General anaesthesia reduces the uniqueness of brain connectivity across individuals and across species.

The human brain is characterised by idiosyncratic patterns of spontaneous thought, rendering each brain uniquely identifiable from its neural activity. However, deep general anaesthesia suppresses subjective experience. Does it also suppress what makes each brain unique? Here we used functional MRI under the effects of the general anaesthetics sevoflurane and propofol to determine whether anaesthetic-induced unconsciousness diminishes the uniqueness of the human brain: both with respect to the brains of other individuals, and the brains of another species. We report that under anaesthesia individual brains become less self-similar and less distinguishable from each other. Loss of distinctiveness is highly organised: it co-localises with the archetypal sensory-association axis, correlating with genetic and morphometric markers of phylogenetic differences between humans and other primates. This effect is more evident at greater anaesthetic depths, reproducible across sevoflurane and propofol, and reversed upon recovery. Providing convergent evidence, we show that under anaesthesia the functional connectivity of the human brain becomes more similar to the macaque brain. Finally, anaesthesia diminishes the match between spontaneous brain activity and meta-analytic brain patterns aggregated from the NeuroSynth engine. Collectively, the present results reveal that anaesthetised human brains are not only less distinguishable from each other, but also less distinguishable from the brains of other primates, with specifically human-expanded regions being the most affected by anaesthesia.

In vivo mapping of pharmacologically induced functional reorganization onto the human brain's neurotransmitter landscape.

To understand how pharmacological interventions can exert their powerful effects on brain function, we need to understand how they engage the brain's rich neurotransmitter landscape. Here, we bridge microscale molecular chemoarchitecture and pharmacologically induced macroscale functional reorganization, by relating the regional distribution of 19 neurotransmitter receptors and transporters obtained from positron emission tomography, and the regional changes in functional magnetic resonance imaging connectivity induced by 10 different mind-altering drugs: propofol, sevoflurane, ketamine, lysergic acid diethylamide (LSD), psilocybin, N,N-Dimethyltryptamine (DMT), ayahuasca, 3,4-methylenedioxymethamphetamine (MDMA), modafinil, and methylphenidate. Our results reveal a many-to-many mapping between psychoactive drugs' effects on brain function and multiple neurotransmitter systems. The effects of both anesthetics and psychedelics on brain function are organized along hierarchical gradients of brain structure and function. Last, we show that regional co-susceptibility to pharmacological interventions recapitulates co-susceptibility to disorder-induced structural alterations. Collectively, these results highlight rich statistical patterns relating molecular chemoarchitecture and drug-induced reorganization of the brain's functional architecture.

Spatial signatures of anesthesia-induced burst-suppression differ between primates and rodents.

During deep anesthesia, the electroencephalographic (EEG) signal of the brain alternates between bursts of activity and periods of relative silence (suppressions). The origin of burst-suppression and its distribution across the brain remain matters of debate. In this work, we used functional magnetic resonance imaging (fMRI) to map the brain areas involved in anesthesia-induced burst-suppression across four mammalian species: humans, long-tailed macaques, common marmosets, and rats. At first, we determined the fMRI signatures of burst-suppression in human EEG-fMRI data. Applying this method to animal fMRI datasets, we found distinct burst-suppression signatures in all species. The burst-suppression maps revealed a marked inter-species difference: in rats, the entire neocortex engaged in burst-suppression, while in primates most sensory areas were excluded-predominantly the primary visual cortex. We anticipate that the identified species-specific fMRI signatures and whole-brain maps will guide future targeted studies investigating the cellular and molecular mechanisms of burst-suppression in unconscious states.

The development of anesthesia was a significant advance in medicine. It allows individuals to undergo surgery without feeling pain or remembering the experience. But scientists still do not know how anesthesia works. During anesthesia, scientists have measured brain activity using electroencephalograms (EEG) and found that the brain appears to turn on and off. Comatose patients also have similar switches between bursts of electrical activity and periods of silence. This burst-suppression pattern may be related to unconsciousness. But scientists still have many questions about how anesthesia causes burst-suppression. One challenge is that while an EEG can tell scientists when the brain turns on and off, it does not show exactly where this occurs. Another imaging method called functional Magnetic Resonance Imaging (fMRI) may fill this gap by allowing scientists to map where the brain activity occurs. Sirmpilatze et al. have created detailed maps of burst-suppression in humans, primates, and rats under anesthesia by analyzing brain scans using fMRI. In rats, the entire outer layer or cortex of the brain underwent a synchronized pattern of burst-suppression. In humans and primates, areas of the brain like those responsible for eyesight did not follow the rest of the cortex in switching on and off. The experiments reveal crucial differences in how rats and humans and other primates respond to anesthesia. The fMRI mapping technique Sirmpilatze et al. created may help scientists learn more about these differences and why some parts of human brains do not undergo burst-suppression. This may help scientists learn more about unconsciousness and help improve anesthesia or the care of comatose patients.

Dynamic Patterns of Global Brain Communication Differentiate Conscious From Unconscious Patients After Severe Brain Injury.

The neurophysiology of the subjective sensation of being conscious is elusive; therefore, it remains controversial how consciousness can be recognized in patients who are not responsive but seemingly awake. During general anesthesia, a model for the transition between consciousness and unconsciousness, specific covariance matrices between the activity of brain regions that we call patterns of global brain communication reliably disappear when people lose consciousness. This functional magnetic imaging study investigates how patterns of global brain communication relate to consciousness and unconsciousness in a heterogeneous sample during general anesthesia and after brain injury. First, we describe specific patterns of global brain communication during wakefulness that disappear during propofol (n = 11) and sevoflurane (n = 14) general anesthesia. Second, we search for these patterns in a cohort of unresponsive wakeful patients (n = 18) and unmatched healthy controls (n = 20) in order to evaluate their potential use in clinical practice. We found that patterns of global brain communication characterized by high covariance in sensory and motor areas or low overall covariance and their dynamic change were strictly associated with intact consciousness in this cohort. In addition, we show that the occurrence of these two patterns is significantly related to activity within the frontoparietal network of the brain, a network known to play a crucial role in conscious perception. We propose that this approach potentially recognizes consciousness in the clinical routine setting.

Brain network integration dynamics are associated with loss and recovery of consciousness induced by sevoflurane.

The dynamic interplay of integration and segregation in the brain is at the core of leading theoretical accounts of consciousness. The human brain dynamically alternates between a sub-state where integration predominates, and a predominantly segregated sub-state, with different roles in supporting cognition and behaviour. Here, we combine graph theory and dynamic functional connectivity to compare resting-state functional MRI data from healthy volunteers before, during, and after loss of responsiveness induced with different concentrations of the inhalational anaesthetic, sevoflurane. We show that dynamic states characterised by high brain integration are especially vulnerable to general anaesthesia, exhibiting attenuated complexity and diminished small-world character. Crucially, these effects are reversed upon recovery, demonstrating their association with consciousness. Higher doses of sevoflurane (3% vol and burst-suppression) also compromise the temporal balance of integration and segregation in the human brain. Additionally, we demonstrate that reduced anticorrelations between the brain's default mode and executive control networks dynamically reconfigure depending on the brain's state of integration or segregation. Taken together, our results demonstrate that the integrated sub-state of brain connectivity is especially vulnerable to anaesthesia, in terms of both its complexity and information capacity, whose breakdown represents a generalisable biomarker of loss of consciousness and its recovery.

Changes in Whole Brain Dynamics and Connectivity Patterns during Sevoflurane- and Propofol-induced Unconsciousness Identified by Functional Magnetic Resonance Imaging.

BACKGROUND: A key feature of the human brain is its capability to adapt flexibly to changing external stimuli. This capability can be eliminated by general anesthesia, a state characterized by unresponsiveness, amnesia, and (most likely) unconsciousness. Previous studies demonstrated decreased connectivity within the thalamus, frontoparietal, and default mode networks during general anesthesia. We hypothesized that these alterations within specific brain networks lead to a change of communication between networks and their temporal dynamics. METHODS: We conducted a pooled spatial independent component analysis of resting-state functional magnetic resonance imaging data obtained from 16 volunteers during propofol and 14 volunteers during sevoflurane general anesthesia that have been previously published. Similar to previous studies, mean z-scores of the resulting spatial maps served as a measure of the activity within a network. Additionally, correlations of associated time courses served as a measure of the connectivity between networks. To analyze the temporal dynamics of between-network connectivity, we computed the correlation matrices during sliding windows of 1 min and applied k-means clustering to the matrices during both general anesthesia and wakefulness. RESULTS: Within-network activity was decreased in the default mode, attentional, and salience networks during general anesthesia (P < 0.001, range of median changes: -0.34, -0.13). Average between-network connectivity was reduced during general anesthesia (P < 0.001, median change: -0.031). Distinct between-network connectivity patterns for both wakefulness and general anesthesia were observed irrespective of the anesthetic agent (P < 0.001), and there were fewer transitions in between-network connectivity patterns during general anesthesia (P < 0.001, median number of transitions during wakefulness: 4 and during general anesthesia: 0). CONCLUSIONS: These results suggest that (1) higher-order brain regions play a crucial role in the generation of specific between-network connectivity patterns and their dynamics, and (2) the capability to interact with external stimuli is represented by complex between-network connectivity patterns.

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.

Simultaneous EEG-PET-fMRI measurements in disorders of consciousness: an exploratory study on diagnosis and prognosis.

Previous studies could demonstrate that functional magnetic resonance imaging (fMRI), fludeoxyglucose positron emission tomography (FDG-PET), and electroencephalography (EEG) measures contain information about patients suffering from disorders of consciousness (DOC) and thus improve the clinical diagnosis. Additionally, the technical modalities were able to predict the outcome of patients. However, most studies lack proven reproducibility in a clinical setting. We here applied a standardized combined EEG/fMRI/FDG-PET measurement to a cohort of 20 patients suffering from DOC and focused on parameters that have been demonstrated to contain information about diagnosis and prognosis of these patients. We evaluated EEG band power, fMRI connectivity in networks associated with consciousness and sensory networks, as well as absolute glucose uptake in the brain as potential markers of preserved consciousness or favorable outcome. Acquired data were analyzed by a principal component analysis to identify the most important markers in a hypothesis-free manner. These were then analyzed with statistical group comparisons. Absolute FDG-PET could prove that glucose metabolism in the occipital lobe is significantly higher in minimally conscious than in vegetative state patients. Delta band power showed to be prognostic marker for a favorable outcome. We conclude that absolute FDG-PET is a suitable tool to evaluate the level consciousness in DOC patients. Additionally, we propose delta band power as marker of a favorable outcome in DOC patients. We suggest that these findings promote a standardized technical evaluation of DOC patients to improve diagnosis and prognosis.

Coherence of BOLD signal and electrical activity in the human brain during deep sevoflurane anesthesia.

INTRODUCTION: Changes in neural activity induce changes in functional magnetic resonance (fMRI) blood oxygenation level dependent (BOLD) signal. Commonly, increases in BOLD signal are ascribed to cellular excitation. OBJECTIVE: The relationship between electrical activity and BOLD signal in the human brain was probed on the basis of burst suppression EEG. This condition includes two distinct states of high and low electrical activity. METHODS: Resting-state simultaneous EEG and BOLD measurements were acquired during deep sevoflurane anesthesia with burst suppression EEG in nineteen healthy volunteers. Afterwards, fMRI volumes were assigned to one of the two states (burst or suppression) as defined by the EEG. RESULTS: In the frontal, parietal and temporal lobes as well as in the basal ganglia, BOLD signal increased after burst onset in the EEG and decreased after onset of EEG suppression. In contrast, BOLD signal in the occipital lobe was anticorrelated to electrical activity. This finding was obtained consistently in a general linear model and in raw data. CONCLUSIONS: In human brains exhibiting burst suppression EEG induced by sevoflurane, the positive correlation between BOLD signal and electrical brain activity could be confirmed in most gray matter. The exceptional behavior of the occipital lobe with an anticorrelation of BOLD signal and electrical activity might be due to specific neurovascular coupling mechanisms that are pronounced in the deeply anesthetized brain.

Neural Correlates of Sevoflurane-induced Unconsciousness Identified by Simultaneous Functional Magnetic Resonance Imaging and Electroencephalography.

BACKGROUND: The neural correlates of anesthetic-induced unconsciousness have yet to be fully elucidated. Sedative and anesthetic states induced by propofol have been studied extensively, consistently revealing a decrease of frontoparietal and thalamocortical connectivity. There is, however, less understanding of the effects of halogenated ethers on functional brain networks. METHODS: The authors recorded simultaneous resting-state functional magnetic resonance imaging and electroencephalography in 16 artificially ventilated volunteers during sevoflurane anesthesia at burst suppression and 3 and 2 vol% steady-state concentrations for 700 s each to assess functional connectivity changes compared to wakefulness. Electroencephalographic data were analyzed using symbolic transfer entropy (surrogate of information transfer) and permutation entropy (surrogate of cortical information processing). Functional magnetic resonance imaging data were analyzed by an independent component analysis and a region-of-interest-based analysis. RESULTS: Electroencephalographic analysis showed a significant reduction of anterior-to-posterior symbolic transfer entropy and global permutation entropy. At 2 vol% sevoflurane concentrations, frontal and thalamic networks identified by independent component analysis showed significantly reduced within-network connectivity. Primary sensory networks did not show a significant change. At burst suppression, all cortical networks showed significantly reduced functional connectivity. Region-of-interest-based thalamic connectivity at 2 vol% was significantly reduced to frontoparietal and posterior cingulate cortices but not to sensory areas. CONCLUSIONS: Sevoflurane decreased frontal and thalamocortical connectivity. The changes in blood oxygenation level dependent connectivity were consistent with reduced anterior-to-posterior directed connectivity and reduced cortical information processing. These data advance the understanding of sevoflurane-induced unconsciousness and contribute to a neural basis of electroencephalographic measures that hold promise for intraoperative anesthesia monitoring.

Cortical alterations in a model for absence epilepsy and febrile seizures: in vivo findings in mice carrying a human GABA(A)R gamma2 subunit mutation.

Childhood absence epilepsy (CAE) is one of the most common forms of epilepsy among children. The study of a large Australian family demonstrated that a point mutation in the gene encoding the gamma2 subunit of the GABA(A) receptor (G2R43Q) leads to an autosomal dominantly inherited form of CAE and febrile seizures (FS). In a transgenic mouse model carrying the gamma2 (R43Q) mutation heterozygous animals recapitulate the human phenotype. In-vitro experiments indicated that this point mutation impairs cortical inhibition and thus increases the likelihood of seizures. Here, using whole-cell (WC) and extracellular (EC) recordings as well as voltage-sensitive dye imaging (VSDI), we systematically searched for an in vivo correlate of cortical alterations caused by the G2R43Q mutation, as suggested by the mentioned in vitro results. We measured spontaneous and whisker-evoked activity in the primary somatosensory cortex and ventral posteriomedial nucleus of the thalamus (VPM) before and after intraperitoneal injection of the ictogenic substance pentylenetetrazol (PTZ) in urethane-anesthetized G2R43Q mice and controls in a blinded setting. Compared to wildtype controls in G2R43Q mice after PTZ injection we found 1.) Increased cortical spontaneous activity in layer 2/3 and layer 5/6 pyramidal neurons (increased standard deviation of the mean membrane potential in WC recordings), 2.) Increased variance of stimulus evoked cortical responses in VSDI experiments. 3.) The cortical effects are not due to increased strength or precision of thalamic output. In summary our findings support the hypothesis of a cortical pathology in this mouse model of human genetic absence epilepsy. Further study is needed to characterize underlying molecular mechanisms.

Blinded sample size re-estimation in crossover bioequivalence trials.

In drug development, bioequivalence studies are used to indirectly demonstrate clinical equivalence of a test formulation and a reference formulation of a specific drug by establishing their equivalence in bioavailability. These studies are typically run as crossover studies. In the planning phase of such trials, investigators and sponsors are often faced with a high variability in the coefficients of variation of the typical pharmacokinetic endpoints such as the area under the concentration curve or the maximum plasma concentration. Adaptive designs have recently been considered to deal with this uncertainty by adjusting the sample size based on the accumulating data. Because regulators generally favor sample size re-estimation procedures that maintain the blinding of the treatment allocations throughout the trial, we propose in this paper a blinded sample size re-estimation strategy and investigate its error rates. We show that the procedure, although blinded, can lead to some inflation of the type I error rate. In the context of an example, we demonstrate how this inflation of the significance level can be adjusted for to achieve control of the type I error rate at a pre-specified level. Furthermore, some refinements of the re-estimation procedure are proposed to improve the power properties, in particular in scenarios with small sample sizes.