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Delirium is a major public health issue associated with considerable morbidity and mortality, particularly after surgery. While the neurobiology of delirium remains incompletely understood, emerging evidence suggests that cognition... more
Delirium is a major public health issue associated with considerable morbidity and mortality, particularly after surgery. While the neurobiology of delirium remains incompletely understood, emerging evidence suggests that cognition requires close proximity to a system state called criticality, which reflects a point of dynamic instability that allows for flexible access to a wide range of brain states. Deviations from criticality are associated with neurocognitive disorders, though the relationship between criticality and delirium has not been formally tested. This study tested the primary hypothesis that delirium in the postanesthesia care unit would be associated with deviations from criticality, based on surrogate electroencephalographic measures. As a secondary objective, the impact of caffeine was also tested on delirium incidence and criticality. To address these aims, we conducted a secondary analysis of a randomized clinical trial that tested the effects of intraoperative ca...
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Fibromyalgia (FM) is a chronic pain condition that is characterized by hypersensitivity to multi-modal sensory stimuli, widespread pain, and fatigue. We have previously proposed explosive synchronization (ES), a phenomenon wherein a small... more
Fibromyalgia (FM) is a chronic pain condition that is characterized by hypersensitivity to multi-modal sensory stimuli, widespread pain, and fatigue. We have previously proposed explosive synchronization (ES), a phenomenon wherein a small perturbation to a network can lead to an abrupt state transition, as a potential mechanism of the hypersensitive FM brain. Therefore, we hypothesized that converting a brain network from ES to general synchronization (GS) may reduce the hypersensitivity of FM brain. To find an effective brain network modulation to convert ES into GS, we constructed a large-scale brain network model near criticality (i.e., an optimally balanced state between order and disorders), which reflects brain dynamics in conscious wakefulness, and adjusted two parameters: local structural connectivity and signal randomness of target brain regions. The network sensitivity to global stimuli was compared between the brain networks before and after the modulation. We found that ...
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Despite the use of shamanism as a healing practice for several millennia, few empirical studies of the shamanic state of consciousness exist. We investigated the neural correlates of shamanic trance using high-density... more
Despite the use of shamanism as a healing practice for several millennia, few empirical studies of the shamanic state of consciousness exist. We investigated the neural correlates of shamanic trance using high-density electroencephalography (EEG) in 24 shamanic practitioners and 24 healthy controls during rest, shamanic drumming, and classical music listening, followed by a validated assessment of altered states of consciousness. EEG data were used to assess changes in absolute power, connectivity, signal diversity, and criticality, which were correlated with assessment measures. We also compared assessment scores to those of individuals in a previous study under the influence of psychedelics. Shamanic practitioners were significantly different from controls in several domains of altered states of consciousness, with scores comparable to or exceeding that of healthy volunteers under the influence of psychedelics. Practitioners also displayed increased gamma power during drumming tha...
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Continuous switching between internal and external modes in the brain is a key process of constructing inner models of the outside world. However, how the brain continuously switches between two modes remains elusive. Here, we propose... more
Continuous switching between internal and external modes in the brain is a key process of constructing inner models of the outside world. However, how the brain continuously switches between two modes remains elusive. Here, we propose that a large synchronization fluctuation of the brain network emerging only near criticality (i.e., a balanced state between order and disorder) spontaneously creates temporal windows with distinct preferences for integrating internal information of the network and external stimuli. Using a computational model and empirical data analysis during alterations of consciousness in human, we present that synchronized and incoherent networks respectively bias toward internal and external information with specific network configurations. The network preferences are the most prominent in conscious states; however, they disrupt in altered states of consciousness. We suggest that criticality produces a functional platform of the brain’s capability for continuous ...
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Integrated information theory (IIT) postulates that consciousness arises from the cause-effect structure of a system but the optimal network conditions for this structure have not been elucidated. In the study, we test the hypothesis that... more
Integrated information theory (IIT) postulates that consciousness arises from the cause-effect structure of a system but the optimal network conditions for this structure have not been elucidated. In the study, we test the hypothesis that network criticality, a dynamically balanced state between a large variation of functional network configurations and a large constraint of structural network configurations, is a necessary condition for the emergence of a cause-effect structure that results in a large Φ, a surrogate of integrated information. We also hypothesized that if the brain deviates from criticality, the cause-effect structure is obscured and Φ diminishes. We tested these hypotheses with a large-scale brain network model and high-density electroencephalography (EEG) acquired during various levels of human consciousness during general anesthesia. In the modeling study, maximal criticality coincided with maximal Φ. The constraint of the structural network on the functional net...
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As pointed out by William James, "the consciousness is a dynamic process, not a thing" , during which short term integration is succeeded by another differentiated neural state through the continual interplay between the... more
As pointed out by William James, "the consciousness is a dynamic process, not a thing" , during which short term integration is succeeded by another differentiated neural state through the continual interplay between the environment, the body, and the brain itself. Thus, the dynamic structure underlying successive states of the brain is important for understanding human consciousness as a process. In order to investigate the dynamic property of human consciousness, we developed a new method to reconstruct a state space from electroencephalogram(EEG), in which a trajectory, reflecting states of consciousness, is constructed based on the global information integration of the brain. EEGs were obtained from 14 subjects received an intravenous bolus of propopol. Here we show that the degree of human consciousness is directly associated with the information integration capacity of gamma wave, which is significantly higher in the conscious state than in the unconscious state. And...
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Brain networks during unconscious states resulting from sleep, anesthesia, or traumatic injuries are associated with a limited capacity for complex responses to stimulation. Even during the conscious resting state, responsiveness to... more
Brain networks during unconscious states resulting from sleep, anesthesia, or traumatic injuries are associated with a limited capacity for complex responses to stimulation. Even during the conscious resting state, responsiveness to stimulus is highly dependent on spontaneous brain activities. Many empirical findings have been suggested that the brain responsiveness is determined mainly by the ongoing brain activity when a stimulus is given. However, there has been no systematic study exploring how such various brain activities with high or low synchronization, amplitude, and phase response to stimuli. In this model study, we simulated large-scale brain network dynamics in three brain states (below, near, and above the critical state) and investigated a relationship between ongoing oscillation properties and a stimulus decomposing the brain activity into fundamental oscillation properties (instantaneous global synchronization, amplitude, and phase). We identified specific stimulatio...
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The heterogeneity of molecular mechanisms, target neural circuits, and neurophysiologic effects of general anesthetics makes it difficult to develop a reliable and drug-invariant index of general anesthesia. No single brain region or... more
The heterogeneity of molecular mechanisms, target neural circuits, and neurophysiologic effects of general anesthetics makes it difficult to develop a reliable and drug-invariant index of general anesthesia. No single brain region or mechanism has been identified as the neural correlate of consciousness, suggesting that consciousness might emerge through complex interactions of spatially and temporally distributed brain functions. The goal of this review article is to introduce the basic concepts of networks and explain why the application of network science to general anesthesia could be a pathway to discover a fundamental mechanism of anesthetic-induced unconsciousness. This article reviews data suggesting that reduced network efficiency, constrained network repertoires, and changes in cortical dynamics create inhospitable conditions for information processing and transfer, which lead to unconsciousness. This review proposes that network science is not just a useful tool but a nec...
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Fibromyalgia (FM) is a chronic widespread pain condition characterized by augmented multi-modal sensory sensitivity. Although the mechanisms underlying this sensitivity are thought to involve an imbalance in excitatory and inhibitory... more
Fibromyalgia (FM) is a chronic widespread pain condition characterized by augmented multi-modal sensory sensitivity. Although the mechanisms underlying this sensitivity are thought to involve an imbalance in excitatory and inhibitory activity throughout the brain, the underlying neural network properties associated with hypersensitivity to pain stimuli are largely unknown. In network science, explosive synchronization (ES) was introduced as a mechanism of hypersensitivity in diverse biological and physical systems that display explosive and global propagations with small perturbations. We hypothesized that ES may also be a mechanism of the hypersensitivity in FM brains. To test this hypothesis, we analyzed resting state electroencephalogram (EEG) of 10 FM patients. First, we examined theoretically well-known ES conditions within functional brain networks reconstructed from EEG, then tested whether a brain network model with ES conditions identified in the EEG data is sensitive to an...
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Recently, multiple time scale characteristics of heart dynamics have received much attention for distinguishing healthy and pathologic cardiac systems. Despite structural peculiarities of the fetal cardiovascular system, the fetal heart... more
Recently, multiple time scale characteristics of heart dynamics have received much attention for distinguishing healthy and pathologic cardiac systems. Despite structural peculiarities of the fetal cardiovascular system, the fetal heart rate(FHR) displays multiple time scale characteristics similar to the adult heart rate due to the autorhythmicity of its different oscillatory tissues and its interaction with other neural controllers. In this paper, we investigate the event and time scale characteristics of the normal and two pathologic fetal heart rate groups with the help of the new measure, called the Unit Time Block Entropy(UTBE), which approximates the entropy at each event and time scale based on symbolic dynamics. This method enables us to match the measurement time and the number of words between fetal heart rate data sets simultaneously. We find that in the small event scale and the large time scale, the normal fetus and the two pathologic fetus are completely distinguished...
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... [9] Vincent, JL, Patel, GH, Fox, MD, Snyder, AZ, Baker, JT, Van Essen, DC, Zempel, JM, Snyder, LH, Corbetta, M., & Raichle, ME, 2007, Intrinsic functional architecture in the anaesthetized monkey brain, Nature, 447 (7140),... more
... [9] Vincent, JL, Patel, GH, Fox, MD, Snyder, AZ, Baker, JT, Van Essen, DC, Zempel, JM, Snyder, LH, Corbetta, M., & Raichle, ME, 2007, Intrinsic functional architecture in the anaesthetized monkey brain, Nature, 447 (7140), 83-86. ... [11] Lee, U., Oh, G., Kim, S., Noh, G., Choi, B., & ...
Background Neurophysiologic complexity in the cortex has been shown to reflect changes in the level of consciousness in adults but remains incompletely understood in the developing brain. This study aimed to address changes in cortical... more
Background Neurophysiologic complexity in the cortex has been shown to reflect changes in the level of consciousness in adults but remains incompletely understood in the developing brain. This study aimed to address changes in cortical complexity related to age and anesthetic state transitions. This study tested the hypotheses that cortical complexity would (1) increase with developmental age and (2) decrease during general anesthesia. Methods This was a single-center, prospective, cross-sectional study of healthy (American Society of Anesthesiologists physical status I or II) children (n = 50) of age 8 to 16 undergoing surgery with general anesthesia at Michigan Medicine. This age range was chosen because it reflects a period of substantial brain network maturation. Whole scalp (16-channel), wireless electroencephalographic data were collected from the preoperative period through the recovery of consciousness. Cortical complexity was measured using the Lempel–Ziv algorithm and anal...
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<p>(a) propofol and (b) sevoflurane. The similarity of the five states was measured with the 60 network backbones that have the highest occupation probability for each state. Darker color indicates higher similarity. The two... more
<p>(a) propofol and (b) sevoflurane. The similarity of the five states was measured with the 60 network backbones that have the highest occupation probability for each state. Darker color indicates higher similarity. The two transition states (induction and recovery) are dissimilar from one another in both anesthetic groups. The red and blue boxes in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0070899#pone-0070899-g009" target="_blank">Figure 9a</a> denote the higher similarities among states in the propofol group, which are not found in the sevoflurane group. The illustrations below the matrices present the distinctive recovery pathways for two anesthetic groups: for propofol, the network backbone configuration was not recovered, whereas it was for sevoflurane.</p
Research Interests: Neuroscience, Physics, Surgery, Anesthesiology, States, and 14 moreConsciousness, Electroencephalography, Neural Networks, Cognitive Neuroscience, Medicine, Biological Sciences, Anesthesia, General Anesthesia, Clinical Neurophysiology, Configurations, Backbone, Similarities, Interdisciplinary Physics, and Anesthetic
The balance of global integration and functional specialization is a critical feature of efficient brain networks, but the relationship of global topology, local node dynamics and information flow across networks has yet to be identified.... more
The balance of global integration and functional specialization is a critical feature of efficient brain networks, but the relationship of global topology, local node dynamics and information flow across networks has yet to be identified. One critical step in elucidating this relationship is the identification of governing principles underlying the directionality of interactions be-tween nodes. Here, we demonstrate such principles through analytical solutions based on the phase lead/lag relationships of general oscillator models in networks. We confirm ana-lytical results with computational simulations using general model networks and anatomical brain networks, as well as high-density electroencephalography collected from humans in the conscious and anesthetized states. Analytical, computational, and empirical results demonstrate that network nodes with more connections (i.e., higher degrees) have larger amplitudes and are directional targets (phase lag) rather than sources (phase l...
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<p>The Stuart-Landau model was simulated on the human anatomical brain network before ((A), (C) and (E)) and after ((B), (D) and (F)) perturbation with preferential disruption of hub nodes. The general relationship of node degree,... more
<p>The Stuart-Landau model was simulated on the human anatomical brain network before ((A), (C) and (E)) and after ((B), (D) and (F)) perturbation with preferential disruption of hub nodes. The general relationship of node degree, amplitude and dPLI is also demonstrated in this modeled human brain network. The strong negative correlations between node degree and dPLI in (A) and the strong positive correlation between node degree and amplitude in (C) disappear in the perturbed homogeneous network ((B) and (D)). Average dPLI for each node was calculated by averaging the dPLI values of each node with respect to all other nodes. The anatomical connectivity of different brain regions are presented in (E) and (F) ring plots together with average dPLI value for each region. The nodes are aligned in groups: frontal lobe, central regions (including motor and somatosensory cortex), parietal lobe, occipital lobe, temporal lobe, limbic region, and Insula (Ins). Red arrow in (E) points to left and right precuneus. Color of each node shows the average dPLI values with respect to other nodes, from red (dPLI = 1) to blue (dPLI = -1). Average dPLI for each group is also shown in color. The inset within the ringplot shows connections between nodes, highlighted by darker color if the node has a higher degree of connections. Only the links from hub nodes (node with degree value within top 30%) are colored. In the simulation, the time delay between each node was given proportional to the delay, with propagation speed of 6m/s. The coupling strength <i>S</i> was given as 3. The full names for the cortical regions of the human brain network are available in Gong et al. [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004225#pcbi.1004225.ref047" target="_blank">47</a>].</p
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The integrated information theory (IIT) proposes a quantitative measure, denoted as Φ, of the amount of integrated information in a physical system, which is postulated to have an identity relationship with consciousness. IIT predicts... more
The integrated information theory (IIT) proposes a quantitative measure, denoted as Φ, of the amount of integrated information in a physical system, which is postulated to have an identity relationship with consciousness. IIT predicts that the value of Φ estimated from brain activities represents the level of consciousness across phylogeny and functional states. Practical limitations, such as the explosive computational demands required to estimate Φ for real systems, have hindered its application to the brain and raised questions about the utility of IIT in general. To achieve practical relevance for studying the human brain, it will be beneficial to establish the reliable estimation of Φ from multichannel electroencephalogram (EEG) and define the relationship of Φ to EEG properties conventionally used to define states of consciousness. In this study, we introduce a practical method to estimate Φ from high-density (128-channel) EEG and determine the contribution of each channel to ...
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How the brain reconstitutes consciousness and cognition after a major perturbation like general anesthesia is an important question with significant neuroscientific and clinical implications. Recent empirical studies in animals and humans... more
How the brain reconstitutes consciousness and cognition after a major perturbation like general anesthesia is an important question with significant neuroscientific and clinical implications. Recent empirical studies in animals and humans suggest that the recovery of consciousness after anesthesia is not random but ordered. Emergence patterns have been classified as progressive and abrupt transitions from anesthesia to consciousness, with associated differences in duration and electroencephalogram (EEG) properties. We hypothesized that the progressive and abrupt emergence patterns from the unconscious state are associated with, respectively, continuous and discontinuous synchronization transitions in functional brain networks. The discontinuous transition is explainable with the concept of explosive synchronization, which has been studied almost exclusively in network science. We used the Kuramato model, a simple oscillatory network model, to simulate progressive and abrupt transiti...
Research Interests: Psychology, Computer Science, Anesthesiology, Magnetic Resonance Imaging, Diffusion Tensor Imaging, and 15 moreConsciousness, Electroencephalography, Neurophysiology, Medicine, Emergence, Functional Connectivity, Brain, Brain Networks, Anesthesia, Clinical Sciences, Kuramoto Model, Isoflurane, Brain Network, Explosives, and Neurosciences
Previous studies have demonstrated inconsistent neurophysiologic effects of ketamine, although discrepant findings might relate to differences in doses studied, brain regions analyzed, coadministration of other anesthetic medications, and... more
Previous studies have demonstrated inconsistent neurophysiologic effects of ketamine, although discrepant findings might relate to differences in doses studied, brain regions analyzed, coadministration of other anesthetic medications, and resolution of the electroencephalograph. The objective of this study was to characterize the dose-dependent effects of ketamine on cortical oscillations and functional connectivity. Ten healthy human volunteers were recruited for study participation. The data were recorded using a 128-channel electroencephalograph during baseline consciousness, subanesthetic dosing (0.5 mg/kg over 40 min), anesthetic dosing (1.5 mg/kg bolus), and recovery. No other sedative or anesthetic medications were administered. Spectrograms, topomaps, and functional connectivity (weighted and directed phase lag index) were computed and analyzed. Frontal theta bandwidth power increased most dramatically during ketamine anesthesia (mean power ± SD, 4.25 ± 1.90 dB) compared to ...
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Identifying how spatially distributed information becomes integrated in the brain is essential to understanding higher cognitive functions. Previous computational and empirical studies suggest a significant influence of brain network... more
Identifying how spatially distributed information becomes integrated in the brain is essential to understanding higher cognitive functions. Previous computational and empirical studies suggest a significant influence of brain network structure on brain network function. However, there have been few analytical approaches to explain the role of network structure in shaping regional activities and directionality patterns. In this study, analytical methods are applied to a coupled oscillator model implemented in inhomogeneous networks. We first derive a mathematical principle that explains the emergence of directionality from the underlying brain network structure. We then apply the analytical methods to the anatomical brain networks of human, macaque, and mouse, successfully predicting simulation and empirical electroencephalographic data. The results demonstrate that the global directionality patterns in resting state brain networks can be predicted solely by their unique network stru...
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The balance of global integration and functional specialization is a critical feature of efficient brain networks, but the relationship of global topology, local node dynamics and information flow across networks has yet to be identified.... more
The balance of global integration and functional specialization is a critical feature of efficient brain networks, but the relationship of global topology, local node dynamics and information flow across networks has yet to be identified. One critical step in elucidating this relationship is the identification of governing principles underlying the directionality of interactions between nodes. Here, we demonstrate such principles through analytical solutions based on the phase lead/lag relationships of general oscillator models in networks. We confirm analytical results with computational simulations using general model networks and anatomical brain networks, as well as high-density electroencephalography collected from humans in the conscious and anesthetized states. Analytical, computational, and empirical results demonstrate that network nodes with more connections (i.e., higher degrees) have larger amplitudes and are directional targets (phase lag) rather than sources (phase lea...
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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... more
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 characteris...
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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... more
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 parado...
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The cardiac system shows various scale dynamic activities from secondly to yearly. Therefore multiple time-scale characteristics of heart dynamics have received much attention for understanding and distinguishing healthy and pathological... more
The cardiac system shows various scale dynamic activities from secondly to yearly. Therefore multiple time-scale characteristics of heart dynamics have received much attention for understanding and distinguishing healthy and pathological cardiac systems. In this paper we expand the multiple time-scale analysis into event and time scales to investigate scale characteristics in healthy and pathologic cardiac systems. To do this, we define a measure based on symbolic dynamics, which calculates complexity at each time and event scale, called the unit time block entropy (UTBE). This measure allows a reliable comparison of experimental data through matching the number of words and the total measurement time at the same time for all RR interval sequences which are composed of the time durations between consecutive R waves of electrocardiograms. We apply the UTBE to the healthy heart-rate (HR) group and pathological HR groups and find that the RR interval acceleration is more effective than the RR interval in distinguishing each group. And we also find that the normal and pathological HR groups are clearly distinguished in some specific event and time-scale regions.
Research Interests: Engineering, Mathematics, Algorithms, Nonlinear dynamics, Complex Systems, and 15 moreComplexity, Medicine, Electrocardiography, Heart Failure, Complex System, Humans, Computer Simulation, Reconstruction, Mathematical Sciences, Physical sciences, Atrial Fibrillation, Heart rate, Symbolic Dynamics, Interspike Intervals, and Experimental Data
Research Interests: Engineering, Computer Science, Artificial Intelligence, Epilepsy, Network Analysis, and 15 moreElectroencephalography, Medicine, Brain Mapping, Complex System, Cross Correlation, Brain, Humans, Mathematical Sciences, Physical sciences, Electroencephalogram, Minimum Spanning Tree, Reproducibility of Results, Network structure, Large Scale, and Dynamic Networks
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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... more
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.
Research Interests: Neuroscience, Cognitive Science, Philosophy, Consciousness, Electroencephalography, and 15 moreMedicine, Brain Mapping, Functional Connectivity, Humans, Cerebral Cortex, Male, Propofol, General Anesthesia, Adult, Parietal Lobe, Indexation, Human Subjects, Loss of Consciousness, Frontal Lobe, and Computational Method
Research Interests: Cognitive Science, Philosophy, Graph Theory, Consciousness, Electroencephalography, and 15 moreMedicine, Entropy, Functional Connectivity, Brain, Humans, Nonlinear Analysis, Female, Male, Gamma Band, Minimum Spanning Tree, Middle Aged, Adult, Neural pathways, Case Control Studies, and Antipsychotic agents
Introduction: 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... more
Introduction: 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. Methods: Graph theoretical network analysis was carried out to study the network properties of 21-channel electroencephalogram data from 10 human volunteers anesthetized on two occasions. The functional brain network was defined by Phase Lag Index, a coherence measure, for three states: wakefulness, loss of consciousness induced by the anesthetic propofol, and recovery of consciousness. The hub nodes were determined by the largest centralities. The correlation between the altered hub organization and the phase relationship between electroencephalographic channels was investigated. Results: Topology rather than connection strength of functional networks correlated with states of conscio...
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Introduction: 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... more
Introduction: 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. Methods: Surgical patients (n = 30) were recruited for induction of anesthesia with intravenous ketamine (2 mg/kg); electroencephalography of the frontal and parietal regions was acquired. The authors used normalized symbolic transfer entropy, a computational method based on information theory, to measure directional connectivity across frontal and parietal regions. Statistical analysis of transfer entropy measures was performed with the permutation test and the time-shift test to exclude false-positive connectivity. For comparison, the authors used normalized symbolic transfer entropy to reanalyze electroencephalographic data gathered from surgical patients receiving either prop...
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Background 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... more
Background 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. Methods Twenty healthy males were anesthetized with an induction dose of propofol, with continuous measurement of 21-channel electroencephalogram at baseline, during anesthesia, and during recovery. From these electroencephalographic data a "genuine network" was reconstructed based on the surrogate data method. The effects of topologic structure and connection strength on information transfer through the network were measured independently across different states. Results Loss of consciousness was consistently associated with a disruption of network topology. However, recovery of consciousness was associated with complex patterns of altered connection strength after the initial topologic structure had slowly recovered. In one group...
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Background 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... more
Background 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. Methods Ten healthy male volunteers were anesthetized with an induction dose of propofol on two separate occasions. The duration of network connections in the brain was analyzed by multichannel electroencephalography and the minimum spanning tree method. Entropy of the connections was calculated based on Shannon entropy. The global temporal configuration of networks was investigated by constructing the cumulative distribution function of connection times in different frequency bands and different states of consciousness. Results General anesthesia was associated with a significant reduction in the number of network connections, as well as significant alterations of their duration. These changes were most prominent in the δ bandwidth and wer...
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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... more
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.