AIMS:Spinal cord stimulation (SCS) is a promising treatment for disorders of consciousness (DoC), but early neurophysiological markers of durable recovery remain unclear. We aimed to determine whether source-space EEG network energy and communication features capture early brain-network reorganization linked to 6-month recovery in chronic DoC. METHODS:Thirty-one chronic DoC patients undergoing cervical SCS completed resting-state EEG before stimulation and at 1 week and 1 month after stimulation onset. Source-space EEG was analyzed across delta, theta, alpha, and beta bands. NetPower quantified network energy within five canonical networks, and ModularAUC quantified threshold-robust within- and between-network communication. EEG features were related to 6-month CRS-R outcomes. RESULTS:Recovery was associated with sustained alpha/beta NetPower enhancement across default mode, frontoparietal, cingulo-opercular, somatomotor, and occipital networks, peaking at 1 month. Beta-band ModularAUC showed the clearest communication-architecture consolidation, with broader within- and cross-network synergy in recovered patients. Low-frequency changes were weaker and less consistent. High-frequency NetPower features, especially FPN alpha at 1 month and CON beta at 1 week, showed the strongest associations with long-term improvement. CONCLUSIONS:SCS-related recovery in DoC is characterized by high-frequency network-energy enhancement and beta-band communication consolidation. Here, high-frequency network reorganization mainly refers to alpha- and beta-band source-space EEG changes. Source-space EEG may provide early potential neurophysiological markers for monitoring recovery.

The search for neural correlates of consciousness has always been a hot topic in the field of consciousness. Previous studies have shown that high-density transcranial direct current stimulation (HD-tDCS) can promote the recovery of consciousness level in patients with disorders of consciousness (DOC). This study intends to explore the neuromodulatory effects of HD-tDCS at different target from the perspectives of brain spatiotemporal dynamics and directed information flow, thereby clarifying the key brain areas for the origin of consciousness. The study prospectively used a high-density transcranial direct current stimulation (HD-tDCS) protocol to perform repeated stimulation at different target points for 46 DOC patients (F3 group, n = 11; sham group, n = 19; Pz group, n = 16). The Coma Recovery Scale-Revised (CRS-R) index was calculated, and microstate analysis and symbolic transfer entropy(STE) brain network construction were performed before and 14 days after HD-tDCS stimulation. We identified seven microstates with different spatial distributions of electrode activation. There were significant differences in microstates (including spatial activation patterns and brain dynamics) for different stimulation protocols. At the same time, the F3 group strengthened the information flow from the anterior to the posterior brain and internal information flow in the anterior brain in the theta band, while the Pz group mainly increased the information flow between the left frontal and parietal lobes in the theta and alpha bands. The study suggests that consciousness is the result of the comprehensive action of the anterior and posterior brain, and there is an overlap in the mechanisms of action between the two HD-tDCS stimulation protocols, suggesting that a multi-target combined stimulation protocol may be a potentially better stimulation scheme.

Introduction: Functional connectivity across large-scale networks is crucial for the regulation of conscious states. Nonetheless, our understanding of potential alterations in the temporal dynamics of dynamic functional connectivity (dFC) among patients with disorders of consciousness (DOC) remains limited. The present study aimed to examine different time-scale spatiotemporal dynamics of electroencephalogram oscillation amplitudes recorded in different consciousness states. Methods: Resting-state electroencephalograms were collected from a cohort of 90 patients with DOC. The sliding window approach was used to create dFC matrices, which were subsequently subjected to kmeans clustering to identify distinct states. Finally, we performed state analysis and developed a decoding model to predict consciousness. Results: There was significantly lower dFC within the forebrain network in patients with unresponsive wakefulness syndrome than in those with a minimally conscious state. Moreover, there were significant differences in temporal properties, mean dwell time, and the number of transitions in the highfrequency band at different time scales between the unresponsive wakefulness syndrome and minimally conscious state groups. Using the multi-band and multi-range temporal dynamics of dFC approach, satisfactory classification accuracy (approximately 83.3 %) was achieved. Conclusion: Loss of consciousness is accompanied by an imbalance of complex dynamics within the brain. Both transitions between states at short and medium time scales in high-frequency bands and the forebrain are important in consciousness recovery. Together, our findings contribute to a better understanding of brain network alterations in patients with DOC. (c) 2024 The Author(s). Published by Elsevier Ltd on behalf of Tsinghua University Press. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

IntroductionThe mismatch negativity (MMN) index has been used to evaluate consciousness levels in patients with disorders of consciousness (DoC). Indeed, MMN has been validated for the diagnosis of vegetative state/unresponsive wakefulness syndrome (VS/UWS) and minimally conscious state (MCS). In this study, we evaluated the accuracy of different MMN amplitude representations in predicting levels of consciousness.MethodsTask-state electroencephalography (EEG) data were obtained from 67 patients with DoC (35 VS and 32 MCS). We performed a microstate analysis of the task-state EEG and used four different representations (the peak amplitude of MMN at electrode Fz (Peak), the average amplitude within a time window −25– 25 ms entered on the latency of peak MMN component (Avg for peak ± 25 ms), the average amplitude of averaged difference wave for 100–250 ms (Avg for 100–250 ms), and the average amplitude difference between the standard stimulus (“S”) and the deviant stimulus (“D”) at the time corresponding to Microstate 1 (MS1) (Avg for MS1) of the MMN amplitude to predict the levels of consciousness.ResultsThe results showed that among the four microstates clustered, MS1 showed statistical significance in terms of time proportion during the 100–250 ms period. Our results confirmed the activation patterns of MMN through functional connectivity analysis. Among the four MMN amplitude representations, the microstate-based representation showed the highest accuracy in distinguishing different levels of consciousness in patients with DoC (AUC = 0.89).ConclusionWe discovered a prediction model based on microstate calculation of MMN amplitude can accurately distinguish between MCS and VS states. And the functional connection of the MS1 is consistent with the activation mode of MMN.

IntroductionExercise rehabilitation is crucial for neurological recovery in hemiplegia-induced upper limb dysfunction. Technology-assisted cortical activation in sensorimotor areas has shown potential for restoring motor function. This study assessed the feasibility of mobile serious games for stroke patients' motor rehabilitation.MethodsA dedicated mobile application targeted shoulder, elbow, and wrist training. Twelve stroke survivors attempted a motor task under two conditions: serious mobile game-assisted and conventional rehabilitation. Electroencephalography and electromyography measured the therapy effects.ResultsPatients undergoing game-assisted rehabilitation showed stronger event-related desynchronization (ERD) in the contralateral hemisphere's motor perception areas compared to conventional rehabilitation (p < 0.05). RMS was notably higher in game-assisted rehabilitation, particularly in shoulder training (p < 0.05).DiscussionSerious mobile game rehabilitation activated the motor cortex without directly improving muscle activity. This suggests its potential in neurological recovery for stroke patients.

AIM:We aimed to assess the effects of cerebral glucagon-like peptide-1 receptor (GLP-1R) activation on the glymphatic system and whether this effect was therapeutic for traumatic brain injury (TBI).METHODS:Immunofluorescence was employed to evaluate glymphatic system function. The blood-brain barrier (BBB) permeability, microvascular basement membrane, and tight junction expression were assessed using Evans blue extravasation, immunofluorescence, and western blot. Immunohistochemistry was performed to assess axonal damage. Neuronal apoptosis was evaluated using Nissl staining, terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) staining, and western blot. Cognitive function was assessed using behavioral tests.RESULTS:Cerebral GLP-1R activation restored glymphatic transport following TBI, alleviating BBB disruption and neuronal apoptosis, thereby improving cognitive function following TBI. Glymphatic function suppression by treatment using aquaporin 4 inhibitor TGN-020 abolished the protective effect of the GLP-1R agonist against cognitive impairment.CONCLUSION:Cerebral GLP-1R activation can effectively ameliorate neuropathological changes and cognitive impairment following TBI; the underlying mechanism could involve the repair of the glymphatic system damaged by TBI.

Objective Acute subdural hematoma (ASDH) is a common neurological emergency, and its appearance on head-computed tomographic (CT) imaging helps guide clinical treatment. To provide a basis for clinical decision-making, we analyzed that the density difference between the gray and white matter of the CT image is associated with the prognosis of patients with ASDH. Methods We analyzed the data of 194 patients who had ASDH as a result of closed traumatic brain injury (TBI) between 2018 and 2021. The patients were subdivided into surgical and non-surgical groups, and the non-surgical group was further subdivided into “diffused [hematoma]” and “non-diffused” groups. The control group's CT scans were normal. The 3D Slicer software was used to quantitatively analyze the density of gray and white matter depicted in the CT images. Results Imaging evaluation showed that the median difference in density between the gray and white matter on the injured side was 4.12 HU (IQR, 3.91–4.22 HU; p < 0.001) and on the non-injured side was 4.07 HU (IQR, 3.90–4.19 HU; p < 0.001), and the hematoma needs to be surgically removed. The median density difference value of the gray and white matter on the injured side was 3.74 HU (IQR, 3.53–4.01 HU; p < 0.001) and on the non-injured side was 3.71 HU (IQR, 3.69–3.73 HU; p < 0.001), and the hematoma could diffuse in a short time. Conclusion Quantitative analysis of the density differences in the gray and white matter of the CT images can be used to evaluate the clinical prognosis of patients with ASDH.

随着急诊和重症医学的发展,脑损伤后形成慢性意识障碍(pDOC)的患者逐年增加,准确评估患者的意识水平成为诊疗的重要环节.失匹配负波(MMN)作为一种不依赖患者主动注意的事件相关电位(ERP),在意识障碍领域具有广阔的应用前景.本文依据现有pDOC及MMN的临床诊治相关研究,梳理总结了慢性意识障碍的分类、诊断和MMN的产生机制、结果判读、临床应用,并进行综述,突出MMN在pDOC中的特殊性和重要性,为后续MMN在pDOC中基础研究和临床诊疗提供参考.

In the present study, we aimed to elucidate changes in electroencephalography (EEG) metrics during recovery of consciousness and to identify possible clinical markers thereof. More specifically, in order to assess changes in multidimensional EEG metrics during neuromodulation, we performed repeated stimulation using a high-density transcranial direct current stimulation (HD-tDCS) protocol in 42 patients with disorders of consciousness (DOC). Coma Recovery Scale-Revised (CRS-R) scores and EEG metrics [brain network indicators, spectral energy, and normalized spatial complexity (NSC)] were obtained before as well as fourteen days after undergoing HD-tDCS stimulation. CRS-R scores increased in the responders (R +) group after HD-tDCS stimulation. The R + group also showed increased spectral energy in the alpha2 and beta1 bands, mainly at the frontal and parietal electrodes. Increased graphical metrics in the alpha1, alpha2, and beta1 bands combined with increased NSC in the beta2 band in the R + group suggested that improved consciousness was associated with a tendency toward stronger integration in the alpha1 band and greater isolation in the beta2 band. Following this, using NSC as a feature to predict responsiveness through machine learning, which yielded a prediction accuracy of 0.929, demonstrated that the NSC of the alpha and gamma bands at baseline successfully predicted improvement in consciousness. According to our findings reported herein, we conclude that neuromodulation of the posterior lobe can lead to an EEG response related to consciousness in DOC, and that the posterior cortex may be one of the key brain areas involved in the formation or maintenance of consciousness.

Objective:To investigate the application value of transcranial Doppler ultrasound (TCD) in the assessment of intracranial pressure (ICP) in patients with traumatic brain injury (TBI).Methods:A retrospective analysis was conducted on the clinical data of 26 patients with TBI who underwent invasive ICP monitoring early after admission from October 2018 to December 2020 in the Neurotrauma Department of the First Hospital of Jilin University. The TCD parameters of all patients (260 cases) were collected, including systolic blood flow velocity (FVs), diastolic blood flow velocity (FVd), mean blood flow velocity (FVm), pulsatility index (PI) and resistance index (RI). We documented invasive monitoring parameters during the same period, including ICP and mean arterial pressure (MAP). Modeling formula 1 [non-invasive ICP 1 (nICP 1) = 4.47×PI+ 12.68], formula 2 [nICP 2 = MAP×(1-FVd/FVm) -14], formula 3 (nICP 3 = 10.93×PI-1.28) were utilized to calculate nICP. The bivariate Pearson correlation coefficient was used to analyze the correlation between nICP and ICP at the same time, the Bland-Altman test plot of nICP and ICP was drawn to compare the consistency deviation, the receiver operating characteristic (ROC) curve was drawn for predicting the increase of ICP [ICP≥20 mm Hg (1 mm Hg=0.133 kPa)] using nICP and its predictive power was calculated. According to the applied invasive monitoring technology, the patients were divided into hydraulic group (159 cases) and piezoelectric group (101 cases). According to whether the patients underwent decompressive craniectomy, they were divided into decompressive craniectomy group (201 cases) and non-decompressive craniectomy group (59 cases). Subgroup analyses were performed separately. Results:Among the parameters of TCD, PI was positively correlated with ICP ( r=0.74, P<0.001). The results of Pearson correlation analysis showed that nICP 1, nICP 2, nICP 3 were all positively correlated with ICP (all P<0.001). Bland-Altman test results showed that the deviations of nICP 1, nICP 2, and nICP 3 were 1.3±2.4 mm Hg, -2.1±6.3 mm Hg, -6.2±2.1 mm Hg respectively. Similar results were obtained in subgroup analyses. The ROC curve analysis results showed that the area under curve(AUC) of nICP 1, nICP 2, and nICP 3 for predicting increased ICP were 0.91, 0.79, and 0.89 respectively (all P<0.001), and nICP 1 had higher accuracy, corresponding sensitivity was 94.44%, specificity was 83.48%. Conclusion:Calculation of nICP based on TCD parameters can assist dynamically assess the changes in ICP in patients with traumatic brain injury, which is simple, accurate, and has certain value of clinical application.

ObjectiveAssessing the risk of postoperative recurrence of chronic subdural hematoma (CSDH) is a clinical focus. To screen the main factors associated with the perioperative hematoma recurrence. The brain re-expansion is the core factor of recurrence. A clinical prognostic scoring system was also proposed.MethodsWe included 295 patients with unilateral CSDH as the training group for modeling. Factors predicting postoperative recurrence requiring reoperation (RrR) were determined using univariate and multivariate regression analyses, and bivariate Pearson correlation coefficient analysis was used to exclude related factors. Receiver operating characteristic curve analysis evaluates the ability of main factors to predict RrR and determines the cut-off value of brain re-expansion rate. We developed a prognostic scoring system and conducted preliminary verification. A verification group including 119 patients with unilateral CSDH was used to verify the grading systems.ResultsThe key factors for predicting unilateral CSDH recurrence were cerebral re-expansion rate (≤ 40%) at postoperative days 7–9 (OR 25.91, p < 0.001) and the preoperative CT density classification (isodense or hyperdense, or separated or laminar types) (OR 8.19, p = 0.007). Cerebral atrophy played a key role in brain re-expansion (OR 2.36, p = 0.002). The CSDH prognostic grading system ranged from 0 to 3. An increased score was associated with a more accurate progressive increase in the RrR rate (AUC = 0.856).ConclusionsOur prognostic grading system could screen clinically high-risk RrR patients with unilateral CSDH. However, increased attention should be paid to brain re-expansion rate after surgery in patients with CSDH.

BACKGROUND AND OBJECTIVES:The resting-state brain is composed of several discrete networks, which remain stable for 10-100 ms. These functional microstates are considered the building blocks of spontaneous consciousness. Electroencephalography (EEG) microstate analysis may provide insight into the altered brain dynamics underlying consciousness recovery in patients with disorders of consciousness (DOC). We aimed to analyze microstates in the resting-state EEG source space in patients with DOC, the relationship between state-specific features and consciousness levels, and the corresponding patterns of microstates and functional networks.METHODS:We obtained resting-state EEG data from 84 patients with DOC (27 in a minimally conscious state [MCS] and 57 in a vegetative state [VS] or with unresponsive wakefulness syndrome). We conducted a microstate analysis of the resting-state (EEG) source space and developed a state-transition analysis protocol for patients with DOC.RESULTS:We identified seven microstates with distinct spatial distributions of cortical activation. Multivariate pattern analyses revealed that different functional connectivity patterns were associated with source-level microstates. There were significant differences in the microstate properties, including spatial activation patterns, temporal dynamics, state shifts, and connectivity construction, between the MCS and VS groups.DISCUSSION:Our findings suggest that consciousness depends on complex dynamics within the brain and may originate from the anterior cortex.

Background Chronic subdural hematoma (CSDH) is a common neurological disease, and the surgical evacuation of subdural collection remains the primary treatment approach for symptomatic patients. Postoperative recurrence is a serious complication, and several factors are correlated with postoperative recurrence. Methods We searched Embase, Web of Science, PubMed, and Cochrane Library from their establishment to September 2020. Reports on randomized, prospective, retrospective, and overall observational studies on the management of surgical patients with CSDH were searched, and an independent reviewer performed research quality assessment. Factors that affect the postoperative recurrence of CSDH were extracted: social demographics, drugs (as the main or auxiliary treatment), surgical management, imaging, and other risk factors. We evaluated the recurrence rate of each risk factor. A random effect model was used to perform a meta-analysis, and each risk factor affecting the postoperative recurrence of CSDH was then evaluated and graded. Findings In total, 402 studies were included in this analysis and 32 potential risk factors were evaluated. Among these, 21 were significantly associated with the postoperative recurrence of CSDH. Three risk factors (male, bilateral hematoma, and no drainage) had convincing evidence. The classification of evidence can help clinicians identify significant risk factors for the postoperative recurrence of CSDH. Interpretation Only few associations were supported by high-quality evidence. Factors with high-quality evidence may be important for treating and preventing CSDH recurrence. Our results can be used as a basis for improving clinical treatment strategies and designing preventive methods. Copyright (C) 2021 The Authors. Published by Elsevier Ltd.

Objective Assessing the risk of postoperative recurrence of chronic subdural hematoma (CSDH) is a clinical focus. To screen the main factors associated with the perioperative hematoma recurrence. We also propose a new prognostic grading system and compare it with previous grading systems to deliver a quick and effective system. Methods We included 242 unilateral patients with CSDH as the training group for modeling. Factors predicting postoperative recurrence requiring reoperation (RrR) were determined using univariate and multivariate regression analyses. The cut-off value for the brain re-expansion rate was determined through receiver operating characteristic curve analysis. Based on these, we developed a new prognostic scoring system and conducted preliminary verification. A verification group including 119 patients with unilateral CSDH was used to verify the predictive performance of the new and other grading systems. Results The key factors for predicting unilateral CSDH recurrence were cerebral re-expansion rate (≤ 40%) at postoperative days 7 – 9 and the preoperative computed tomography density classification (isodense or hyperdense, or separated or laminar types). Cerebral atrophy played a key role in brain re-expansion. The CSDH prognostic grading system ranged from 0 to 3. An increased score was associated with a more accurate progressive increase in the RrR rate. Our grading system demonstrated the best predictive performance compared with other systems (area under the curve = 0.856). Conclusions Our prognostic grading system could quickly and effectively screen high-risk RrR patients with unilateral CSDH. However, increased attention should be paid to brain re-expansion rate after surgery in patients with CSDH.