Factoring the brain signatures of anesthesia concentration and level of arousal across individuals

Dynamical structure-function correlations provide robust and generalizable signatures of consciousness in humans

Resting-state functional magnetic resonance imaging evolves through a repertoire of functional connectivity patterns which might reflect ongoing cognition, as well as the contents of conscious awareness. We investigated whether the dynamic exploration of these states can provide robust and generalizable markers for the state of consciousness in human participants, across loss of consciousness induced by general anaesthesia or slow wave sleep. By clustering transient states of functional connectivity, we demonstrated that brain activity during unconsciousness is dominated by a recurrent pattern primarily mediated by structural connectivity and with a reduced capacity to transition to other patterns. Our results provide evidence supporting the pronounced differences between conscious and unconscious brain states in terms of whole-brain dynamics; in particular, the maintenance of rich brain dynamics measured by entropy is a critical aspect of conscious awareness. Collectively, our results may have significant implications for our understanding of consciousness and the neural basis of human awareness, as well as for the discovery of robust signatures of consciousness that are generalizable among different brain conditions.

Dynamical changes of interaction across functional brain communities during propofol-induced sedation

It is crucial to understand how anesthetics disrupt information transmission within the whole-brain network and its hub structure to gain insight into the network-level mechanisms underlying propofol-induced sedation. However, the influence of propofol on functional integration, segregation, and community structure of whole-brain networks were still unclear. We recruited 12 healthy subjects and acquired resting-state functional magnetic resonance imaging data during 5 different propofol-induced effect-site concentrations (CEs): 0, 0.5, 1.0, 1.5, and 2.0 μg/ml. We constructed whole-brain functional networks for each subject under different conditions and identify community structures. Subsequently, we calculated the global and local topological properties of whole-brain network to investigate the alterations in functional integration and segregation with deepening propofol sedation. Additionally, we assessed the alteration of key nodes within the whole-brain community structure at each effect-site concentrations level. We found that global participation was significantly increased at high effect-site concentrations, which was mediated by bilateral postcentral gyrus. Meanwhile, connector hubs appeared and were located in posterior cingulate cortex and precentral gyrus at high effect-site concentrations. Finally, nodal participation coefficients of connector hubs were closely associated to the level of sedation. These findings provide valuable insights into the relationship between increasing propofol dosage and enhanced functional interaction within the whole-brain networks.

Low-dimensional organization of global brain states of reduced consciousness

Brain states are frequently represented using a unidimensional scale measuring the richness of subjective experience (level of consciousness). This description assumes a mapping between the high-dimensional space of whole-brain configurations and the trajectories of brain states associated with changes in consciousness, yet this mapping and its properties remain unclear. We combine whole-brain modeling, data augmentation, and deep learning for dimensionality reduction to determine a mapping representing states of consciousness in a low-dimensional space, where distances parallel similarities between states. An orderly trajectory from wakefulness to patients with brain injury is revealed in a latent space whose coordinates represent metrics related to functional modularity and structure-function coupling, increasing alongside loss of consciousness. Finally, we investigate the effects of model perturbations, providing geometrical interpretation for the stability and reversibility of states. We conclude that conscious awareness depends on functional patterns encoded as a low-dimensional trajectory within the vast space of brain configurations.

Proceedings of the Second Curing Coma Campaign NIH Symposium: Challenging the Future of Research for Coma and Disorders of Consciousness

This proceedings article presents actionable research targets on the basis of the presentations and discussions at the 2nd Curing Coma National Institutes of Health (NIH) symposium held from May 3 to May 5, 2021. Here, we summarize the background, research priorities, panel discussions, and deliverables discussed during the symposium across six major domains related to disorders of consciousness. The six domains include (1) Biology of Coma, (2) Coma Database, (3) Neuroprognostication, (4) Care of Comatose Patients, (5) Early Clinical Trials, and (6) Long-term Recovery. Following the 1st Curing Coma NIH virtual symposium held on September 9 to September 10, 2020, six workgroups, each consisting of field experts in respective domains, were formed and tasked with identifying gaps and developing key priorities and deliverables to advance the mission of the Curing Coma Campaign. The highly interactive and inspiring presentations and panel discussions during the 3-day virtual NIH symposium identified several action items for the Curing Coma Campaign mission, which we summarize in this article.

Resting State Functional Connectivity Analysis During General Anesthesia: A High-Density EEG Study

The depth of anesthesia monitoring is helpful to guide administrations of general anesthetics during surgical procedures,however, the conventional 2-4 channels electroencephalogram (EEG) derived monitors have their limitations in monitoring conscious states due to low spatial resolution and suboptimal algorithm. In this study, 256-channel high-density EEG signals in 24 subjects receiving three types of general anesthetics (propofol, sevoflurane and ketamine) respectively were recorded both before and after anesthesia. The raw EEG signals were preprocessed by EEGLAB 14.0. Functional connectivity (FC) analysis by traditional coherence analysis (CA) method and a novel sparse representation (SR) method. And the network parameters, average clustering coefficient (ACC) and average shortest path length (ASPL) before and after anesthesia were calculated. The results show SR method find more significant FC differences in frontal and occipital cortices, and whole brain network (p<0.05). In contrast, CA can hardly obtain consistent ASPL in the whole brain network (p>0.05). Further, ASPL calculated by SR for whole brain connections in all of three anesthesia groups increased, which can be a unified EEG biomarker of general anesthetics-induced loss of consciousness (LOC). Therefore FC analysis based on SR analysis has better performance in distinguishing anesthetic-induced LOC from awake state.

fMRI lag structure during waking up from early sleep stages

The brain mechanisms by which we transition from sleep to a conscious state remain largely unknown in humans, partly because of methodological challenges. Here we study a pre-existing dataset of waking up participants originally designed for a study of dreaming (Horikawa, Tamaki, Miyawaki, & Kamitani, 2013) and suggest that suddenly awakening from early sleep stages results from a two-stage process that involves a sequence of cortical and subcortical brain activity. First, subcortical and sensorimotor structures seem to be recruited before most cortical regions, followed by fast, ignition-like whole-brain activation-with frontal regions engaging a little after the rest of the brain. Second, a comparably slower and possibly mirror-reversed stage might take place, with cortical regions activating before subcortical structures and the cerebellum. This pattern of activation points to a key role of subcortical structures for the initiation and maintenance of conscious states.

Mechanisms Underlying Disorders of Consciousness: Bridging Gaps to Move Toward an Integrated Translational Science

AIM

In order to successfully detect, classify, prognosticate, and develop targeted therapies for patients with disorders of consciousness (DOC), it is crucial to improve our mechanistic understanding of how severe brain injuries result in these disorders.

METHODS

To address this need, the Curing Coma Campaign convened a Mechanisms Sub-Group of the Coma Science Work Group (CSWG), aiming to identify the most pressing knowledge gaps and the most promising approaches to bridge them.

RESULTS

We identified a key conceptual gap in the need to differentiate the neural mechanisms of consciousness per se, from those underpinning connectedness to the environment and behavioral responsiveness. Further, we characterised three fundamental gaps in DOC research: (1) a lack of mechanistic integration between structural brain damage and abnormal brain function in DOC; (2) a lack of translational bridges between micro- and macro-scale neural phenomena; and (3) an incomplete exploration of possible synergies between data-driven and theory-driven approaches.

CONCLUSION

In this white paper, we discuss research priorities that would enable us to begin to close these knowledge gaps. We propose that a fundamental step towards this goal will be to combine translational, multi-scale, and multimodal data, with new biomarkers, theory-driven approaches, and computational models, to produce an integrated account of neural mechanisms in DOC. Importantly, we envision that reciprocal interaction between domains will establish a "virtuous cycle," leading towards a critical vantage point of integrated knowledge that will enable the advancement of the scientific understanding of DOC and consequently, an improvement of clinical practice.

Propofol sedation-induced alterations in brain connectivity reflect parvalbumin interneurone distribution in human cerebral cortex

BACKGROUND

Propofol, a commonly used intravenous anaesthetic, binds to type A gamma aminobutyric acid (GABA) receptors in mammalian brain. Previous work on its anaesthetic action has characterised either the biochemistry underlying propofol binding or the associated changes in brain network dynamics during sedation. Despite these advances, no study has focused on understanding how propofol action at the cellular level results in changes in brain network connectivity.

METHODS

We used human whole-brain microarray data to generate distribution maps for genes that mark the primary GABAergic cortical interneurone subtypes (somatostatin, parvalbumin [PV], and 5-hydroxytryptamine 3A. Next, 25 healthy participants underwent propofol-induced sedation during resting state functional MRI scanning. We used partial least squares analysis to identify the brain regions in which connectivity patterns were most impacted by propofol sedation. We then correlated these multimodal cortical patterns to determine if a specific interneurone subtype was disproportionately expressed in brain regions in which connectivity patterns were altered during sedation.

RESULTS

Brain networks that were significantly altered by propofol sedation had a high density of PV-expressing GABAergic interneurones. Brain networks that anticorrelated during normal wakefulness, namely the default mode network and attentional and frontoparietal control networks, increased in correlation during sedation.

CONCLUSIONS

PV-expressing interneurones are highly expressed in brain regions with altered connectivity profiles during propofol-induced sedation. This study also demonstrates the utility of leveraging multiple datasets to address multiscale neurobiological problems.

Altered Intrinsic Brain Activity and Functional Connectivity Before and After Knee Arthroplasty in the Elderly: A Resting-State fMRI Study

Objective: This study aimed to investigate the brain functional alterations with resting-state functional magnetic resonance imaging (rs-fMRI) in older patients with knee osteoarthritis (KOA) before and after total knee arthroplasty (TKA) and to assess the causal relationship of the brain function and neuropsychological changes.

Methods: We performed rs-fMRI to investigate brain function of 23 patients aged ≥65 with KOA and 23 healthy matched controls. Of the KOA patients, 15 completed postoperative rs-fMRI examinations. Analyzes of the amplitude of low-frequency fluctuation (ALFF) and functional connectivity (FC) were used to estimate differences in brain functional parameters between KOA patients, postoperative patients, and the controls. The relationship between changes of pre- and post-surgical status in ALFF and neuropsychological test results was analyzed.

Results: Compared with the controls, all patients with KOA exhibited decreased ALFF in the default mode network (bilateral angular gyrus, precuneus gyrus, medial superior frontal gyrus) and increased ALFF in the bilateral amygdala and cerebellum posterior lobe before surgery (P < 0.001). Altered ALFF persisted in the same brain regions 1 week postoperatively. The decreased ALFF in the left precuneus gyrus and middle temporal gyrus was found after surgery when compared with preoperative data (P < 0.01). Preoperatively, the KOA patients exhibited increased FC between the left precuneus gyrus and the right supplementary motor area compared to the controls (P < 0.001), but this connectivity became no significant difference after TKA. The left Cerebelum_9 was found to have decreased FC with the right precuneus gyrus postoperatively (P < 0.001) although this was not significantly different before surgery. The significantly altered ALFF values were not correlated with changes in cognitive assessment scores.

Conclusion: In older patients with end-stage KOA, functional alterations in important brain regions were detected with the persistence and further changes observed at an early stage after knee replacement. Our data further our understanding of brain functional abnormalities and cognitive impairment in older patients following knee replacement, which may provide therapeutic targets for preventive/treatment strategy to be developed.

Trial registration: Clinical Trial Registration: http://www.chictr.org.cn/index.aspx, ChiCTR1800016437; Registered June 1, 2018.

Sedation Modulates Frontotemporal Predictive Coding Circuits and the Double Surprise Acceleration Effect

Two important theories in cognitive neuroscience are predictive coding (PC) and the global workspace (GW) theory. A key research task is to understand how these two theories relate to one another, and particularly, how the brain transitions from a predictive early state to the eventual engagement of a brain-scale state (the GW). To address this question, we present a source-localization of EEG responses evoked by the local-global task—an experimental paradigm that engages a predictive hierarchy, which encompasses the GW. The results of our source reconstruction suggest three phases of processing. The first phase involves the sensory (here auditory) regions of the superior temporal lobe and predicts sensory regularities over a short timeframe (as per the local effect). The third phase is brain-scale, involving inferior frontal, as well as inferior and superior parietal regions, consistent with a global neuronal workspace (GNW; as per the global effect). Crucially, our analysis suggests that there is an intermediate (second) phase, involving modulatory interactions between inferior frontal and superior temporal regions. Furthermore, sedation with propofol reduces modulatory interactions in the second phase. This selective effect is consistent with a PC explanation of sedation, with propofol acting on descending predictions of the precision of prediction errors; thereby constraining access to the GNW.

Propofol Anesthesia Increases Long-range Frontoparietal Corticocortical Interaction in the Oculomotor Circuit in Macaque Monkeys

WHAT WE ALREADY KNOW ABOUT THIS TOPIC

A decrease in frontoparietal functional connectivity has been demonstrated with multiple anesthetic agents, and this decrease has been proposed as a final common functional pathway to produce anesthesia.Two alternative measures of long-range cortical interaction are coherence and phase-amplitude coupling. Although phase-amplitude coupling within frontal cortex changes with propofol administration, the effects of propofol on phase-amplitude coupling between different cortical areas have not previously been reported.

WHAT THIS ARTICLE TELLS US THAT IS NEW

Using a previously published monkey electrocorticography data set, it was found that propofol induced coherent slow oscillations in visual and oculomotor networks made up of cortical areas with strong anatomic projections.Frontal eye field within-area phase-amplitude coupling increased.Contrary to expectations from previous functional connectivity studies, interareal phase-amplitude coupling also increased with propofol.

BACKGROUND

Frontoparietal functional connectivity decreases with multiple anesthetics using electrophysiology and functional imaging. This decrease has been proposed as a final common functional pathway to produce anesthesia. Two alternative measures of long-range cortical interaction are coherence and phase-amplitude coupling. Although phase-amplitude coupling within frontal cortex changes with propofol administration, the effects of propofol on phase-amplitude coupling between different cortical areas have not previously been reported. Based on phase-amplitude coupling observed within frontal lobe during the anesthetized period, it was hypothesized that between-lead phase-amplitude coupling analysis should decrease between frontal and parietal leads during propofol anesthesia.

METHODS

A published monkey electrocorticography data set (N = 2 animals) was used to test for interactions in the cortical oculomotor circuit, which is robustly interconnected in primates, and in the visual system during propofol anesthesia using coherence and interarea phase-amplitude coupling.

RESULTS

Propofol induces coherent slow oscillations in visual and oculomotor networks made up of cortical areas with strong anatomic projections. Frontal eye field within-area phase-amplitude coupling increases with a time course consistent with a bolus response to intravenous propofol (modulation index increase of 12.6-fold). Contrary to the hypothesis, interareal phase-amplitude coupling also increases with propofol, with the largest increase in phase-amplitude coupling in frontal eye field low-frequency phase modulating lateral intraparietal area β-power (27-fold increase) and visual area 2 low-frequency phase altering visual area 1 β-power (19-fold increase).

CONCLUSIONS

Propofol anesthesia induces coherent oscillations and increases certain frontoparietal interactions in oculomotor cortices. Frontal eye field and lateral intraparietal area show increased coherence and phase-amplitude coupling. Visual areas 2 and 1, which have similar anatomic projection patterns, show similar increases in phase-amplitude coupling, suggesting higher order feedback increases in influence during propofol anesthesia relative to wakefulness. This suggests that functional connectivity between frontal and parietal areas is not uniformly decreased by anesthetics.

Reorganisation of Brain Hubs across Altered States of Consciousness

Patterns of functional interactions across distributed brain regions are suggested to provide a scaffold for the conscious processing of information, with marked topological alterations observed in loss of consciousness. However, establishing a firm link between macro-scale brain network organisation and conscious cognition requires direct investigations into neuropsychologically-relevant architectural modifications across systematic reductions in consciousness. Here we assessed both global and regional disturbances to brain graphs in a group of healthy participants across baseline resting state fMRI as well as two distinct levels of propofol-induced sedation. We found a persistent modular architecture, yet significant reorganisation of brain hubs that formed parts of a wider rich-club collective. Furthermore, the reduction in the strength of rich-club connectivity was significantly associated with the participants’ performance in a semantic judgment task, indicating the importance of this higher-order topological feature for conscious cognition. These results highlight a remarkable interplay between global and regional properties of brain functional interactions in supporting conscious cognition that is relevant to our understanding of clinical disorders of consciousness.

Consciousness-specific dynamic interactions of brain integration and functional diversity

Prominent theories of consciousness emphasise different aspects of neurobiology, such as the integration and diversity of information processing within the brain. Here, we combine graph theory and dynamic functional connectivity to compare resting-state functional MRI data from awake volunteers, propofol-anaesthetised volunteers, and patients with disorders of consciousness, in order to identify consciousness-specific patterns of brain function. We demonstrate that cortical networks are especially affected by loss of consciousness during temporal states of high integration, exhibiting reduced functional diversity and compromised informational capacity, whereas thalamo-cortical functional disconnections emerge during states of higher segregation. Spatially, posterior regions of the brain’s default mode network exhibit reductions in both functional diversity and integration with the rest of the brain during unconsciousness. These results show that human consciousness relies on spatio-temporal interactions between brain integration and functional diversity, whose breakdown may represent a generalisable biomarker of loss of consciousness, with potential relevance for clinical practice.

How do diversity (entropy) and integration of activity across brain regions interact to support consciousness? Here the authors show that anaesthetised individuals and patients with disorders of consciousness exhibit overlapping reductions in both diversity and integration in the brain’s default mode network.

Predicting seizure outcome of vagus nerve stimulation using MEG-based network topology

Vagus nerve stimulation (VNS) is a low-risk surgical option for patients with drug resistant epilepsy, although it is impossible to predict which patients may respond to VNS treatment. Resting-state magnetoencephalography (rs-MEG) connectivity analysis has been increasingly utilized to investigate the impact of epilepsy on brain networks and identify alteration of these networks after different treatments; however, there is no study to date utilizing this modality to predict the efficacy of VNS treatment. We investigated whether the rs-MEG network topology before VNS implantation can be used to predict efficacy of VNS treatment. Twenty-three patients with epilepsy who had MEG before VNS implantation were included in this study. We also included 89 healthy control subjects from the Human Connectome Project. Using the phase-locking value in the theta, alpha, and beta frequency bands as a measure of rs-MEG functional connectivity, we calculated three global graph measures: modularity, transitivity, and characteristic path length (CPL). Our results revealed that the rs-MEG graph measures were significantly heritable and had an overall good test-retest reliability, and thus these measures may be used as potential biomarkers of the network topology. We found that the modularity and transitivity in VNS responders were significantly larger and smaller, respectively, than those observed in VNS non-responders. We also observed that the modularity and transitivity in three frequency bands and CPL in delta and beta bands were significantly different in controls than those found in responders or non-responders, although the values of the graph measures in controls were closer to those of responders than non-responders. We used the modularity and transitivity as input features of a naïve Bayes classifier, and achieved an accuracy of 87% in classification of non-responders, responders, and controls. The results of this study revealed that MEG-based graph measures are reliable biomarkers, and that these measures may be used to predict seizure outcome of VNS treatment.

Propofol-induced sedation diminishes the strength of frontal-parietal-occipital EEG network

The level of conscious experience can be effectively and reversibly altered by the administration of sedative agents. Several studies attempted to explore the variations in frontal-parietal network during propofol-induced sedation. However, contradictory outcomes warrant further investigations. In this study, we implemented the Neural Gas algorithm-based delay symbolic transfer entropy (NG-dSTE) for investigation of frontal-parietal-occipital (F-P-O) network using scalp EEG signals recorded during altered levels of consciousness. Our results show significant disruption of the F-P-O network during mild and moderate levels of propofol sedation. In particular, the interaction between frontal and parietal-occipital region is highly disturbed. Moreover, we found measurable effect of sedation on local interactions in the frontal network whereas parietal-occipital network experienced least variations. The results support the conclusion that the connectivity based features can be utilized as reliable biomarker for assessment of sedation levels effectively.

Electroencephalographic markers of brain development during sevoflurane anaesthesia in children up to 3 years old

BACKGROUND

General anaesthetics generate spatially defined brain oscillations in the EEG that relate fundamentally to neural-circuit architecture. Few studies detailing the neural-circuit activity of general anaesthesia in children have been described. The study aim was to identify age-related changes in EEG characteristics that mirror different stages of early human brain development during sevoflurane anaesthesia.

METHODS

Multichannel EEG recordings were performed in 91 children aged 0-3 yr undergoing elective surgery. We mapped spatial power and coherence over the frontal, parietal, temporal, and occipital cortices during maintenance anaesthesia.

RESULTS

During sevoflurane exposure: (i) slow-delta (0.1-4 Hz) oscillations were present in all ages, (ii) theta (4-8 Hz) and alpha (8-12 Hz) oscillations emerge by ∼4 months, (iii) alpha oscillations increased in power from 4 to 10 months, (iv) frontal alpha-oscillation predominance emerged at ∼6 months, (v) frontal slow oscillations were coherent from birth until 6 months, and (vi) frontal alpha oscillations became coherent ∼10 months and persisted in older ages.

CONCLUSIONS

Key developmental milestones in the maturation of the thalamo-cortical circuitry likely generate changes in EEG patterns in infants undergoing sevoflurane general anaesthesia. Characterisation of anaesthesia-induced EEG oscillations in children demonstrates the importance of developing age-dependent strategies to monitor properly the brain states of children receiving general anaesthesia. These data have the potential to guide future studies investigating neurodevelopmental pathologies involving altered excitatory-inhibitory balance, such as epilepsy or Rett syndrome.

Presurgical thalamocortical connectivity is associated with response to vagus nerve stimulation in children with intractable epilepsy

Although chronic vagus nerve stimulation (VNS) is an established treatment for medically-intractable childhood epilepsy, there is considerable heterogeneity in seizure response and little data are available to pre-operatively identify patients who may benefit from treatment. Since the therapeutic effect of VNS may be mediated by afferent projections to the thalamus, we tested the hypothesis that intrinsic thalamocortical connectivity is associated with seizure response following chronic VNS in children with epilepsy. Twenty-one children (ages 5-21 years) with medically-intractable epilepsy underwent resting-state fMRI prior to implantation of VNS. Ten received sedation, while 11 did not. Whole brain connectivity to thalamic regions of interest was performed. Multivariate generalized linear models were used to correlate resting-state data with seizure outcomes, while adjusting for age and sedation status. A supervised support vector machine (SVM) algorithm was used to classify response to chronic VNS on the basis of intrinsic connectivity. Of the 21 subjects, 11 (52%) had 50% or greater improvement in seizure control after VNS. Enhanced connectivity of the thalami to the anterior cingulate cortex (ACC) and left insula was associated with greater VNS efficacy. Within our test cohort, SVM correctly classified response to chronic VNS with 86% accuracy. In an external cohort of 8 children, the predictive model correctly classified the seizure response with 88% accuracy. We find that enhanced intrinsic connectivity within thalamocortical circuitry is associated with seizure response following VNS. These results encourage the study of intrinsic connectivity to inform neural network-based, personalized treatment decisions for children with intractable epilepsy.

An unaware agenda: interictal consciousness impairments in epileptic patients

Consciousness impairments have been described as a cornerstone of epilepsy. Generalized seizures are usually characterized by a complete loss of consciousness, whereas focal seizures have more variable degrees of responsiveness. In addition to these impairments that occur during ictal episodes, alterations of consciousness have also been repeatedly observed between seizures (i.e. during interictal periods). In this opinion article, we review evidence supporting the novel hypothesis that epilepsy produces consciousness impairments which remain present interictally. Then, we discuss therapies aimed to reduce seizure frequency, which may modulate consciousness between epileptic seizures. We conclude with a consideration of relevant pathophysiological mechanisms. In particular, the thalamocortical network seems to be involved in both seizure generation and interictal consciousness impairments, which could inaugurate a promising translational agenda for epilepsy studies.

Large-scale signatures of unconsciousness are consistent with a departure from critical dynamics

Loss of cortical integration and changes in the dynamics of electrophysiological brain signals characterize the transition from wakefulness towards unconsciousness. In this study, we arrive at a basic model explaining these observations based on the theory of phase transitions in complex systems. We studied the link between spatial and temporal correlations of large-scale brain activity recorded with functional magnetic resonance imaging during wakefulness, propofol-induced sedation and loss of consciousness and during the subsequent recovery. We observed that during unconsciousness activity in frontothalamic regions exhibited a reduction of long-range temporal correlations and a departure of functional connectivity from anatomical constraints. A model of a system exhibiting a phase transition reproduced our findings, as well as the diminished sensitivity of the cortex to external perturbations during unconsciousness. This framework unifies different observations about brain activity during unconsciousness and predicts that the principles we identified are universal and independent from its causes.

Interhemispheric resting-state functional connectivity of the claustrum in the awake and anesthetized states

The claustrum is a brain region whose function remains unknown, though many investigators suggest it plays a role in conscious attention. Resting-state functional magnetic resonance imaging (RS-fMRI) has revealed how anesthesia alters many functional connections in the brain, but the functional role of the claustrum with respect to the awake versus anesthetized states remains unknown. Therefore, we employed a combination of seed-based RS-fMRI and neuroanatomical tracing to reveal how the anatomical connections of the claustrum are related to its functional connectivity during quiet wakefulness and the isoflurane-induced anesthetic state. In awake rats, RS-fMRI indicates that the claustrum has interhemispheric functional connections with the mediodorsal thalamus (MD) and medial prefrontal cortex (mPFC), as well as other known connections with cortical areas that correspond to the connections revealed by neuroanatomical tracing. During deep isoflurane anesthesia, the functional connections of the claustrum with mPFC and MD were significantly attenuated, while those with the rest of cortex were not significantly altered. These changes in claustral functional connectivity were also observed when seeds were placed in mPFC or MD during RS-fMRI comparisons of the awake and deeply anesthetized states. Collectively, these data indicate that the claustrum has functional connections with mPFC and MD-thalamus that are significantly lessened by anesthesia.