Spontaneous and Visual Stimulation Evoked Firing Sequences Are Distinct Under Desflurane Anesthesia.

Recurring spike sequences are thought to underlie cortical computations and may be essential for information processing in the conscious state. How anesthesia at graded levels may influence spontaneous and stimulus-related spike sequences in visual cortex has not been fully elucidated. We recorded extracellular single-unit activity in the rat primary visual cortex in vivo during wakefulness and three levels of anesthesia produced by desflurane. The latencies of spike sequences within 0-200 ms from the onset of spontaneous UP states and visual flash-evoked responses were compared. During wakefulness, spike latency patterns linked to the local field potential theta cycle were similar to stimulus-evoked patterns. Under desflurane anesthesia, spontaneous UP state sequences differed from flash-evoked sequences due to the recruitment of low-firing excitatory neurons to the UP state. Flash-evoked spike sequences showed higher reliability and longer latency when stimuli were applied during DOWN states compared to UP states. At deeper levels, desflurane altered both UP state and flash-evoked spike sequences by selectively suppressing inhibitory neuron firing. The results reveal desflurane-induced complex changes in cortical firing sequences that may influence visual information processing.

Network Model With Reduced Metabolic Rate Predicts Spatial Synchrony of Neuronal Activity.

In a cerebral hypometabolic state, cortical neurons exhibit slow synchronous oscillatory activity with sparse firing. How such a synchronization spatially organizes as the cerebral metabolic rate decreases have not been systemically investigated. We developed a network model of leaky integrate-and-fire neurons with an additional dependency on ATP dynamics. Neurons were scattered in a 2D space, and their population activity patterns at varying ATP levels were simulated. The model predicted a decrease in firing activity as the ATP production rate was lowered. Under hypometabolic conditions, an oscillatory firing pattern, that is, an ON-OFF cycle arose through a failure of sustainable firing due to reduced excitatory positive feedback and rebound firing after the slow recovery of ATP concentration. The firing rate oscillation of distant neurons developed at first asynchronously that changed into burst suppression and global synchronization as ATP production further decreased. These changes resembled the experimental data obtained from anesthetized rats, as an example of a metabolically suppressed brain. Together, this study substantiates a novel biophysical mechanism of neuronal network synchronization under limited energy supply conditions.

Differential Effect of Anesthesia on Visual Cortex Neurons with Diverse Population Coupling.

Cortical neurons display diverse firing patterns and synchronization properties. How anesthesia alters the firing response of different neuron groups relevant for sensory information processing is unclear. Here we investigated the graded effect of anesthesia on spontaneous and visual flash-induced spike activity of different neuron groups classified based on their spike waveform, firing rate, and population coupling (the extent neurons conform to population spikes). Single-unit activity was measured from multichannel extracellular recordings in deep layers of primary visual cortex of freely moving rats in wakefulness and at three concentrations of desflurane. Anesthesia generally decreased firing rate and increased population coupling and burstiness of neurons. Population coupling and firing rate became more correlated and the pairwise correlation between neurons became more predictable by their population coupling in anesthesia. During wakefulness, visual stimulation increased firing rate; this effect was the largest and the most prolonged in neurons that exhibited high population coupling and high firing rate. During anesthesia, the early increase in firing rate (20-150 ms post-stimulus) of these neurons was suppressed, their spike timing was delayed and split into two peaks. The late response (200-400 ms post-stimulus) of all neurons was also suppressed. We conclude that anesthesia alters the visual response of primarily high-firing highly coupled neurons, which may interfere with visual sensory processing. The increased association of population coupling and firing rate during anesthesia suggests a decrease in sensory information content.

State-Dependent Cortical Unit Activity Reflects Dynamic Brain State Transitions in Anesthesia.

Understanding the effects of anesthesia on cortical neuronal spiking and information transfer could help illuminate the neuronal basis of the conscious state. Recent investigations suggest that the brain state identified by local field potential spectrum is not stationary but changes spontaneously at a fixed level of anesthetic concentration. How cortical unit activity changes with dynamically transitioning brain states under anesthesia is unclear. Extracellular unit activity was measured with 64-channel silicon microelectrode arrays in cortical layers 5/6 of the primary visual cortex of chronically instrumented, freely moving male rats (n = 7) during stepwise reduction of the anesthetic desflurane (6%, 4%, 2%, and 0%). Unsupervised machine learning applied to multiunit spike patterns revealed five distinct brain states. A novel desynchronized brain state with increased spike rate variability, sample entropy, and EMG activity occurred in 6% desflurane with 40.0% frequency. The other four brain states reflected graded levels of anesthesia. As anesthesia deepened the spike rate of neurons decreased regardless of their spike rate profile at baseline conscious state. Actively firing neurons with wide-spiking pattern showed increased bursting activity along with increased spike timing variability, unit-to-population correlation, and unit-to-unit transfer entropy, despite the overall decrease in transfer entropy. The narrow-spiking neurons showed similar changes but to a lesser degree. These results suggest that (1) anesthetic effect on spike rate is distinct from sleep, (2) synchronously fragmented spiking pattern is a signature of anesthetic-induced unconsciousness, and (3) the paradoxical, desynchronized brain state in deep anesthesia contends the generally presumed monotonic, dose-dependent anesthetic effect on the brain.SIGNIFICANCE STATEMENT Recent studies suggest that spontaneous changes in brain state occur under anesthesia. However, the spiking behavior of cortical neurons associated with such state changes has not been investigated. We found that local brain states defined by multiunit activity had a nonunitary relationship with the current anesthetic level. A paradoxical brain state displaying asynchronous firing pattern and high EMG activity was found unexpectedly in deep anesthesia. In contrast, the synchronous fragmentation of neuronal spiking appeared to be a robust signature of the state of anesthesia. The findings challenge the assumption of monotonic, anesthetic dose-dependent behavior of cortical neuron populations. They enhance the interpretation of neuroscientific data obtained under anesthesia and the understanding of the neuronal basis of anesthetic-induced state of unconsciousness.

Desflurane Anesthesia Alters Cortical Layer-specific Hierarchical Interactions in Rat Cerebral Cortex.

BACKGROUND: Neurocognitive investigations suggest that conscious sensory perception depends on recurrent neuronal interactions among sensory, parietal, and frontal cortical regions, which are suppressed by general anesthetics. The purpose of this work was to investigate if local interactions in sensory cortex are also altered by anesthetics. The authors hypothesized that desflurane would reduce recurrent neuronal interactions in cortical layer-specific manner consistent with the anatomical disposition of feedforward and feedback pathways. METHODS: Single-unit neuronal activity was measured in freely moving adult male rats (268 units; 10 animals) using microelectrode arrays chronically implanted in primary and secondary visual cortex. Layer-specific directional interactions were estimated by mutual information and transfer entropy of multineuron spike patterns within and between cortical layers three and five. The effect of incrementally increasing and decreasing steady-state concentrations of desflurane (0 to 8% to 0%) was tested for statistically significant quadratic trend across the successive anesthetic states. RESULTS: Desflurane produced robust, state-dependent reduction (P = 0.001) of neuronal interactions between primary and secondary visual areas and between layers three and five, as indicated by mutual information (37 and 41% decrease at 8% desflurane from wakeful baseline at [mean ± SD] 0.52 ± 0.51 and 0.53 ± 0.51 a.u., respectively) and transfer entropy (77 and 78% decrease at 8% desflurane from wakeful baseline at 1.86 ± 1.56 a.u. and 1.87 ± 1.67 a.u., respectively). In addition, a preferential suppression of feedback between secondary and primary visual cortex was suggested by the reduction of directional index of transfer entropy overall (P = 0.001; 89% decrease at 8% desflurane from 0.11 ± 0.18 a.u. at baseline) and specifically, in layer five (P = 0.001; 108% decrease at 8% desflurane from 0.12 ± 0.19 a.u. at baseline). CONCLUSIONS: Desflurane anesthesia reduces neuronal interactions in visual cortex with a preferential effect on feedback. The findings suggest that neuronal disconnection occurs locally, among hierarchical sensory regions, which may contribute to global functional disconnection underlying anesthetic-induced unconsciousness.

Relationship of critical dynamics, functional connectivity, and states of consciousness in large-scale human brain networks.

Recent modeling and empirical studies support the hypothesis that large-scale brain networks function near a critical state. Similar functional connectivity patterns derived from resting state empirical data and brain network models at criticality provide further support. However, despite the strong implication of a relationship, there has been no principled explanation of how criticality shapes the characteristic functional connectivity in large-scale brain networks. Here, we hypothesized that the network science concept of partial phase locking is the underlying mechanism of optimal functional connectivity in the resting state. We further hypothesized that the characteristic connectivity of the critical state provides a theoretical boundary to quantify how far pharmacologically or pathologically perturbed brain connectivity deviates from its critical state, which could enable the differentiation of various states of consciousness with a theory-based metric. To test the hypothesis, we used a neuroanatomically informed brain network model with the resulting source signals projected to electroencephalogram (EEG)-like sensor signals with a forward model. Phase lag entropy (PLE), a measure of phase relation diversity, was estimated and the topography of PLE was analyzed. To measure the distance from criticality, the PLE topography at a critical state was compared with those of the EEG data from baseline consciousness, isoflurane anesthesia, ketamine anesthesia, vegetative state/unresponsive wakefulness syndrome, and minimally conscious state. We demonstrate that the partial phase locking at criticality shapes the functional connectivity and asymmetric anterior-posterior PLE topography, with low (high) PLE for high (low) degree nodes. The topographical similarity and the strength of PLE differentiates various pharmacologic and pathologic states of consciousness. Moreover, this model-based EEG network analysis provides a novel metric to quantify how far a pharmacologically or pathologically perturbed brain network is away from critical state, rather than merely determining whether it is in a critical or non-critical state.

Desynchronization of Theta Oscillations in Prefrontal Cortex during Self-stimulation of the Medial Forebrain Bundles in Mice.

Stimulation of the medial forebrain bundle (MFB) can reinforce intracranial self-stimulation (ICSS) in rodents (i.e., reward-seeking behavior). The MFB stimulation produces a highly reliable behavioral output that enabled a clear distinction of the animal behavioral states between the non-ICSS and ICSS periods. However, the cortical states during these reward-seeking behaviors are not fully characterized in comparison to those during volitional behavior. This study was designed to characterize the cortical rhythms of and coherence between prefrontal cortex and hippocampus during the wheel-turning behavior reinforced by the ICSS in comparison to the wheel-turning without ICSS. We used a wheel for freely moving mice, which was programmed to deliver cathode currents through an electrode in the MFB at each one-quarter turn of the wheel to induce ICSS. The wheel-turning epochs were extracted from the pre-ICSS, ICSS and post-ICSS sessions and the prefrontal EEGs and the hippocampal LFPs in the epochs were analyzed with power and synchronization analyses. During the ICSS, the EEG power decreased at 6~10 Hz in the prefrontal cortex, while was not significantly altered in the hippocampus. Furthermore, we found that the phase synchrony between the prefrontal cortex and the hippocampus corresponding to information transmission between the two regions during reward-seeking motion decreased preceding MFB stimulation reinforced by ICSS. Our findings suggest that theta-activity can be reliably dissociated from active behavior if the animal is involved in self-stimulation.

Topographic Reconfiguration of Local and Shared Information in Anesthetic-Induced Unconsciousness.

Theoretical consideration predicts that the alteration of local and shared information in the brain is a key element in the mechanism of anesthetic-induced unconsciousness. Ordinal pattern analysis, such as permutation entropy (PE) and symbolic mutual information (SMI), have been successful in quantifying local and shared information in neurophysiological data; however, they have been rarely applied to altered states of consciousness, especially to data obtained with functional magnetic resonance imaging (fMRI). PE and SMI analysis, together with the superb spatial resolution of fMRI recording, enables us to explore the local information of specific brain areas, the shared information between the areas, and the relationship between the two. Given the spatially divergent action of anesthetics on regional brain activity, we hypothesized that anesthesia would differentially influence entropy (PE) and shared information (SMI) across various brain areas, which may represent fundamental, mechanistic indicators of loss of consciousness. FMRI data were collected from 15 healthy participants during four states: wakefulness (W), light (conscious) sedation (L), deep (unconscious) sedation (D), and recovery (R). Sedation was produced by the common, clinically used anesthetic, propofol. Firstly, we found that that global PE decreased from W to D, and increased from D to R. The PE was differentially affected across the brain areas; specifically, the PE in the subcortical network was reduced more than in the cortical networks. Secondly, SMI was also differentially affected in different areas, as revealed by the reconfiguration of its spatial pattern (topographic structure). The topographic structures of SMI in the conscious states W, L, and R were distinctively different from that of the unconscious state D. Thirdly, PE and SMI were positively correlated in W, L, and R, whereas this correlation was disrupted in D. And lastly, PE changes occurred preferentially in highly connected hub regions. These findings advance our understanding of brain dynamics and information exchange, emphasizing the importance of topographic structure and the relationship of local and shared information in anesthetic-induced unconsciousness.

Diversity of functional connectivity patterns is reduced in propofol-induced unconsciousness.

INTRODUCTION: Recent evidence suggests that the conscious brain is characterized by a diverse repertoire of functional connectivity patterns while the anesthetized brain shows stereotyped activity. However, classical time-averaged methods of connectivity dismiss dynamic and temporal characteristics of functional configurations. Here we demonstrate a new approach which characterizes time-varying patterns of functional connectivity at the subsecond time scale. METHODS: We introduce phase-lag entropy (PLE), a measure of the diversity of temporal patterns in the phase relationships between two signals. The proposed measure was applied to multichannel electroencephalogram (EEG), which were recorded from two distinct experimental settings: (1) propofol was administrated at a constant infusion rate for 60 min (n = 96); (2) administration of propofol by a target effect-site concentration-controlled infusion with simultaneous assessment of the level of consciousness (n = 10). RESULTS: From the first dataset, two substantial changes of the phase relationship during anesthesia was found: (1) the dynamics of the phase relationship between frontal channels became progressively less diverse and more stereotyped during unconsciousness, quantified as a reduction in PLE; and (2) the reduction in PLE was consistent across subjects. Furthermore, PLE provided better performance in the classification of states of consciousness than did phase-lag index, a classical time-averaged connectivity method. From the second dataset, PLE showed the highest agreement with the level of consciousness, compared to existing anesthetic depth indicators. CONCLUSIONS: This study suggests that a scarcity of functional configurations is closely associated with anesthetically induced unconsciousness, and shows promise as a basis for a new consciousness monitoring system during general anesthesia. Hum Brain Mapp 38:4980-4995, 2017. © 2017 Wiley Periodicals, Inc.

Suppressed neural complexity during ketamine- and propofol-induced unconsciousness.

Ketamine and propofol have distinctively different molecular mechanisms of action and neurophysiological features, although both induce loss of consciousness. Therefore, identifying a common feature of ketamine- and propofol-induced unconsciousness would provide insight into the underlying mechanism of losing consciousness. In this study we search for a common feature by applying the concept of type-II complexity, and argue that neural complexity is essential for a brain to maintain consciousness. To test this hypothesis, we show that complexity is suppressed during loss of consciousness induced by ketamine or propofol. We analyzed the randomness (type-I complexity) and complexity (type-II complexity) of electroencephalogram (EEG) signals before and after bolus injection of ketamine or propofol. For the analysis, we use Mean Information Gain (MIG) and Fluctuation Complexity (FC), which are information-theory-based measures that quantify disorder and complexity of dynamics respectively. Both ketamine and propofol reduced the complexity of the EEG signal, but ketamine increased the randomness of the signal and propofol decreased it. The finding supports our claim and suggests EEG complexity as a candidate for a consciousness indicator.

Neural Correlates of Wakefulness, Sleep, and General Anesthesia: An Experimental Study in Rat.

BACKGROUND: Significant advances have been made in our understanding of subcortical processes related to anesthetic- and sleep-induced unconsciousness, but the associated changes in cortical connectivity and cortical neurochemistry have yet to be fully clarified. METHODS: Male Sprague-Dawley rats were instrumented for simultaneous measurement of cortical acetylcholine and electroencephalographic indices of corticocortical connectivity-coherence and symbolic transfer entropy-before, during, and after general anesthesia (propofol, n = 11; sevoflurane, n = 13). In another group of rats (n = 7), these electroencephalographic indices were analyzed during wakefulness, slow wave sleep (SWS), and rapid eye movement (REM) sleep. RESULTS: Compared to wakefulness, anesthetic-induced unconsciousness was characterized by a significant decrease in cortical acetylcholine that recovered to preanesthesia levels during recovery wakefulness. Corticocortical coherence and frontal-parietal symbolic transfer entropy in high γ band (85 to 155 Hz) were decreased during anesthetic-induced unconsciousness and returned to preanesthesia levels during recovery wakefulness. Sleep-wake states showed a state-dependent change in coherence and transfer entropy in high γ bandwidth, which correlated with behavioral arousal: high during wakefulness, low during SWS, and lowest during REM sleep. By contrast, frontal-parietal θ connectivity during sleep-wake states was not correlated with behavioral arousal but showed an association with well-established changes in cortical acetylcholine: high during wakefulness and REM sleep and low during SWS. CONCLUSIONS: Corticocortical coherence and frontal-parietal connectivity in high γ bandwidth correlates with behavioral arousal and is not mediated by cholinergic mechanisms, while θ connectivity correlates with cortical acetylcholine levels.

Reconfiguration of network hub structure after propofol-induced unconsciousness.

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 consciousness. The average path length, clustering coefficient, and modularity significantly increased after administration of propofol, which disrupted long-range connections. In particular, the strength of hub nodes significantly decreased. The primary hub location shifted from the parietal to frontal region, in association with propofol-induced unconsciousness. The phase lead of frontal to parietal regions in the α frequency band (8-13 Hz) observed during wakefulness reversed direction after propofol and returned during recovery. CONCLUSIONS: Propofol reconfigures network hub structure in the brain and reverses the phase relationship between frontal and parietal regions. Changes in network topology are more closely associated with states of consciousness than connectivity and may be the primary mechanism for the observed loss of frontal to parietal feedback during general anesthesia.

Altered cortical communication in amyotrophic lateral sclerosis.

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.

Genuine and spurious phase synchronization strengths during consciousness and general anesthesia.

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.

Determination of paroxetine in plasma by liquid chromatography coupled to tandem mass spectrometry for pharmacokinetic and bioequivalence studies.

A rapid and validated liquid chromatography coupled to tandem mass spectrometric method (LC-MS-MS) has been developed and applied to pharmacokinetic and bioequivalence studies in 24 healthy male Korean volunteers. The procedure involves a liquid-liquid extraction of paroxetine (CAS 61869-08-7) and fluoxetine (internal standard, CAS 54910-89-3) with ether/methyl chloride (7:3, v/v) and separated by LC equipped with C18 column using acetonitrile: 5 mmol/L ammonium formate (4:3, v/v) as mobile phase. Detection is carried out on an API 2000 MS system by multiple reactions monitoring mode. The ionization was optimized using ESI(+) and selectivity was achieved by MS-MS analysis, mlz 330.0-->192.0 and m/ z 310-->148 for paroxetine and fluoxetine, respectively. The method has a total run time of 1.5 min and was linear over a working range of 0.05-20 ng/mL and the lower limit of quantification was 0.05 ng/ mL. No endogenous compounds were found to interfere with the analysis. The inter-day and intra-day accuracy was in the ranges of 102.69-107.79% and 102.07-109.57%, respectively and precision of inter-day and intra-day expressed as relative standard deviation were 1.86-9.99% and 1.52-6.28%, respectively. The validation of this method on linearity, specificity, accuracy, precision as well as applicability to pharmacokinetic and bioequivalence studies by analysis of blood samples taken up to 72 h after oral administration of 20 mg of paroxetine in 24 healthy volunteers were found to be good performance.