Cognitive Motor Dissociation in Disorders of Consciousness.

BACKGROUND: Patients with brain injury who are unresponsive to commands may perform cognitive tasks that are detected on functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). This phenomenon, known as cognitive motor dissociation, has not been systematically studied in a large cohort of persons with disorders of consciousness. METHODS: In this prospective cohort study conducted at six international centers, we collected clinical, behavioral, and task-based fMRI and EEG data from a convenience sample of 353 adults with disorders of consciousness. We assessed the response to commands on task-based fMRI or EEG in participants without an observable response to verbal commands (i.e., those with a behavioral diagnosis of coma, vegetative state, or minimally conscious state-minus) and in participants with an observable response to verbal commands. The presence or absence of an observable response to commands was assessed with the use of the Coma Recovery Scale-Revised (CRS-R). RESULTS: Data from fMRI only or EEG only were available for 65% of the participants, and data from both fMRI and EEG were available for 35%. The median age of the participants was 37.9 years, the median time between brain injury and assessment with the CRS-R was 7.9 months (25% of the participants were assessed with the CRS-R within 28 days after injury), and brain trauma was an etiologic factor in 50%. We detected cognitive motor dissociation in 60 of the 241 participants (25%) without an observable response to commands, of whom 11 had been assessed with the use of fMRI only, 13 with the use of EEG only, and 36 with the use of both techniques. Cognitive motor dissociation was associated with younger age, longer time since injury, and brain trauma as an etiologic factor. In contrast, responses on task-based fMRI or EEG occurred in 43 of 112 participants (38%) with an observable response to verbal commands. CONCLUSIONS: Approximately one in four participants without an observable response to commands performed a cognitive task on fMRI or EEG as compared with one in three participants with an observable response to commands. (Funded by the James S. McDonnell Foundation and others.).

Re-awakening the brain: Forcing transitions in disorders of consciousness by external in silico perturbation.

A fundamental challenge in neuroscience is accurately defining brain states and predicting how and where to perturb the brain to force a transition. Here, we investigated resting-state fMRI data of patients suffering from disorders of consciousness (DoC) after coma (minimally conscious and unresponsive wakefulness states) and healthy controls. We applied model-free and model-based approaches to help elucidate the underlying brain mechanisms of patients with DoC. The model-free approach allowed us to characterize brain states in DoC and healthy controls as a probabilistic metastable substate (PMS) space. The PMS of each group was defined by a repertoire of unique patterns (i.e., metastable substates) with different probabilities of occurrence. In the model-based approach, we adjusted the PMS of each DoC group to a causal whole-brain model. This allowed us to explore optimal strategies for promoting transitions by applying off-line in silico probing. Furthermore, this approach enabled us to evaluate the impact of local perturbations in terms of their global effects and sensitivity to stimulation, which is a model-based biomarker providing a deeper understanding of the mechanisms underlying DoC. Our results show that transitions were obtained in a synchronous protocol, in which the somatomotor network, thalamus, precuneus and insula were the most sensitive areas to perturbation. This motivates further work to continue understanding brain function and treatments of disorders of consciousness.

An Unpredictable Brain Is a Conscious, Responsive Brain.

Severe traumatic brain injuries typically result in loss of consciousness or coma. In deeply comatose patients with traumatic brain injury, cortical dynamics become simple, repetitive, and predictable. We review evidence that this low-complexity, high-predictability state results from a passive cortical state, represented by a stable repetitive attractor, that hinders the flexible formation of neuronal ensembles necessary for conscious experience. Our data and those from other groups support the hypothesis that this cortical passive state is because of the loss of thalamocortical input. We identify the unpredictability and complexity of cortical dynamics captured by local field potential as a sign of recovery from this passive coma attractor. In this Perspective article, we discuss how these electrophysiological biomarkers of the recovery of consciousness could inform the design of closed-loop stimulation paradigms to treat disorders of consciousness.

Exploring the clinical diagnostic value of linguistic learning ability in patients with disorders of consciousness using electrooculography.

For patients with disorders of consciousness (DoC), accurate assessment of residual consciousness levels and cognitive abilities is critical for developing appropriate rehabilitation interventions. In this study, we investigated the potential of electrooculography (EOG) in assessing language processing abilities and consciousness levels. Patients' EOG data and related electrophysiological data were analysed before and after explicit language learning. The results showed distinct differences in vocabulary learning patterns among patients with varying levels of consciousness. While minimally conscious patients showed significant neural tracking of artificial words and notable learning effects similar to those observed in healthy controls, whereas patients with unresponsive wakefulness syndrome did not show such effects. Correlation analysis further indicated that EOG detected vocabulary learning effects with comparable validity to electroencephalography, reinforcing the credibility of EOG indicator as a diagnostic tool. Critically, EOG also revealed significant correlations between individual patients' linguistic learning performance and their Oromotor/verbal function as assessed through behavioural scales. In conclusion, this study explored the differences in language processing abilities among patients with varying consciousness levels. By demonstrating the utility of EOG in evaluating consciousness and detecting vocabulary learning effects, as well as its potential to guide personalised rehabilitation, our findings indicate that EOG indicators show promise as a rapid, accurate and effective additional tool for diagnosing and managing patients with DoC.

Multimodal approaches supporting the diagnosis, prognosis and investigation of neural correlates of disorders of consciousness: A systematic review.

The limits of the standard, behaviour-based clinical assessment of patients with disorders of consciousness (DoC) prompted the employment of functional neuroimaging, neurometabolic, neurophysiological and neurostimulation techniques, to detect brain-based covert markers of awareness. However, uni-modal approaches, consisting in employing just one of those techniques, are usually not sufficient to provide an exhaustive exploration of the neural underpinnings of residual awareness. This systematic review aimed at collecting the evidence from studies employing a multimodal approach, that is, combining more instruments to complement DoC diagnosis, prognosis and better investigating their neural correlates. Following the PRISMA guidelines, records from PubMed, EMBASE and Scopus were screened to select peer-review original articles in which a multi-modal approach was used for the assessment of adult patients with a diagnosis of DoC. Ninety-two observational studies and 32 case reports or case series met the inclusion criteria. Results highlighted a diagnostic and prognostic advantage of multi-modal approaches that involve electroencephalography-based (EEG-based) measurements together with neuroimaging or neurometabolic data or with neurostimulation. Multimodal assessment deepened the knowledge on the neural networks underlying consciousness, by showing correlations between the integrity of the default mode network and the different clinical diagnosis of DoC. However, except for studies using transcranial magnetic stimulation combined with electroencephalography, the integration of more than one technique in most of the cases occurs without an a priori-designed multi-modal diagnostic approach. Our review supports the feasibility and underlines the advantages of a multimodal approach for the diagnosis, prognosis and for the investigation of neural correlates of DoCs.

Exploring the Significance of Cognitive Motor Dissociation on Patient Outcome in Acute Disorders of Consciousness.

Cognitive motor dissociation (CMD) is characterized by a dissociation between volitional brain responses and motor control, detectable only through techniques such as electroencephalography (EEG) and functional magnetic resonance imaging. Hence, it has recently emerged as a major challenge in the assessment of patients with disorders of consciousness. Specifically, this review focuses on the prognostic implications of CMD detection during the acute stage of brain injury. CMD patients were identified in each diagnostic category (coma, unresponsive wakefulness syndrome/vegetative state, minimally conscious state minus) with a relatively similar prevalence of around 20%. Current knowledge tends to indicate that the diagnosis of CMD in the acute phase often predicts a more favorable clinical outcome compared with other unresponsive non-CMD patients. Nevertheless, the review underscores the limited research in this domain, probably at least partially explained by its nascent nature and the lack of uniformity in the nomenclature for CMD-related disorders, hindering the impact of the literature in the field.

Correlation between Thalamocortical Tract and Default Mode Network with Consciousness Levels in Hypoxic-Ischemic Brain Injury Patients: A Comparative Study Using the Coma Recovery Scale-Revised.

BACKGROUND The thalamocortical tract (TCT) links nerve fibers between the thalamus and cerebral cortex, relaying motor/sensory information. The default mode network (DMN) comprises bilateral, symmetrical, isolated cortical regions of the lateral and medial parietal and temporal brain cortex. The Coma Recovery Scale-Revised (CRS-R) is a standardized neurobehavioral assessment of disorders of consciousness (DOC). In the present study, 31 patients with hypoxic-ischemic brain injury (HI-BI) were compared for changes in the TCT and DMN with consciousness levels assessed using the CRS-R. MATERIAL AND METHODS In this retrospective study, 31 consecutive patients with HI-BI (17 DOC,14 non-DOC) and 17 age- and sex-matched normal control subjects were recruited. Magnetic resonance imaging was used to diagnose HI-BI, and the CRS-R was used to evaluate consciousness levels at the time of diffusion tensor imaging (DTI). The fractional anisotropy (FA) values and tract volumes (TV) of the TCT and DMN were compared. RESULTS In patients with DOC, the FA values and TV of both the TCT and DMN were significantly lower compared to those of patients without DOC and the control subjects (p<0.05). When comparing the non-DOC and control groups, the TV of the TCT and DMN were significantly lower in the non-DOC group (p<0.05). Moreover, the CRS-R score had strong positive correlations with the TV of the TCT (r=0.501, p<0.05), FA of the DMN (r=0.532, p<0.05), and TV of the DMN (r=0.501, p<0.05) in the DOC group. CONCLUSIONS This study suggests that both the TCT and DMN exhibit strong correlations with consciousness levels in DOC patients with HI-BI.

Brain-Computer Interfaces for Communication in Patients with Disorders of Consciousness: A Gap Analysis and Scientific Roadmap.

BACKGROUND: We developed a gap analysis that examines the role of brain-computer interfaces (BCI) in patients with disorders of consciousness (DoC), focusing on their assessment, establishment of communication, and engagement with their environment. METHODS: The Curing Coma Campaign convened a Coma Science work group that included 16 clinicians and neuroscientists with expertise in DoC. The work group met online biweekly and performed a gap analysis of the primary question. RESULTS: We outline a roadmap for assessing BCI readiness in patients with DoC and for advancing the use of BCI devices in patients with DoC. Additionally, we discuss preliminary studies that inform development of BCI solutions for communication and assessment of readiness for use of BCIs in DoC study participants. Special emphasis is placed on the challenges posed by the complex pathophysiologies caused by heterogeneous brain injuries and their impact on neuronal signaling. The differences between one-way and two-way communication are specifically considered. Possible implanted and noninvasive BCI solutions for acute and chronic DoC in adult and pediatric populations are also addressed. CONCLUSIONS: We identify clinical and technical gaps hindering the use of BCI in patients with DoC in each of these contexts and provide a roadmap for research aimed at improving communication for adults and children with DoC, spanning the clinical spectrum from intensive care unit to chronic care.

Covert Consciousness in Acute Brain Injury Revealed by Automated Pupillometry and Cognitive Paradigms.

BACKGROUND: Identifying covert consciousness in intensive care unit (ICU) patients with coma and other disorders of consciousness (DoC) is crucial for treatment decisions, but sensitive low-cost bedside markers are missing. We investigated whether automated pupillometry combined with passive and active cognitive paradigms can detect residual consciousness in ICU patients with DoC. METHODS: We prospectively enrolled clinically low-response or unresponsive patients with traumatic or nontraumatic DoC from ICUs of a tertiary referral center. Age-matched and sex-matched healthy volunteers served as controls. Patients were categorized into clinically unresponsive (coma or unresponsive wakefulness syndrome) or clinically low-responsive (minimally conscious state or better). Using automated pupillometry, we recorded pupillary dilation to passive (visual and auditory stimuli) and active (mental arithmetic) cognitive paradigms, with task-specific success criteria (e.g., ≥ 3 of 5 pupillary dilations on five consecutive mental arithmetic tasks). RESULTS: We obtained 699 pupillometry recordings at 178 time points from 91 ICU patients with brain injury (mean age 60 ± 13.8 years, 31% women, and 49.5% nontraumatic brain injuries). Recordings were also obtained from 26 matched controls (59 ± 14.8 years, 38% women). Passive paradigms yielded limited distinctions between patients and controls. However, active paradigms enabled discrimination between different states of consciousness. With mental arithmetic of moderate complexity, ≥ 3 pupillary dilations were seen in 17.8% of clinically unresponsive patients and 50.0% of clinically low-responsive patients (odds ratio 4.56, 95% confidence interval 2.09-10.10; p < 0.001). In comparison, 76.9% healthy controls responded with ≥ 3 pupillary dilations (p = 0.028). Results remained consistent across sensitivity analyses using different thresholds for success. Spearman's rank analysis underscored the robust association between pupillary dilations during mental arithmetic and consciousness levels (rho = 1, p = 0.017). Notably, one behaviorally unresponsive patient demonstrated persistent command-following behavior 2 weeks before overt signs of awareness, suggesting prolonged cognitive motor dissociation. CONCLUSIONS: Automated pupillometry combined with mental arithmetic can identify cognitive efforts, and hence covert consciousness, in ICU patients with acute DoC.

[Recovery of consciousness under therapy with benzodiazepines. A case report and literature review]. / Vosstanovlenie yasnogo soznaniya na fone priema benzodiazepinov. Opisanie sluchaya i obzor literatury.

BACKGROUND: Treatment of patients with prolonged and permanent disturbance of consciousness is still an extremely difficult problem. Nowadays, management is based on pathophysiological and molecular mechanisms of impaired consciousness. Several electrophysiological and pharmacological methods were proposed to restore consciousness in appropriate patients. OBJECTIVE: We present recovery of clear consciousness under therapy with phenazepam and literature review devoted to therapy of these disorders. RESULTS AND CONCLUSION: This case confirms available data on drug neuromodulation in complex treatment of patients with prolonged impairment of consciousness and substantiates the need for individual multimodal assessment of structural and functional disorders in prolonged and chronic impairment of consciousness for adequate therapy.

Global Field Time-Frequency Representation-Based Discriminative Similarity Analysis of Passive Auditory ERPs for Diagnosis of Disorders of Consciousness.

Behavioural diagnosis of patients with disorders of consciousness (DOC) is challenging and prone to inaccuracies. Consequently, there have been increased efforts to develop bedside assessment based on EEG and event-related potentials (ERPs) that are more sensitive to the neural factors supporting conscious awareness. However, individual detection of residual consciousness using these techniques is less established. Here, we hypothesize that the cross-state similarity (defined as the similarity between healthy and impaired conscious states) of passive brain responses to auditory stimuli can index the level of awareness in individual DOC patients. To this end, we introduce the global field time-frequency representation-based discriminative similarity analysis (GFTFR-DSA). This method quantifies the average cross-state similarity index between an individual patient and our constructed healthy templates using the GFTFR as an EEG feature. We demonstrate that the proposed GFTFR feature exhibits superior within-group consistency in 34 healthy controls over traditional EEG features such as temporal waveforms. Second, we observed the GFTFR-based similarity index was significantly higher in patients with a minimally conscious state (MCS, 40 patients) than those with unresponsive wakefulness syndrome (UWS, 54 patients), supporting our hypothesis. Finally, applying a linear support vector machine classifier for individual MCS/UWS classification, the model achieved a balanced accuracy and F1 score of 0.77. Overall, our findings indicate that combining discriminative and interpretable markers, along with automatic machine learning algorithms, is effective for the differential diagnosis in patients with DOC. Importantly, this approach can, in principle, be transferred into any ERP of interest to better inform DOC diagnoses.

Neck muscle spasticity in patients with disorder of consciousness: a pilot study.

BACKGROUND: Disorder of consciousness (DOC) is a state of prolonged altered consciousness due to severe acquired brain injury (ABI). DOC can be differentiated into coma, unresponsive wakefulness syndrome (UWS), or minimally conscious state (MCS) depending on the behavioral features observed and their relationship to the level of consciousness. Spasticity is one of the most frequently reported medical comorbidities in DOC patients. Since there is a critical lack of spasticity-focused studies and, in turn, of target treatment, we designed this pilot prospective study to evaluate cervical spine muscle spasticity and its effect on rehabilitation outcome in a large cohort of patients followed from the post-acute phase to 6 months after severe ABI. AIM: To evaluate neck muscle spasticity and investigate its impact on neurological and functional outcome in a large cohort of adult patients with DOC followed from post-acute to 6 months after severe ABI. DESIGN: Single-center prospective pilot study. SETTING: Highly specialized inpatient neurorehabilitation clinic. POPULATION: Patients with severe ABI admitted within 3 months after the acute event to our Neurorehabilitation Unit between May 21st, 2019 and April 23rd, 2020 for treatment of DOC as a part of their rehabilitation program. METHODS: In this single-center prospective pilot study demographic data, etiology of ABI (traumatic versus non-traumatic), DOC evaluated with the revised Coma Recovery Scale (CRS-R), and neurological and functional outcome assessed respectively with the Glasgow Coma Scale (GCS) and Functional Independence Measure (FIM) were considered. During cervical examination, we assessed spasticity with the Modified Ashworth Scale (MAS), deviation of head alignment with a goniometer, and pain with the Nociception Coma Scale-Revised (NCS-R). RESULTS: Of the 48 patients, 41.7% were diagnosed with UWS and 58.3% were in a minimally conscious state (MCS). We found spasticity of neck muscles in 91.7% of patients, with no difference in severity (assessed with MAS) between UWV and MCS. The NCS-R score at cervical spine examination was lower in UWS than MCS. Spasticity was severer in patients with traumatic brain injury (TBI) compared to non-traumatic. At multiple linear regression analysis, younger age, hemisyndrome, and tetraparesis were independent predictors of severity of neck muscle spasticity in MCS. More severe spasticity was a predictor of worse neurological and functional outcome at discharge in UWS patients, independently of the other confounding variables at admission (e.g., age, severity of brain injury, functional assessment, and pain). CONCLUSIONS: Spasticity of neck muscles frequently develops in patients with DOC and is more severe in those after TBI. UWV and MCS have different spasticity profiles as regards risk factors and neurological and functional outcome. Severity of neck muscle spasticity in UWV patients may represent an early indicator of worse neurological and functional outcome after inpatient rehabilitation. CLINICAL REHABILITATION IMPACT: Our findings could prompt clinicians to redefine the rehabilitation aims regarding spasticity and to estimate the functional outcome in patients undergoing intensive rehabilitation after severe ABI.

Verbal Glasgow Coma Scale as predictor of persistent disorder of consciousness: Insights for improving accuracy and reliability in clinical practice.

This brief report discusses the relationship between verbal function, disorders of consciousness, and neurological follow-up after acute brain injury. It provides valuable insights for improving the accuracy and reliability of Verbal Glasgow Coma Scale scoring in clinical practice. The report addresses the need for standardized training and underlines the importance of physiological stabilization before assessment. Clarity in communication, recognition of non-verbal cues, and serial assessments are emphasized as critical factors to reduce the Verbal Glasgow Coma Scale inconsistencies. It also promotes interdisciplinary collaboration and cultural sensitivity to refine the Verbal Glasgow Coma Scale evaluation, improving the prediction of long-term neurological outcomes after acute brain injury and optimizing effective rehabilitation programs. Possible strategies to implement in the routine clinical practice the provided tips are discussed.

Musical and electrical stimulation as intervention in disorder of consciousness (DOC) patients: A randomised cross-over trial.

BACKGROUND: Disorders of consciousness (DOC), i.e., unresponsive wakefulness syndrome (UWS) or vegetative state (VS) and minimally conscious state (MCS), are conditions that can arise from severe brain injury, inducing widespread functional changes. Given the damaging implications resulting from these conditions, there is an increasing need for rehabilitation treatments aimed at enhancing the level of consciousness, the quality of life, and creating new recovery perspectives for the patients. Music may represent an additional rehabilitative tool in contexts where cognition and language are severely compromised, such as among DOC patients. A further type of rehabilitation strategies for DOC patients consists of Non-Invasive Brain Stimulation techniques (NIBS), including transcranial electrical stimulation (tES), affecting neural excitability and promoting brain plasticity. OBJECTIVE: We here propose a novel rehabilitation protocol for DOC patients that combines music-based intervention and NIBS in neurological patients. The main objectives are (i) to assess the residual neuroplastic processes in DOC patients exposed to music, (ii) to determine the putative neural modulation and the clinical outcome in DOC patients of non-pharmacological strategies, i.e., tES(control condition), and music stimulation, and (iii) to evaluate the putative positive impact of this intervention on caregiver's burden and psychological distress. METHODS: This is a randomised cross-over trial in which a total of 30 participants will be randomly allocated to one of three different combinations of conditions: (i) Music only, (ii) tES only (control condition), (iii) Music + tES. The music intervention will consist of listening to an individually tailored playlist including familiar and self-relevant music together with fixed songs; concerning NIBS, tES will be applied for 20 minutes every day, 5 times a week, for two weeks. After these stimulations two weeks of placebo treatments will follow, with sham stimulation combined with noise for other two weeks. The primary outcomes will be clinical, i.e., based on the differences in the scores obtained on the neuropsychological tests, such as Coma Recovery Scale-Revised, and neurophysiological measures as EEG, collected pre-intervention, post-intervention and post-placebo. DISCUSSION: This study proposes a novel rehabilitation protocol for patients with DOC including a combined intervention of music and NIBS. Considering the need for rigorous longitudinal randomised controlled trials for people with severe brain injury disease, the results of this study will be highly informative for highlighting and implementing the putative beneficial role of music and NIBS in rehabilitation treatments. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT05706831, registered on January 30, 2023.

Interpreting Change in Disorders of Consciousness Using the Coma Recovery Scale-Revised.

The purpose of this study was to differentiate clinically meaningful improvement or deterioration from normal fluctuations in patients with disorders of consciousness (DoC) following severe brain injury. We computed indices of responsiveness for the Coma Recovery Scale-Revised (CRS-R) using data from a clinical trial of 180 participants with DoC. We used CRS-R scores from baseline (enrollment in a clinical trial) and a 4-week follow-up assessment period for these calculations. To improve precision, we transformed ordinal CRS-R total scores (0-23 points) to equal-interval measures on a 0-100 unit scale using Rasch Measurement theory. Using the 0-100 unit total Rasch measures, we calculated distribution-based 0.5 standard deviation (SD) minimal clinically important difference, minimal detectable change using 95% confidence intervals, and conditional minimal detectable change using 95% confidence intervals. The distribution-based minimal clinically important difference evaluates group-level changes, whereas the minimal detectable change values evaluate individual-level changes. The minimal clinically important difference and minimal detectable change are derived using the overall variability across total measures at baseline and 4 weeks. The conditional minimal detectable change is generated for each possible pair of CRS-R Rasch person measures and accounts for variation in standard error across the scale. We applied these indices to determine the proportions of participants who made a change beyond measurement error within each of the two subgroups, based on treatment arm (amantadine hydrochloride or placebo) or categorization of baseline Rasch person measure to states of consciousness (i.e., unresponsive wakefulness syndrome and minimally conscious state). We compared the proportion of participants in each treatment arm who made a change according to the minimal detectable change and determined whether they also changed to another state of consciousness. CRS-R indices of responsiveness (using the 0-100 transformed scale) were as follows: 0.5SD minimal clinically important difference = 9 units, minimal detectable change = 11 units, and the conditional minimal detectable change ranged from 11 to 42 units. For the amantadine and placebo groups, 70% and 58% of participants showed change beyond measurement error using the minimal detectable change, respectively. For the unresponsive wakefulness syndrome and minimally conscious state groups, 54% and 69% of participants changed beyond measurement error using the minimal detectable change, respectively. Among 115 participants (64% of the total sample) who made a change beyond measurement error, 29 participants (25%) did not change state of consciousness. CRS-R indices of responsiveness can support clinicians and researchers in discerning when behavioral changes in patients with DoC exceed measurement error. Notably, the minimal detectable change can support the detection of patients who make a "true" change within or across states of consciousness. Our findings highlight that the continued use of ordinal scores may result in incorrect inferences about the degree and relevance of a change score.

Transcutaneous auricular vagal nerve stimulation for consciousness recovery in patients with prolonged disorders of consciousness (TAVREC): study protocol for a multicenter, triple-blind, randomized controlled trial in China.

INTRODUCTION: Prolonged disorders of consciousness (pDoC) are a catastrophic condition following brain injury with few therapeutic options. Transcutaneous auricular vagal nerve stimulation (taVNS), a safe, non-invasive intervention modulating thalamo-cortical connectivity and brain function, is a possible treatment option of pDoC. We developed a protocol for a randomised controlled study to evaluate the effectiveness of taVNS on consciousness recovery in patients with pDoC (TAVREC). METHODS AND ANALYSIS: The TAVREC programme is a multicentre, triple-blind, randomised controlled trial with 4 weeks intervention followed by 4 weeks follow-up period. A minimum number of 116 eligible pDoC patients will be recruited and randomly receive either: (1) conventional therapy plus taVNS (30 s monophasic square current of pulse width 300 µs, frequency of 25 Hz and intensity of 1 mA followed by 30 s rest, 60 min, two times per day, for 4 weeks); or (2) conventional therapy plus taVNS placebo. Primary outcome of TAVREC is the rate of improved consciousness level based on the Coma Recovery Scale-Revised (CRS-R) at week 4. Secondary outcomes are CRS-R total and subscale scores, Glasgow Coma Scale score, Full Outline of UnResponsiveness score, ECG parameters, brainstem auditory evoked potential, upper somatosensory evoked potential, neuroimaging parameters from positron emission tomography/functional MRI, serum biomarkers associated with consciousness level and adverse events. ETHICS AND DISSEMINATION: This study was reviewed and approved by the Research Ethics Committee of the First Affiliated Hospital of Nanjing Medical University (Reference number: 2023-SR-392). Findings will be disseminated in a peer-reviewed journal and presented at relevant conferences. TRIAL REGISTRATION NUMBER: ChiCTR2300073950.

Breakdown of effective information flow in disorders of consciousness: Insights from TMS-EEG.

BACKGROUND: The complexity of the neurophysiological mechanisms underlying human consciousness is widely acknowledged, with information processing and flow originating in cortex conceived as a core mechanism of consciousness emergence. Combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) is considered as a promising technique to understand the effective information flow associated with consciousness. OBJECTIVES: To investigate information flow with TMS-EEG and its relationship to different consciousness states. METHODS: We applied an effective information flow analysis by combining time-varying multivariate adaptive autoregressive model and adaptive directed transfer function on TMS-EEG data of frontal, motor and parietal cortex in patients with disorder of consciousness (DOC), including 14 vegetative state/unresponsive wakefulness syndrome (VS/UWS) patients, 21 minimally conscious state (MCS) patients, and 22 healthy subjects. RESULTS: TMS in DOC patients, particularly VS/UWS, induced a significantly weaker effective information flow compared to healthy subjects. The bidirectional directed information flow was lost in DOC patients with TMS of frontal, motor and parietal cortex. The interactive ROI rate of the information flow network induced by TMS of frontal and parietal cortex was significantly lower in VS/UWS than in MCS. The interactive ROI rate correlated with DOC clinical scales. CONCLUSIONS: TMS-EEG revealed a physiologically relevant correlation between TMS-induced information flow and levels of consciousness. This suggests that breakdown of effective cortical information flow serves as a viable marker of human consciousness. SIGNIFICANCE: Findings offer a unique perspective on the relevance of information flow in DOC, thus providing a novel way of understanding the physiological basis of human consciousness.

Predicting outcome in disorders of consciousness: A mega-analysis.

OBJECTIVE: Assessing recovery potential in patients with disorders of consciousness (DoC) is pivotal for guiding clinical and ethical decisions. We conducted a mega-analysis of individual patient data to understand (1) if a time threshold exists, beyond which regaining consciousness is almost impossible, and (2) how recovery varies based on factors such as diagnosis, etiology, age, sex, and neuropsychological status. METHODS: A systematic literature search revealed a total of 3290 patients. In this sample, we performed a Cox proportional hazards analysis for interval censored data. RESULTS: We observed a late saturation of probability to regain consciousness in Kaplan-Meier curves, and the annual rate of recovery was remarkably stable, in that approximately 35% of patients regained consciousness per year. Patients in minimally conscious state (MCS) recovered more frequently than patients in unresponsive wakefulness syndrome (UWS). No significant difference was observed between the recovery dynamics of MCS subgroups: MCS+ and MCS-. Patients with hypoxic brain lesions showed worse recovery rate than patients with traumatic brain injury and patients with vascular brain lesions, while the latter two categories did not differ from each other. Male patients had moderately better chance to regain consciousness. While younger UWS patients recovered more frequently than older patients, it was not the case in MCS. INTERPRETATION: Our findings highlight the necessity for neurologists to exercise caution when making negative predictions in individual cases, challenge traditional beliefs regarding recovery timelines, and underscore the importance of conducting detailed and prolonged assessments to better understand recovery prospects in DoC.

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).

A Hybrid BCI Integrating EEG and Eye-Tracking for Assisting Clinical Communication in Patients With Disorders of Consciousness.

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.