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We aimed to investigate the electrocardiogram (ECG) features in persons with chronic disorders of consciousness (DOC, ≥ 29 days since injury, DSI) resulted from the most severe brain damages. The ECG data from 30 patients with chronic DOC and 18 healthy controls (HCs) were recorded during resting wakefulness state for about five minutes. The patients were classified into vegetative state (VS) and minimally conscious state (MCS). Eight ECG metrics were extracted for comparisons between the subject subgroups, and regression analysis of the metrics were conducted on the DSI (29-593 days). The DOC patients exhibit a significantly higher heart rate (HR, p = 0.009) and lower values for SDNN (p = 0.001), CVRR (p = 0.009), and T-wave amplitude (p < 0.001) compared to the HCs. However, there're no significant differences in QRS, QT, QTc, or ST amplitude between the two groups (p > 0.05). Three ECG metrics of the DOC patients-HR, SDNN, and CVRR-are significantly correlated with the DSI. The ECG abnormalities persist in chronic DOC patients. The abnormalities are mainly manifested in the rhythm features HR, SDNN and CVRR, but not the waveform features such as QRS width, QT, QTc, ST and T-wave amplitudes., (© 2024. International Federation for Medical and Biological Engineering.)

Background: Disorders of Consciousness (DoC) caused by severe brain injuries represent a challenging clinical entity, which is easy to misdiagnosis and lacks effective treatment options. Repetitive Transcranial Magnetic Stimulation (rTMS) is a non-invasive neuroelectric stimulation method that shows promise in improving consciousness for DoC, especially in minimally conscious state (MCS). However, there is little evidence of its effectiveness, especially in RCT studies., Methods: Twenty MCS patients participated in a double-blind, randomized, crossover, sham-controlled clinical study to evaluate the safety and efficacy of rTMS for MCS. Subjects were randomized into two groups: one group received rTMS-active for 10 consecutive days (n = 10), and the other group received rTMS-sham for 10 consecutive days (n = 10). After a 10-day washout period, the two groups were crossed over and received the opposite treatment. the rTMS protocol consisted of 2,000 pulses per day in the left dorsolateral prefrontal cortex (L-DLPFC), sent at 10 Hz. The stimulation intensity was 90% of the resting motor threshold. Coma Recovery Scale Revised (CRS-R), the main evaluation index, was evaluated before and after each phase in a double-blind manner. Meanwhile RS-EEG and TMS-EEG data were acquired and relative alpha power (RAP), and perturbational complexity index based on state transitions (PCIst) were caculated., Results: One-way ANOVA revealed significantly higher scores in rTMS-active treatment compared to rTMS-sham across various measures, including CRS-R total score, RAP, PCIst (all P < 0.05). Among the 20 MCS patients, 7 (35%) were identified as responders following rTMS treatment. Compared to rTMS-sham, responder scores for CRS-R, RAP, and PCIst (all P < 0.05) were significantly elevated after rTMS-active treatment. Conversely, there was no significant difference observed in non-responders. Furthermore, post-hoc analysis revealed that baseline PCIst was significantly higher in responders than non-responders. Upon a 6-month follow-up, CRS-R scores significantly increased in all 20 patients (P = 0.026). However, the responder group exhibited a more favorable prognosis compared to the non-responder group (P = 0.031)., Conclusions: Applying 10 Hz rTMS to L-DLPFC significantly increased consciousness level in MCS patients. PCIst is a neurophysiological index that has the potential to evaluate and predict therapeutic efficacy., Trial Registration: www., Clinicaltrials: gov , identifier: NCT05187000., (© 2024. The Author(s).)

The potential influence of pituitary-related hormones (including both pituitary gland and target gland hormones) on functional recovery after traumatic brain injury has been observed. However, the relationship between these hormones and the recovery of consciousness in patients with disorders of consciousness (DOC) remains unclear. In this retrospective and observational study, 208 patients with DOC were recruited. According to the Glasgow Outcome Scale (GOS) scores after 6 months, patients with DOC were categorized into two subgroups: a favorable prognosis subgroup ( n  = 38) comprising those who regained consciousness (GOS score ≥3), and a poor prognosis subgroup ( n  = 156) comprising those who remained in DOC (GOS score <3). Comparative analyses of pituitary-related hormone levels between the two subgroups were conducted. Further, a binary logistic regression analysis was conducted to assess the predictive value of pituitary-related hormones for the patients' prognosis. The favorable prognosis subgroup showed a significant increase in adrenocorticotropic hormone (ACTH) levels ( p  = 0.036). Moreover, higher ACTH levels and shorter days since injury were significantly associated with a better prognosis, with odds ratios (ORs) of 0.928 (95% confidence interval [CI] = 0.873-0.985, p  = 0.014) and 1.015 (95% CI = 1.005-1.026, p  = 0.005), respectively. A subsequent receiver operating characteristic (ROC) analysis demonstrated the potential to predict patients' prognosis with an area under the curve value of 0.78, an overall accuracy of 75.5%, a sensitivity of 77.5%, and a specificity of 66.7%. Our findings indicate that ACTH levels could serve as a clinically valuable and convenient predictor for patients' prognosis.

Objective: This study aimed to determine whether patients with disorders of consciousness (DoC) could experience neural entrainment to individualized music, which explored the cross-modal influences of music on patients with DoC through phase-amplitude coupling (PAC). Furthermore, the study assessed the efficacy of individualized music or preferred music (PM) versus relaxing music (RM) in impacting patient outcomes, and examined the role of cross-modal influences in determining these outcomes., Methods: Thirty-two patients with DoC [17 with vegetative state/unresponsive wakefulness syndrome ( VS /UWS) and 15 with minimally conscious state (MCS)], alongside 16 healthy controls (HCs), were recruited for this study. Neural activities in the frontal-parietal network were recorded using scalp electroencephalography (EEG) during baseline (BL), RM and PM. Cerebral-acoustic coherence (CACoh) was explored to investigate participants' abilitiy to track music, meanwhile, the phase-amplitude coupling (PAC) was utilized to evaluate the cross-modal influences of music. Three months post-intervention, the outcomes of patients with DoC were followed up using the Coma Recovery Scale-Revised (CRS-R)., Results: HCs and patients with MCS showed higher CACoh compared to VS /UWS patients within musical pulse frequency ( p  = 0.016, p  = 0.045; p  < 0.001, p  = 0.048, for RM and PM, respectively, following Bonferroni correction). Only theta-gamma PAC demonstrated a significant interaction effect between groups and music conditions ( F (2,44)  = 2.685, p  = 0.036). For HCs, the theta-gamma PAC in the frontal-parietal network was stronger in the PM condition compared to the RM ( p  = 0.016) and BL condition ( p  < 0.001). For patients with MCS, the theta-gamma PAC was stronger in the PM than in the BL ( p  = 0.040), while no difference was observed among the three music conditions in patients with VS /UWS. Additionally, we found that MCS patients who showed improved outcomes after 3 months exhibited evident neural responses to preferred music ( p  = 0.019). Furthermore, the ratio of theta-gamma coupling changes in PM relative to BL could predict clinical outcomes in MCS patients ( r  = 0.992, p  < 0.001)., Conclusion: Individualized music may serve as a potential therapeutic method for patients with DoC through cross-modal influences, which rely on enhanced theta-gamma PAC within the consciousness-related network., Competing Interests: YW is the founder of Music and Reflection Incorporated. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Xiao, Zheng, Wen, Yuan, Chen, Lan, Li, Huang, Zhong, Xu, Zhan, Pan and Xie.)

Background: Transcutaneous auricular vagus nerve stimulation (taVNS) has garnered attention for stroke rehabilitation, with studies demonstrating its benefits when combined with motor rehabilitative training or delivered before motor training. The necessity of concurrently applying taVNS with motor training for post-stroke motor rehabilitation remains unclear. We aimed to investigate the necessity and advantages of applying the taVNS concurrently with motor training by an electromyography (EMG)-triggered closed-loop system for post-stroke rehabilitation., Methods: We propose a double-blinded, randomized clinical trial involving 150 stroke patients assigned to one of three groups: concurrent taVNS, sequential taVNS, or sham control condition. In the concurrent group, taVNS bursts will synchronize with upper extremity motor movements with EMG-triggered closed-loop system during the rehabilitative training, while in the sequential group, a taVNS session will precede the motor rehabilitative training. TaVNS intensity will be set below the pain threshold for both concurrent and sequential conditions and at zero for the control condition. The primary outcome measure is the Fugl-Meyer Assessment of Upper Extremity (FMA-UE). Secondary measures include standard upper limb function assessments, as well as EMG and electrocardiogram (ECG) features., Ethics and Dissemination: Ethical approval has been granted by the Medical Ethics Committee, affiliated with Zhujiang Hospital of Southern Medical University for Clinical Studies (2023-QX-012-01). This study has been registered on ClinicalTrials (NCT05943431). Signed informed consent will be obtained from all included participants. The findings will be published in peer-reviewed journals and presented at relevant stakeholder conferences and meetings., Discussion: This study represents a pioneering effort in directly comparing the impact of concurrent taVNS with motor training to that of sequential taVNS with motor training on stroke rehabilitation. Secondly, the incorporation of an EMG-triggered closed-loop taVNS system has enabled the automation and individualization of both taVNS and diverse motor training tasks-a novel approach not explored in previous research. This technological advancement holds promise for delivering more precise and tailored training interventions for stroke patients. However, it is essential to acknowledge a limitation of this study, as it does not delve into examining the neural mechanisms underlying taVNS in the context of post-stroke rehabilitation., Competing Interests: X-ZX is the co-founder of BrainClos company. SL is the RA of BrainClos company. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Xiao, Li, Xu, Liang, Yang, Zhong, Huang, Ma and Xie.)

Diagnosis of disorders of consciousness (DOC) remains a formidable challenge. Deep learning methods have been widely applied in general neurological and psychiatry disorders, while limited in DOC domain. Considering the successful use of resting-state functional MRI (rs-fMRI) for evaluating patients with DOC, this study seeks to explore the conjunction of deep learning techniques and rs-fMRI in precisely detecting awareness in DOC. We initiated our research with a benchmark dataset comprising 140 participants, including 76 unresponsive wakefulness syndrome (UWS), 25 minimally conscious state (MCS), and 39 Controls, from three independent sites. We developed a cascade 3D EfficientNet-B3-based deep learning framework tailored for discriminating MCS from UWS patients, referred to as "DeepDOC", and compared its performance against five state-of-the-art machine learning models. We also included an independent dataset consists of 11 DOC patients to test whether our model could identify patients with cognitive motor dissociation (CMD), in which DOC patients were behaviorally diagnosed unconscious but could be detected conscious by brain computer interface (BCI) method. Our results demonstrate that DeepDOC outperforms the five machine learning models, achieving an area under curve (AUC) value of 0.927 and accuracy of 0.861 for distinguishing MCS from UWS patients. More importantly, DeepDOC excels in CMD identification, achieving an AUC of 1 and accuracy of 0.909. Using gradient-weighted class activation mapping algorithm, we found that the posterior cortex, encompassing the visual cortex, posterior middle temporal gyrus, posterior cingulate cortex, precuneus, and cerebellum, as making a more substantial contribution to classification compared to other brain regions. This research offers a convenient and accurate method for detecting covert awareness in patients with MCS and CMD using rs-fMRI data., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interest., (Copyright © 2024. Published by Elsevier Inc.)

Arousal and awareness are two components of consciousness whose neural mechanisms remain unclear. Spontaneous peaks of global (brain-wide) blood-oxygenation-level-dependent (BOLD) signal have been found to be sensitive to changes in arousal. By contrasting BOLD signals at different arousal levels, we find decreased activation of the ventral posterolateral nucleus (VPL) during transient peaks in the global signal in low arousal and awareness states (non-rapid eye movement sleep and anesthesia) compared to wakefulness and in eyes-closed compared to eyes-open conditions in healthy awake individuals. Intriguingly, VPL-global co-activation remains high in patients with unresponsive wakefulness syndrome (UWS), who exhibit high arousal without awareness, while it reduces in rapid eye movement sleep, a state characterized by low arousal but high awareness. Furthermore, lower co-activation is found in individuals during N3 sleep compared to patients with UWS. These results demonstrate that co-activation of VPL and global activity is critical to arousal but not to awareness., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Numerous studies have shown that musical stimulation can activate corresponding functional brain areas. Electroencephalogram (EEG) activity during musical stimulation can be used to assess the consciousness states of patients with disorders of consciousness (DOC). In this study, a musical stimulation paradigm and verifiable criteria were used for consciousness assessment. Twenty-nine participants (13 healthy subjects, 6 patients in a minimally conscious state (MCS) and 10 patients in a vegetative state (VS)) were recruited, and EEG signals were collected while participants listened to preferred and relaxing music. Fusion features based on differential entropy (DE), common spatial pattern (CSP), and EEG-based network pattern (ENP) features were extracted from EEG signals, and a convolutional neural network-long short-term memory (CNN-LSTM) model was employed to classify preferred and relaxing music.The results showed that the average classification accuracy for healthy subjects reached 85.58%. For two of the patients in the MCS group, the classification accuracies reached 78.18% and 66.14%, and they were diagnosed with emergence from MCS (EMCS) two months later. The accuracies of three patients in the VS group were 58.18%, 64.32% and 62.05%, with two patients showing slight increases in scale scores. Our study suggests that musical stimulation could be an effective method for consciousness detection, with significant diagnostic implications for patients with DOC.

Assessing communication abilities in patients with disorders of consciousness (DOCs) is challenging due to limitations in the behavioral scale. Electroencephalogram-based brain-computer interfaces (BCIs) and eye-tracking for detecting ocular changes can capture mental activities without requiring physical behaviors and thus may be a solution. This study proposes a hybrid BCI that integrates EEG and eye tracking to facilitate communication in patients with DOC. Specifically, the BCI presented a question and two randomly flashing answers (yes/no). The subjects were instructed to focus on an answer. A multimodal target recognition network (MTRN) is proposed to detect P300 potentials and eye-tracking responses (i.e., pupil constriction and gaze) and identify the target in real time. In the MTRN, the dual-stream feature extraction module with two independent multiscale convolutional neural networks extracts multiscale features from multimodal data. Then, the multimodal attention strategy adaptively extracts the most relevant information about the target from multimodal data. Finally, a prototype network is designed as a classifier to facilitate small-sample data classification. Ten healthy individuals, nine DOC patients and one LIS patient were included in this study. All healthy subjects achieved 100% accuracy. Five patients could communicate with our BCI, with 76.1±7.9% accuracy. Among them, two patients who were noncommunicative on the behavioral scale exhibited communication ability via our BCI. Additionally, we assessed the performance of unimodal BCIs and compared MTRNs with other methods. All the results suggested that our BCI can yield more sensitive outcomes than the CRS-R and can serve as a valuable communication tool.

Purpose: Severe traumatic brain injury (TBI) leads to acute coma and may result in prolonged disorder of consciousness (pDOC). We aimed to determine whether right median nerve electrical stimulation is a safe and effective treatment for accelerating emergence from coma after TBI., Methods: This randomised controlled trial was performed in 22 centres in China. Participants with acute coma at 7-14 days after TBI were randomly assigned (1:1) to either routine therapy and right median nerve electrical stimulation (RMNS group) or routine treatment (control group). The RMNS group received 20 mA, 300 μs, 40 Hz stimulation pulses, lasting 20 s per minutes, 8 h per day, for 2 weeks. The primary outcome was the proportion of patients who regained consciousness 6 months post-injury. The secondary endpoints were Glasgow Coma Scale (GCS), Full Outline of Unresponsiveness scale (FOUR), Coma Recovery Scale-Revised (CRS-R), Disability Rating Scale (DRS) and Glasgow Outcome Scale Extended (GOSE) scores reported as medians on day 28, 3 months and 6 months after injury, and GCS and FOUR scores on day 1 and day 7 during stimulation. Primary analyses were based on the intention-to-treat set., Results: Between March 26, 2016, and October 18, 2020, 329 participants were recruited, of whom 167 were randomised to the RMNS group and 162 to the control group. At 6 months post-injury, a higher proportion of patients in the RMNS group regained consciousness compared with the control group (72.5%, n = 121, 95% confidence interval (CI) 65.2-78.7% vs. 56.8%, n = 92, 95% CI 49.1-64.2%, p = 0.004). GOSE at 3 months and 6 months (5 [interquartile range (IQR) 3-7] vs. 4 [IQR 2-6], p = 0.002; 6 [IQR 3-7] vs. 4 [IQR 2-7], p = 0.0005) and FOUR at 28 days (15 [IQR 13-16] vs. 13 [interquartile range (IQR) 11-16], p = 0.002) were significantly increased in the RMNS group compared with the control group. Trajectory analysis showed that significantly more patients in the RMNS group had faster GCS, CRS-R and DRS improvement (p = 0.01, 0.004 and 0.04, respectively). Adverse events were similar in both groups. No serious adverse events were associated with the stimulation device., Conclusion: Right median nerve electrical stimulation is a possible effective treatment for patients with acute traumatic coma, that will require validation in a confirmatory trial., (© 2023. The Author(s).)

Objective: This study aimed to explore whether olfactory response can be a sign of consciousness and represent higher cognitive processing in patients with disorders of consciousness (DoC) using clinical and electroencephalogram data., Methods: Twenty-eight patients with DoC [13 vegetative states ( VS )/unresponsive wakefulness syndrome (UWS) and 15 minimally conscious states (MCS)] were divided into two groups: the presence of olfactory response (ORES) group and the absence of olfactory response (N-ORES) group according to behavioral signs from different odors, i.e., vanillin, decanoic acid, and blank stimuli. We recorded an olfactory task-related electroencephalogram (EEG) and analyzed the relative power and functional connectivity at the whole-brain level in patients with DoC and healthy controls (HCs). After three months, the outcomes of DoC patients were followed up using the coma recovery scale-revised (CRS-R)., Results: A significant relationship was found between olfactory responses and the level of consciousness ( χ 2 (1) = 6.892, p  = 0.020). For olfactory EEG, N-ORES patients showed higher theta functional connectivity than ORES patients after stimulation with vanillin ( p  = 0.029; p  = 0.027). Patients with N-ORES showed lower alpha and beta relative powers than HCs at the group level ( p  = 0.019; p  = 0.033). After three months, 62.5% (10/16) of the ORES patients recovered consciousness compared to 16.7% (2/12) in the N-ORES group. The presence of olfactory response was significantly associated with an improvement in consciousness ( χ 2 (1) = 5.882, p  = 0.023)., Conclusion: Olfactory responses should be considered signs of consciousness. The differences in olfactory processing between DoC patients with and without olfactory responses may be a way to explore the neural correlates of olfactory consciousness in these patients. The olfactory response may help in the assessment of consciousness and may contribute to therapeutic orientation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Wu, Xu, Liang, Zheng, Xiao, Zhong, Chen, Lan, Huang and Xie.)

Using task-dependent neuroimaging techniques, recent studies discovered a fraction of patients with disorders of consciousness (DOC) who had no command-following behaviors but showed a clear sign of awareness as healthy controls, which was defined as cognitive motor dissociation (CMD). However, existing task-dependent approaches might fail when CMD patients have cognitive function (e.g., attention, memory) impairments, in which patients with covert awareness cannot perform a specific task accurately and are thus wrongly considered unconscious, which leads to false-negative findings. Recent studies have suggested that sustaining a stable functional organization over time, i.e., high temporal stability, is crucial for supporting consciousness. Thus, temporal stability could be a powerful tool to detect the patient's cognitive functions (e.g., consciousness), while its alteration in the DOC and its capacity for identifying CMD were unclear. The resting-state fMRI (rs-fMRI) study included 119 participants from three independent research sites. A sliding-window approach was used to investigate global and regional temporal stability, which measured how stable the brain's functional architecture was across time. The temporal stability was compared in the first dataset (36/16 DOC/controls), and then a Support Vector Machine (SVM) classifier was built to discriminate DOC from controls. Furthermore, the generalizability of the SVM classifier was tested in the second independent dataset (35/21 DOC/controls). Finally, the SVM classifier was applied to the third independent dataset, where patients underwent rs-fMRI and brain-computer interface assessment (4/7 CMD/potential non-CMD), to test its performance in identifying CMD. Our results showed that global and regional temporal stability was impaired in DOC patients, especially in regions of the cingulo-opercular task control network, default-mode network, fronto-parietal task control network, and salience network. Using temporal stability as the feature, the SVM model not only showed good performance in the first dataset (accuracy = 90%), but also good generalizability in the second dataset (accuracy = 84%). Most importantly, the SVM model generalized well in identifying CMD in the third dataset (accuracy = 91%). Our preliminary findings suggested that temporal stability could be a potential tool to assist in diagnosing CMD. Furthermore, the temporal stability investigated in this study also contributed to a deeper understanding of the neural mechanism of consciousness., Competing Interests: Declaration of competing interest The authors report no competing interests., (Copyright © 2023. Published by Elsevier Inc.)

Background: Repetitive transcranial magnetic stimulation (rTMS), as a non-invasive brain stimulation technique, has shown potentials for consciousness recovery of patients with disorders of consciousness (DoC), as, to a certain extent, it is effective in regulating the excitability of central nervous system. However, it is difficult to achieve satisfactory effect with "one size fits all" rTMS treatment due to different clinical conditions of patients. There is an urgent need to develop individualized strategy to improve the effectiveness of rTMS on patients with DoC., Methods: Our protocol is a randomized double-blind sham-controlled crossover trial that includes 30 DoC patients. Each patient will received 20 sessions, in which 10 sessions will be rTMS-active stimulus, and the other 10 sessions will be sham stimulus, separated by no less than 10 days' washout period. The rTMS-active will include 10 Hz rTMS over the individualized-targeted selection area for each patient according to the different insult regions of the brain. Coma Recovery Scale-Revised (CRS-R) will be used as primary outcome at baseline, after the first stage of stimulation, at the end of the washout period, and after the second stage of stimulation. Secondary outcomes will be measured at the same time, including efficiency, relative spectral power, and functional connectivity of high-density electroencephalograph (EEG). Adverse events will be recorded during the study., Discussion: rTMS has obtained grade A evidence in treating patients with several central nervous system diseases, and there has been some evidence showing partial improvement on level of consciousness in DoC patients. However, the effectiveness of rTMS in DoC is only 30~36%, mostly due to the non-specific target selection. In this protocol, we present a double-blind crossover randomized sham-controlled trial based on the individualized-targeted selection strategy that aims to study the effectiveness of rTMS therapy for DoC, and the result may provide new insights to non-invasive brain stimulation., Trial Registration: ClinicalTrials.gov : NCT05187000. Registered on January 10, 2022., (© 2023. The Author(s).)

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., Competing Interests: On behalf of all authors, the corresponding author states that there are no competing interests., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Background: Recent studies have shown that patients with disorders of consciousness (DoC) can benefit from repetitive transcranial magnetic stimulation (rTMS) therapy. The posterior parietal cortex (PPC) is becoming increasingly important in neuroscience research and clinical treatment for DoC as it plays a crucial role in the formation of human consciousness. However, the effect of rTMS on the PPC in improving consciousness recovery remains to be studied., Method: We conducted a crossover, randomized, double-blind, sham-controlled clinical study to assess the efficacy and safety of 10 Hz rTMS over the left PPC in unresponsive patients. Twenty patients with unresponsive wakefulness syndrome were recruited. The participants were randomly divided into two groups: one group received active rTMS treatment for 10 consecutive days ( n = 10) and the other group received sham treatment for the same period ( n = 10). After a 10-day washout period, the groups crossed over and received the opposite treatment. The rTMS protocol involved the delivery of 2000 pulses/day at a frequency of 10 Hz, targeting the left PPC (P3 electrode sites) at 90% of the resting motor threshold. The primary outcome measure was the JFK Coma Recovery Scele-Revised (CRS-R), and evaluations were conducted blindly. EEG power spectrum assessments were also conducted simultaneously before and after each stage of the intervention., Result: rTMS-active treatment resulted in a significant improvement in the CRS-R total score ( F = 8.443, p = 0.009) and the relative alpha power ( F = 11.166, p = 0.004) compared to sham treatment. Furthermore, 8 out of 20 patients classified as rTMS responders showed improvement and evolved to a minimally conscious state (MCS) as a result of active rTMS. The relative alpha power also significantly improved in responders ( F = 26.372, p = 0.002) but not in non-responders ( F = 0.704, p = 0.421). No adverse effects related to rTMS were reported in the study., Conclusions: This study suggests that 10 Hz rTMS over the left PPC can significantly improve functional recovery in unresponsive patients with DoC, with no reported side effects., Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT05187000., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Xu, Wu, Zheng, Liang, Huang, Zhong, Xiao, Lan, Bai and Xie.)

Objectives : Disorders of consciousness (DoC) is a dynamic and challenging discipline, presenting intriguing challenges to clinicians and neurorehabilitation specialists for the lack of reliable assessment methods and interventions. Understanding DoC keeps pace with scientific research is urgent to need. We quantitively analyzed publications on DoC over the recent 10 years via bibliometrics analysis, to summarize the intellectual structure, current research hotspots, and future research trends in the field of DoC. Methods : Literature was obtained from the Science Citation Index Expanded of Web of Science Core Collection (WoSCC). To illustrate the knowledge structure of DoC, CiteSpace 5.8.R3 was used to conduct a co-occurrence analysis of countries, institutions, and keywords, and a co-citation analysis of references and journals. Also, Gephi 0.9.2 contributed to the author and co-cited author analysis. We found the most influential journals, authors, and countries and the most talked about keywords in the last decade of research. Results : A total of 1919 publications were collected. Over the past 10 years, the total number of annual publications has continued to increase, with the largest circulation in 2018. We found most DoC research and close cooperation originated from developed countries, e.g., the USA, Canada, and Italy. Academics from Belgium appear to have a strong presence in the field of DoC. The most influential journals were also mainly distributed in the USA and some European countries. Conclusions : This bibliometric study sheds light on the knowledge architecture of DoC research over the past decade, reflecting current hotspots and emerging trends, and providing new insights for clinicians and academics interested in DoC. The hot issues in DoC were diagnosing and differentiating the level of consciousness, and detecting covert awareness in early severe brain-injured patients. New trends focus on exploring the recovery mechanism of DoC and neuromodulation techniques.

For patients with disorders of consciousness, such as unresponsive wakefulness syndrome (UWS) patients and minimally conscious state (MCS) patients, their long treatment cycle and high cost commonly put a heavy burden on the patient's family and society. Therefore, it is vital to accurately diagnose and predict consciousness recovery for such patients. In this paper, we explored the role of the P300 signal based on an audiovisual BCI in the classification and prognosis prediction of patients with disorders of consciousness. This experiment included 18 patients: 10 UWS patients and 8 MCS- patients. At the three-month follow-up, we defined patients with an improved prognosis (from UWS to MCS-, from UWS to MCS+, or from MCS- to MCS+) as "improved patients" and those who stayed in UWS/MCS as "not improved patients". First, we compared and analyzed different types of patients, and the results showed that the P300 detection accuracy rate of "improved" patients was significantly higher than that of "not improved" patients. Furthermore, the P300 detection accuracy of traumatic brain injury (TBI) patients was significantly higher than that of non-traumatic brain injury (NTBI, including acquired brain injury and cerebrovascular disease) patients. We also found that there was a positive linear correlation between P300 detection accuracy and CRS-R score, and patients with higher P300 detection accuracy were likely to achieve higher CRS-R scores. In addition, we found that the patients with higher P300 detection accuracies tend to have better prognosis in this audiovisual BCI. These findings indicate that the detection accuracy of P300 is significantly correlated with the level of consciousness, etiology, and prognosis of patients. P300 can be used to represent the preservation level of consciousness in clinical neurophysiology and predict the possibility of recovery in patients with disorders of consciousness.

Objective: When regaining consciousness, patients who emerge from a minimally conscious state (EMCS) present with different levels of functional disability, which pose great challenges for treatment. This study investigated the frontoparietal activity in EMCS patients and its effects on functional disability., Materials and Methods: In this preliminary study, 12 EMCS patients and 12 healthy controls were recruited. We recorded a resting-state scalp electroencephalogram (EEG) for at least 5 min for each participant. Each patient was assessed using the disability rating scale (DRS) to determine the level of functional disability. We analyzed the EEG power spectral density and sensor-level functional connectivity in relation to the patient's functional disability., Results: In the frontoparietal region, EMCS patients demonstrated lower relative beta power ( P < 0.01) and higher weighted phase lag index (wPLI) values in the theta ( P < 0.01) and gamma ( P < 0.01) bands than healthy controls. The frontoparietal theta wPLI values of EMCS patients were positively correlated with the DRS scores ( r s = 0.629, P = 0.029). At the whole-brain level, EMCS patients only had higher wPLI values in the theta band ( P < 0.01) than healthy controls. The whole-brain theta wPLI values of EMCS patients were also positively correlated with the DRS scores ( r s = 0.650, P = 0.022). No significant difference in the power and connectivity between the frontoparietal region and the whole brain in EMCS patients was observed., Conclusion: EMCS patients still experience neural dysfunction, especially in the frontoparietal region. However, the theta connectivity in the frontoparietal region did not increase specifically. At the level of the whole brain, the same shift could also be seen. Theta functional connectivity in the whole brain may underlie different levels of functional disability., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Wu, Xu, Huang, Xiao, Zheng, Zhong, Liang and Xie.)

Music can effectively improve people's emotions, and has now become an effective auxiliary treatment method in modern medicine. With the rapid development of neuroimaging, the relationship between music and brain function has attracted much attention. In this study, we proposed an integrated framework of multi-modal electroencephalogram (EEG) and functional near infrared spectroscopy (fNIRS) from data collection to data analysis to explore the effects of music (especially personal preferred music) on brain activity. During the experiment, each subject was listening to two different kinds of music, namely personal preferred music and neutral music. In analyzing the synchronization signals of EEG and fNIRS, we found that music promotes the activity of the brain (especially the prefrontal lobe), and the activation induced by preferred music is stronger than that of neutral music. For the multi-modal features of EEG and fNIRS, we proposed an improved Normalized-ReliefF method to fuse and optimize them and found that it can effectively improve the accuracy of distinguishing between the brain activity evoked by preferred music and neutral music (up to 98.38%). Our work provides an objective reference based on neuroimaging for the research and application of personalized music therapy., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Qiu, Zhong, Xie, He, Wang, Chen, Zhan and Pan.)

Behavioral assessment of sound localization in the Coma Recovery Scale-Revised (CRS-R) poses a significant challenge due to motor disability in patients with disorders of consciousness (DOC). Brain-computer interfaces (BCIs), which can directly detect brain activities related to external stimuli, may thus provide an approach to assess DOC patients without the need for any physical behavior. In this study, a novel audiovisual BCI system was developed to simulate sound localization evaluation in CRS-R. Specifically, there were two alternatively flashed buttons on the left and right sides of the graphical user interface, one of which was randomly chosen as the target. The auditory stimuli of bell sounds were simultaneously presented by the ipsilateral loudspeaker during the flashing of the target button, which prompted patients to selectively attend to the target button. The recorded electroencephalography data were analyzed in real time to detect event-related potentials evoked by the target and further to determine whether the target was attended to or not. A significant BCI accuracy for a patient implied that he/she had sound localization. Among eighteen patients, eleven and four showed sound localization in the BCI and CRS-R, respectively. Furthermore, all patients showing sound localization in the CRS-R were among those detected by our BCI. The other seven patients who had no sound localization behavior in CRS-R were identified by the BCI assessment, and three of them showed improvements in the second CRS-R assessment after the BCI experiment. Thus, the proposed BCI system is promising for assisting the assessment of sound localization and improving the clinical diagnosis of DOC patients.

Background: The detection of intrinsic brain activity (iBA) could assist clinical assessment for disorder of consciousness (DOC) patients. Previous studies have revealed the altered iBA in thalamocortical, frontoparietal, and default mode network in DOC patients using functional connectivity (FC) analysis. However, due to the assumption of synchronized iBA in FC, these studied may be inadequate for understanding the effect of severe brain injury on the temporal organization of iBA and the relationship between temporal organization and clinical feature in DOC patients. Recently, the time delay estimation (TDE) and probabilistic flow estimation (PFE) were proposed to analyze temporal organization, which could provide propagation structure and propagation probability at whole-brain level., Methods: We applied voxel-wise TDE and PFE to assess propagation structure and propagation probability for the DOC patients and then applied the connectome-based predictive modeling (CPM) to predict clinical scores for patients based on the ROI-wise TDE and PFE., Results: We found that: 1) the DOC patients showed abnormal voxel-wise time delay (TD) and probabilistic flow (PF) in the precentral gyrus, precuneus, middle cingulate cortex, and postcentral gyrus, 2) the range of TD value in the patients was shorter than that in the controls, and 3) the ROI-wise TD had a better predictive performance for clinical scores of the patients compared with that based on ROI-wise PF., Conclusion: Our findings may suggest that the propagation structure of iBA could be used to predict clinical scores in DOC patients., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

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., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain.)

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.

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., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Currently, it is challenging to detect the awareness of patients who suffer disorders of consciousness (DOC). Brain-computer interfaces (BCIs), which do not depend on the behavioral response of patients, may serve for detecting the awareness in patients with DOC. However, we must develop effective BCIs for these patients because their ability to use BCIs does not as good as healthy users., Methods: Because patients with DOC generally do not exhibit eye movements, a gaze-independent audiovisual BCI is put forward in the study where semantically congruent and incongruent audiovisual number stimuli were sequentially presented to evoke event-related potentials (ERPs). Subjects were required to pay attention to congruent audiovisual stimuli (target) and ignore the incongruent audiovisual stimuli (non-target). The BCI system was evaluated by analyzing online and offline data from 10 healthy subjects followed by being applied to online awareness detection in 8 patients with DOC., Results: According to the results on healthy subjects, the audiovisual BCI system outperformed the corresponding auditory-only and visual-only systems. Multiple ERP components, including the P300, N400 and late positive complex (LPC), were observed using the audiovisual system, strengthening different brain responses to target stimuli and non-target stimuli. The results revealed the abilities of three of eight patients to follow commands and recognize numbers., Conclusions: This gaze-independent audiovisual BCI system represents a useful auxiliary bedside tool to detect the awareness of patients with DOC.

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 88% 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 reported implementation of a multidomain prognostic model that is based on resting state functional MRI and clinical characteristics in chronic disorders of consciousness, which we suggest is accurate, robust, and interpretable., Competing Interests: MS, YY, JH, ZY, SY, QX, XX, YD, QZ, XW, YC, BH, RY, RX, TJ No competing interests declared, (© 2018, Song et al.)

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.

For patients with disorders of consciousness (DOC), such as vegetative state (VS) and minimally conscious state (MCS), detecting and assessing the residual cognitive functions of the brain remain challenging. Emotion-related cognitive functions are difficult to detect in patients with DOC using motor response-based clinical assessment scales such as the Coma Recovery Scale-Revised (CRS-R) because DOC patients have motor impairments and are unable to provide sufficient motor responses for emotion-related communication. In this study, we proposed an EEG-based brain-computer interface (BCI) system for emotion recognition in patients with DOC. Eight patients with DOC (5 VS and 3 MCS) and eight healthy controls participated in the BCI-based experiment. During the experiment, two movie clips flashed (appearing and disappearing) eight times with a random interstimulus interval between flashes to evoke P300 potentials. The subjects were instructed to focus on the crying or laughing movie clip and to count the flashes of the corresponding movie clip cued by instruction. The BCI system performed online P300 detection to determine which movie clip the patients responsed to and presented the result as feedback. Three of the eight patients and all eight healthy controls achieved online accuracies based on P300 detection that were significantly greater than chance level. P300 potentials were observed in the EEG signals from the three patients. These results indicated the three patients had abilities of emotion recognition and command following. Through spectral analysis, common spatial pattern (CSP) and differential entropy (DE) features in the delta, theta, alpha, beta, and gamma frequency bands were employed to classify the EEG signals during the crying and laughing movie clips. Two patients and all eight healthy controls achieved offline accuracies significantly greater than chance levels in the spectral analysis. Furthermore, stable topographic distribution patterns of CSP and DE features were observed in both the healthy subjects and these two patients. Our results suggest that cognitive experiments may be conducted using BCI systems in patients with DOC despite the inability of such patients to provide sufficient behavioral responses.

Background: 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., Methods: 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/m 2 , n = 34) or normal-weight (18.5 ≤ BMI < 25 kg/m 2 , n = 48). BMR was estimated for each group using the Harris-Benedict (H-B), Schofield, or Cunningham equations and compared to the measured BMR using Bland-Altman analyses., Results: For 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., Conclusions: 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., (Copyright © 2016. Published by Elsevier Ltd.)

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.

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.

Objective: 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.

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., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

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.

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.

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., (Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

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 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 patient's 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.