Minimally Conscious State Patients Research Articles

Perturbational complexity index in assessing responsiveness to rTMS treatment in patients with disorders of consciousness: a cross-over randomized controlled trial study

BackgroundDisorders 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.MethodsTwenty 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.ResultsOne-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).ConclusionsApplying 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 registrationwww.ClinicalTrials.gov, identifier: NCT05187000.

Analyzing brain-activation responses to auditory stimuli improves the diagnosis of a disorder of consciousness by non-linear dynamic analysis of the EEG

Although auditory stimuli benefit patients with disorders of consciousness (DOC), the optimal stimulus remains unclear. We explored the most effective electroencephalography (EEG)-tracking method for eliciting brain responses to auditory stimuli and assessed its potential as a neural marker to improve DOC diagnosis. We collected 58 EEG recordings from patients with DOC to evaluate the classification model’s performance and optimal auditory stimulus. Using non-linear dynamic analysis (approximate entropy [ApEn]), we assessed EEG responses to various auditory stimuli (resting state, preferred music, subject’s own name [SON], and familiar music) in 40 patients. The diagnostic performance of the optimal stimulus-induced EEG classification for vegetative state (VS)/unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) was compared with the Coma Recovery Scale-Revision in 18 patients using the machine learning cascade forward backpropagation neural network model. Regardless of patient status, preferred music significantly activated the cerebral cortex. Patients in MCS showed increased activity in the prefrontal pole and central, occipital, and temporal cortices, whereas those in VS/UWS showed activity in the prefrontal and anterior temporal lobes. Patients in VS/UWS exhibited the lowest preferred music-induced ApEn differences in the central, middle, and posterior temporal lobes compared with those in MCS. The resting state ApEn value of the prefrontal pole (0.77) distinguished VS/UWS from MCS with 61.11% accuracy. The cascade forward backpropagation neural network tested for ApEn values in the resting state and preferred music-induced ApEn differences achieved an average of 83.33% accuracy in distinguishing VS/UWS from MCS (based on K-fold cross-validation). EEG non-linear analysis quantifies cortical responses in patients with DOC, with preferred music inducing more intense EEG responses than SON and familiar music. Machine learning algorithms combined with auditory stimuli showed strong potential for improving DOC diagnosis. Future studies should explore the optimal multimodal sensory stimuli tailored for individual patients.Trial registration: The study is registered in the Chinese Registry of Clinical Trials (Approval no: KYLL-2023-414, Registration code: ChiCTR2300079310).

Permutation conditional mutual information to quantify TMS-evoked cortical connectivity in disorders of consciousness

Objective. To improve the understanding and diagnostic accuracy of disorders of consciousness (DOC) by quantifying transcranial magnetic stimulation (TMS) evoked electroencephalography connectivity using permutation conditional mutual information (PCMI). Approach. PCMI can characterize the functional connectivity between different brain regions. This study employed PCMI to analyze TMS-evoked cortical connectivity (TEC) in 154 DOC patients and 16 normal controls, focusing on optimizing parameter selection for PCMI (Data length, Order length, Time delay). We compared short-range and long-range PCMI values across different consciousness states—unresponsive wakefulness syndrome (UWS), minimally conscious state (MCS), and normal (NOR)—and assessed various feature selection and classification techniques to distinguish these states. Main results. (1) PCMI can quantify TEC. We found optimal parameters to be Data length: 500 ms; Order: 3; Time delay: 6 ms. (2) TMS evoked potentials (TEPs) for NOR showed a rich response, while MCS patients showed only a few components, and UWS patients had almost no significant components. The values of PCMI connectivity metrics demonstrated its usefulness for measuring cortical connectivity evoked by TMS. From NOR to MCS to UWS, the number and strength of TEC decreased. Quantitative analysis revealed significant differences in the strength and number of TEC in the entire brain, local regions and inter-regions among different consciousness states. (3) A decision tree with feature selection by mutual information performed the best (balanced accuracy: 87.0% and accuracy: 83.5%). This model could accurately identify NOR (100.0%), but had lower identification accuracy for UWS (86.5%) and MCS (74.1%). Significance. The application of PCMI in measuring TMS-evoked connectivity provides a robust metric that enhances our ability to differentiate between various states of consciousness in DOC patients. This approach not only aids in clinical diagnosis but also contributes to the broader understanding of cortical connectivity and consciousness.

Individualized music induces theta-gamma phase-amplitude coupling in patients with disorders of consciousness.

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. 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). 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). 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.

Low-density EEG-based Functional Connectivity Discriminates Minimally Conscious State plus from minus

Objective: Within the continuum of consciousness, patients in a Minimally Conscious State (MCS) may exhibit high-level behavioral responses (MCS+) or may not (MCS−). The evaluation of residual consciousness and related classification is crucial to propose tailored rehabilitation and pharmacological treatments, considering the inherent differences among groups in diagnosis and prognosis. Currently, differential diagnosis relies on behavioral assessments posing a relevant risk of misdiagnosis. In this context, EEG offers a non-invasive approach to model the brain as a complex network. The search for discriminating features could reveal whether behavioral responses in post-comatose patients have a defined physiological background. Additionally, it is essential to determine whether the standard behavioral assessment for quantifying responsiveness holds physiological significance. Methods: In this prospective observational study, we investigated whether low-density EEG-based graph metrics could discriminate MCS+/− patients by enrolling 57 MCS patients (MCS−: 30; males: 28). At admission to intensive rehabilitation, 30 min resting-state closed-eyes EEG recordings were performed together with consciousness diagnosis following international guidelines. After EEG preprocessing, graphs’ metrics were estimated using different connectivity measures, at multiple connection densities and frequency bands (α,θ,δ). Metrics were also provided to cross-validated Machine Learning (ML) models with outcome MCS+/−. Results: A lower level of brain activity integration was found in the MCS− group in the α band. Instead, in the δ band MCS− group presented an higher level of clustering (weighted clustering coefficient) respect to MCS+. The best-performing solution in discriminating MCS+/− through the use of ML was an Elastic-Net regularized logistic regression with a cross-validation accuracy of 79% (sensitivity and specificity of 74% and 85% respectively). Conclusion: Despite tackling the MCS+/− differential diagnosis is highly challenging, a daily-routine low-density EEG might allow to differentiate across these differently responsive brain networks. Significance: Graph-theoretical features are shown to discriminate between these two neurophysiologically similar conditions, and may thus support the clinical diagnosis.

Dissociations between spontaneous electroencephalographic features and the perturbational complexity index in the minimally conscious state.

The analysis of spontaneous electroencephalogram (EEG) is a cornerstone in the assessment of patients with disorders of consciousness (DoC). Although preserved EEG patterns are highly suggestive of consciousness even in unresponsive patients, moderately or severely abnormal patterns are difficult to interpret. Indeed, growing evidence shows that consciousness can be present despite either large delta or reduced alpha activity in spontaneous EEG. Quantifying the complexity of EEG responses to direct cortical perturbations (perturbational complexity index [PCI]) may complement the observational approach and provide a reliable assessment of consciousness even when spontaneous EEG features are inconclusive. To seek empirical evidence of this hypothesis, we compared PCI with EEG spectral measures in the same population of minimally conscious state (MCS) patients (n= 40) hospitalized in rehabilitation facilities. We found a remarkable variability in spontaneous EEG features across MCS patients as compared with healthy controls: in particular, a pattern of predominant delta and highly reduced alpha power-more often observed in vegetative state/unresponsive wakefulness syndrome (VS/UWS) patients-was found in a non-negligible number of MCS patients. Conversely, PCI values invariably fell above an externally validated empirical cutoff for consciousness in all MCS patients, consistent with the presence of clearly discernible, albeit fleeting, behavioural signs of awareness. These results confirm that, in some MCS patients, spontaneous EEG rhythms may be inconclusive about the actual capacity for consciousness and suggest that a perturbational approach can effectively compensate for this pitfall with practical implications for the individual patient's stratification and tailored rehabilitation.

Effects of different frequencies music on cortical responses and functional connectivity in patients with minimal conscious state.

The objective of this study was to investigate brain activation and functional network patterns during musical interventions in different frequency bands using functional near-infrared spectroscopy, and to provide a basis for more effective music therapy strategy selection for patients in minimally conscious state (MCS). Twenty six MCS patients and 20 healthy people were given music intervention with low frequency (31-180 Hz), medium frequency (180-4k Hz), and high frequency (4k-22k Hz) audio. In MCS patients, low frequency music intervention induced activation of left prefrontal cortex and left primary sensory cortex (S1), also a left-hemisphere lateralization effect of dorsolateral prefrontal cortex (DLPFC). And the functional connectivity of right DLPFC-right S1 was significantly improved by high frequency music intervention. The low frequency and high frequency music may contribute more than medium frequency music to the recovery of consciousness. This study also validated the effectiveness of fNIRS in studies of brain function in MCS patients.

Temporal and spatial variability of dynamic microstate brain network in disorders of consciousness.

Accurately diagnosing patients with the vegetative state (VS) and the minimally conscious state (MCS) reached a misdiagnosis of approximately 40%. A method combined microstate and dynamic functional connectivity (dFC) to study the spatiotemporal variability of the brain in disorders of consciousness (DOC) patients was proposed. Resting-state EEG data were obtained from 16 patients with MCS and 16 patients with VS. Mutual information (MI) was used to assess the EEG connectivity in each microstate. MI-based features with statistical differences were selected as the total feature subset (TFS), then the TFS was utilized to feature selection and fed into the classifier, obtaining the optimal feature subsets (OFS) in each microstate. Subsequently, an OFS-based MI functional connectivity network (MIFCN) was constructed in the cortex. The group-average MI connectivity matrix focused on all channels revealed that all five microstates exhibited stronger information interaction in the MCS when comparing with the VS. While OFS-based MIFCN, which only focused on a few channels, revealed greater MI flow in VS patients than in MCS patients under microstates A, B, C, and E, except for microstate D. Additionally, the average classification accuracy of OFS in the five microstates was 96.2%. Constructing features based on microstates to distinguish between two categories of DOC patients had effectiveness.

Anti-Inflammatory and Cortical Responses after Transcranial Direct Current Stimulation in Disorders of Consciousness: An Exploratory Study.

Disorders of consciousness (DoC) due to severe traumatic brain injury (TBI) are associated with severe disability and an alteration of cortical activation, angiogenesis, and inflammation, which are crucial elements for behavioural recovery. This exploratory study aimed to evaluate anti-inflammatory and cortical responses after transcranial direct current stimulation (tDCS) in traumatic prolonged disorders of consciousness. Ten minimally conscious state (MCS) patients underwent ten sessions of anodal tDCS (five sessions/week, two weeks, 40 min/session) on the primary motor cortex bilaterally. Clinical evaluations were performed using the Coma Recovery Scale-Revised (CRS-R) pre- and post-treatment. In contrast, after single and multiple tDCS sessions, the haemodynamic cortical response was obtained with functional near-infrared spectroscopy (fNIRS). Moreover, angiogenesis (angiopoietin-2, BMP9, endoglin, HbEFG, HGF, IL8, Leptin, PLGF, VEGF-A, and VEGF-C) and inflammation (GM-CSF, IFNg, IP10, MCP1, and TNFα) circulating biomarkers were collected. A significant haemodynamic response was observed after a single tDCS session, with an increased activation from 4.4 (3.1-6.1) to 7.6 (2.9-15.7) a.u. (p = 0.035). After ten tDCS sessions, a significant reduction of angiopoietin-2, VEGF-C, and IP-10 was detected. Moreover, a correlation between behavioural (CRS-R), TNFα (r = 0.89; p = 0.007), and IP10 (r = 0.81; p = 0.014) variation was found. In conclusion, a single tDCS session can increase the cortical activation in MCS patients. Moreover, multiple tDCS sessions showed an anti-inflammatory effect related to behavioural improvement.

The efficacy and safety of transcutaneous auricular vagus nerve stimulation for patients with minimally conscious state: a sham-controlled randomized double-blind clinical trial.

Transcutaneous auricular vagus nerve stimulation (taVNS) has emerged as a potentially effective neuromodulation technique for addressing neurological disorders, including disorders of consciousness. Expanding upon our prior clinical study, which demonstrated the superior effectiveness of a 4-week taVNS treatment in patients with minimally conscious state (MCS) compared to those in a vegetative state/unresponsive wakefulness state, the aim of this investigation was to evaluate the safety and therapeutic efficacy of taVNS in individuals with MCS through a sham-controlled randomized double-blind clinical trial. A cohort of 50 adult patients (male = 33, female = 17) diagnosed with a MCS were randomly assigned to either the active taVNS (N = 25) or sham taVNS (N = 25) groups. The treatment period lasted for 4 weeks, followed by an 8-week follow-up period. The Coma Recovery Scale-Revised (CRS-R) and Glasgow Coma Scale (GCS) were administered at baseline and weekly during the initial 4 weeks. Additionally, the Disability Rating Scale (DRS) was used to assess the patients' functional abilities via telephone at week 12. Furthermore, various neurophysiological measures, including electroencephalogram (EEG), upper-limb somatosensory evoked potentials (USEP), brainstem auditory evoked potentials (BAEP), and P300 event-related potentials (P300), were employed to monitor changes in brain activity and neural conduction pathways. The scores for the active taVNS group in the CRS-R and GCS showed greater improvement over time compared to the sham taVNS group (CRS-R: 1-week, Z = -1.248, p = 0.212; 2-week, Z = -1.090, p = 0.276; 3-week, Z = -2.017, p = 0.044; 4-week, Z = -2.267, p = 0.023. GCS: 1-week, Z = -1.325, p = 0.185; 2-week, Z = -1.245, p = 0.213; 3-week, Z = -1.848, p = 0.065; 4-week, Z = -1.990, p = 0.047). Additionally, the EEG, USEP, BAEP, and P300 also demonstrated significant improvement in the active taVNS group compared to the sham taVNS group at week 4 (EEG, Z = -2.086, p = 0.037; USEP, Z = -2.014, p = 0.044; BAEP, Z = -2.298, p = 0.022; P300 amplitude, Z = -1.974, p = 0.049; P300 latency, t = 2.275, p = 0.027). Subgroup analysis revealed that patients with MCS derived greater benefits from receiving taVNS treatment earlier (CRS-R, Disease duration ≤ 1-month, mean difference = 8.50, 95% CI = [2.22, 14.78], p = 0.027; GCS, Disease duration ≤ 1-month, mean difference = 3.58, 95% CI = [0.14, 7.03], p = 0.044). By week 12, the active taVNS group exhibited lower Disability Rating Scale (DRS) scores compared to the sham taVNS group (Z = -2.105, p = 0.035), indicating a more favorable prognosis for MCS patients who underwent taVNS. Furthermore, no significant adverse events related to taVNS were observed during treatment. The findings of this study suggest that taVNS may serve as a potentially effective and safe intervention for facilitating the restoration of consciousness in individuals diagnosed with MCS. This therapeutic approach appears to enhance cerebral functioning and optimize neural conduction pathways. http://www.chictr.org.cn, Identifier ChiCTR2200066629.

The EEG complexity, information integration and brain network changes in minimally conscious state patients during general anesthesia

Objective. General anesthesia (GA) can induce reversible loss of consciousness. Nonetheless, the electroencephalography (EEG) characteristics of patients with minimally consciousness state (MCS) during GA are seldom observed. Approach. We recorded EEG data from nine MCS patients during GA. We used the permutation Lempel–Ziv complexity (PLZC), permutation fluctuation complexity (PFC) to quantify the type I and II complexities. Additionally, we used permutation cross mutual information (PCMI) and PCMI-based brain network to investigate functional connectivity and brain networks in sensor and source spaces. Main results. Compared to the preoperative resting state, during the maintenance of surgical anesthesia state, PLZC decreased (p < 0.001), PFC increased (p < 0.001) and PCMI decreased (p < 0.001) in sensor space. The results for these metrics in source space are consistent with sensor space. Additionally, node network indicators nodal clustering coefficient (NCC) (p < 0.001) and nodal efficiency (NE) (p < 0.001) decreased in these two spaces. Global network indicators normalized average path length () (p < 0.01) and modularity (Q) (p < 0.05) only decreased in sensor space, while the normalized average clustering coefficient () and small-world index () did not change significantly. Moreover, the dominance of hub nodes is reduced in frontal regions in these two spaces. After recovery of consciousness, PFC decreased in the two spaces, while PLZC, PCMI increased. NCC, NE, and frontal region hub node dominance increased only in the sensor space. These indicators did not return to preoperative levels. In contrast, global network indicators and Q were not significantly different from the preoperative resting state in sensor space. Significance. GA alters the complexity of the EEG, decreases information integration, and is accompanied by a reconfiguration of brain networks in MCS patients. The PLZC, PFC, PCMI and PCMI-based brain network metrics can effectively differentiate the state of consciousness of MCS patients during GA.

Neurophysiological and Psychometric Outcomes in Minimal Consciousness State after Advanced Audio-Video Emotional Stimulation: A Retrospective Study.

In the last ten years, technological innovations have led to the development of new, advanced sensory stimulation (SS) tools, such as PC-based rehabilitative programs or virtual reality training. These are meant to stimulate residual cognitive abilities and, at the same time, assess cognition and awareness, also in patients with a minimally conscious state (MCS). Our purpose was to evaluate the clinical and neurophysiological effects of multi-sensory and emotional stimulation provided by Neurowave in patients with MCS, as compared to a conventional SS treatment. The psychological status of their caregivers was also monitored. In this retrospective study, we have included forty-two MCS patients and their caregivers. Each MCS subject was included in either the control group (CG), receiving a conventional SS, or the experimental group (EG), who was submitted to the experimental training with the Neurowave. They were assessed before (T0) and after the training (T1) through a specific clinical battery, including both motor and cognitive outcomes. Moreover, in the EG, we also monitored the brain electrophysiological activity (EEG and P300). In both study groups (EG and CG), the psychological caregiver's aspects, including anxiety levels, were measured using the Zung Self-Rating Anxiety Scale (SAS). The intra-group analysis (T0-T1) of the EG showed statistical significances in all patients' outcome measures, while in the CG, we found statistical significances in consciousness and awareness outcomes. The inter-group analysis between the EG and the CG showed no statistical differences, except for global communication skills. In conclusion, the multi-sensory stimulation approach through Neurowave was found to be an innovative rehabilitation treatment, also allowing the registration of brain activity during treatment.

Deep brain stimulation in disorders of consciousness: 10 years of a single center experience

Disorders of consciousness (DoC), namely unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS), represent severe conditions with significant consequences for patients and their families. Several studies have reported the regaining of consciousness in such patients using deep brain stimulation (DBS) of subcortical structures or brainstem nuclei. Our study aims to present the 10 years’ experience of a single center using DBS as a therapy on a cohort of patients with DoC. Eighty Three consecutive patients were evaluated between 2011 and 2022; entry criteria consisted of neurophysiological and neurological evaluations and neuroimaging examinations. Out of 83, 36 patients were considered candidates for DBS implantation, and 32 patients were implanted: 27 patients had UWS, and five had MCS. The stimulation target was the centromedian-parafascicular complex in the left hemisphere in hypoxic brain lesion or the one better preserved in patients with traumatic brain injury. The level of consciousness was improved in seven patients. Three out of five MCS patients emerged to full awareness, with the ability to interact and communicate. Two of them can live largely independently. Four out of 27 UWS patients showed consciousness improvement with two patients emerging to full awareness, and the other two reaching MCS. In patients with DoC lasting longer than 12 months following traumatic brain injury or 6 months following anoxic-ischemic brain lesion, spontaneous recovery is rare. Thus, DBS of certain thalamic nuclei could be recommended as a treatment option for patients who meet neurological, neurophysiological and neuroimaging criteria, especially in earlier phases, before occurrence of irreversible musculoskeletal changes. Furthermore, we emphasize the importance of cooperation between centers worldwide in studies on the potentials of DBS in treating patients with DoC.

The Characteristics of Electroencephalogram Signatures in Minimally Conscious State Patients Induced by General Anesthesia.

General anesthesia (GA) is necessary for surgery, even for patients in a minimally conscious state (MCS). The characteristics of the electroencephalogram (EEG) signatures of the MCS patients under GA are still unclear. The EEG during GA were recorded from 10 MCS patients undergoing spinal cord stimulation surgery. The power spectrum, phase-amplitude coupling (PAC), the diversity of connectivity, and the functional network were investigated. Long term recovery was assessed by the Coma Recovery Scale-Revised at one year after the surgery, and the characteristics of the patients with good or bad prognosis status were compared. For the four MCS patients with good prognostic recovery, slow oscillation (0.1-1 Hz) and the alpha band (8-12 Hz) in the frontal areas increased during the maintenance of a surgical state of anesthesia (MOSSA), and "peak-max" and "trough-max" patterns emerged in frontal and parietal areas. During MOSSA, the six MCS patients with bad prognosis demonstrated: increased modulation index, reduced diversity of connectivity (from mean±SD of 0.877 ± 0.003 to 0.776 ± 0.003, p < 0.001), reduced function connectivity significantly in theta band (from mean±SD of 1.032 ± 0.043 to 0.589 ± 0.036, p < 0.001, in prefrontal-frontal; and from mean±SD of 0.989 ± 0.043 to 0.684 ± 0.036, p < 0.001, in frontal-parietal) and reduced local and global efficiency of the network in delta band. A bad prognosis in MCS patients is associated with signs of impaired thalamocortical and cortico-cortical connectivity - as indicated by inability to produce inter-frequency coupling and phase synchronization. These indices may have a role in predicting the long-term recovery of MCS patients.

Prevalence of the Minimally Conscious State Among Institutionalized Patients in the Netherlands: A Nationwide Study.

The minimally conscious state (MCS) is a prolonged disorder of consciousness (pDoC) and one of the most severe outcomes of acquired brain injury. Prevalence data are scarce. The aim of this study was to establish the nationwide point prevalence of institutionalized patients in MCS in the Netherlands. This was a descriptive cross-sectional study in which all 86 Dutch hospitals, all 5 specialized pDoC rehabilitation facilities, and all 274 nursing homes were asked whether they were treating patients with a pDoC on the point prevalence date of September 15, 2021. Each patient's legal representative provided informed consent for their inclusion. Patient level of consciousness was verified using the Coma Recovery Scale-Revised (CRS-R) in a single assessment session performed in the facility of residence by an experienced physician. Data on patient demographics, etiology, level of consciousness, facility of residence, and clinical status were collected from a questionnaire by the treating physician. The prevalence of institutionalized patients in MCS of per 100,000 members of the Dutch population was calculated, based on actual census data. Seventy patients were reported to have a pDoC, of whom 6 were excluded. The level of consciousness was verified for 49 patients while for 15, it could not be verified. Of the patients verified, 38 had a pDoC, of whom 32 were in MCS (mean age 44.8 years, 68.8% male). The prevalence of institutionalized patients in MCS is 0.2-0.3 per 100,000 Dutch inhabitants. Traumatic brain injury was present in 21 of 32 patients (65.6%). Specialized pDoC rehabilitation was received by 17 of 32 patients (53%), with the rest admitted to nursing homes. The most frequent signs of consciousness on the CRS-R were visual pursuit, reproducible movement to command, and automatic motor response. This nationwide study revealed a low prevalence of institutionalized patients in MCS in the Netherlands. These findings are now being used to organize pDoC care in this country.

Effects of simultaneous transcutaneous auricular vagus nerve stimulation and high-definition transcranial direct current stimulation on disorders of consciousness: a study protocol.

Non-invasive brain stimulation (NIBS) techniques are now widely used in patients with disorders of consciousness (DOC) for accelerating their recovery of consciousness, especially minimally conscious state (MCS). However, the effectiveness of single NIBS techniques for consciousness rehabilitation needs further improvement. In this regard, we propose to enhance from bottom to top the thalamic-cortical connection by using transcutaneous auricular vagus nerve stimulation (taVNS) and increase from top to bottom cortical-cortical connections using simultaneous high-definition transcranial direct current stimulation (HD-tDCS) to reproduce the network of consciousness. The study will investigate the effect and safety of simultaneous joint stimulation (SJS) of taVNS and HD-tDCS for the recovery of consciousness. We will enroll 84 MCS patients and randomize them into two groups: a single stimulation group (taVNS and HD-tDCS) and a combined stimulation group (SJS and sham stimulation). All patients will undergo a 4-week treatment. The primary outcome will be assessed using the coma recovery scale-revised (CRS-R) at four time points to quantify the effect of treatment: before treatment (T0), after 1 week of treatment (T1), after 2 weeks of treatment (T2), and after 4 weeks of treatment (T3). At the same time, nociception coma scale-revised (NCS-R) and adverse effects (AEs) will be collected to verify the safety of the treatment. The secondary outcome will involve an analysis of electroencephalogram (EEG) microstates to assess the response mechanisms of dynamic brain networks to SJS. Additionally, CRS-R and AEs will continue to be obtained for a 3-month follow-up (T4) after the end of the treatment. This study protocol aims to innovatively develop a full-time and multi-brain region combined neuromodulation paradigm based on the mesocircuit model to steadily promote consciousness recovery by restoring thalamocortical and cortical-cortical interconnections.

EEG fractal dimensions predict high-level behavioral responses in minimally conscious patients

Objective. Brain-injured patients may enter a state of minimal or inconsistent awareness termed minimally conscious state (MCS). Such patient may (MCS+) or may not (MCS-) exhibit high-level behavioral responses, and the two groups retain two inherently different rehabilitative paths and expected outcomes. We hypothesized that brain complexity may be treated as a proxy of high-level cognition and thus could be used as a neural correlate of consciousness. Approach. In this prospective observational study, 68 MCS patients (MCS-: 30; women: 31) were included (median [IQR] age 69 [20]; time post-onset 83 [28]). At admission to intensive rehabilitation, 30 min resting-state closed-eyes recordings were performed together with consciousness diagnosis following international guidelines. The width of the multifractal singularity spectrum (MSS) was computed for each channel time series and entered nested cross-validated interpretable machine learning models targeting the differential diagnosis of MCS±. Main results. Frontal MSS widths (p < 0.05), as well as the ones deriving from the left centro-temporal network (C3: p = 0.018, T3: p = 0.017; T5: p = 0.003) were found to be significantly higher in the MCS+ cohort. The best performing solution was found to be the K-nearest neighbor model with an aggregated test accuracy of 75.5% (median [IQR] AuROC for 100 executions 0.88 [0.02]). Coherently, the electrodes with highest Shapley values were found to be Fz and Cz, with four out the first five ranked features belonging to the fronto-central network. Significance. MCS+ is a frequent condition associated with a notably better prognosis than the MCS-. High fractality in the left centro-temporal network results coherent with neurological networks involved in the language function, proper of MCS+ patients. Using EEG-based interpretable algorithm to complement differential diagnosis of consciousness may improve rehabilitation pathways and communications with caregivers.

Altered brain functional connectivity in vegetative state and minimally conscious state.

The pathological mechanism for a disorder of consciousness (DoC) is still not fully understood. Based on traditional behavioral scales, there is a high rate of misdiagnosis for subtypes of DoC. We aimed to explore whether topological characterization may explain the pathological mechanisms of DoC and be effective in diagnosing the subtypes of DoC. Using resting-state functional magnetic resonance imaging data, the weighted brain functional networks for normal control subjects and patients with vegetative state (VS) and minimally conscious state (MCS) were constructed. Global and local network characteristics of each group were analyzed. A support vector machine was employed to identify MCS and VS patients. The average connection strength was reduced in DoC patients and roughly equivalent in MCS and VS groups. Global efficiency, local efficiency, and clustering coefficients were reduced, and characteristic path length was increased in DoC patients (p < 0.05). For patients of both groups, global network measures were not significantly different (p > 0.05). Nodal efficiency, nodal local efficiency, and nodal clustering coefficient were reduced in frontoparietal brain areas, limbic structures, and occipital and temporal brain areas (p < 0.05). The comparison of nodal centrality suggested that DoC causes reorganization of the network structure on a large scale, especially the thalamus. Lobal network measures emphasized that the differences between the two groups of patients mainly involved frontoparietal brain areas. The accuracy, sensitivity, and specificity of the classifier for identifying MCS and VS patients were 89.83, 78.95, and 95%, respectively. There is an association between altered network structures and clinical symptoms of DoC. With the help of network metrics, it is feasible to differentiate MCS and VS patients.

Effect of Transcranial Direct Current Stimulation on Patients With Disorders of Consciousness: A Systematic Review and Meta-analysis.

The aims of this study are to evaluate the efficacy of transcranial direct current stimulation for improving disorders of consciousness and to compare efficacy of the different etiologies of disorders of consciousness. Randomized controlled trials or crossover trials examining effects of transcranial direct current stimulation in patients with disorders of consciousness were searched in PubMed, Embase, Cochrane Library, and Web of Science. The sample characteristics, etiology, transcranial direct current stimulation treatment characteristics, and outcomes were extracted. Meta-analysis was performed using the RevMan software. We included nine trials providing data with 331 participants and found that transcranial direct current stimulation improved the Coma Recovery Scale-Revised score of disorders of consciousness patients. We found a significant improvement of Coma Recovery Scale-Revised score in the minimally conscious state group (weighted mean difference = 0.77, 95% confidence interval = 0.30-1.23, P = 0.001), but not in the vegetative state or unresponsive wakefulness syndrome group. The effects of transcranial direct current stimulation are related to etiology, as the Coma Recovery Scale-Revised score was improved in the traumatic brain injury group (weighted mean difference = 1.18, 95% confidence interval = 0.60-1.75, P < 0.001), but not in vascular accident and anoxia groups. This meta-analysis revealed the evidence for positive effects of transcranial direct current stimulation on disorders of consciousness without adverse effects observed in minimally conscious state patients. In particular, transcranial direct current stimulation may be an effective treatment in rehabilitating cognitive functions in people with traumatic brain injury.

Heart rate variability for the evaluation of patients with disorders of consciousness

ObjectiveClinical responsiveness of patients with a Disorder of Consciousness (DoC) correlates to sympathetic/parasympathetic homeostatic balance. Heart Rate Variability (HRV) metrics result in non-invasive proxies of modulation capabilities of visceral states. In this work, our aim was to evaluate whether HRV measures could improve the differential diagnosis between Unresponsive Wakefulness Syndrome (UWS) and Minimally Conscious State (MCS) with respect to multivariate models based on standard clinical electroencephalography (EEG) labeling only in a rehabilitation setting. MethodsA prospective observational study was performed consecutively enrolling 82 DoC patients. Polygraphic recordings were performed. HRV-metrics and EEG descriptors derived from the American Clinical Neurophysiology Society's Standardized Critical Care terminology were included. Descriptors entered univariate and then multivariate logistic regressions with the target set to the UWS/MCS diagnosis. ResultsHRV measures resulted significantly different between UWS and MCS patients, with higher values being associated with better consciousness levels. Specifically, adding HRV-related metrics to ACNS EEG descriptors increased the Nagelkerke R2 from 0.350 (only EEG descriptors) to 0.565 (HRV-EEG combination) with the outcome set to the consciousness diagnosis. ConclusionsHRV changes across the lowest states of consciousness. Rapid changes in heart rate, occurring in better consciousness levels, confirm the mutual correlation between visceral state functioning patterns and consciousness alterations. SignificanceQuantitative analysis of heart rate in patients with a DoC paves the way for the implementation of low-cost pipelines supporting medical decisions within multimodal consciousness assessments.