Recent studies of propofol-induced unconsciousness have identified characteristic properties of electroencephalographic alpha rhythms that may be mediated by drug activity at ?-aminobutyric acid (GABA) receptors in the thalamus. However, the effect of ketamine (a primarily non-GABAergic anesthetic drug) on alpha oscillations has not been systematically evaluated. We analyzed the electroencephalogram of 28 surgical patients during consciousness and ketamine-induced unconsciousness with a focus on frontal power, frontal cross-frequency coupling, frontal-parietal functional connectivity (measured by coherence and phase lag index), and frontal-to-parietal directional connectivity (measured by directed phase lag index) in the alpha bandwidth. Unlike past studies of propofol, ketamine-induced unconsciousness was not associated with increases in the power of frontal alpha rhythms, characteristic cross-frequency coupling patterns of frontal alpha power and slow-oscillation phase, or decreases in coherence in the alpha bandwidth. Like past studies of propofol using undirected and directed phase lag index, ketamine reduced frontal-parietal (functional) and frontal-to-parietal (directional) connectivity in the alpha bandwidth. These results suggest that directional connectivity changes in the alpha bandwidth may be state-related markers of unconsciousness induced by both GABAergic and non-GABAergic anesthetics.
General anesthesia induces unconsciousness along with functional changes in brain networks. Considering the essential role of hub structures for efficient information transmission, the authors hypothesized that anesthetics have an effect on the hub structure of functional brain networks.
The brain is assumed to be hypoactive during cardiac arrest. However, the neurophysiological state of the brain immediately following cardiac arrest has not been systematically investigated. In this study, we performed continuous electroencephalography in rats undergoing experimental cardiac arrest and analyzed changes in power density, coherence, directed connectivity, and cross-frequency coupling. We identified a transient surge of synchronous gamma oscillations that occurred within the first 30 s after cardiac arrest and preceded isoelectric electroencephalogram. Gamma oscillations during cardiac arrest were global and highly coherent; moreover, this frequency band exhibited a striking increase in anterior-posterior-directed connectivity and tight phase-coupling to both theta and alpha waves. High-frequency neurophysiological activity in the near-death state exceeded levels found during the conscious waking state. These data demonstrate that the mammalian brain can, albeit paradoxically, generate neural correlates of heightened conscious processing at near-death.
Directional connectivity from anterior to posterior brain regions (or "feedback" connectivity) has been shown to be inhibited by propofol and sevoflurane. In this study the authors tested the hypothesis that ketamine would also inhibit cortical feedback connectivity in frontoparietal networks.
Amyotrophic lateral sclerosis (ALS) is a disorder associated primarily with the degeneration of the motor system. More recently, functional connectivity studies have demonstrated potentially adaptive changes in ALS brain organization, but disease-related changes in cortical communication remain unknown. We recruited individuals with ALS and age-matched controls to operate a brain-computer interface while electroencephalography was recorded over three sessions. Using normalized symbolic transfer entropy, we measured directed functional connectivity from frontal to parietal (feedback connectivity) and parietal to frontal (feedforward connectivity) regions. Feedback connectivity was not significantly different between groups, but feedforward connectivity was significantly higher in individuals with ALS. This result was consistent across a broad electroencephalographic spectrum (4-35 Hz), and in theta, alpha and beta frequency bands. Feedback connectivity has been associated with conscious state and was found to be independent of ALS symptom severity in this study, which may have significant implications for the detection of consciousness in individuals with advanced ALS. We suggest that increases in feedforward connectivity represent a compensatory response to the ALS-related loss of input such that sensory stimuli have sufficient strength to cross the threshold necessary for conscious processing in the global neuronal workspace.
General anesthesia significantly alters brain network connectivity. Graph-theoretical analysis has been used extensively to study static brain networks but may be limited in the study of rapidly changing brain connectivity during induction of or recovery from general anesthesia. Here we introduce a novel method to study the temporal evolution of network modules in the brain. We recorded multichannel electroencephalograms (EEG) from 18 surgical patients who underwent general anesthesia with either propofol (n?=?9) or sevoflurane (n?=?9). Time series data were used to reconstruct networks; each electroencephalographic channel was defined as a node and correlated activity between the channels was defined as a link. We analyzed the frequency of subgraphs in the network with a defined number of links; subgraphs with a high probability of occurrence were deemed network "backbones." We analyzed the behavior of network backbones across consciousness, anesthetic induction, anesthetic maintenance, and two points of recovery. Constitutive, variable and state-specific backbones were identified across anesthetic state transitions. Brain networks derived from neurophysiologic data can be deconstructed into network backbones that change rapidly across states of consciousness. This technique enabled a granular description of network evolution over time. The concept of network backbones may facilitate graph-theoretical analysis of dynamically changing networks.
The precise mechanism and optimal measure of anesthetic-induced unconsciousness has yet to be elucidated. Preferential inhibition of feedback connectivity from frontal to parietal brain networks is one potential neurophysiologic correlate, but has only been demonstrated in animals or under limited conditions in healthy volunteers.
It is still unknown whether anesthetic state transitions are continuous or binary. Mathematical graph theory is one method by which to assess whether brain networks change gradually or abruptly upon anesthetic induction and emergence.
Loss of consciousness is an essential feature of general anesthesia. Although alterations of neural networks during anesthesia have been identified in the spatial domain, there has been relatively little study of temporal organization.
Sleep and general anesthesia are distinct states of consciousness that share many traits. Prior studies suggest that propofol anesthesia facilitates recovery from rapid eye movement (REM) and non-REM (NREM) sleep deprivation, but the effects of inhaled anesthetics have not yet been studied. We tested the hypothesis that isoflurane anesthesia would also facilitate recovery from REM sleep deprivation.
Previous work employing graph theory and nonlinear analysis has found increased spatial and temporal disorder, respectively, of functional brain connectivity in schizophrenia. We present a new method combining graph theory and nonlinear techniques that measures the temporal disorder of functional brain connections. Multichannel electroencephalographic data were windowed and functional networks were reconstructed using the minimum spanning trees of correlation matrices. Using a method based on Shannon entropy, we found elevated connection entropy in gamma activity of patients with schizophrenia; however, gamma connection entropy remained elevated in patients with schizophrenia even after a reduction in symptoms due to treatment with antipsychotics. Our results are consistent with several possibilities: (1) aberrant functional connectivity is epiphenomenal to schizophrenia, (2) aberrant functional connectivity is a central feature but antipsychotics reduce symptoms by an independent mechanism, or (3) connection entropy is not an appropriately sensitive measure of brain abnormalities in schizophrenia.
The cognitive unbinding paradigm suggests that the synthesis of neural information is attenuated by general anesthesia. Here, we analyzed the functional organization of brain activities in the conscious and anesthetized states, based on functional segregation and integration. Electroencephalography (EEG) recordings were obtained from 14 subjects undergoing induction of general anesthesia with propofol. We quantified changes in mean information integration capacity in each band of the EEG. After induction with propofol, mean information integration capacity was reduced most prominently in the gamma band of the EEG (p=.0001). Furthermore, we demonstrate that loss of consciousness is reflected by the breakdown of the spatiotemporal organization of gamma waves. We conclude that induction of general anesthesia with propofol reduces the capacity for information integration in the brain. These data directly support the information integration theory of consciousness and the cognitive unbinding paradigm of general anesthesia.
Frontoparietal connectivity has been suggested to be important in conscious processing and its interruption is thought to be one mechanism of general anesthesia. Data in animals demonstrate that feedforward processing of information may persist during the anesthetized state, while feedback processing is inhibited. We investigated the directionality and functional organization of frontoparietal connectivity in 10 human subjects anesthetized with propofol on two separate occasions. Multichannel electroencephalography and a computational method of assessing directed functional connectivity were employed. We demonstrate that directed feedback connectivity is diminished with loss of consciousness and returns with responsiveness to verbal command. We also applied the Dendrogram classification method to assess the global organization of directed functional connectivity during consciousness and anesthesia. We demonstrate a state-specific hierarchy and subject-specific subhierarchy in functional organization. These data support the hypothesis that specific states of human consciousness are defined by specific states of frontoparietal connectivity.
Spectral content in a physiological dataset of finite size has the potential to produce spurious measures of coherence. This is especially true for electroencephalography (EEG) during general anesthesia because of the significant alteration of the power spectrum. In this study we quantitatively evaluated the genuine and spurious phase synchronization strength (PSS) of EEG during consciousness, general anesthesia, and recovery. A computational approach based on the randomized data method was used for evaluating genuine and spurious PSS. The validity of the method was tested with a simulated dataset. We applied this method to the EEG of normal subjects undergoing general anesthesia and investigated the finite size effects of EEG references, data length and spectral content on phase synchronization. The most influential factor for genuine PSS was the type of EEG reference; the most influential factor for spurious PSS was the spectral content. Genuine and spurious PSS showed characteristic temporal patterns for each frequency band across consciousness and anesthesia. Simultaneous measurement of both genuine and spurious PSS during general anesthesia is necessary in order to avoid incorrect interpretations regarding states of consciousness.
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