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Disentangling how cognitive functions emerge from the interplay of brain dynamics and network architecture is among the major challenges that neuroscientists face. Pharmacological and pathological perturbations of consciousness provide a lens to investigate these complex challenges. Here, we review how recent advances about consciousness and the brain's functional organisation have been driven by a common denominator: decomposing brain function into fundamental constituents of time, space, and information. Whereas unconsciousness increases structure-function coupling across scales, psychedelics may decouple brain function from structure. Convergent effects also emerge: anaesthetics, psychedelics, and disorders of consciousness can exhibit similar reconfigurations of the brain's unimodal-transmodal functional axis. Decomposition approaches reveal the potential to translate discoveries across species, with computational modelling providing a path towards mechanistic integration., Competing Interests: Declaration of interests The authors have no competing interests to declare., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Mind-blanking (MB) is termed as the inability to report our immediate-past mental content. In contrast to mental states with reportable content, such as mind-wandering or sensory perceptions, the neural correlates of MB started getting elucidated only recently. A notable particularity that pertains to MB studies is the way MB is instructed for reporting, like by deliberately asking participants to "empty their minds." Such instructions were shown to induce fMRI activations in frontal brain regions, typically associated with metacognition and self-evaluative processes, suggesting that MB may be a result of intentional mental content suppression. Here, we aim at examining this hypothesis by determining the neural correlates of MB without induction. Using fMRI combined with experience-sampling in 31 participants (22 female), univariate analysis of MB reports revealed deactivations in occipital, frontal, parietal, and thalamic areas, but no activations in prefrontal regions. These findings were confirmed using Bayesian region-of-interest analysis on areas previously shown to be implicated in induced MB, where we report evidence for frontal deactivations during MB reports compared with other mental states. Contrast analysis between reports of MB and content-oriented mental states also revealed deactivations in the left angular gyrus. We propose that these effects characterize a neuronal profile of MB, where key thalamocortical nodes are unable to communicate and formulate reportable content. Collectively, we show that study instructions for MB lead to differential neural activation. These results provide mechanistic insights linked to the phenomenology of MB and point to the possibility of MB being expressed in different forms. SIGNIFICANCE STATEMENT This study explores how brain activity changes when individuals report unidentifiable thoughts, a phenomenon known as mind-blanking (MB). It aims to detect changes in brain activations and deactivations when MB is reported spontaneously, as opposed to the neural responses that have been previously reported when MB is induced. By means of brain imaging and experience-sampling, the study points to reduced brain activity in a wide number of regions, including those mesio-frontally which were previously detected as activated during induced MB. These results enhance our understanding of the complexity of spontaneous thinking and contribute to broader discussions on consciousness and reportable experience., (Copyright © 2023 the authors.)

Consciousness transiently fades away during deep sleep, more stably under anesthesia, and sometimes permanently due to brain injury. The development of an index to quantify the level of consciousness across these different states is regarded as a key problem both in basic and clinical neuroscience. We argue that this problem is ill-defined since such an index would not exhaust all the relevant information about a given state of consciousness. While the level of consciousness can be taken to describe the actual brain state, a complete characterization should also include its potential behavior against external perturbations. We developed and analyzed whole-brain computational models to show that the stability of conscious states provides information complementary to their similarity to conscious wakefulness. Our work leads to a novel methodological framework to sort out different brain states by their stability and reversibility, and illustrates its usefulness to dissociate between physiological (sleep), pathological (brain-injured patients), and pharmacologically-induced (anesthesia) loss of consciousness., Competing Interests: The authors have declared that no competing interests exist.

Recent evidence on resting-state functional magnetic resonance imaging (rs-fMRI) suggests that healthy human brains have a temporal organization represented in a widely complex time-delay structure. This structure seems to underlie brain communication flow, integration/propagation of brain activity, as well as information processing. Therefore, it is probably linked to the emergence of highly coordinated complex brain phenomena, such as consciousness. Nevertheless, possible changes in this structure during an altered state of consciousness remain poorly investigated. In this work, we hypothesized that due to a disruption in high-order functions and alterations of the brain communication flow, patients with disorders of consciousness (DOC) might exhibit changes in their time-delay structure of spontaneous brain activity. We explored this hypothesis by comparing the time-delay projections from fMRI resting-state data acquired in resting state from 48 patients with DOC and 27 healthy controls (HC) subjects. Results suggest that time-delay structure modifies for patients with DOC conditions when compared with HC. Specifically, the average value and the directionality of latency inside the midcingulate cortex (mCC) shift with the level of consciousness. In particular, positive values of latency inside the mCC relate to preserved states of consciousness, whereas negative values change proportionally with the level of consciousness in patients with DOC. These results suggest that the mCC may play a critical role as an integrator of brain activity in HC subjects, but this role vanishes in an altered state of consciousness.

Introduction: Functional connectivity alterations within individual resting state networks (RSNs) are linked to disorders of consciousness (DOC). If these alterations influence the interaction quality with other RNSs, then, brain alterations in patients with DOC would be characterized by connectivity changes in the large-scale model composed of RSNs. How are functional interactions between RSNs influenced by internal alterations of individual RSNs? Do the functional alterations induced by DOC change some key properties of the large-scale network, which have been suggested to be critical for the consciousness emergence? Here, we use network analysis to measure functional connectivity in patients with DOC and address these questions. We hypothesized that network properties provide descriptions of brain functional reconfiguration associated with consciousness alterations., Methods: We apply nodal and global network measurements to study the reconfiguration linked with the disease severity. We study changes in integration, segregation, and centrality properties of the functional connectivity between the RSNs in subjects with different levels of consciousness., Results: Our analysis indicates that nodal measurements are more sensitive to disease severity than global measurements, particularly, for functional connectivity of sensory and cognitively related RSNs., Conclusion: The network property alterations of functional connectivity in different consciousness levels suggest a whole-brain topological reorganization of the large-scale functional connectivity in patients with DOC., (© 2019 The Authors. Brain and Behavior published by Wiley Periodicals, Inc.)

Adopting the framework of brain dynamics as a cornerstone of human consciousness, we determined whether dynamic signal coordination provides specific and generalizable patterns pertaining to conscious and unconscious states after brain damage. A dynamic pattern of coordinated and anticoordinated functional magnetic resonance imaging signals characterized healthy individuals and minimally conscious patients. The brains of unresponsive patients showed primarily a pattern of low interareal phase coherence mainly mediated by structural connectivity, and had smaller chances to transition between patterns. The complex pattern was further corroborated in patients with covert cognition, who could perform neuroimaging mental imagery tasks, validating this pattern's implication in consciousness. Anesthesia increased the probability of the less complex pattern to equal levels, validating its implication in unconsciousness. Our results establish that consciousness rests on the brain's ability to sustain rich brain dynamics and pave the way for determining specific and generalizable fingerprints of conscious and unconscious states.

Objective: The relationship between residual brain tissue in patients with disorders of consciousness (DOC) and the clinical condition is unclear. This observational study aimed to quantify gray (GM) and white matter (WM) atrophy in states of (altered) consciousness., Methods: Structural T1-weighted magnetic resonance images were processed for 102 severely brain-injured and 52 healthy subjects. Regional brain volume was quantified for 158 (sub)cortical regions using Freesurfer. The relationship between regional brain volume and clinical characteristics of patients with DOC and conscious brain-injured patients was assessed using a linear mixed-effects model. Classification of patients with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) using regional volumetric information was performed and compared to classification using cerebral glucose uptake from fluorodeoxyglucose positron emission tomography. For validation, the T1-based classifier was tested on independent datasets., Results: Patients were characterized by smaller regional brain volumes than healthy subjects. Atrophy occurred faster in UWS compared to MCS (GM) and conscious (GM and WM) patients. Classification was successful (misclassification with leave-one-out cross-validation between 2% and 13%) and generalized to the independent data set with an area under the receiver operator curve of 79% (95% confidence interval [CI; 67-91.5]) for GM and 70% (95% CI [55.6-85.4]) for WM., Interpretation: Brain volumetry at the single-subject level reveals that regions in the default mode network and subcortical gray matter regions, as well as white matter regions involved in long range connectivity, are most important to distinguish levels of consciousness. Our findings suggest that changes of brain structure provide information in addition to the assessment of functional neuroimaging and thus should be evaluated as well. Ann Neurol 2018;83:842-853., (© 2018 American Neurological Association.)

Purpose To assess whether early brain functional connectivity is associated with functional recovery 1 year after cardiac arrest (CA). Materials and Methods Enrolled in this prospective multicenter cohort were 46 patients who were comatose after CA. Principal outcome was cerebral performance category at 12 months, with favorable outcome (FO) defined as cerebral performance category 1 or 2. All participants underwent multiparametric structural and functional magnetic resonance (MR) imaging less than 4 weeks after CA. Within- and between-network connectivity was measured in dorsal attention network (DAN), default-mode network (DMN), salience network (SN), and executive control network (ECN) by using seed-based analysis of resting-state functional MR imaging data. Structural changes identified with fluid-attenuated inversion recovery and diffusion-weighted imaging sequences were analyzed by using validated morphologic scales. The association between connectivity measures, structural changes, and the principal outcome was explored with multivariable modeling. Results Patients underwent MR imaging a mean 12.6 days ± 5.6 (standard deviation) after CA. At 12 months, 11 patients had an FO. Patients with FO had higher within-DMN connectivity and greater anticorrelation between SN and DMN and between SN and ECN compared with patients with unfavorable outcome, an effect that was maintained after multivariable adjustment. Anticorrelation of SN-DMN predicted outcomes with higher accuracy than fluid-attenuated inversion recovery or diffusion-weighted imaging scores (area under the receiver operating characteristic curves, respectively, 0.88, 0.74, and 0.71). Conclusion MR imaging-based measures of cerebral functional network connectivity obtained in the acute phase of CA were independently associated with FO at 1 year, warranting validation as early markers of long-term recovery potential in patients with anoxic-ischemic encephalopathy. © RSNA, 2017.

Microgravity, confinement, isolation, and immobilization are just some of the features astronauts have to cope with during space missions. Consequently, long-duration space travel can have detrimental effects on human physiology. Although research has focused on the cardiovascular and musculoskeletal system in particular, the exact impact of spaceflight on the human central nervous system remains to be determined. Previous studies have reported psychological problems, cephalic fluid shifts, neurovestibular problems, and cognitive alterations, but there is paucity in the knowledge of the underlying neural substrates. Previous space analogue studies and preliminary spaceflight studies have shown an involvement of the cerebellum, cortical sensorimotor, and somatosensory areas and the vestibular pathways. Extending this knowledge is crucial, especially in view of long-duration interplanetary missions (e.g., Mars missions) and space tourism. In addition, the acquired insight could be relevant for vestibular patients, patients with neurodegenerative disorders, as well as the elderly population, coping with multisensory deficit syndromes, immobilization, and inactivity.

Objective: We here aimed at characterizing heart-brain interactions in patients with disorders of consciousness. We tested how this information impacts data-driven classification between unresponsive and minimally conscious patients., Methods: A cohort of 127 patients in vegetative state/unresponsive wakefulness syndrome (VS/UWS; n = 70) and minimally conscious state (MCS; n = 57) were presented with the local-global auditory oddball paradigm, which distinguishes 2 levels of processing: short-term deviation of local auditory regularities and global long-term rule violations. In addition to previously validated markers of consciousness extracted from electroencephalograms (EEG), we computed autonomic cardiac markers, such as heart rate (HR) and HR variability (HRV), and cardiac cycle phase shifts triggered by the processing of the auditory stimuli., Results: HR and HRV were similar in patients across groups. The cardiac cycle was not sensitive to the processing of local regularities in either the VS/UWS or MCS patients. In contrast, global regularities induced a phase shift of the cardiac cycle exclusively in the MCS group. The interval between the auditory stimulation and the following R peak was significantly shortened in MCS when the auditory rule was violated. When the information for the cardiac cycle modulations and other consciousness-related EEG markers were combined, single patient classification performance was enhanced compared to classification with solely EEG markers., Interpretation: Our work shows a link between residual cognitive processing and the modulation of autonomic somatic markers. These results open a new window to evaluate patients with disorders of consciousness via the embodied paradigm, according to which body-brain functions contribute to a holistic approach to conscious processing. Ann Neurol 2017;82:578-591., (© 2017 American Neurological Association.)

Background: We used functional connectivity measures from brain resting state functional magnetic resonance imaging to identify human neural correlates of sedation with dexmedetomidine or propofol and their similarities with natural sleep., Methods: Connectivity within the resting state networks that are proposed to sustain consciousness generation was compared between deep non-rapid-eye-movement (N3) sleep, dexmedetomidine sedation, and propofol sedation in volunteers who became unresponsive to verbal command. A newly acquired dexmedetomidine dataset was compared with our previously published propofol and N3 sleep datasets., Results: In all three unresponsive states (dexmedetomidine sedation, propofol sedation, and N3 sleep), within-network functional connectivity, including thalamic functional connectivity in the higher-order (default mode, executive control, and salience) networks, was significantly reduced as compared with the wake state. Thalamic functional connectivity was not reduced for unresponsive states within lower-order (auditory, sensorimotor, and visual) networks. Voxel-wise statistical comparisons between the different unresponsive states revealed that thalamic functional connectivity with the medial prefrontal/anterior cingulate cortex and with the mesopontine area was reduced least during dexmedetomidine-induced unresponsiveness and most during propofol-induced unresponsiveness. The reduction seen during N3 sleep was intermediate between those of dexmedetomidine and propofol., Conclusions: Thalamic connectivity with key nodes of arousal and saliency detection networks was relatively preserved during N3 sleep and dexmedetomidine-induced unresponsiveness as compared to propofol. These network effects may explain the rapid recovery of oriented responsiveness to external stimulation seen under dexmedetomidine sedation., Trial Registry Number: Committee number: 'Comité d'Ethique Hospitalo-Facultaire Universitaire de Liège' (707); EudraCT number: 2012-003562-40; internal reference: 20121/135; accepted on August 31, 2012; Chair: Prof G. Rorive. As it was considered a phase I clinical trial, this protocol does not appear on the EudraCT public website., (© The Author 2017. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com)

Introduction: Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non-contiguous regions. To date, the spatial patterns of the networks have been analyzed with techniques developed for volumetric data., Objective: Here, we detail a graph building technique that allows these ICNs to be analyzed with graph theory., Methods: First, ICA was performed at the single-subject level in 15 healthy volunteers using a 3T MRI scanner. The identification of nine networks was performed by a multiple-template matching procedure and a subsequent component classification based on the network "neuronal" properties. Second, for each of the identified networks, the nodes were defined as 1,015 anatomically parcellated regions. Third, between-node functional connectivity was established by building edge weights for each networks. Group-level graph analysis was finally performed for each network and compared to the classical network., Results: Network graph comparison between the classically constructed network and the nine networks showed significant differences in the auditory and visual medial networks with regard to the average degree and the number of edges, while the visual lateral network showed a significant difference in the small-worldness., Conclusions: This novel approach permits us to take advantage of the well-recognized power of ICA in BOLD signal decomposition and, at the same time, to make use of well-established graph measures to evaluate connectivity differences. Moreover, by providing a graph for each separate network, it can offer the possibility to extract graph measures in a specific way for each network. This increased specificity could be relevant for studying pathological brain activity or altered states of consciousness as induced by anesthesia or sleep, where specific networks are known to be altered in different strength.

Background: To reduce head movement during resting state functional magnetic resonance imaging, post-coma patients with disorders of consciousness (DOC) are frequently sedated with propofol. However, little is known about the effects of this sedation on the brain connectivity patterns in the damaged brain essential for differential diagnosis. In this study, we aimed to assess these effects., Methods: Using resting state functional magnetic resonance imaging 3T data obtained over several years of scanning patients for diagnostic and research purposes, we employed a seed-based approach to examine resting state connectivity in higher-order (default mode, bilateral external control, and salience) and lower-order (auditory, sensorimotor, and visual) resting state networks and connectivity with the thalamus, in 20 healthy unsedated controls, 8 unsedated patients with DOC, and 8 patients with DOC sedated with propofol. The DOC groups were matched for age at onset, etiology, time spent in DOC, diagnosis, standardized behavioral assessment scores, movement intensities, and pattern of structural brain injury (as assessed with T1-based voxel-based morphometry)., Results: DOC were associated with severely impaired resting state network connectivity in all but the visual network. Thalamic connectivity to higher-order network regions was also reduced. Propofol administration to patients was associated with minor further decreases in thalamic and insular connectivity., Conclusions: Our findings indicate that connectivity decreases associated with propofol sedation, involving the thalamus and insula, are relatively small compared with those already caused by DOC-associated structural brain injury. Nonetheless, given the known importance of the thalamus in brain arousal, its disruption could well reflect the diminished movement obtained in these patients. However, more research is needed on this topic to fully address the research question.

Background: Consciousness-altering anesthetic agents disturb connectivity between brain regions composing the resting-state consciousness networks (RSNs). The default mode network (DMn), executive control network, salience network (SALn), auditory network, sensorimotor network (SMn), and visual network sustain mentation. Ketamine modifies consciousness differently from other agents, producing psychedelic dreaming and no apparent interaction with the environment. The authors used functional magnetic resonance imaging to explore ketamine-induced changes in RSNs connectivity., Methods: Fourteen healthy volunteers received stepwise intravenous infusions of ketamine up to loss of responsiveness. Because of agitation, data from six subjects were excluded from analysis. RSNs connectivity was compared between absence of ketamine (wake state [W1]), light ketamine sedation, and ketamine-induced unresponsiveness (deep sedation [S2])., Results: Increasing the depth of ketamine sedation from W1 to S2 altered DMn and SALn connectivity and suppressed the anticorrelated activity between DMn and other brain regions. During S2, DMn connectivity, particularly between the medial prefrontal cortex and the remaining network (effect size β [95% CI]: W1 = 0.20 [0.18 to 0.22]; S2 = 0.07 [0.04 to 0.09]), and DMn anticorrelated activity (e.g., right sensory cortex: W1 = -0.07 [-0.09 to -0.04]; S2 = 0.04 [0.01 to 0.06]) were broken down. SALn connectivity was nonuniformly suppressed (e.g., left parietal operculum: W1 = 0.08 [0.06 to 0.09]; S2 = 0.05 [0.02 to 0.07]). Executive control networks, auditory network, SMn, and visual network were minimally affected., Conclusions: Ketamine induces specific changes in connectivity within and between RSNs. Breakdown of frontoparietal DMn connectivity and DMn anticorrelation and sensory and SMn connectivity preservation are common to ketamine and propofol-induced alterations of consciousness.

To date, hampered physiological function after exposure to microgravity has been primarily attributed to deprived peripheral neuro-sensory systems. For the first time, this study elucidates alterations in human brain function after long-duration spaceflight. More specifically, we found significant differences in resting-state functional connectivity between motor cortex and cerebellum, as well as changes within the default mode network. In addition, the cosmonaut showed changes in the supplementary motor areas during a motor imagery task. These results highlight the underlying neural basis for the observed physiological deconditioning due to spaceflight and are relevant for future interplanetary missions and vestibular patients.

Propofol is one of the most commonly used anesthetics in the world, but much remains unknown about the mechanisms by which it induces loss of consciousness. In this resting-state functional magnetic resonance imaging study, we examined qualitative and quantitative changes of resting-state networks (RSNs), total brain connectivity, and mean oscillation frequencies of the regional blood oxygenation level-dependent (BOLD) signal, associated with propofol-induced mild sedation and loss of responsiveness in healthy subjects. We found that detectability of RSNs diminished significantly with loss of responsiveness, and total brain connectivity decreased strongly in the frontal cortex, which was associated with increased mean oscillation frequencies of the BOLD signal. Our results suggest a pivotal role of the frontal cortex in propofol-induced loss of responsiveness.

Introduction: The mildly invasive 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established imaging technique to measure 'resting state' cerebral metabolism. This technique made it possible to assess changes in metabolic activity in clinical applications, such as the study of severe brain injury and disorders of consciousness., Objective: We assessed the possibility of creating functional MRI activity maps, which could estimate the relative levels of activity in FDG-PET cerebral metabolic maps. If no metabolic absolute measures can be extracted, our approach may still be of clinical use in centers without access to FDG-PET. It also overcomes the problem of recognizing individual networks of independent component selection in functional magnetic resonance imaging (fMRI) resting state analysis., Methods: We extracted resting state fMRI functional connectivity maps using independent component analysis and combined only components of neuronal origin. To assess neuronality of components a classification based on support vector machine (SVM) was used. We compared the generated maps with the FDG-PET maps in 16 healthy controls, 11 vegetative state/unresponsive wakefulness syndrome patients and four locked-in patients., Results: The results show a significant similarity with ρ = 0.75 ± 0.05 for healthy controls and ρ = 0.58 ± 0.09 for vegetative state/unresponsive wakefulness syndrome patients between the FDG-PET and the fMRI based maps. FDG-PET, fMRI neuronal maps, and the conjunction analysis show decreases in frontoparietal and medial regions in vegetative patients with respect to controls. Subsequent analysis in locked-in syndrome patients produced also consistent maps with healthy controls., Conclusions: The constructed resting state fMRI functional connectivity map points toward the possibility for fMRI resting state to estimate relative levels of activity in a metabolic map.

Despite advances in resting state functional magnetic resonance imaging investigations, clinicians remain with the challenge of how to implement this paradigm on an individualized basis. Here, we assessed the clinical relevance of resting state functional magnetic resonance imaging acquisitions in patients with disorders of consciousness by means of a systems-level approach. Three clinical centres collected data from 73 patients in minimally conscious state, vegetative state/unresponsive wakefulness syndrome and coma. The main analysis was performed on the data set coming from one centre (Liège) including 51 patients (26 minimally conscious state, 19 vegetative state/unresponsive wakefulness syndrome, six coma; 15 females; mean age 49 ± 18 years, range 11-87; 16 traumatic, 32 non-traumatic of which 13 anoxic, three mixed; 35 patients assessed >1 month post-insult) for whom the clinical diagnosis with the Coma Recovery Scale-Revised was congruent with positron emission tomography scanning. Group-level functional connectivity was investigated for the default mode, frontoparietal, salience, auditory, sensorimotor and visual networks using a multiple-seed correlation approach. Between-group inferential statistics and machine learning were used to identify each network's capacity to discriminate between patients in minimally conscious state and vegetative state/unresponsive wakefulness syndrome. Data collected from 22 patients scanned in two other centres (Salzburg: 10 minimally conscious state, five vegetative state/unresponsive wakefulness syndrome; New York: five minimally conscious state, one vegetative state/unresponsive wakefulness syndrome, one emerged from minimally conscious state) were used to validate the classification with the selected features. Coma Recovery Scale-Revised total scores correlated with key regions of each network reflecting their involvement in consciousness-related processes. All networks had a high discriminative capacity (>80%) for separating patients in a minimally conscious state and vegetative state/unresponsive wakefulness syndrome. Among them, the auditory network was ranked the most highly. The regions of the auditory network which were more functionally connected in patients in minimally conscious state compared to vegetative state/unresponsive wakefulness syndrome encompassed bilateral auditory and visual cortices. Connectivity values in these three regions discriminated congruently 20 of 22 independently assessed patients. Our findings point to the significance of preserved abilities for multisensory integration and top-down processing in minimal consciousness seemingly supported by auditory-visual crossmodal connectivity, and promote the clinical utility of the resting paradigm for single-patient diagnostics., (© The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Introduction: In healthy conditions, group-level fMRI resting state analyses identify ten resting state networks (RSNs) of cognitive relevance. Here, we aim to assess the ten-network model in severely brain-injured patients suffering from disorders of consciousness and to identify those networks which will be most relevant to discriminate between patients and healthy subjects., Methods: 300 fMRI volumes were obtained in 27 healthy controls and 53 patients in minimally conscious state (MCS), vegetative state/unresponsive wakefulness syndrome (VS/UWS) and coma. Independent component analysis (ICA) reduced data dimensionality. The ten networks were identified by means of a multiple template-matching procedure and were tested on neuronality properties (neuronal vs non-neuronal) in a data-driven way. Univariate analyses detected between-group differences in networks' neuronal properties and estimated voxel-wise functional connectivity in the networks, which were significantly less identifiable in patients. A nearest-neighbor "clinical" classifier was used to determine the networks with high between-group discriminative accuracy., Results: Healthy controls were characterized by more neuronal components compared to patients in VS/UWS and in coma. Compared to healthy controls, fewer patients in MCS and VS/UWS showed components of neuronal origin for the left executive control network, default mode network (DMN), auditory, and right executive control network. The "clinical" classifier indicated the DMN and auditory network with the highest accuracy (85.3%) in discriminating patients from healthy subjects., Conclusions: FMRI multiple-network resting state connectivity is disrupted in severely brain-injured patients suffering from disorders of consciousness. When performing ICA, multiple-network testing and control for neuronal properties of the identified RSNs can advance fMRI system-level characterization. Automatic data-driven patient classification is the first step towards future single-subject objective diagnostics based on fMRI resting state acquisitions., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Functional neuroimaging shows that patients with disorders of consciousness exhibit disrupted system-level functional connectivity. Unresponsive/"vegetative state" patients preserve wakefulness networks of brainstem and basal forebrain but the cerebral networks accounting for external perceptual awareness and internal self-related mentation are disrupted. Specifically, the 'external awareness' network encompassing lateral fronto-temporo-parietal cortices bilaterally, and the 'internal awareness' network including midline anterior cingulate/mesiofrontal and posterior cingulate/precuneal cortices, are functionally disconnected. By contrast, patients in minimally conscious state 'minus', who show non-reflex behaviors, are characterized by right-lateralized recovery of the external awareness network. Similarly, patients who evolve to minimally conscious state 'plus' and respond to commands recover the dominant left-lateralized language network. Now, the use of active experimental paradigms targeting at detecting motor-independent signs of awareness or even establishing communication with these patients, challenge these two clinical boundaries. Such advances are naturally accompanied by legitimate neuroscientific and ethical queries demanding our attention on the medical implementations of this new knowledge., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Patients in a minimally conscious state (MCS) show restricted signs of awareness but are unable to communicate. We assessed cerebral glucose metabolism in MCS patients and tested the hypothesis that this entity can be subcategorized into MCS- (i.e., patients only showing nonreflex behavior such as visual pursuit, localization of noxious stimulation and/or contingent behavior) and MCS+ (i.e., patients showing command following).Patterns of cerebral glucose metabolism were studied using [(18)F]-fluorodeoxyglucose-PET in 39 healthy volunteers (aged 46 ± 18 years) and 27 MCS patients of whom 13 were MCS- (aged 49 ± 19 years; 4 traumatic; 21 ± 23 months post injury) and 14 MCS+ (aged 43 ± 19 years; 5 traumatic; 19 ± 26 months post injury). Results were thresholded for significance at false discovery rate corrected p < 0.05.We observed a metabolic impairment in a bilateral subcortical (thalamus and caudate) and cortical (fronto-temporo-parietal) network in nontraumatic and traumatic MCS patients. Compared to MCS-, patients in MCS+ showed higher cerebral metabolism in left-sided cortical areas encompassing the language network, premotor, presupplementary motor, and sensorimotor cortices. A functional connectivity study showed that Broca's region was disconnected from the rest of the language network, mesiofrontal and cerebellar areas in MCS- as compared to MCS+ patients.The proposed subcategorization of MCS based on the presence or absence of command following showed a different functional neuroanatomy. MCS- is characterized by preserved right hemispheric cortical metabolism interpreted as evidence of residual sensory consciousness. MCS+ patients showed preserved metabolism and functional connectivity in language networks arguably reflecting some additional higher order or extended consciousness albeit devoid of clinical verbal or nonverbal expression.

Objective: An extrinsic cerebral network (encompassing lateral frontoparietal cortices) related to external/sensory awareness and an intrinsic midline network related to internal/self-awareness have been identified recently. This study measured brain metabolism in both networks in patients with severe brain damage., Design: Prospective [18F]-fluorodeoxyglucose-positron emission tomography and Coma Recovery Scale-Revised assessments in a university hospital setting., Subjects: Healthy volunteers and patients in vegetative state/unresponsive wakefulness syndrome (VS/UWS), minimally conscious state (MCS), emergence from MCS (EMCS), and locked-in syndrome (LIS)., Results: A total of 70 patients were included in the study: 24 VS/UWS, 28 MCS, 10 EMCS, 8 LIS and 39 age-matched controls. VS/UWS showed metabolic dysfunction in extrinsic and intrinsic networks and thalami. MCS showed dysfunction mostly in intrinsic network and thalami. EMCS showed impairment in posterior cingulate/retrosplenial cortices. LIS showed dysfunction only in infratentorial regions. Coma Recovery Scale-Revised total scores correlated with metabolic activity in both extrinsic and part of the intrinsic network and thalami., Conclusion: Progressive recovery of extrinsic and intrinsic awareness network activity was observed in severely brain-damaged patients, ranging from VS/UWS, MCS, EMCS to LIS. The predominance of intrinsic network impairment in MCS could reflect altered internal/self-awareness in these patients, which is difficult to quantify at the bedside.

Objectives: Recent fMRI studies have shown that it is possible to reliably identify the default-mode network (DMN) in the absence of any task, by resting-state connectivity analyses in healthy volunteers. We here aimed to identify the DMN in the challenging patient population of disorders of consciousness encountered following coma., Experimental Design: A spatial independent component analysis-based methodology permitted DMN assessment, decomposing connectivity in all its different sources either neuronal or artifactual. Three different selection criteria were introduced assessing anticorrelation-corrected connectivity with or without an automatic masking procedure and calculating connectivity scores encompassing both spatial and temporal properties. These three methods were validated on 10 healthy controls and applied to an independent group of 8 healthy controls and 11 severely brain-damaged patients [locked-in syndrome (n = 2), minimally conscious (n = 1), and vegetative state (n = 8)]., Principal Observations: All vegetative patients showed fewer connections in the default-mode areas, when compared with controls, contrary to locked-in patients who showed near-normal connectivity. In the minimally conscious-state patient, only the two selection criteria considering both spatial and temporal properties were able to identify an intact right lateralized BOLD connectivity pattern, and metabolic PET data suggested its neuronal origin., Conclusions: When assessing resting-state connectivity in patients with disorders of consciousness, it is important to use a methodology excluding non-neuronal contributions caused by head motion, respiration, and heart rate artifacts encountered in all studied patients., (Copyright © 2011 Wiley Periodicals, Inc.)

The underlying functional neuroanatomy of tinnitus remains poorly understood. Few studies have focused on functional cerebral connectivity changes in tinnitus patients. The aim of this study was to test if functional MRI "resting-state" connectivity patterns in auditory network differ between tinnitus patients and normal controls. Thirteen chronic tinnitus subjects and fifteen age-matched healthy controls were studied on a 3 tesla MRI. Connectivity was investigated using independent component analysis and an automated component selection approach taking into account the spatial and temporal properties of each component. Connectivity in extra-auditory regions such as brainstem, basal ganglia/NAc, cerebellum, parahippocampal, right prefrontal, parietal, and sensorimotor areas was found to be increased in tinnitus subjects. The right primary auditory cortex, left prefrontal, left fusiform gyrus, and bilateral occipital regions showed a decreased connectivity in tinnitus. These results show that there is a modification of cortical and subcortical functional connectivity in tinnitus encompassing attentional, mnemonic, and emotional networks. Our data corroborate the hypothesized implication of non-auditory regions in tinnitus physiopathology and suggest that various regions of the brain seem involved in the persistent awareness of the phenomenon as well as in the development of the associated distress leading to disabling chronic tinnitus.

Evidence from functional neuroimaging studies on resting state suggests that there are two distinct anticorrelated cortical systems that mediate conscious awareness: an "extrinsic" system that encompasses lateral fronto-parietal areas and has been linked with processes of external input (external awareness), and an "intrinsic" system which encompasses mainly medial brain areas and has been associated with internal processes (internal awareness). The aim of our study was to explore the neural correlates of resting state by providing behavioral and neuroimaging data from healthy volunteers. With no a priori assumptions, we first determined behaviorally the relationship between external and internal awareness in 31 subjects. We found a significant anticorrelation between external and internal awareness with a mean switching frequency of 0.05 Hz (range: 0.01-0.1 Hz). Interestingly, this frequency is similar to BOLD fMRI slow oscillations. We then evaluated 22 healthy volunteers in an fMRI paradigm looking for brain areas where BOLD activity correlated with "internal" and "external" scores. Activation of precuneus/posterior cingulate, anterior cingulate/mesiofrontal cortices, and parahippocampal areas ("intrinsic system") was linearly linked to intensity of internal awareness, whereas activation of lateral fronto-parietal cortices ("extrinsic system") was linearly associated with intensity of external awareness.

Resting state fMRI (functional magnetic resonance imaging) acquisitions are characterized by low-frequency spontaneous activity in a default mode network (encompassing medial brain areas and linked to self-related processes) and an anticorrelated "extrinsic" system (encompassing lateral frontoparietal areas and modulated via external sensory stimulation). In order to better determine the functional contribution of these networks to conscious awareness, we here sought to transiently modulate their relationship by means of hypnosis. We used independent component analysis (ICA) on resting state fMRI acquisitions during normal wakefulness, under hypnotic state, and during a control condition of autobiographical mental imagery. As compared to mental imagery, hypnosis-induced modulation of resting state fMRI networks resulted in a reduced "extrinsic" lateral frontoparietal cortical connectivity, possibly reflecting a decreased sensory awareness. The default mode network showed an increased connectivity in bilateral angular and middle frontal gyri, whereas its posterior midline and parahippocampal structures decreased their connectivity during hypnosis, supposedly related to an altered "self" awareness and posthypnotic amnesia. In our view, fMRI resting state studies of physiological (e.g., sleep or hypnosis), pharmacological (e.g., sedation or anesthesia), and pathological modulation (e.g., coma or related states) of "intrinsic" default mode and anticorrelated "extrinsic" sensory networks, and their interaction with other cerebral networks, will further improve our understanding of the neural correlates of subjective awareness., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Recent advances in the study of spontaneous brain activity have demonstrated activity patterns that emerge with no task performance or sensory stimulation; these discoveries hold promise for the study of higher-order associative network functionality. Additionally, such advances are argued to be relevant in pathological states, such as disorders of consciousness (DOC), i.e., coma, vegetative and minimally conscious states. Recent studies on resting state activity in DOC, measured with functional magnetic resonance imaging (fMRI) techniques, show that functional connectivity is disrupted in the task-negative or the default mode network. However, the two main approaches employed in the analysis of resting state functional connectivity data (i.e., hypothesis-driven seed-voxel and data-driven independent component analysis) present multiple methodological difficulties, especially in non-collaborative DOC patients. Improvements in motion artifact removal and spatial normalization are needed before fMRI resting state data can be used as proper biomarkers in severe brain injury. However, we anticipate that such developments will boost clinical resting state fMRI studies, allowing for easy and fast acquisitions and ultimately improve the diagnosis and prognosis in the absence of DOC patients' active collaboration in data acquisition.

Monitoring the level of consciousness in brain-injured patients with disorders of consciousness is crucial as it provides diagnostic and prognostic information. Behavioral assessment remains the gold standard for assessing consciousness but previous studies have shown a high rate of misdiagnosis. This study aimed to investigate the usefulness of electroencephalography (EEG) entropy measurements in differentiating unconscious (coma or vegetative) from minimally conscious patients. Left fronto-temporal EEG recordings (10-minute resting state epochs) were prospectively obtained in 56 patients and 16 age-matched healthy volunteers. Patients were assessed in the acute (≤1 month post-injury; n=29) or chronic (>1 month post-injury; n=27) stage. The etiology was traumatic in 23 patients. Automated online EEG entropy calculations (providing an arbitrary value ranging from 0 to 91) were compared with behavioral assessments (Coma Recovery Scale-Revised) and outcome. EEG entropy correlated with Coma Recovery Scale total scores (r=0.49). Mean EEG entropy values were higher in minimally conscious (73±19; mean and standard deviation) than in vegetative/unresponsive wakefulness syndrome patients (45±28). Receiver operating characteristic analysis revealed an entropy cut-off value of 52 differentiating acute unconscious from minimally conscious patients (sensitivity 89% and specificity 90%). In chronic patients, entropy measurements offered no reliable diagnostic information. EEG entropy measurements did not allow prediction of outcome. User-independent time-frequency balanced spectral EEG entropy measurements seem to constitute an interesting diagnostic - albeit not prognostic - tool for assessing neural network complexity in disorders of consciousness in the acute setting. Future studies are needed before using this tool in routine clinical practice, and these should seek to improve automated EEG quantification paradigms in order to reduce the remaining false negative and false positive findings.

Background: Assessment of visual fixation is commonly used in the clinical examination of patients with disorders of consciousness. However, different international guidelines seem to disagree whether fixation is compatible with the diagnosis of the vegetative state (i.e., represents "automatic" subcortical processing) or is a sufficient sign of consciousness and higher order cortical processing., Methods: We here studied cerebral metabolism in ten patients with chronic post-anoxic encephalopathy and 39 age-matched healthy controls. Five patients were in a vegetative state (without fixation) and five presented visual fixation but otherwise showed all criteria typical of the vegetative state. Patients were matched for age, etiology and time since insult and were followed by repeated Coma Recovery Scale-Revised (CRS-R) assessments for at least 1 year. Sustained visual fixation was considered as present when the eyes refixated a moving target for more than 2 seconds as defined by CRS-R criteria., Results: Patients without fixation showed metabolic dysfunction in a widespread fronto-parietal cortical network (with only sparing of the brainstem and cerebellum) which was not different from the brain function seen in patients with visual fixation. Cortico-cortical functional connectivity with visual cortex showed no difference between both patient groups. Recovery rates did not differ between patients without or with fixation (none of the patients showed good outcome)., Conclusions: Our findings suggest that sustained visual fixation in (non-traumatic) disorders of consciousness does not necessarily reflect consciousness and higher order cortical brain function.

Disorders of consciousness (DOC) raise profound scientific, clinical, ethical, and philosophical issues. Growing knowledge on fundamental principles of brain organization in healthy individuals offers new opportunities for a better understanding of residual brain function in DOCs. We here discuss new perspectives derived from a recently proposed scheme of brain organization underlying consciousness in healthy individuals. In this scheme, thalamo-cortical networks can be divided into two, often antagonistic, global systems: (i) a system of externally oriented, sensory-motor networks (the "extrinsic" system); and (ii) a system of inward-oriented networks (the "intrinsic" or default system). According to this framework, four distinct mental states would be possible that could be relevant for understanding DOCs. In normal healthy volunteers and locked-in syndrome patients, a state of high functionality of both the extrinsic and intrinsic or default systems is expected--associated with full awareness of environment and self. In this case, mental imagery tasks combined with fMRI can be used to detect covert awareness in patients that are unable to communicate. According to the framework, two complementary states of system imbalance are also possible, in which one system is in a hyperfunctional state, while the other is hypoactive. Extrinsic system hyperfunction is expected to lead to a state of total sensory-motor "absorption" or "lost self." In contrast, intrinsic or default system hyperfunction is expected to lead to a state of complete detachment from the external world. A state where both extrinsic and intrinsic systems are hypofunctional is predicted to lead to markedly impaired consciousness as seen in DOCs. Finally, we review the potential use of ultra-slow fluctuations in BOLD signal as a tool for assessing the functional integrity of extrinsic and intrinsic systems during "resting state" fMRI acquisitions. In particular, we discuss the potential provided by assessment of these slow spontaneous BOLD fluctuations as a novel tool in assessing the cognitive state and chances of recovery from brain pathologies underlying DOCs.

The bedside detection of awareness in disorders of consciousness (DOC) caused by acquired brain injury is not an easy task. For this reason, differential diagnosis using neuroimaging and electrophysiological tools in search for objective markers of consciousness is being employed. However, such tools cannot be considered as diagnostic per se, but as assistants to the clinical evaluation, which, at present, remains the gold standard. Regarding therapeutic management in DOC, no evidence-based recommendations can be made in favor of a specific treatment. The present review summarizes clinical and paraclinical studies that have been conducted with neuroimaging and electrophysiological techniques in search of residual awareness in DOC. We discuss the medical, scientific and ethical implications that derive from these studies and we argue that, in the future, the role of neuroimaging and electrophysiology will be important not only for the diagnosis and prognosis of DOC but also in establishing communication with these challenging patients.

Functional cerebral imaging techniques allow the in vivo study of human cognitive and sensorimotor functions in physiological or pathological conditions. In this paper, we review the advantages and limitations of functional magnetic resonance imaging (fMRI), positron emission tomography (PET) and magnetoencephalography (MEG). fMRI and PET measure haemodynamic changes induced by regional changes in neuronal activity. These techniques have a high spatial resolution (a few millimeters), but a poor temporal resolution (a few seconds to several minutes). Electroencephalogram (EEG) and MEG measure the neuronal electrical or magnetic activity with a high temporal resolution (i.e., milliseconds) albeit with a poorer spatial resolution (i.e., a few millimeters to one centimeter). The combination of these different neuroimaging techniques allows studying different components of the brain's activity (e.g., neurovascular coupling, electromagnetic activity) with both a high temporal and spatial resolution.

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.

Exposure to altered g-levels causes unusual sensorimotor demands that must be dealt with by the brain. This study aimed to investigate whether fighter pilots, who are exposed to frequent g-level transitions and high g-levels, show differential functional characteristics compared to matched controls, indicative of neuroplasticity. We acquired resting-state functional magnetic resonance imaging data to assess brain functional connectivity (FC) changes with increasing flight experience in pilots and to assess differences in FC between pilots and controls. We performed whole-brain exploratory and region-of-interest (ROI) analyses, with the right parietal operculum 2 (OP2) and the right angular gyrus (AG) as ROIs. Our results show positive correlations with flight experience in the left inferior and right middle frontal gyri, and in the right temporal pole. Negative correlations were observed in primary sensorimotor regions. We found decreased whole-brain functional connectivity of the left inferior frontal gyrus in fighter pilots compared to controls and this cluster showed decreased functional connectivity with the medial superior frontal gyrus. Functional connectivity increased between the right parietal operculum 2 and the left visual cortex, and between the right and left angular gyrus in pilots compared to controls. These findings suggest altered motor, vestibular, and multisensory processing in the brains of fighter pilots, possibly reflecting coping strategies to altered sensorimotor demands during flight. Altered functional connectivity in frontal areas may reflect adaptive cognitive strategies to cope with challenging conditions during flight. These findings provide novel insights into brain functional characteristics of fighter pilots, which may be of interest to humans traveling to space.

Exposure to altered g-levels causes unusual sensorimotor demands that must be dealt with by the brain. This study aimed to investigate whether fighter pilots, who are exposed to frequent g-level transitions and high g-levels, show differential functional characteristics compared to matched controls, indicative of neuroplasticity. We acquired resting-state functional magnetic resonance imaging data to assess brain functional connectivity (FC) changes with increasing flight experience in pilots and to assess differences in FC between pilots and controls. We performed whole-brain exploratory and region-of-interest (ROI) analyses, with the right parietal operculum 2 (OP2) and the right angular gyrus (AG) as ROIs. Our results show positive correlations with flight experience in the left inferior and right middle frontal gyri, and in the right temporal pole. Negative correlations were observed in primary sensorimotor regions. We found decreased whole-brain functional connectivity of the left inferior frontal gyrus in fighter pilots compared to controls and this cluster showed decreased functional connectivity with the medial superior frontal gyrus. Functional connectivity increased between the right parietal operculum 2 and the left visual cortex, and between the right and left angular gyrus in pilots compared to controls. These findings suggest altered motor, vestibular, and multisensory processing in the brains of fighter pilots, possibly reflecting coping strategies to altered sensorimotor demands during flight. Altered functional connectivity in frontal areas may reflect adaptive cognitive strategies to cope with challenging conditions during flight. These findings provide novel insights into brain functional characteristics of fighter pilots, which may be of interest to humans traveling to space. [ABSTRACT FROM AUTHOR]