the welfare challenges presented by current methods, we critically evaluate the literature, consider emerging methodologies that may have potential for refinement and highlight knowledge gaps for future research. The evidence supports the conclusion that scientists and laboratory personnel should seek to avoid killing laboratory rodents by exposing them to carbon dioxide (CO₂), unless exploiting its high-throughput advantage. We suggest that stakeholders and policymakers should advocate for the removal of CO₂ from existing guidelines, instead making its use conditionally acceptable with justification for additional rationale for its application. With regards to physical methods such as cervical dislocation, decapitation and concussion, major welfare concerns are based on potential inaccuracy in application and their susceptibility to high failure rates. There is a need for independent quality-controlled training programmes to facilitate optimal success rates and the development of specialist tools to improve outcomes and reliability. Furthermore, we highlight questions surrounding the inconsistent inclusion criteria and acceptability of physical methods in international regulation and/or guidance, demonstrating a lack of cohesion across countries and lack of a comprehensive 'gold standard' methodology. We encourage better review of new data and championing of open access scientific resources to advocate for best practice and enable significant changes to policy and legislation to improve the welfare of laboratory rodents at killing.

Electroencephalographic Evidence for Individual Neural Inertia in Mice That Decreases With Time

Previous studies have demonstrated that the brain has an intrinsic resistance to changes in arousal state. This resistance is most easily measured at the population level in the setting of general anesthesia and has been termed neural inertia. To date, no study has attempted to determine neural inertia in individuals. We hypothesize that individuals with markedly increased or decreased neural inertia might be at increased risk for complications related to state transitions, from awareness under anesthesia, to delayed emergence or confusion/impairment after emergence. Hence, an improved theoretical and practical understanding of neural inertia may have the potential to identify individuals at increased risk for these complications. This study was designed to explicitly measure neural inertia in individuals and empirically test the stochastic model of neural inertia using spectral analysis of the murine EEG. EEG was measured after induction of and emergence from isoflurane administered near the EC₅₀ dose for loss of righting in genetically inbred mice on a timescale that minimizes pharmacokinetic confounds. Neural inertia was assessed by employing classifiers constructed using linear discriminant or supervised machine learning methods to determine if features of EEG spectra reliably demonstrate path dependence at steady-state anesthesia. We also report the existence of neural inertia at the individual level, as well as the population level, and that neural inertia decreases over time, providing direct empirical evidence supporting the predictions of the stochastic model of neural inertia.

Differential effects of the novel neurosteroid hypnotic (3β,5β,17β)-3-hydroxyandrostane-17-carbonitrile on electroencephalogram activity in male and female rats

BACKGROUND

We recently showed that a neurosteroid analogue, (3β,5β,17β)-3-hydroxyandrostane-17-carbonitrile (3β-OH), induced hypnosis in rats. The aim of the present study was to evaluate the hypnotic and anaesthetic potential of 3β-OH further using electroencephalography.

METHODS

We used behavioural assessment and cortical electroencephalogram (EEG) spectral power analysis to examine hypnotic and anaesthetic effects of 3β-OH (30 and 60 mg kg-1) administered intraperitoneally or intravenously to young adult male and female rats.

RESULTS

We found dose-dependent sex differences in 3β-OH-induced hypnosis and EEG changes. Both male and female rats responded similarly to i.p. 3β-OH 30 mg kg-1. However, at the higher dose (60 mg kg-1, i.p.), female rats had two-fold longer duration of spontaneous immobility than male rats (203.4 [61.6] min vs 101.3 [32.1] min), and their EEG was suppressed in the low-frequency range (2-6 Hz), in contrast to male rats. Although a sex-dependent hypnotic effect was not confirmed after 30 mg kg-1 i.v., female rats appeared more sensitive to 3β-OH with relatively small changes within delta (1-4 Hz) and alpha (8-13 Hz) bands. Finally, 3β-OH had a rapid onset of action and potent hypnotic/anaesthetic effect after 60 mg kg-1 i.v. in rats of both sexes; however, all female rats and only half of the male rats reached burst suppression, an EEG pattern usually associated with profound inhibition of thalamocortical networks.

CONCLUSIONS

Based on its behavioural effects and EEG signature, 3β-OH is a potent hypnotic in rats, with female rats being more sensitive than male rats.

Preconditioning Exercise in Rats Attenuates Early Brain Injury Resulting from Subarachnoid Hemorrhage by Reducing Oxidative Stress, Inflammation, and Neuronal Apoptosis

Subarachnoid hemorrhage (SAH) is a catastrophic form of stroke responsible for significant morbidity and mortality. Oxidative stress, inflammation, and neuronal apoptosis are important in the pathogenesis of early brain injury (EBI) following SAH. Preconditioning exercise confers neuroprotective effects, mitigating EBI; however, the basis for such protection is unknown. We investigated the effects of preconditioning exercise on brain damage and sensorimotor function after SAH. Male rats were assigned to either a sham-operated (Sham) group, exercise (Ex) group, or no-exercise (No-Ex) group. After a 3-week exercise program, they underwent SAH by endovascular perforation. Consciousness level, neurological score, and sensorimotor function were studied. The expression of nuclear factor erythroid 2 p45-related factor 2 (Nrf2), heme oxygenase 1 (HO-1), 4-hydroxynonenal (4HNE), nitrotyrosine (NT), ionized calcium-binding adaptor molecule 1 (Iba1), tumor necrosis factor alpha (TNF-α), interleukin 6 (IL-6), interleukin 1β (IL-1β), 14-3-3γ, p-β-catenin Ser37, Bax, and caspase-3 were evaluated by immunohistochemistry or western blotting. The terminal deoxynucleotidyl transferase-mediated biotinylated dUTP nick end labeling (TUNEL) assay was also performed. After SAH, the Ex group had significantly reduced neurological deficits, sensorimotor dysfunction, and consciousness disorder compared with the No-Ex group. Nrf2, HO-1, and 14-3-3γ were significantly higher in the Ex group, while 4HNE, NT, Iba1, TNF-α, IL-6, IL-1β, Bax, caspase-3, and TUNEL-positive cells were significantly lower. Our findings suggest that preconditioning exercise ameliorates EBI after SAH. The expression of 4HNE and NT was reduced by Nrf2/HO-1 pathway activation; additionally, both oxidative stress and inflammation were reduced. Furthermore, preconditioning exercise reduced apoptosis, likely via the 14-3-3γ/p-β-catenin Ser37/Bax/caspase-3 pathway.

Quantification of stroke lesion volume using epidural EEG in a cerebral ischaemic rat model

Precise monitoring of the brain after a stroke is essential for clinical decision making. Due to the non-invasive nature and high temporal resolution of electroencephalography (EEG), it is widely used to evaluate real-time cortical activity. In this study, we investigated the stroke-related EEG biomarkers and developed a predictive model for quantifying the structural brain damage in a focal cerebral ischaemic rat model. We enrolled 31 male Sprague-Dawley rats and randomly assigned them to mild stroke, moderate stroke, severe stroke, and control groups. We induced photothrombotic stroke targeting the right auditory cortex. We then acquired EEG signal responses to sound stimuli (frequency linearly increasing from 8 to 12 kHz with 750 ms duration). Power spectral analysis revealed a significant correlation of the relative powers of alpha, theta, delta, delta/alpha ratio, and (delta + theta)/(alpha + beta) ratio with the stroke lesion volume. The auditory evoked potential analysis revealed a significant association of amplitude and latency with stroke lesion volume. Finally, we developed a multiple regression model combining EEG predictors for quantifying the ischaemic lesion (R2 = 0.938, p value < 0.001). These findings demonstrate the potential application of EEG as a valid modality for monitoring the brain after a stroke.

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

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

Neuronal excitability and sensory responsiveness in the thalamo-cortical network in a novel rat model of isoelectric brain state

KEY POINTS

The neuronal and network properties that persist during an isoelectric coma remain largely unknown.  We developed a new in vivo rat model to assess cell excitability and sensory responsiveness in the thalamo-cortical pathway during an isoflurane-induced isoelectric brain state.  The isoelectric electrocorticogram reflected a complete interruption of spontaneous synaptic and firing activities in cortical and thalamic neurons.  Cell excitability and sensory responses in the thalamo-cortical network persisted at a reduced level in the isoelectric condition and returned to control values after resumption of background brain activity.  These findings could lead to a reassessment of the functional status of the drug-induced isoelectric state: a latent state in which individual neurons and networks retain to some extent the ability of being activated by external inputs.

ABSTRACT

The neuronal and network properties that persist in an isoelectric brain completely deprived of spontaneous electrical activity remain largely unexplored. Here, we developed a new in vivo rat model to examine cell excitability and sensory responsiveness in somatosensory thalamo-cortical networks during the interruption of endogenous brain activity induced by high doses of isoflurane. Electrocorticograms (ECoGs) from the barrel cortex were captured simultaneously with either intracellular recordings of subjacent cortical pyramidal neurons or extracellular records of the related thalamo-cortical neurons. Isoelectric ECoG periods reflected the disappearance of spontaneous synaptic and firing activities in cortical and thalamic neurons. This was associated with a sustained membrane hyperpolarization and a reduced intrinsic excitability in deep-layer cortical neurons, without significant changes in their membrane input resistance. Concomitantly, we found that whisker-evoked potentials in the ECoG and synaptic responses in cortical neurons were attenuated in amplitude and increased in latency. Impaired responsiveness in the barrel cortex paralleled with a lowering of the sensory-induced firing in thalamic cells. The return of endogenous brain electrical activities, after reinstatement of a control isoflurane concentration, led to the recovery of cortical neurons excitability and sensory responsiveness. These findings demonstrate the persistence of a certain level of cell excitability and sensory integration in the isoelectric state and the full recovery of cortico-thalamic functions after restoration of internal cerebral activities.

Propofol Affects Cortico-Hippocampal Interactions via β3 Subunit-Containing GABAA Receptors

BACKGROUND

General anesthetics depress neuronal activity. The depression and uncoupling of cortico-hippocampal activity may contribute to anesthetic-induced amnesia. However, the molecular targets involved in this process are not fully characterized. GABA_A receptors, especially the type with β3 subunits, represent a main molecular target of propofol. We therefore hypothesized that GABA_A receptors with β3 subunits mediate the propofol-induced disturbance of cortico-hippocampal interactions.

METHODS

We used local field potential (LFP) recordings from chronically implanted cortical and hippocampal electrodes in wild-type and β3(N265M) knock-in mice. In the β3(N265M) mice, the action of propofol via β3subunit containing GABA_A receptors is strongly attenuated. The analytical approach contained spectral power, phase locking, and mutual information analyses in the 2-16 Hz range to investigate propofol-induced effects on cortico-hippocampal interactions.

RESULTS

Propofol caused a significant increase in spectral power between 14 and 16 Hz in the cortex and hippocampus of wild-type mice. This increase was absent in the β3(N265M) mutant. Propofol strongly decreased phase locking of 6-12 Hz oscillations in wild-type mice. This decrease was attenuated in the β3(N265M) mutant. Finally, propofol reduced the mutual information between 6-16 Hz in wild-type mice, but only between 6 and 8 Hz in the β3(N265M) mutant.

CONCLUSIONS

GABA_A receptors containing β3 subunits contribute to frequency-specific perturbation of cortico-hippocampal interactions. This likely explains some of the amnestic actions of propofol.

Resistance to state transitions in responsiveness is differentially modulated by different volatile anaesthetics in male mice

BACKGROUND

Recent studies point to a fundamental distinction between population-based and individual-based anaesthetic pharmacology. At the population level, anaesthetic potency is defined as the relationship between drug concentration and the likelihood of response to a stimulus. At the individual level, even when the anaesthetic concentration is held constant, fluctuations between the responsive and unresponsive states are observed. Notably, these spontaneous fluctuations exhibit resistance to state transitions R_st. Therefore, the response probability in each individual depends not just upon the drug concentration, but also upon responses to previous stimuli. Here, we hypothesise that R_st is distinct from drug potency and is differentially modulated by different anaesthetics.

METHODS

Adult (14-24 weeks old) C57BL/6J male mice (n=60) were subjected to repeated righting reflex (RR) assays at equipotent steady-state concentrations of isoflurane (0.6 vol%), sevoflurane (1.0 vol%), and halothane (0.4 vol%).

RESULTS

Fluctuations in RR were observed for all tested anaesthetics. Analysis of these fluctuations revealed that R_st was differentially modulated by different anaesthetics (F[2, 56.01]=49.59; P<0.0001). Fluctuations in RR were modelled using a stochastic dynamical system. This analysis confirmed that the amount of noise that drives behavioural state transitions depends on the anaesthetic agent (F[2, 42.86]=16.72; P<0.0001).

CONCLUSIONS

Whilst equipotent doses of distinct anaesthetics produce comparable population response probabilities, they engage dramatically different dynamics in each individual animal. This manifests as a differential aggregate propensity to exhibit state transitions. Thus, resistance to state transitions is a fundamentally distinct, novel measure of individualised anaesthetic pharmacology.

The Science of Transitional States of Consciousness and Euthanasia

The science of transitional states of consciousness is reviewed. Despite intensive study, determining the subjective experience of animals during transitional states of consciousness remains inherently limited. Until better assessment tools become available, behavior-based observations, such as loss of righting reflex/loss of posture, remain among our most useful guides to the onset of unconsciousness in animals. To minimize potential animal suffering and to ensure a truly unconscious state is unambiguously achieved, a state of general anesthesia relying on gamma amino butyric acid type A agonists or N-methyl-d-aspartate antagonist agents continues to be a necessary component of the companion animal euthanasia process.

Cortical functional connectivity indexes arousal state during sleep and anesthesia

Disruption of cortical connectivity likely contributes to loss of consciousness (LOC) during both sleep and general anesthesia, but the degree of overlap in the underlying mechanisms is unclear. Both sleep and anesthesia comprise states of varying levels of arousal and consciousness, including states of largely maintained conscious experience (sleep: N1, REM; anesthesia: sedated but responsive) as well as states of substantially reduced conscious experience (sleep: N2/N3; anesthesia: unresponsive). Here, we tested the hypotheses that (1) cortical connectivity will exhibit clear changes when transitioning into states of reduced consciousness, and (2) these changes will be similar for arousal states of comparable levels of consciousness during sleep and anesthesia. Using intracranial recordings from five adult neurosurgical patients, we compared resting state cortical functional connectivity (as measured by weighted phase lag index, wPLI) in the same subjects across arousal states during natural sleep [wake (WS), N1, N2, N3, REM] and propofol anesthesia [pre-drug wake (WA), sedated/responsive (S), and unresponsive (U)]. Analysis of alpha-band connectivity indicated a transition boundary distinguishing states of maintained and reduced conscious experience in both sleep and anesthesia. In wake states WS and WA, alpha-band wPLI within the temporal lobe was dominant. This pattern was largely unchanged in N1, REM, and S. Transitions into states of reduced consciousness N2, N3, and U were characterized by dramatic changes in connectivity, with dominant connections shifting to prefrontal cortex. Secondary analyses indicated similarities in reorganization of cortical connectivity in sleep and anesthesia. Shifts from temporal to frontal cortical connectivity may reflect impaired sensory processing in states of reduced consciousness. The data indicate that functional connectivity can serve as a biomarker of arousal state and suggest common mechanisms of LOC in sleep and anesthesia.

Arousal-induced cortical activity triggers lactate release from astrocytes

It has been suggested that, in states of arousal, release of noradrenaline and β-adrenergic signalling affect long-term memory formation by stimulating astrocytic lactate production from glycogen. However, the temporal relationship between cortical activity and cellular lactate fluctuations upon changes in arousal remains to be fully established. Also, the role of β-adrenergic signalling and brain glycogen metabolism on neural lactate dynamics in vivo is still unknown. Here, we show that an arousal-induced increase in cortical activity triggers lactate release into the extracellular space, and this correlates with a fast and prominent lactate dip in astrocytes. The immediate drop in astrocytic lactate concentration and the parallel increase in extracellular lactate levels underline an activity-dependent lactate release from astrocytes. Moreover, when β-adrenergic signalling is blocked or the brain is depleted of glycogen, the arousal-evoked cellular lactate surges are significantly reduced. We provide in vivo evidence that cortical activation upon arousal triggers lactate release from astrocytes, a rise in intracellular lactate levels mediated by β-adrenergic signalling and the mobilization of lactate from glycogen stores.

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

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

Anesthetics Have Different Effects on the Electrocorticographic Spectra of Wild-type and Mitochondrial Mutant Mice

WHAT WE ALREADY KNOW ABOUT THIS TOPIC

WHAT THIS ARTICLE TELLS US THAT IS NEW: BACKGROUND:: Knockout of the mitochondrial protein Ndufs4 (Ndufs4[KO]) in mice causes hypersensitivity to volatile anesthetics but resistance to ketamine. The authors hypothesized that electrocorticographic changes underlying the responses of Ndufs4(KO) to volatile anesthetics and to ketamine would be similar in mutant and control mice.

METHODS

Electrocorticographic recordings at equipotent volatile anesthetic concentrations were compared between genotypes. In separate studies, control and cell type-specific Ndufs4(KO) mice were anesthetized with intraperitoneal ketamine to determine their ED50s.

RESULTS

Ndufs4 (KO) did not differ from controls in baseline electrocorticography (N = 5). Compared to baseline, controls exposed to isoflurane (EC50) lost power (expressed as mean baseline [µV/Hz]; mean isoflurane [µV/Hz]) in delta (2.45; 0.50), theta (1.41; 0.16), alpha (0.23; 0.05), beta (0.066; 0.016), and gamma (0.020; 0.005) frequency bands (N = 5). Compared to baseline, at their isoflurane EC50, Ndufs4(KO) maintained power in delta (1.08; 1.38), theta (0.36; 0.26), and alpha (0.09; 0.069) frequency bands but decreased in beta (0.041; 0.023) and gamma (0.020; 0.0068) frequency bands (N = 5). Similar results were seen for both genotypes in halothane. Vesicular glutamate transporter 2 (VGLUT2)-specific Ndufs4(KO) mice were markedly resistant to ketamine (ED50; 125 mg/kg) compared to control mice (ED50; 75 mg/kg; N = 6). At their respective ED95s for ketamine, mutant (N = 5) electrocorticography spectra showed a decrease in power in the beta (0.040; 0.020) and gamma (0.035; 0.015) frequency bands not seen in controls (N = 7).

CONCLUSIONS

Significant differences exist between the electrocorticographies of mutant and control mice at equipotent doses for volatile anesthetics and ketamine. The energetic state specifically of excitatory neurons determines the behavioral response to ketamine.

Single-trial classification of awareness state during anesthesia by measuring critical dynamics of global brain activity

In daily life, in the operating room and in the laboratory, the operational way to assess wakefulness and consciousness is through responsiveness. A number of studies suggest that the awake, conscious state is not the default behavior of an assembly of neurons, but rather a very special state of activity that has to be actively maintained and curated to support its functional properties. Thus responsiveness is a feature that requires active maintenance, such as a homeostatic mechanism to balance excitation and inhibition. In this work we developed a method for monitoring such maintenance processes, focusing on a specific signature of their behavior derived from the theory of dynamical systems: stability analysis of dynamical modes. When such mechanisms are at work, their modes of activity are at marginal stability, neither damped (stable) nor exponentially growing (unstable) but rather hovering in between. We have previously shown that, conversely, under induction of anesthesia those modes become more stable and thus less responsive, then reversed upon emergence to wakefulness. We take advantage of this effect to build a single-trial classifier which detects whether a subject is awake or unconscious achieving high performance. We show that our approach can be developed into a means for intra-operative monitoring of the depth of anesthesia, an application of fundamental importance to modern clinical practice.

Calculations of consciousness: electroencephalography analyses to determine anesthetic depth

PURPOSE OF REVIEW

Electroencephalography (EEG) was introduced into anesthesia practice in the 1990s as a tool to titrate anesthetic depth. However, limitations in current analysis techniques have called into question whether these techniques improve standard of care, or instead call for improved, more ubiquitously applicable measures to assess anesthetic transitions and depth. This review highlights emerging analytical approaches and techniques from neuroscience research that have the potential to better capture anesthetic transitions to provide better measurements of anesthetic depth.

RECENT FINDINGS

Since the introduction of electroencephalography, neuroscientists, engineers, mathematicians, and clinicians have all been developing new ways of analyzing continuous electrical signals. Collaborations between these fields have proliferated several analytical techniques that demonstrate how anesthetics affect brain dynamics and conscious transitions. Here, we review techniques in the following categories: network science, integration and information, nonlinear dynamics, and artificial intelligence.

SUMMARY

Up-and-coming techniques have the potential to better clinically define and characterize altered consciousness time points. Such new techniques used alongside traditional measures have the potential to improve depth of anesthesia measurements and enhance an understanding of how the brain is affected by anesthetic agents. However, new measures will be needed to be tested for robustness in real-world environments and on diverse experimental protocols.

Do Complexity Measures of Frontal EEG Distinguish Loss of Consciousness in Geriatric Patients Under Anesthesia?

While geriatric patients have a high likelihood of requiring anesthesia, they carry an increased risk for adverse cognitive outcomes from its use. Previous work suggests this could be mitigated by better intraoperative monitoring using indexes defined by several processed electroencephalogram (EEG) measures. Unfortunately, inconsistencies between patients and anesthetic agents in current analysis techniques have limited the adoption of EEG as standard of care. In attempts to identify new analyses that discriminate clinically-relevant anesthesia timepoints, we tested 1/f frequency scaling as well as measures of complexity from nonlinear dynamics. Specifically, we tested whether analyses that characterize time-delayed embeddings, correlation dimension (CD), phase-space geometric analysis, and multiscale entropy (MSE) capture loss-of-consciousness changes in EEG activity. We performed these analyses on EEG activity collected from a traditionally hard-to-monitor patient population: geriatric patients on beta-adrenergic blockade who were anesthetized using a combination of fentanyl and propofol. We compared these analyses to traditional frequency-derived measures to test how well they discriminated EEG states before and after loss of response to verbal stimuli. We found spectral changes similar to those reported previously during loss of response. We also found significant changes in 1/f frequency scaling. Additionally, we found that our phase-space geometric characterization of time-delayed embeddings showed significant differences before and after loss of response, as did measures of MSE. Our results suggest that our new spectral and complexity measures are capable of capturing subtle differences in EEG activity with anesthesia administration-differences which future work may reveal to improve geriatric patient monitoring.

Dexmedetomidine and propofol sedation requirements in an autistic rat model

Background

Autism is a challenging neurodevelopmental disorder. Previous clinical observations have suggested altered sedation requirements for children with autism. Our study aimed to test this observation experimentally in an animal model and to explore its possible mechanisms.

Methods

Eight adult pregnant female Sprague-Dawley rats were randomly divided into two groups. Four were injected with intraperitoneal sodium valproate on gestational day 12 and four were injected with normal saline. On postnatal day 28, the newborn male rats were subjected to the open-field test to confirm autistic features. Each rat was injected intraperitoneally with a single dose of propofol (50 mg/kg) or dexmedetomidine (0.2 mg/kg). The times to loss of righting reflex (LORR) and to return of righting reflex (RORR) were recorded. On the following day, all rats were re-sedated and underwent electroencephalography (EEG). Thereafter, the rats were euthanized and their hippocampal gamma-aminobutyric acid type A (GABA_A) and glutamate N-methyl-D-aspartate (NMDA) receptor gene expressions were assessed.

Results

Autistic rats showed significantly longer LORR times and shorter RORR times than did the controls (median LORR times: 12.0 versus 5.0 min for dexmedetomidine and 22.0 versus 8.0 min for propofol; P < 0.05). EEG showed a low-frequency, high-amplitude wave pattern 2 min after LORR in the control rats. Autistic rats showed a high-frequency, low-amplitude awake pattern. Hippocampal GABA_A receptor gene expression was significantly lower and NMDA gene expression was greater in autistic rats.

Conclusions

This study supports the clinical observations of increased anesthetic sedative requirements in children with autism and our biochemical analyses using GABA_A and glutamate receptor gene expression highlight possible underlying mechanisms.

Remifentanil and Nitrous Oxide Anesthesia Produces a Unique Pattern of EEG Activity During Loss and Recovery of Response

Nitrous oxide (N₂O) and remifentanil (remi) are used along with other anesthetic and adjuvant agents for routine surgical anesthesia, yet the electroencephalogram (EEG) changes produced by this combination are poorly described. N₂O administered alone produces EEG spectral characteristics that are distinct from most hypnotics. Furthermore, EEG frequency-derived trends before and after clinically relevant time points vary depending on N₂O concentration. Remifentanil typically increases low frequency and decreases high frequency activity in the EEG, but how it influences N₂O's EEG effect is not known. Previous attempts to characterize EEG signals of patients anesthetized with N₂O using frequency-derived measures have shown conflicts and inconsistencies. Thus, in addition to determining the spectral characteristics of this unique combination, we also test whether a newly proposed characterization of time-delayed embeddings of the EEG signal tracks loss and recovery of consciousness significantly at clinically relevant time points. We retrospectively investigated the effects of remi and N₂O on EEG signals recorded from 32 surgical patients receiving anesthesia for elective abdominal surgeries. Remifentanil and N₂O (66%) were co-administered during the procedures. Patients were tested for loss and recovery of response (ROR) to verbal stimuli after induction and upon cessation of anesthesia, respectively. We found that the addition of remifentanil to N₂O anesthesia improves the ability of traditional frequency-derived measures, including the Bispectral Index (BIS), to discriminate between loss and ROR. Finally, we found that a novel analysis of EEG using nonlinear dynamics showed more significant differences between states than most spectral measures.

Regional knockdown of NDUFS4 implicates a thalamocortical circuit mediating anesthetic sensitivity

Knockout of the mitochondrial complex I protein, NDUFS4, profoundly increases sensitivity of mice to volatile anesthetics. In mice carrying an Ndufs4lox/lox gene, adeno-associated virus expressing Cre recombinase was injected into regions of the brain postulated to affect sensitivity to volatile anesthetics. These injections generated otherwise phenotypically wild type mice with region-specific, postnatal inactivation of Ndufs4, minimizing developmental effects of gene loss. Sensitivities to the volatile anesthetics isoflurane and halothane were measured using loss of righting reflex (LORR) and movement in response to tail clamp (TC) as endpoints. Knockdown (KD) of Ndufs4 in the vestibular nucleus produced resistance to both anesthetics for movement in response to TC. Ndufs4 loss in the central and dorsal medial thalami and in the parietal association cortex increased anesthetic sensitivity to both TC and LORR. Knockdown of Ndufs4 only in the parietal association cortex produced striking hypersensitivity for both endpoints, and accounted for half the total change seen in the global KO (Ndufs4(KO)). Excitatory synaptic transmission in the parietal association cortex in slices from Ndufs4(KO) animals was hypersensitive to isoflurane compared to control slices. We identified a direct neural circuit between the parietal association cortex and the central thalamus, consistent with a model in which isoflurane sensitivity is mediated by a thalamic signal relayed through excitatory synapses to the parietal association cortex. We postulate that the thalamocortical circuit is crucial for maintenance of consciousness and is disrupted by the inhibitory effects of isoflurane/halothane on mitochondria.

Cocaine Exposure Enhances the Activity of Ventral Tegmental Area Dopamine Neurons via Calcium-Impermeable NMDARs

Potentiation of excitatory inputs onto dopamine neurons of the ventral tegmental area (VTA) induced by cocaine exposure allows remodeling of the mesocorticolimbic circuitry, which ultimately drives drug-adaptive behavior. This potentiation is mediated by changes in NMDAR and AMPAR subunit composition. It remains unknown how this synaptic plasticity affects the activity of dopamine neurons. Here, using rodents, we demonstrate that a single cocaine injection increases the firing rate and bursting activity of VTA dopamine neurons, and that these increases persist for 7 d. This enhanced activity depends on the insertion of low-conductance, Ca²⁺-impermeable NMDARs that contain GluN3A. Since such receptors are not capable of activating small-conductance potassium channels, the intrinsic excitability of VTA dopamine neurons increases. Activation of group I mGluRs rescues synaptic plasticity and restores small-conductance calcium-dependent potassium channel function, normalizing the firing activity of dopamine neurons. Our study characterizes a mechanism linking drug-evoked synaptic plasticity to neural activity, revealing novel targets for therapeutic interventions.

SIGNIFICANCE STATEMENT

We show that cocaine-evoked synaptic changes onto ventral tegmental area (VTA) dopamine (DA) neurons leads to long-lasting increases in their burst firing. This increase is due to impaired function of Ca²⁺-activated small-conductance calcium-dependent potassium (SK) channels; SK channels regulate firing of VTA DA neurons, but this regulation was absent after cocaine. Cocaine exposure drives the insertion of GluN3A-containing NMDARs onto VTA DA neurons. These receptors are Ca²⁺-impermeable, and thus SK channels are not efficiently activated by synaptic activity. In GluN3A knock-out mice, cocaine did not alter SK channel function or VTA DA neuron firing. This study directly links synaptic changes to increased intrinsic excitability of VTA DA neurons after cocaine, and explains how acute cocaine induces long-lasting remodeling of the mesolimbic DA system.

Global reduction of information exchange during anesthetic-induced unconsciousness

During anesthetic-induced unconsciousness (AIU), the brain undergoes a dramatic change in its capacity to exchange information between regions. However, the spatial distribution of information exchange loss/gain across the entire brain remains elusive. In the present study, we acquired and analyzed resting-state functional magnetic resonance imaging (rsfMRI) data in rats during wakefulness and graded levels of consciousness induced by incrementally increasing the concentration of isoflurane. We found that, regardless of spatial scale, the functional connectivity (FC) change (i.e., ∆FC) was proportionally dependent on the FC strength at the awake state across all connections. This dependency became stronger at higher doses of isoflurane. In addition, the relative FC change at each anesthetized condition (i.e., ∆FC normalized to the corresponding FC strength at the awake state) was exclusively negative across the whole brain, indicating a global loss of meaningful information exchange between brain regions during AIU. To further support this notion, we showed that during unconsciousness, the entropy of rsfMRI signal increased to a value comparable to random noise while the mutual information decreased appreciably. Importantly, consistent results were obtained when unconsciousness was induced by dexmedetomidine, an anesthetic agent with a distinct molecular action than isoflurane. This result indicates that the observed global reduction in information exchange may be agent invariant. Taken together, these findings provide compelling neuroimaging evidence suggesting that the brain undergoes a widespread disruption in the exchange of meaningful information during AIU and that this phenomenon may represent a common system-level neural mechanism of AIU.

Midbrain dopaminergic neuron activity across alternating brain states of urethane anaesthetized rat

Midbrain dopaminergic neurons are implicated in the control of motor functions and reward-driven behaviours. The function of this neuronal population is strongly connected with distinct patterns of firing - irregular or bursting, which either maintains basal levels of dopamine (DA) or leads to phasic release, respectively. Heterogeneity of dopaminergic neurons, observed on both structural and functional levels, is also reflected in different responses of DA neurons to changes in global brain states. Preparation of urethane anaesthetized animal is a broadly used model to study brain state dependent activity of neurons. Unfortunately activity of midbrain DA neurons across urethane induced cyclic, spontaneous brain state alternations is poorly described. To fulfil this gap in our knowledge we have performed simultaneous, extracellular recordings of the firing of single putative DA neurons combined with continuous brain state monitoring. We found that during slow wave activity, the firing rate of recorded putative DA neurons was significantly higher compared to firing rates during activated state, both in ventral tegmental area (VTA) and substantia nigra pars compacta (SNc). In the presence of cortical slow waves, putative dopaminergic neurons also intensified bursting activity, but the magnitude of this phenomena differed in respect to the examined region (VTA or SNc). Our results show that activity of DA neurons under urethane anaesthesia is brain-state dependent and emphasize the importance of brain state monitoring during electrophysiological experiments.

Dynamic Connectivity Patterns in Conscious and Unconscious Brain

Brain functional connectivity undergoes dynamic changes from the awake to unconscious states. However, how the dynamics of functional connectivity patterns are linked to consciousness at the behavioral level remains elusive. In this study, we acquired resting-state functional magnetic resonance imaging data during wakefulness and graded levels of consciousness in rats. Data were analyzed using a dynamic approach combining the sliding window method and k-means clustering. Our results demonstrate that whole-brain networks contained several quasi-stable patterns that dynamically recurred from the awake state into anesthetized states. Remarkably, two brain connectivity states with distinct spatial similarity to the structure of anatomical connectivity were strongly biased toward high and low consciousness levels, respectively. These results provide compelling neuroimaging evidence linking the dynamics of whole-brain functional connectivity patterns and states of consciousness at the behavioral level.

The Development of Nociceptive Network Activity in the Somatosensory Cortex of Freely Moving Rat Pups

Cortical perception of noxious stimulation is an essential component of pain experience but it is not known how cortical nociceptive activity emerges during brain development. Here we use continuous telemetric electrocorticogram (ECoG) recording from the primary somatosensory cortex (S1) of awake active rat pups to map functional nociceptive processing in the developing brain over the first 4 weeks of life. Cross-sectional and longitudinal recordings show that baseline S1 ECoG energy increases steadily with age, with a distinctive beta component replaced by a distinctive theta component in week 3. Event-related potentials were evoked by brief noxious hindpaw skin stimulation at all ages tested, confirming the presence of functional nociceptive spinothalamic inputs in S1. However, hindpaw incision, which increases pain sensitivity at all ages, did not increase S1 ECoG energy until week 3. A significant increase in gamma (20–50 Hz) energy occurred in the presence of skin incision at week 3 accompanied by a longer-lasting increase in theta (4–8 Hz) energy at week 4. Continuous ECoG recording demonstrates specific postnatal functional stages in the maturation of S1 cortical nociception. Somatosensory cortical coding of an ongoing pain “state” in awake rat pups becomes apparent between 2 and 4 weeks of age.

Physiologic Measures of Animal Stress during Transitional States of Consciousness

Determination of the humaneness of methods used to produce unconsciousness in animals, whether for anesthesia, euthanasia, humane slaughter, or depopulation, relies on our ability to assess stress, pain, and consciousness within the contexts of method and application. Determining the subjective experience of animals during transitional states of consciousness, however, can be quite difficult; further, loss of consciousness with different agents or methods may occur at substantially different rates. Stress and distress may manifest behaviorally (e.g., overt escape behaviors, approach-avoidance preferences [aversion]) or physiologically (e.g., movement, vocalization, changes in electroencephalographic activity, heart rate, sympathetic nervous system [SNS] activity, hypothalamic-pituitary axis [HPA] activity), such that a one-size-fits-all approach cannot be easily applied to evaluate methods or determine specific species applications. The purpose of this review is to discuss methods of evaluating stress in animals using physiologic methods, with emphasis on the transition between the conscious and unconscious states.

Tuning pathological brain oscillations with neurofeedback: a systems neuroscience framework

Neurofeedback (NFB) is emerging as a promising technique that enables self-regulation of ongoing brain oscillations. However, despite a rise in empirical evidence attesting to its clinical benefits, a solid theoretical basis is still lacking on the manner in which NFB is able to achieve these outcomes. The present work attempts to bring together various concepts from neurobiology, engineering, and dynamical systems so as to propose a contemporary theoretical framework for the mechanistic effects of NFB. The objective is to provide a firmly neurophysiological account of NFB, which goes beyond traditional behaviorist interpretations that attempt to explain psychological processes solely from a descriptive standpoint whilst treating the brain as a “black box”. To this end, we interlink evidence from experimental findings that encompass a broad range of intrinsic brain phenomena: starting from “bottom-up” mechanisms of neural synchronization, followed by “top-down” regulation of internal brain states, moving to dynamical systems plus control-theoretic principles, and concluding with activity-dependent as well as homeostatic forms of brain plasticity. In support of our framework, we examine the effects of NFB in several brain disorders, including attention-deficit hyperactivity (ADHD) and post-traumatic stress disorder (PTSD). In sum, it is argued that pathological oscillations emerge from an abnormal formation of brain-state attractor landscape(s). The central thesis put forward is that NFB tunes brain oscillations toward a homeostatic set-point which affords an optimal balance between network flexibility and stability (i.e., self-organised criticality (SOC)).