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Disorders of consciousness are impaired states of consciousness caused by severe brain injuries. Previous resting-state functional magnetic resonance imaging studies have reported abnormal brain network properties at different topological scales in patients with disorders of consciousness by using graph theoretical analysis. However, it is still unclear how inter-regional directed propagation activities affect the topological organization of functional brain networks in patients with disorders of consciousness. To reveal the altered topological organization in patients with disorders of consciousness, we constructed whole-brain directed functional networks by combining functional connectivity analysis and time delay estimation. Then we performed graph theoretical analysis based on the directed functional brain networks at three topological scales, from the nodal scale, the resting-state network scale to the global scale. Finally, the canonical correlation analysis was used to determine the correlations between altered topological properties and clinical scores in patients with disorders of consciousness. At the nodal scale, we observed decreased in-degree and increased out-degree in the precuneus in patients with disorders of consciousness. At the resting-state network scale, the patients with disorders of consciousness showed reorganized motif patterns within the default mode network and between the default mode network and other resting-state networks. At the global scale, we found a lower global clustering coefficient in the patients with disorders of consciousness than in the controls. The results of the canonical correlation analysis showed that the abnormal degree and the disrupted motif were significantly correlated with the clinical scores of the patients with disorders of consciousness. Our findings showed that consciousness impairment can be revealed by abnormal directed connection patterns at multiple topological scales in the whole brain, and the disrupted directed connection patterns may serve as clinical biomarkers to assess the dysfunction of patients with disorders of consciousness.

Recognizing human emotions based on electroencephalogram (EEG) signals has received a great deal of attentions. Most of the existing studies focused on offline analysis, and real-time emotion recognition using a brain computer interface (BCI) approach remains to be further investigated. In this paper, we proposed an EEG-based BCI system for emotion recognition. Specifically, two classes of video clips that represented positive and negative emotions were presented to the subjects one by one, while the EEG data were collected and processed simultaneously, and instant feedback was provided after each clip. Ten healthy subjects participated in the experiment and achieved a high average online accuracy of 91.5% ± 6.34%. The experimental results demonstrated that the subjects emotions had been sufficiently evoked and efficiently recognized by our system. Clinically, patients with disorder of consciousness (DOC), such as coma, vegetative state, and minimally conscious state, suffer from motor impairment and generally cannot provide adequate emotion expressions. Therefore, we applied our emotion recognition BCI system to patients with DOC. Eight DOC patients participated in our experiment, and three of them achieved significant online accuracy. The experimental results show that the proposed BCI system could be a promising tool to detect the emotional states of patients with DOC.

This study aimed to elucidate the neurotherapeutic effect of hyperbaric oxygen (HBO) on brain injury and the potential role of dynamin-related protein 1 (Drp1) and its regulatory pathway in heatstroke (HS) rats. In in vivo experiments, rats were exposed to HBO after the onset of HS, or the same pressure but normal air as a control. The results indicated that HBO decreased the mortality and thermoregulatory dysfunction and prolonged the survival time of HS rats. Neurological dysfunction induced by HS was attenuated by HBO through assessment of modified neurological severity score and Morris water maze. HBO also alleviated histopathologic changes and oxidative injury (malondialdehyde and 8-hydroxyguanine), increased activities of superoxide dismutase (SOD) and glutathione/oxidized glutathione and ameliorated apoptotic parameters (caspase-3/6 activities and the number of apoptotic cells) of the hippocampus, hypothalamus and brain stem in rats compared to the HS group. Phosphorylation of DrpSer616 was increased by HS but decreased by HBO in the brains of rats determined by Western blot and immunohistochemical staining. In experiments in vitro, rat hippocampal neurons were used as a heat stress (HS) cellular model to examine the effects of HBO. As the results, HBO attenuated HS-induced cytotoxicity, oxidative injury (malondialdehyde), reactive oxygen species (ROS) generation, decreasing SOD activity and apoptosis. Drp1 inhibitor (Mdivi-1) treatment produced the same effects and had a trend to decrease oxidative injury. But the difference is not statistically significant. HBO and Mdivi-1decreased the phosphorylation of DrpSer616 induced by HS and HBO decreased the phosphorylation of protein kinase C (PKC) induced by HS. Moreover, both PKC inhibitor and ROS scavenger inhibited HS-induced p-DrpSer616. In conclusion, HBO may alleviate the brain injury caused by HS by decreasing ROS/PKC-regulated p-DrpSer616.

See Owen (doi:10.1093/brain/awaa056) for a scientific commentary on this article. Pan et al. report that in patients with disorders of consciousness who show no detectable command-following behaviours, about 80% of those identified via a brain-computer interface as having cognitive motor dissociation (CMD) regained or improved consciousness on a behavioural level, versus about 20% of non-CMD patients., Cognitive motor dissociation describes a subset of patients with disorders of consciousness who show neuroimaging evidence of consciousness but no detectable command-following behaviours. Although essential for family counselling, decision-making, and the design of rehabilitation programmes, the prognosis for patients with cognitive motor dissociation remains under-investigated. The current study included 78 patients with disorders of consciousness who showed no detectable command-following behaviours. These patients included 45 patients with unresponsive wakefulness syndrome and 33 patients in a minimally conscious state, as diagnosed using the Coma Recovery Scale-Revised. Each patient underwent an EEG-based brain-computer interface experiment, in which he or she was instructed to perform an item-selection task (i.e. select a photograph or a number from two candidates). Patients who achieved statistically significant brain-computer interface accuracies were identified as cognitive motor dissociation. Two evaluations using the Coma Recovery Scale-Revised, one before the experiment and the other 3 months later, were carried out to measure the patients’ behavioural improvements. Among the 78 patients with disorders of consciousness, our results showed that within the unresponsive wakefulness syndrome patient group, 15 of 18 patients with cognitive motor dissociation (83.33%) regained consciousness, while only five of the other 27 unresponsive wakefulness syndrome patients without significant brain-computer interface accuracies (18.52%) regained consciousness. Furthermore, within the minimally conscious state patient group, 14 of 16 patients with cognitive motor dissociation (87.5%) showed improvements in their Coma Recovery Scale-Revised scores, whereas only four of the other 17 minimally conscious state patients without significant brain-computer interface accuracies (23.53%) had improved Coma Recovery Scale-Revised scores. Our results suggest that patients with cognitive motor dissociation have a better outcome than other patients. Our findings extend current knowledge of the prognosis for patients with cognitive motor dissociation and have important implications for brain-computer interface-based clinical diagnosis and prognosis for patients with disorders of consciousness.

Objective Nervous dysfunction is the main manifestation of heat stroke (HS). Here we investigated the clinical signs for HS-induced nerve injuries. Methods Retrospective data were collected on 119 patients who got HS from 2016 to 2020. Patients were divided into 4 groups, including the cerebellar injury group, the other nerve injuries group, non-cerebellar injury group and non-nerve injury group. The age, body temperature (Tc), degree of consciousness disorder, liver and kidney function, blood coagulation function, blood routine and cardiac indicators within 24 h after HS were summarized. Moreover, we performed regression analyses to identify risk factors for nervous dysfunction. The Activity of Daily Living (ADL) score was assessed 3 months after HS to evaluate the prognosis of HS. Results Compared with other groups, the cerebellar injury group had shorter Tc recovering time, lower GSC scales, longer coma time and more hypotension, gastrointestinal bleeding, multiple organ dysfunction syndrome (MODS) and metabolic acidosis significantly. The cerebellar injury group had higher myocardial enzymogram and indexes of liver and kidney dysfunction, immune and coagulation dysfunction significantly. Risk factors associated with HS-induced cerebellar injury are Tc, recovery time of Tc, NSE, GCS scale, lymphocyte count, HLA-DR/CD14, coagulation dysfunction, cardiac injury, metabolic acidosis and MODS. The ADL scale of the cerebellar injury group and the other nerve injury group were significantly lower than other groups. Conclusions Patients with severe coma and MODS are more prone to cerebellar injury after HS and the HS-induced nerve injury leaded to a worse prognosis.

Visual fixation is an item in the visual function subscale of the Coma Recovery Scale-Revised (CRS-R). Sometimes clinicians using the behavioral scales find it difficult to detect because of the motor impairment in patients with disorders of consciousness (DOCs). Brain-computer interface (BCI) can be used to improve clinical assessment because it directly detects the brain response to an external stimulus in the absence of behavioral expression. In this study, we designed a BCI system to assist the visual fixation assessment of DOC patients. The results from 15 patients indicated that three showed visual fixation in both CRS-R and BCI assessments and one did not show such behavior in the CRS-R assessment but achieved significant online accuracy in the BCI assessment. The results revealed that electroencephalography-based BCI can detect the brain response for visual fixation. Therefore, the proposed BCI may provide a promising method for assisting behavioral assessment using the CRS-R.

A number of studies have indicated that disorders of consciousness result from multifocal injuries as well as from the impaired functional and anatomical connectivity between various anterior forebrain regions. However, the specific causal mechanism linking these regions remains unclear. In this study, we used spectral dynamic causal modeling to assess how the effective connections (ECs) between various regions differ between individuals. Next, we used connectome-based predictive modeling to evaluate the performance of the ECs in predicting the clinical scores of DOC patients. We found increased ECs from the striatum to the globus pallidus as well as from the globus pallidus to the posterior cingulate cortex, and decreased ECs from the globus pallidus to the thalamus and from the medial prefrontal cortex to the striatum in DOC patients as compared to healthy controls. Prediction of the patients' outcome was effective using the negative ECs as features. In summary, the present study highlights a key role of the thalamo-basal ganglia-cortical loop in DOCs and supports the anterior forebrain mesocircuit hypothesis. Furthermore, EC could be potentially used to assess the consciousness level.

Visual pursuit assessment is extensively applied in the behavioral scale-based clinical examination of patients with disorders of consciousness (DOC). However, this assessment is challenging because it relies on behavioral markers, and these patients severely lack behavioral responses. Brain-computer interfaces (BCIs) may provide a potential solution to detect brain responses to external stimuli without requiring behavioral expressions. A BCI system was designed to simulate visual pursuit detection in the coma recovery scale-revised (CRS-R). The graphical user interface included four buttons, one that moved on the screen and three that did not. These buttons flashed in a random order. The patients were prompted to follow the moving button. Based on the collected electroencephalography data, the algorithm determined whether the patient focused on the moving target. Among the 14 DOC patients who participated in the assessments based on the BCI system and the CRS-R, four patients exhibited visual pursuit, and three were nonresponsive in both assessments. More importantly, seven patients who did not exhibit visual pursuit in CRS-R were detected to be responsive to the moving target stimuli in the BCI assessment. Furthermore, five out of seven recovered consciousness to some degree and showed visual pursuit in the second CRS-R assessment. The proposed BCI system is better able to detect visual pursuit than the behavioral scale-based assessment and thus can assist in clinically evaluating the challenging population of DOC patients.

Over the last 20 years, studies have provided greater insight into disorders of consciousness (DOC), also known as altered state of consciousness. Increased brain residual functions have been identified in patients with DOC due to the successful application of novel next-generation imaging technologies. Many unconscious patients have now been confirmed to retain considerable cognitive functions. It is hoped that greater insight regarding the psychological state of patients may be achieved through the use of functional magnetic resonance imaging and brain-computer interfaces. However, issues surrounding the research and treatment of DOC remain problematic. These include differing opinions on the definition of consciousness, difficulties in diagnosis, assessment, prognosis and/or treatment, and newly emerging ethical, legal and social issues. To overcome these, appropriate care must be offered to patients with DOC by clinicians and families, as DOC patients may now be considered to live in more than just a vegetative state. The present article reviews the controversy surrounding the definition of consciousness and the reliability of novel technologies, prognostic prediction, communication with DOC patients and treatment methods. The ethical and social issues surrounding the treatment of DOC and future perspectives are also considered.

Highlights • The DOC showed reduced dFC in sensorimotor network compared with the HC. • The dFC could be used to predict the clinical scores of the DOC. • The different in number of transitions indicated an instable brain state in the DOC., Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to research abnormal functional connectivity (FC) in patients with disorders of consciousness (DOC). However, most studies assumed steady spatial-temporal signal interactions between distinct brain regions during the scan period. The aim of this study was to explore abnormal dynamic functional connectivity (dFC) in DOC patients. After excluding 26 patients’ data that failed to meet the requirements of imaging quality, we retained 19 DOC patients (12 with unresponsive wakefulness syndrome and 7 in a minimally conscious state, diagnosed with the Coma Recovery Scale-Revised [CRS-R]) for the dFC analysis. We used the sliding windows approach to construct dFC matrices. Then these matrices were clustered into distinct states using the k-means clustering algorithm. We found that the DOC patients showed decreased dFC in the sensory and somatomotor networks compared with the healthy controls. There were also significant differences in temporal properties, the mean dwell time (MDT) and the number of transitions (NT), between the DOC patients and the healthy controls. In addition, we also used a hidden Markov model (HMM) to test the robustness of the results. With the connectome-based predictive modeling (CPM) approach, we found that the properties of abnormal dynamic network can be used to predict the CRS-R scores of the patients after severe brain injury. These findings may contribute to a better understanding of the abnormal brain networks in DOC patients.

The coma recovery scale-revised (CRS-R) behavioral scale is commonly used for the clinical evaluation of patients with disorders of consciousness (DOC). However, since DOC patients generally cannot supply stable and efficient behavioral responses to external stimulation, evaluation results based on behavioral scales are not sufficiently accurate. In this paper, we proposed a novel brain–computer interface (BCI) based on 3D stereo audiovisual stimuli to supplement object recognition evaluation in the CRS-R. During the experiment, subjects needed to follow the instructions and to focus on the target object on the screen, whereas EEG data were recorded and analyzed in real time to determine the object of focus, and the detection result was output as feedback. Thirteen DOC patients participated in the object recognition assessments using the 3D audiovisual BCI and CRS-R. None of the patients showed object recognition function in the CRS-R assessment before the BCI experiment. However, six of these DOC patients achieved accuracies that were significantly higher than the chance level in the BCI-based assessment, indicating the successful detection of object recognition function in these six patients using our 3D audiovisual BCI system. These results suggest that the BCI method may provide a more sensitive object recognition evaluation compared with CRS-R and may be used to assist clinical CRS-R for DOC patients.

Disorders of consciousness are a heterogeneous mixture of different diseases or injuries. Although some indicators and models have been proposed for prognostication, any single method when used alone carries a high risk of false prediction. This study aimed to develop a multidomain prognostic model that combines resting state functional MRI with three clinical characteristics to predict one year outcomes at the single-subject level. The model discriminated between patients who would later recover consciousness and those who would not with an accuracy of around 90% on three datasets from two medical centers. It was also able to identify the prognostic importance of different predictors, including brain functions and clinical characteristics. To our knowledge, this is the first implementation reported of a multidomain prognostic model based on resting state functional MRI and clinical characteristics in chronic disorders of consciousness. We therefore suggest that this novel prognostic model is accurate, robust, and interpretable., Comment: Although some prognostic indicators and models have been proposed for disorders of consciousness, each single method when used alone carries risks of false prediction. Song et al. report that a model combining resting state functional MRI with clinical characteristics provided accurate, robust, and interpretable prognostications. 52 pages, 1 table, 7 figures

Understanding the neural mechanisms of disorders of consciousness (DOC) is essential for estimating the conscious level and diagnosing DOC patients. Although previous studies reported brain functional connectivity (FC) and spontaneous neural activity patterns associated with consciousness, the relationship between them remains unclear. In this study, we identified the abnormal brain regions in DOC patients by performing voxel-wise FC strength (FCS) and fractional amplitude of low-frequency fluctuations (fALFF) analyses on resting-state functional magnetic resonance imaging data of 15 DOC patients and 24 healthy controls. Furthermore, we detected spatial intersections between two measures and estimated the correlations between either the FCS or the fALFF and the subscales of the Coma Recovery Scale-Revised (CRS-R). We found that the right superior frontal gyrus, left thalamus and right precuneus in which the DOC patients had a lower local FCS and fALFF than healthy controls, are coincident with regions of the mesocircuit model. In the right precuneus, the local FCS/fALFF was significantly positively correlated with the oromotor and motor scores/motor score of the CRS-R. Our findings may indicate that the co-occurrent pattern of spontaneous neural activity and functional connectivity in the thalamo-frontal circuit and the precuneus are associated with motor function in DOC patients.

Objective To date, no study has examined the effect of hyperbaric oxygen (HBO) on the cognitive performance and spontaneous brain activity in healthy adults using resting-state functional magnetic resonance imaging (rsfMRI). Our aim was to reveal the neural mechanism underlying the change in cognitive performance caused by increased oxygen. Methods In this study, we acquired fMRI data from 20 healthy young adults and used placebo-controlled (PBO) rsfMRI to identify the effect of HBO on the cognitive measures and the regional homogeneity (ReHo) in healthy adults. Results Compared to the PBO group, the HBO group showed the following: (1) the scores of the spatial working memory and memory quotient were significantly increased after HBO administration; (2) the ReHo value was significantly increased in three clusters, the left hippocampus, right inferior frontal, and lingual gyri, and for these three clusters, their functional connectivity with the subcortical brain system was significantly increased after HBO administration; and (3) the changes of ReHo values in these clusters generated by HBO administration were correlated with several aspects of cognitive performance, clarifying the cognitive locus of the effect. Conclusion Our results suggested that the increased availability of oxygen can, to some extent, improve memory performance. Significant Our findings may improve our understanding of the role of HBO in clinical and practical applications.

Currently, the clinical diagnosis of patients with disorders of consciousness (DOC) is based on behavioral assessments, which rely on the patients' behavioral responses to external stimulation. However, high rates of clinical misdiagnosis occurred, because many patients cannot provide efficient physical movements during the evaluation. Brain-computer interfaces (BCIs) provide an alternative approach to assist clinical assessments in patients with DOC. This study proposed a three-dimensional (3D) BCI based on stereo stimuli to assist the clinical object recognition for patients with DOC. Subjects were instructed to selectively focus on the target object cued by instruction. Four healthy subjects participated in two experiment sessions corresponding to the two-dimensional (2D) and 3D modes respectively. The results indicated that the 3D BCI system outperformed the 2D BCI system. This 3D B-CI system was then applied to assess the object recognition of a patient in the minimally conscious state (MCS). The patient cannot recognize objects in the JFK CRS-R assessment before the experiment, but got a score of 75% in the BCI experiment. The result demonstrated his residual awareness and object recognition ability.

With the global warming, the incidence of heat stroke was significantly higher than before. Severe heat stroke has a high mortality, high morbidity and consolidated central nervous system injury characteristics. The main features of severe heat stroke cerebral injury include cognitive impairment, delirium, convulsions and coma. Its mechanism is related with heat shock induced cerebral tissue ischemia and hypoxia, vascular dysfunction, secondary cascade inflammation and so on. Currently, the main treatment of heat stroke cerebral injury is the hypothermia therapy, dehydration for the reduction of intracranial pressure, naloxone and other cerebral protection and nutrition treatments. Hyperbaric oxygen therapy (HBOT) is effective in treating brain injury. HBOT can alleviate tissue ischemia and hypoxia, improve circulation, reduce cerebral edema, and anti-inflammatory, anti-oxidative damage, anti-apoptosis and other molecular biological effects. HBOT also play a wake up-promoting effect of nerve repair in the cerebral injury. The treatment of cerebral injury has been the difficulty and weakness of heat stroke research. Therefore, this article reviewed the epidemiology, pathogenesis, the therapeutic effect and mechanism of hyperbaric oxygen on cerebral injury in severe heat stroke to clarify the advantages of HBOT and to provide experimental basis for further research.

Visual fixation is an item of the Coma Recovery Scale-Revised (CRS-R), it is difficult to be detected by clinicians using the behavioral scales because of fluctuations of arousal level and the presence of motor impairment in disorders of consciousness (DOC) patients. Brain-computer interfaces (BCIs), which directly detect brain response without any behavioral expression, can be used to evaluate a patient's response to the stimuli. In this study, we explored the application of a 4-choice visual BCI in assisting visual fixation assessment of DOC patients. The results obtained from three patients indicated that one locked-in syndrome (LIS) patient showed visual fixation with the BCI assessment while exhibit higher visual function with the CRS-R assessment. The other two patients did not show any response to visual fixation with BCI assessment. The result revealed that EEG based BCI could detect brain response to the evaluation item of CRS-R in DOC patients. Therefore, the proposed BCI may provide a promising method for more objective result and thus assist CRS-R behavioral assessment.

The aim of this study is to determine the potential prognostic value of using Brain-computer Interface (BCI) to identify patients with disorder of consciousness (DOC), who show potential for recovery. A retrospective study involved 51 patients with DOC were conducted. Each patient conducted in a BCI experiment to detect awareness and received a 3-months follow-up. The BCI accuracies were correlated to patient outcomes according to the Coma Recovery Scale Revised (CRS-R). The statistical tests showed that patients with significant accuracies higher than the chance level showed greater improvement in CRS-R scores after 3 months compared to patients without significant accuracies. The sensitivity and specificity of the BCI accuracies in determining individual's consciousness recovery after 3 months are 67.7% and 90% respectively. A highly significant relationship between BCI accuracies and subsequent recovery was thus found. The BCI is suggested as an important tool to assess information-processing capacities that can predict the likelihood of recovery in patients with disorder of consciousness.

Existing evidence suggests that the default-mode network (DMN) and fronto-pariatal network (FPN) play an important role in altered states of consciousness. However, the brain mechanisms underlying impaired consciousness and the specific network interactions involved are not well understood. We studied the topological properties of brain functional networks using resting-state functional MRI data acquired from 18 patients (11 vegetative state/unresponsive wakefulness syndrome, VS/UWS, and 7 minimally conscious state, MCS) and compared these properties with those of healthy controls. We identified that the topological properties in DMN and FPN are anti-correlated which comes, in part, from the contribution of interactions between dorsolateral prefrontal cortex of the FPN and precuneus of the DMN. Notably, altered nodal connectivity strength was distance-dependent, with most disruptions appearing in long-distance connections within the FPN but in short-distance connections within the DMN. A multivariate pattern-classification analysis revealed that combination of topological patterns between the FPN and DMN could predict conscious state more effectively than connectivity within either network. Taken together, our results imply distinct interactions between the FPN and DMN, which may mediate conscious state.

The Coma Recovery Scale-Revised (CRS-R) is a consistent and sensitive behavioral assessment standard for disorders of consciousness (DOC) patients. However, the CRS-R has limitations due to its dependence on behavioral markers, which has led to a high rate of misdiagnosis. Brain-computer interfaces (BCIs), which directly detect brain activities without any behavioral expression, can be used to evaluate a patient’s state. In this study, we explored the application of BCIs in assisting CRS-R assessments of DOC patients. Specifically, an auditory passive EEG-based BCI system with an oddball paradigm was proposed to facilitate the evaluation of one item of the auditory function scale in the CRS-R – the auditory startle. The results obtained from five healthy subjects validated the efficacy of the BCI system. Nineteen DOC patients participated in the CRS-R and BCI assessments, of which three patients exhibited no responses in the CRS-R assessment but were responsive to auditory startle in the BCI assessment. These results revealed that a proportion of DOC patients who have no behavioral responses in the CRS-R assessment can generate neural responses, which can be detected by our BCI system. Therefore, the proposed BCI may provide more sensitive results than the CRS-R and thus assist CRS-R behavioral assessments.

Consciousness loss in patients with severe brain injuries is associated with reduced functional connectivity of the default mode network (DMN), fronto-parietal network, and thalamo-cortical network. However, it is still unclear if the brain white matter connectivity between the above mentioned networks is changed in patients with disorders of consciousness (DOC). In this study, we collected diffusion tensor imaging (DTI) data from 13 patients and 17 healthy controls, constructed whole-brain white matter (WM) structural networks with probabilistic tractography. Afterward, we estimated and compared topological properties, and revealed an altered structural organization in the patients. We found a disturbance in the normal balance between segregation and integration in brain structural networks and detected significantly decreased nodal centralities primarily in the basal ganglia and thalamus in the patients. A network-based statistical analysis detected a subnetwork with uniformly significantly decreased structural connections between the basal ganglia, thalamus, and frontal cortex in the patients. Further analysis indicated that along the WM fiber tracts linking the basal ganglia, thalamus, and frontal cortex, the fractional anisotropy was decreased and the radial diffusivity was increased in the patients compared to the controls. Finally, using the receiver operating characteristic method, we found that the structural connections within the NBS-derived component that showed differences between the groups demonstrated high sensitivity and specificity (>90%). Our results suggested that major consciousness deficits in DOC patients may be related to the altered WM connections between the basal ganglia, thalamus, and frontal cortex.

Accurately predicting the basal metabolic rate (BMR) of patients in a vegetative state (VS) or minimally conscious state (MCS) is critical to proper nutritional therapy, but commonly used equations have not been shown to be accurate. Therefore, we compared the BMR measured by indirect calorimetry (IC) to BMR values estimated using common predictive equations in VS and MCS patients.Body composition variables were measured using the bioelectric impedance analysis (BIA) technique. BMR was measured by IC in 82 patients (64 men and 18 women) with VS or MCS. Patients were classified by body mass index as underweight (18.5 kg/mFor the underweight group, there was a significant difference between the measured BMR values and the estimated BMR values calculated using the H-B, Schofield, and Cunningham equations (p 0.05). For the normal-weight group, the BMR values estimated using the H-B and Cunningham equations were different significantly from the measured BMR (p 0.05 and p 0.01 respectively). Of the predictive equations, only Schofield was not significantly different from the measured BMR in the normal-weight group. The Schofield equation showed the best concordance (only 41.5%) with the BMR values measured by IC.None of the commonly used equations to estimate BMR were suitable for the VS or MCS populations. Indirect calorimetry is the preferred way to avoid either over or underestimate of BMR values.

Background For patients with disorders of consciousness such as coma, a vegetative state or a minimally conscious state, one challenge is to detect and assess the residual cognitive functions in their brains. Number processing and mental calculation are important brain functions but are difficult to detect in patients with disorders of consciousness using motor response-based clinical assessment scales such as the Coma Recovery Scale-Revised due to the patients’ motor impairments and inability to provide sufficient motor responses for number- and calculation-based communication. Methods In this study, we presented a hybrid brain-computer interface that combines P300 and steady state visual evoked potentials to detect number processing and mental calculation in Han Chinese patients with disorders of consciousness. Eleven patients with disorders of consciousness who were in a vegetative state (n = 6) or in a minimally conscious state (n = 3) or who emerged from a minimally conscious state (n = 2) participated in the brain-computer interface-based experiment. During the experiment, the patients with disorders of consciousness were instructed to perform three tasks, i.e., number recognition, number comparison, and mental calculation, including addition and subtraction. In each experimental trial, an arithmetic problem was first presented. Next, two number buttons, only one of which was the correct answer to the problem, flickered at different frequencies to evoke steady state visual evoked potentials, while the frames of the two buttons flashed in a random order to evoke P300 potentials. The patients needed to focus on the target number button (the correct answer). Finally, the brain-computer interface system detected P300 and steady state visual evoked potentials to determine the button to which the patients attended, further presenting the results as feedback. Results Two of the six patients who were in a vegetative state, one of the three patients who were in a minimally conscious state, and the two patients that emerged from a minimally conscious state achieved accuracies significantly greater than the chance level. Furthermore, P300 potentials and steady state visual evoked potentials were observed in the electroencephalography signals from the five patients. Conclusions Number processing and arithmetic abilities as well as command following were demonstrated in the five patients. Furthermore, our results suggested that through brain-computer interface systems, many cognitive experiments may be conducted in patients with disorders of consciousness, although they cannot provide sufficient behavioral responses.

Currently, detecting awareness in patients with disorders of consciousness (DOC) is a challenging task, which is commonly addressed through behavioral observation scales such as the JFK Coma Recovery Scale-Revised. Brain-computer interfaces (BCIs) provide an alternative approach to detect awareness in patients with DOC. However, these patients have a much lower capability of using BCIs compared to healthy individuals. This study proposed a novel BCI using temporally, spatially, and semantically congruent audiovisual stimuli involving numbers (i.e., visual and spoken numbers). Subjects were instructed to selectively attend to the target stimuli cued by instruction. Ten healthy subjects first participated in the experiment to evaluate the system. The results indicated that the audiovisual BCI system outperformed auditory-only and visual-only systems. Through event-related potential analysis, we observed audiovisual integration effects for target stimuli, which enhanced the discriminability between brain responses for target and nontarget stimuli and thus improved the performance of the audiovisual BCI. This system was then applied to detect the awareness of seven DOC patients, five of whom exhibited command following as well as number recognition. Thus, this audiovisual BCI system may be used as a supportive bedside tool for awareness detection in patients with DOC.

Currently, detecting awareness in patients with disorders of consciousness (DOC) is a challenging task, which is commonly addressed through behavioral observation scales such as the JFK Coma Recovery Scale-Revised. Brain-computer interfaces (BCIs) provide an alternative approach to detect awareness in patients with DOC. However, these patients have a much lower capability of using BCIs compared to healthy individuals. This study proposed a novel BCI using temporally, spatially and semantically congruent audiovisual stimuli involving numbers (i.e., visual and spoken numbers). Subjects were instructed to selectively attend to the target stimuli cued by instruction. Ten healthy subjects first participated in the experiment to evaluate the system. The results indicated that the audiovisual BCI system outperformed auditory-only and visual-only systems. Through event-related potential analysis, we observed audiovisual integration effects for target stimuli, which enhanced the discriminability between brain responses for target and nontarget stimuli and thus improved the performance of the audiovisual BCI. This system was then applied to detect the awareness of seven DOC patients, five of whom exhibited command following as well as number recognition. Thus, this audiovisual BCI system may be used as a supportive bedside tool for awareness detection in patients with DOC.

Objective. The JFK coma recovery scale-revised (JFK CRS-R), a behavioral observation scale, is widely used in the clinical diagnosis/assessment of patients with disorders of consciousness (DOC). However, the JFK CRS-R is associated with a high rate of misdiagnosis (approximately 40%) because DOC patients cannot provide sufficient behavioral responses. A brain–computer interface (BCI) that detects command/intention-specific changes in electroencephalography (EEG) signals without the need for behavioral expression may provide an alternative method. Approach. In this paper, we proposed an audiovisual BCI communication system based on audiovisual 'yes' and 'no' stimuli to supplement the JFK CRS-R for assessing the communication ability of DOC patients. Specifically, patients were given situation-orientation questions as in the JFK CRS-R and instructed to select the answers using the BCI. Main results. Thirteen patients (eight vegetative state (VS) and five minimally conscious state (MCS)) participated in our experiments involving both the BCI- and JFK CRS-R-based assessments. One MCS patient who received a score of 1 in the JFK CRS-R achieved an accuracy of 86.5% in the BCI-based assessment. Seven patients (four VS and three MCS) obtained unresponsive results in the JFK CRS-R-based assessment but responsive results in the BCI-based assessment, and 4 of those later improved scores in the JFK CRS-R-based assessment. Five patients (four VS and one MCS) obtained usresponsive results in both assessments. Significance. The experimental results indicated that the audiovisual BCI could provide more sensitive results than the JFK CRS-R and therefore supplement the JFK CRS-R.

To conduct a clinical trial of ketogenic diet (KD) in patients with acute spinal cord injury (SCI) and evaluate its safety and feasibility by measuring blood ketone bodies and blood glucose levels.Ten patients with acute SCI were recruited in the trial during the period from May, 2012 to October, 2013. The patients received a standard KD after fasting for 48 h. The levels of blood ketone, blood glucose and uric ketone were tested daily, and routine blood examination, electrolytes, liver and kidney function, body mass index (BMI), sensory and motor function, and adverse reactions were monitored weekly to assess the safety and feasibility of KD.KD treatment lasted for a mean of 12.9 days (4 to 29 days) in these patients. In all the patients, blood ketone level increased during the fasting and maintained a level above 2.0 mmol/L after taking KD, while the uric ketone level ranged from +++ to ++++. The blood glucose level was in the normal range during KD. Except for blood chloride level and BMI, routine blood test results, electrolytes, liver and kidney function showed no significant changes after KD. No significant changes were observed in the sensation of light touch and pinprick. The average motor ASIA score increased from 33.3 to 35.1 after KD. Gastrointestinal dysfunction (diarrhea, nausea, poor appetite, gastric pain, and abdominal distension) was recorded in 5 patients, hypoglycemia occurred in one patient early after KD, and one patient experienced urticaria during KD. All the adverse reactions were relieved after symptomatic treatments.This preliminary clinical trial demonstrated that KD could increase ketone bodies level and maintain a normal blood glucose level, suggesting its safety and feasibility in patients with acute SCI.

Objective. The bedside detection of potential awareness in patients with disorders of consciousness (DOC) currently relies only on behavioral observations and tests; however, the misdiagnosis rates in this patient group are historically relatively high. In this study, we proposed a visual hybrid brain–computer interface (BCI) combining P300 and steady-state evoked potential (SSVEP) responses to detect awareness in severely brain injured patients. Approach. Four healthy subjects, seven DOC patients who were in a vegetative state (VS, n = 4) or minimally conscious state (MCS, n = 3), and one locked-in syndrome (LIS) patient attempted a command-following experiment. In each experimental trial, two photos were presented to each patient; one was the patientʼs own photo, and the other photo was unfamiliar. The patients were instructed to focus on their own or the unfamiliar photos. The BCI system determined which photo the patient focused on with both P300 and SSVEP detections. Main results. Four healthy subjects, one of the 4 VS, one of the 3 MCS, and the LIS patient were able to selectively attend to their own or the unfamiliar photos (classification accuracy, 66–100%). Two additional patients (one VS and one MCS) failed to attend the unfamiliar photo (50–52%) but achieved significant accuracies for their own photo (64–68%). All other patients failed to show any significant response to commands (46–55%). Significance. Through the hybrid BCI system, command following was detected in four healthy subjects, two of 7 DOC patients, and one LIS patient. We suggest that the hybrid BCI system could be used as a supportive bedside tool to detect awareness in patients with DOC.