Highly connected and highly variable: A Core brain network during resting state supports Propofol-induced unconsciousness.

Despite that leading theories of consciousness make diverging predictions for where and how neural activity gives rise to subjective experience, they all seem to partially agree that the neural correlates of consciousness (NCC) require globally integrated brain activity across a network of functionally specialized modules. However, it is not clear yet whether such functional configurations would be able to identify the NCC. We scanned resting-state fMRI data from 21 subjects during wakefulness, propofol-induced sedation, and anesthesia. Graph-theoretical analyses were conducted on awake fMRI data to search for the NCC candidates as brain regions that exhibit both high rich-clubness and high modular variability, which were found to locate in prefrontal and temporoparietal cortices. Another independent data set of 10 highly-sampled subjects was used to validate the NCC distribution at the individual level. Brain module-based dynamic analysis revealed two discrete reoccurring brain states, one of which was dominated by the NCC candidates (state 1), while the other state was predominately composed of primary sensory/motor regions (state 2). Moreover, state 1 appeared to be temporally more stable than state 2, suggesting that the identified NCC members could sustain conscious content as metastable network representations. Finally, we showed that the identified NCC was modulated in terms of functional connectedness and modular variability in response to the loss of consciousness induced by propofol anesthesia. This work offers a framework to search for neural correlates of consciousness by charting the brain network topology and provides new insights into understanding the roles of different regions in underpinning human consciousness.

Temporary or Permanent? A Clinical Challenge in the Evaluation of Traumatic Brain Injury Patients with Unconsciousness and Normal Initial Head CT.

BACKGROUND: Traumatic brain injury (TBI) patients with unconsciousness and normal initial head computed tomography (CT) present a clinical dilemma for physicians and neurosurgeons in the emergency department (ED). We recorded how long it took for patients to regain consciousness and evaluated the patients' characteristics. METHODS: From 2018 to 2020, TBI patients with unconsciousness and normal initial head CT [Glasgow coma scale (GCS) score < 13, negative CT scan and normal laboratory test results] were evaluated. Patients who regained consciousness were analyzed. Multivariate logistic regression (MLR) analyses were used to evaluate independent factors for regaining consciousness. RESULTS: A total of 77 patients were included in this study. Fifty-eight (75.3%) patients regained consciousness, most within one day (43.1%). Nineteen (24.7%) patients never regained consciousness. MLR analysis showed that initial GCS score (odds 1.85, p = 0.017), early airway protection in ED (odds 25.02, p = 0.018) and 72-h GCS score improvement by two points (odds 0.02, p = 0.001) were independent factors for regaining consciousness. Overall, 94.1% of patients who received early airway protection and improved 2 points in 72-h GCS score regained consciousness. The association between days to M5 status and days to M6 status (consciousness) was highly significant. Fewer days to M5 status were highly associated with needing fewer days to regain consciousness. CONCLUSIONS: For TBI patients with unconsciousness and normal initial head CT, a higher probability of regaining consciousness was observed in those who underwent early airway protection and who improved 2 points in 72-h GCS score. Regaining consciousness within a short period could be expected in patients with M5 status.

Associations among civilian mild traumatic brain injury with loss of consciousness, posttraumatic stress disorder symptom trajectories, and structural brain volumetric data.

Posttraumatic stress disorder (PTSD) is prevalent and associated with significant morbidity. Mild traumatic brain injury (mTBI) concurrent with psychiatric trauma may be associated with PTSD. Prior studies of PTSD-related structural brain alterations have focused on military populations. The current study examined correlations between PTSD, acute mTBI, and structural brain alterations longitudinally in civilian patients (N = 504) who experienced a recent Criterion A traumatic event. Participants who reported loss of consciousness (LOC) were characterized as having mTBI; all others were included in the control group. PTSD symptoms were assessed at enrollment and over the following year; a subset of participants (n = 89) underwent volumetric brain MRI (M = 53 days posttrauma). Classes of PTSD symptom trajectories were modeled using latent growth mixture modeling. Associations between PTSD symptom trajectories and cortical thicknesses or subcortical volumes were assessed using a moderator-based regression. mTBI with LOC during trauma was positively correlated with the likelihood of developing a chronic PTSD symptom trajectory. mTBI showed significant interactions with cortical thickness in the rostral anterior cingulate cortex (rACC) in predicting PTSD symptoms, r = .461-.463. Bilateral rACC thickness positively predicted PTSD symptoms but only among participants who endorsed LOC, p < .001. The results demonstrate positive correlations between mTBI with LOC and PTSD symptom trajectories, and findings related to mTBI with LOC and rACC thickness interactions in predicting subsequent chronic PTSD symptoms suggest the importance of further understanding the role of mTBI in the context of PTSD to inform intervention and risk stratification.

Neuronal mechanisms of adenosine A2A receptors in the loss of consciousness induced by propofol general anesthesia with functional magnetic resonance imaging.

Propofol is the most common intravenous anesthetic agent for induction and maintenance of anesthesia, and has been used clinically for more than 30 years. However, the mechanism by which propofol induces loss of consciousness (LOC) remains largely unknown. The adenosine A2A receptor (A2A R) has been extensively proven to have an effect on physiological sleep. It is, therefore, important to investigate the role of A2A R in the induction of LOC using propofol. In the present study, the administration of the highly selective A2A R agonist (CGS21680) and antagonist (SCH58261) was utilized to investigate the function of A2A R under general anesthesia induced by propofol by means of animal behavior studies, resting-state magnetic resonance imaging and c-Fos immunofluorescence staining approaches. Our results show that CGS21680 significantly prolonged the duration of LOC induced by propofol, increased the c-Fos expression in nucleus accumbens (NAc) and suppressed the functional connectivity of NAc-dorsal raphe nucleus (DR) and NAc-cingulate cortex (CG). However, SCH58261 significantly shortened the duration of LOC induced by propofol, decreased the c-Fos expression in NAc, increased the c-Fos expression in DR, and elevated the functional connectivity of NAc-DR and NAc-CG. Collectively, our findings demonstrate the important roles played by A2A R in the LOC induced by propofol and suggest that the neural circuit between NAc-DR maybe controlled by A2A R in the mechanism of anesthesia induced by propofol.

Clinical use and indications for head computed tomography in children presenting with acute medical illness in a low- and middle-income setting.

BACKGROUND: Computed tomography (CT) imaging is an indispensable tool in the management of acute paediatric neurological illness providing rapid answers that facilitate timely decisions and interventions that may be lifesaving. While clear guidelines exist for use of CT in trauma to maximise individual benefits against the risk of radiation exposure and the cost to the healthcare system, the same is not the case for medical emergency. AIMS: The study primarily aimed to retrospectively describe indications for non-trauma head CT and the findings at a tertiary paediatric hospital. METHODS: Records of children presenting with acute illness to the medical emergency unit of Red Cross War Children's Hospital, Cape Town, over one year (2013) were retrospectively reviewed. Participants were included if they underwent head CT scan within 24 hours of presentation with a non-trauma event. Clinical data and reports of CT findings were extracted. RESULTS: Inclusion criteria were met by 311 patients; 188 (60.5%) were boys. The median age was 39.2 (IQR 12.6-84.0) months. Most common indications for head CT were seizures (n = 169; 54.3%), reduced level of consciousness (n = 140;45.0%), headache (n = 74;23.8%) and suspected ventriculoperitoneal shunt (VPS) malfunction (n = 61;19.7%). In 217 (69.8%) patients CT showed no abnormal findings. In the 94 (30.2%) with abnormal CT results the predominant findings were hydrocephalus (n = 54;57.4%) and cerebral oedema (n = 29;30.9%). Papilloedema was more common in patients with abnormal CT (3/56; 5.4%) compared with none in those with normal CT; P = 0.015; while long tract signs were found in 42/169 (24.9%) and 23/56 (41.1%) of patients with normal and abnormal CT findings, respectively; P = 0.020. Post-CT surgery was required by 47(15.1%) of which 40 (85.1%) needed a ventricular drainage. A larger proportion of patients with VPS (25/62; 40.3%) required surgery compared to patients without VPS (22/249; 8.8%; P<0.001). CONCLUSION: A majority of head CT scans in children with medical emergency with acute neurological illness were normal. Patients with VPS constituted the majority of patients with abnormal CT scans that required subsequent neurosurgical intervention. Evidence-based guidelines are required to guide the best use of head CT in the management of children without head trauma.

Spontaneous subarachnoidal hemorrhage in patients with Covid-19: case report.

In this article, subarachnoidal hemorrhage developing in a case with Covid-19-related pneumonia was evaluated. In the presence of respiratory system infection signs such as cough and weakness in patient who present with sudden loss of consciousness, performing lung imaging as well as performing brain computerized tomography scan can allow the detection of an underlying Covid-19 infection.

Reorganization of rich-clubs in functional brain networks during propofol-induced unconsciousness and natural sleep.

BACKGROUND: General anesthesia (GA) provides an invaluable experimental tool to understand the essential neural mechanisms underlying consciousness. Previous neuroimaging studies have shown the functional integration and segregation of brain functional networks during anesthetic-induced alteration of consciousness. However, the organization pattern of hubs in functional brain networks remains unclear. Moreover, comparisons with the well-characterized physiological unconsciousness can help us understand the neural mechanisms of anesthetic-induced unconsciousness. METHODS: Resting-state functional magnetic resonance imaging was performed during wakefulness, mild propofol-induced sedation (m-PIS), and deep PIS (d-PIS) with clinical unconsciousness on 8 healthy volunteers and wakefulness and natural sleep on 9 age- and sex-matched healthy volunteers. Large-scale functional brain networks of each volunteer were constructed based on 160 regions of interest. Then, rich-club organizations in brain functional networks and nodal properties (nodal strength and efficiency) were assessed and analyzed among the different states and groups. RESULTS: Rich-clubs in the functional brain networks were reorganized during alteration of consciousness induced by propofol. Firstly, rich-club nodes were switched from the posterior cingulate cortex (PCC), angular gyrus, and anterior and middle insula to the inferior parietal lobule (IPL), inferior parietal sulcus (IPS), and cerebellum. When sedation was deepened to unconsciousness, the rich-club nodes were switched to the occipital and angular gyrus. These results suggest that the rich-club nodes were switched among the high-order cognitive function networks (default mode network [DMN] and fronto-parietal network [FPN]), sensory networks (occipital network [ON]), and cerebellum network (CN) from consciousness (wakefulness) to propofol-induced unconsciousness. At the same time, compared with wakefulness, local connections were switched to rich-club connections during propofol-induced unconsciousness, suggesting a strengthening of the overall information commutation of networks. Nodal efficiency of the anterior and middle insula and ventral frontal cortex was significantly decreased. Additionally, from wakefulness to natural sleep, a similar pattern of rich-club reorganization with propofol-induced unconsciousness was observed: rich-club nodes were switched from the DMN (including precuneus and PCC) to the sensorimotor network (SMN, including part of the frontal and temporal gyrus). Compared with natural sleep, nodal efficiency of the insula, frontal gyrus, PCC, and cerebellum significantly decreased during propofol-induced unconsciousness. CONCLUSIONS: Our study demonstrated that the rich-club reorganization in functional brain networks is characterized by switching of rich-club nodes between the high-order cognitive and sensory and motor networks during propofol-induced alteration of consciousness and natural sleep. These findings will help understand the common neurological mechanism of pharmacological and physiological unconsciousness.

Cortical functional connectivity indexes arousal state during sleep and anesthesia.

Disruption of cortical connectivity likely contributes to loss of consciousness (LOC) during both sleep and general anesthesia, but the degree of overlap in the underlying mechanisms is unclear. Both sleep and anesthesia comprise states of varying levels of arousal and consciousness, including states of largely maintained conscious experience (sleep: N1, REM; anesthesia: sedated but responsive) as well as states of substantially reduced conscious experience (sleep: N2/N3; anesthesia: unresponsive). Here, we tested the hypotheses that (1) cortical connectivity will exhibit clear changes when transitioning into states of reduced consciousness, and (2) these changes will be similar for arousal states of comparable levels of consciousness during sleep and anesthesia. Using intracranial recordings from five adult neurosurgical patients, we compared resting state cortical functional connectivity (as measured by weighted phase lag index, wPLI) in the same subjects across arousal states during natural sleep [wake (WS), N1, N2, N3, REM] and propofol anesthesia [pre-drug wake (WA), sedated/responsive (S), and unresponsive (U)]. Analysis of alpha-band connectivity indicated a transition boundary distinguishing states of maintained and reduced conscious experience in both sleep and anesthesia. In wake states WS and WA, alpha-band wPLI within the temporal lobe was dominant. This pattern was largely unchanged in N1, REM, and S. Transitions into states of reduced consciousness N2, N3, and U were characterized by dramatic changes in connectivity, with dominant connections shifting to prefrontal cortex. Secondary analyses indicated similarities in reorganization of cortical connectivity in sleep and anesthesia. Shifts from temporal to frontal cortical connectivity may reflect impaired sensory processing in states of reduced consciousness. The data indicate that functional connectivity can serve as a biomarker of arousal state and suggest common mechanisms of LOC in sleep and anesthesia.

Cortical lesions causing loss of consciousness are anticorrelated with the dorsal brainstem.

Brain lesions can provide unique insight into the neuroanatomical substrate of human consciousness. For example, brainstem lesions causing coma map to a specific region of the tegmentum. Whether specific lesion locations outside the brainstem are associated with loss of consciousness (LOC) remains unclear. Here, we investigate the topography of cortical lesions causing prolonged LOC (N = 16), transient LOC (N = 91), or no LOC (N = 64). Using standard voxel lesion symptom mapping, no focus of brain damage was associated with LOC. Next, we computed the network of brain regions functionally connected to each lesion location using a large normative connectome dataset (N = 1,000). This technique, termed lesion network mapping, can test whether lesions causing LOC map to a connected brain circuit rather than one brain region. Connectivity between cortical lesion locations and an a priori coma-specific region of brainstem tegmentum was an independent predictor of LOC (B = 1.2, p = .004). Connectivity to the dorsal brainstem was the only predictor of LOC in a whole-brain voxel-wise analysis. This relationship was driven by anticorrelation (negative correlation) between lesion locations and the dorsal brainstem. The map of regions anticorrelated to the dorsal brainstem thus defines a distributed brain circuit that, when damaged, is most likely to cause LOC. This circuit showed a slight posterior predominance and had peaks in the bilateral claustrum. Our results suggest that cortical lesions causing LOC map to a connected brain circuit, linking cortical lesions that disrupt consciousness to brainstem sites that maintain arousal.

Pharmacologically informed machine learning approach for identifying pathological states of unconsciousness via resting-state fMRI.

Determining the level of consciousness in patients with disorders of consciousness (DOC) remains challenging. To address this challenge, resting-state fMRI (rs-fMRI) has been widely used for detecting the local, regional, and network activity differences between DOC patients and healthy controls. Although substantial progress has been made towards this endeavor, the identification of robust rs-fMRI-based biomarkers for level of consciousness is still lacking. Recent developments in machine learning show promise as a tool to augment the discrimination between different states of consciousness in clinical practice. Here, we investigated whether machine learning models trained to make a binary distinction between conscious wakefulness and anesthetic-induced unconsciousness would then be capable of reliably identifying pathologically induced unconsciousness. We did so by extracting rs-fMRI-based features associated with local activity, regional homogeneity, and interregional functional activity in 44 subjects during wakefulness, light sedation, and unresponsiveness (deep sedation and general anesthesia), and subsequently using those features to train three distinct candidate machine learning classifiers: support vector machine, Extra Trees, artificial neural network. First, we show that all three classifiers achieve reliable performance within-dataset (via nested cross-validation), with a mean area under the receiver operating characteristic curve (AUC) of 0.95, 0.92, and 0.94, respectively. Additionally, we observed comparable cross-dataset performance (making predictions on the DOC data) as the anesthesia-trained classifiers demonstrated a consistent ability to discriminate between unresponsive wakefulness syndrome (UWS/VS) patients and healthy controls with mean AUC's of 0.99, 0.94, 0.98, respectively. Lastly, we explored the potential of applying the aforementioned classifiers towards discriminating intermediate states of consciousness, specifically, subjects under light anesthetic sedation and patients diagnosed as having a minimally conscious state (MCS). Our findings demonstrate that machine learning classifiers trained on rs-fMRI features derived from participants under anesthesia have potential to aid the discrimination between degrees of pathological unconsciousness in clinical patients.

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.

The Relation Between Loss of Consciousness, Severity of Traumatic Brain Injury, and Injury of Ascending Reticular Activating System in Patients With Traumatic Brain Injury.

OBJECTIVE: Loss of consciousness is an indicator of the severity of traumatic brain injury and the ascending reticular activating system has been considered as a main structure for consciousness. However, no study on the relation between loss of consciousness and ascending reticular activating system injury in traumatic brain injury has been reported. We investigated the relation between loss of consciousness, severity of traumatic brain injury, and ascending reticular activating system injury using diffusion tensor tractography. DESIGN: One hundred twenty patients were recruited. Three components of ascending reticular activating system, fractional anisotropy, and tract volume were measured. RESULTS: In lower dorsal and ventral ascending reticular activating system, fractional anisotropy and tract volume value in mild group were higher than those of moderate and severe groups, and there was no difference between moderate and severe groups. In upper ascending reticular activating system, fractional anisotropy value in mild group was higher than in moderate group, and it was higher than in moderate group than in severe group. Tract volume value in mild group was higher than in severe group. Loss of consciousness showed moderate negative correlations with tract volume value of lower dorsal ascending reticular activating system (r = -0.348), fractional anisotropy value of lower ventral ascending reticular activating system (r = -0.343), and fractional anisotropy value of upper ascending reticular activating system (r = -0.416). CONCLUSIONS: Injury severity was different among the three traumatic brain injury groups in upper ascending reticular activating system but did not differ between moderate and severe groups in lower dorsal and ventral ascending reticular activating system.

Loss of consciousness and altered mental state predicting depressive and post-concussive symptoms after mild traumatic brain injury.

Objective: Limited studies exist on the association between loss of consciousness (LOC) and altered mental state (AMS) and development of depressive and post-concussive symptoms within six months after mild traumatic brain injury (mTBI). We tested the hypothesis that presence of both LOC and AMS predict the highest risk of symptoms within the first six months post-mTBI compared to either variable alone, and that LOC alone is more strongly associated with these symptoms. Research design: We analyzed data from 407 subjects with mTBI from the Head injury Serum Markers for Assessing Response to Trauma (HeadSMART) cohort, a prospective cohort of patients post-TBI presenting to two urban emergency departments. Results: There were higher rates of depressive (44%) and post-concussive symptoms (54%) at 1 month post-injury, among participants with both LOC and AMS compared to other groups. AMS was associated with depressive symptoms at one and six months (OR = 1.59, p = .038; OR = 1.60; p = .060) and post-concussive symptoms at one month (OR = 1.56, p = .053). LOC was associated only with post-concussive symptoms at one month (OR = 1.55;p = .048). Among those without LOC, AMS was associated with depressive symptoms at one month (OR = 2.24; p = .028). Conclusions: AMS predicts post-mTBI depressive symptoms both in the acute and chronic mTBI phases whereas LOC is a more sensitive predictor of post-concussive symptoms in the acute mTBI period.

A Novel Framework for Unconscious Processing.

Understanding the distinction between conscious and unconscious cognition remains a priority in psychology and neuroscience. A comprehensive neurocognitive account of conscious awareness will not be possible without a sound framework to isolate and understand unconscious information processing. Here, we provide a brain-based framework that allows the identification of unconscious processes, even with null effects on behaviour.

Trousseau syndrome in a patient with advanced oral squamous cell carcinoma: a case report.

BACKGROUND: Trousseau syndrome is known as a variant of cancer-associated thrombosis. Trousseau syndrome commonly occurs in patients with lung or prostate cancer. Hypercoagulability is thought to be initiated by mucins produced by the adenocarcinoma, which react with leukocyte and platelet selectins to form platelet-rich microthrombi. This is the first report of Trousseau syndrome in a patient with oral cancer. CASE PRESENTATION: Here, we describe the case of a 61-year-old Japanese man diagnosed as having advanced buccal carcinoma (T4bN2bM1; the right scapula, erector spinae muscles, and the right femur), who experienced aphasia and loss of consciousness. Although magnetic resonance imaging showed cerebral infarction, carotid invasion by the tumor and carotid sheath rupturing, cardiovascular problems, and bacterial infection were not present, which indicated Trousseau syndrome. CONCLUSIONS: Trousseau syndrome in oral cancer is rare, but we must always consider cancer-associated thrombosis in patients with advanced stages of cancer regardless of the primary site of the cancer and take steps to prevent it.

Disrupted neural variability during propofol-induced sedation and unconsciousness.

Variability quenching is a widespread neural phenomenon in which trial-to-trial variability (TTV) of neural activity is reduced by repeated presentations of a sensory stimulus. However, its neural mechanism and functional significance remain poorly understood. Recurrent network dynamics are suggested as a candidate mechanism of TTV, and they play a key role in consciousness. We thus asked whether the variability-quenching phenomenon is related to the level of consciousness. We hypothesized that TTV reduction would be compromised during reduced level of consciousness by propofol anesthetics. We recorded functional magnetic resonance imaging signals of resting-state and stimulus-induced activities in three conditions: wakefulness, sedation, and unconsciousness (i.e., deep anesthesia). We measured the average (trial-to-trial mean, TTM) and variability (TTV) of auditory stimulus-induced activity under the three conditions. We also examined another form of neural variability (temporal variability, TV), which quantifies the overall dynamic range of ongoing neural activity across time, during both the resting-state and the task. We found that (a) TTM deceased gradually from wakefulness through sedation to anesthesia, (b) stimulus-induced TTV reduction normally seen during wakefulness was abolished during both sedation and anesthesia, and (c) TV increased in the task state as compared to resting-state during both wakefulness and sedation, but not anesthesia. Together, our results reveal distinct effects of propofol on the two forms of neural variability (TTV and TV). They imply that the anesthetic disrupts recurrent network dynamics, thus prevents the stabilization of cortical activity states. These findings shed new light on the temporal dynamics of neuronal variability and its alteration during anesthetic-induced unconsciousness.

Imaging the Unconscious "Found Down" Patient in the Emergency Department.

Unconsciousness may be due to severe brain damage or to potentially reversible causes. Noncontrast head computed tomography (CT) helps identify acute ischemic and hemorrhagic lesions as well as certain patterns of toxic encephalopathy. MR imaging plays an important role in the assessment of acutely encephalopathic patients who may show no significant abnormality on CT. This review describes some of the common and infrequent entities that can lead to unconsciousness, including epilepsy and vascular, traumatic, metabolic, and toxic disorders.

Investigation and diagnostic formulation in patients admitted with transient loss of consciousness.

Several commonly completed tests have low diagnostic yield in the setting of transient loss of consciousness (T-LOC). We estimated the use and cost of inappropriate investigations in patients admitted with T-LOC and assessed if these patients were given a definitive diagnosis for their presentation. We identified 80 consecutive patients admitted with T-LOC to a university teaching hospital. Eighty-eight percent (70/80) had a computerized topography (CT) brain scan and 49% (34/70) of these scans were inappropriate based on standard guidelines. Almost half (17/80) of electroencephalograms (EEG) and 82% (9/11) of carotid doppler ultrasound performed were not based on clinical evidence of seizure or stroke respectively. Forty-four percent (35/80) of patients had no formal diagnosis documented for their presentation. Inappropriate investigation in T-LOC is very prevalent in the acute hospital, increasing cost of patient care. In addition, there is poor diagnostic formulation for T-LOC making recurrent events more likely in the absence of definitive diagnoses.

Functional MRI for Assessment of the Default Mode Network in Acute Brain Injury.

BACKGROUND: Assessment of the default mode network (DMN) using resting-state functional magnetic resonance imaging (fMRI) may improve assessment of the level of consciousness in chronic brain injury, and therefore, fMRI may also have prognostic value in acute brain injury. However, fMRI is much more challenging in critically ill patients because of cardiovascular vulnerability, intravenous sedation, and artificial ventilation. METHODS: Using resting-state fMRI, we investigated the DMN in a convenience sample of patients with acute brain injury admitted to the intensive care unit. The DMN was classified dichotomously into "normal" and "grossly abnormal." Clinical outcome was assessed at 3 months. RESULTS: Seven patients with acute brain injury (4 females; median age 37 years [range 14-71 years]; 1 traumatic brain injury [TBI]; 6 non-TBI) were investigated by fMRI a median of 15 days after injury (range 5-25 days). Neurological presentation included 2 coma, 1 vegetative state/unresponsive wakefulness syndrome (VS/UWS), 3 minimal conscious state (MCS) minus, and 1 MCS plus. Clinical outcomes at 3 months included 1 death, 1 VS/UWS, 1 MCS plus, and 4 conscious states (CS; 1 modified Rankin Scale 0; 2 mRS 4; 1 mRS 5). Normal DMNs were seen in 4 out of 7 patients (1 MCS plus, 3 CS at follow-up). CONCLUSIONS: It is feasible to assess the DMN by resting-state fMRI in patients with acute brain injury already in the very early period of intensive care unit admission. Although preliminary data, all patients with a preserved DMN regained consciousness levels at follow-up compatible with MCS+ or better.