Disrupted Interactions Between Arousal and Cortical Awareness Networks in MCS and VS/UWS Patients: Evidence from Resting-state Functional Imaging Connectivity

Neuroimaging biomarkers for the diagnosis and prognosis of patients with disorders of consciousness

The progress in neuroimaging and electrophysiological techniques has shown substantial promise in improving the clinical assessment of disorders of consciousness (DOC). Through the examination of both stimulus-induced and spontaneous brain activity, numerous comprehensive investigations have explored variations in brain activity patterns among patients with DOC, yielding valuable insights for clinical diagnosis and prognostic purposes. Nonetheless, reaching a consensus on precise neuroimaging biomarkers for patients with DOC remains a challenge. Therefore, in this review, we begin by summarizing the empirical evidence related to neuroimaging biomarkers for DOC using various paradigms, including active, passive, and resting-state approaches, by employing task-based fMRI, resting-state fMRI (rs-fMRI), electroencephalography (EEG), and positron emission tomography (PET) techniques. Subsequently, we conducted a review of studies examining the neural correlates of consciousness in patients with DOC, with the findings holding potential value for the clinical application of DOC. Notably, previous research indicates that neuroimaging techniques have the potential to unveil covert awareness that conventional behavioral assessments might overlook. Furthermore, when integrated with various task paradigms or analytical approaches, this combination has the potential to significantly enhance the accuracy of both diagnosis and prognosis in DOC patients. Nonetheless, the stability of these neural biomarkers still needs additional validation, and future directions may entail integrating diagnostic and prognostic methods with big data and deep learning approaches.

Meta-analysis of the diagnostic value of functional magnetic resonance imaging for distinguishing unresponsive wakefulness syndrome/vegetative state and minimally conscious state

Objective

Unresponsive wakefulness syndrome/vegetative state (UWS/VS) and minimally conscious state (MCS) are considered different clinical entities, but their differential diagnosis remains challenging. As a potential clinical tool, functional magnetic resonance imaging (fMRI) could detect residual awareness without the need for the patients' actual motor responses. This study aimed to investigate the diagnostic value of fMRI for distinguishing between UWS/VS and MCS through a meta-analysis of the existing studies.

Methods

We conducted a comprehensive search (from the database creation date to November. 2023) for relevant English articles on fMRI for the differential diagnosis of UWS/VS and MCS. The pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), summary receiver operating characteristic (SROC) curve, and area under the curve (AUC) were calculated to assess the diagnostic value of fMRI in distinguishing between UWS/VS and MCS. The statistical I 2 test was used to assess heterogeneity, and the source of heterogeneity was investigated by performing a meta-regression analysis. Publication bias was assessed using the Deeks funnel plot asymmetry test.

Results

Ten studies were included in the meta-analysis. The pooled sensitivity and specificity were 0.71 (95% CI 0.62-0.79) and 0.71 (95% CI 0.54-0.84), respectively. The fMRI for the differential diagnosis of UWS/VS and MCS has a moderate positive likelihood ratio (2.5) and a relatively low negative likelihood ratio (0.40). Additionally, SROC curves showed that the AUC was 0.76 (95% CI 0.72-0.80).

Conclusion

Functional magnetic resonance imaging has a good performance in the differential diagnosis of UWS/VS and MCS, and may provide a potential tool for evaluating the prognosis and guiding the rehabilitation therapy in patients with disorders of consciousness.

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

BACKGROUND

Accurately diagnosing patients with the vegetative state (VS) and the minimally conscious state (MCS) reached a misdiagnosis of approximately 40%.

METHODS

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.

RESULTS

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%.

CONCLUSION

Constructing features based on microstates to distinguish between two categories of DOC patients had effectiveness.

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 (Lave/Lr) (p< 0.01) and modularity (Q) (p< 0.05) only decreased in sensor space, while the normalized average clustering coefficient (Cave/Cr) and small-world index (σ) 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 indicatorsLave/LrandQwere 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.

Functional hub disruption emphasizes consciousness recovery in severe traumatic brain injury

Severe traumatic brain injury can lead to transient or even chronic disorder of consciousness. To increase diagnosis and prognosis accuracy of disorder of consciousness, functional neuroimaging is recommended 1 month post-injury. Here, we investigated brain networks remodelling on longitudinal data between 1 and 3 months post severe traumatic brain injury related to change of consciousness. Thirty-four severe traumatic brain-injured patients were included in a cross-sectional and longitudinal clinical study, and their MRI data were compared to those of 20 healthy subjects. Long duration resting-state functional MRI were acquired in minimally conscious and conscious patients at two time points after their brain injury. The first time corresponds to the exit from intensive care unit and the second one to the discharge from post-intensive care rehabilitation ward. Brain networks data were extracted using graph analysis and metrics at each node quantifying local (clustering) and global (degree) connectivity characteristics. Comparison with brain networks of healthy subjects revealed patterns of hyper- and hypo-connectivity that characterize brain networks reorganization through the hub disruption index, a value quantifying the functional disruption in each individual severe traumatic brain injury graph. At discharge from intensive care unit, 24 patients' graphs (9 minimally conscious and 15 conscious) were fully analysed and demonstrated significant network disruption. Clustering and degree nodal metrics, respectively, related to segregation and integration properties of the network, were relevant to distinguish minimally conscious and conscious groups. At discharge from post-intensive care rehabilitation unit, 15 patients' graphs (2 minimally conscious, 13 conscious) were fully analysed. The conscious group still presented a significant difference with healthy subjects. Using mixed effects models, we showed that consciousness state, rather than time, explained the hub disruption index differences between minimally conscious and conscious groups. While severe traumatic brain-injured patients recovered full consciousness, regional functional connectivity evolved towards a healthy pattern. More specifically, the restoration of a healthy brain functional segregation could be necessary for consciousness recovery after severe traumatic brain injury. For the first time, extracting the hub disruption index directly from each patient's graph, we were able to track the clinical alteration and subsequent recovery of consciousness during the first 3 months following a severe traumatic brain injury.

Dysfunctional connectivity as a neurophysiologic mechanism of disorders of consciousness: a systematic review

Introduction

Disorders of consciousness (DOC) has been an object of numbers of research regarding the diagnosis, treatment and prognosis in last few decades. We believe that the DOC could be considered as a disconnection syndrome, although the exact mechanisms are not entirely understood. Moreover, different conceptual frameworks highly influence results interpretation. The aim of this systematic review is to assess the current knowledge regarding neurophysiological mechanisms of DOC and to establish possible influence on future clinical implications and usage.

Methods

We have conducted a systematic review according to PRISMA guidelines through PubMed and Cochrane databases, with studies being selected for inclusion via a set inclusion and exclusion criteria.

Results

Eighty-nine studies were included in this systematic review according to the selected criteria. This includes case studies, randomized controlled trials, controlled clinical trials, and observational studies with no control arms. The total number of DOC patients encompassed in the studies cited in this review is 1,533.

Conclusion

Connectomics and network neuroscience offer quantitative frameworks for analysing dynamic brain connectivity. Functional MRI studies show evidence of abnormal connectivity patterns and whole-brain topological reorganization, primarily affecting sensory-related resting state networks (RSNs), confirmed by EEG studies. As previously described, DOC patients are identified by diminished global information processing, i.e., network integration and increased local information processing, i.e., network segregation. Further studies using effective connectivity measurement tools instead of functional connectivity as well as the standardization of the study process are needed.

Dissociable brainstem functional connectivity changes correlate with objective and subjective vigilance decline after total sleep deprivation in healthy male subjects

The maintenance of vigilance relies on the activation of the cerebral cortex by the arousal system centered on the brainstem. Previous studies have suggested that both objective and subjective vigilance are susceptible to sleep deprivation. This study aims to explore the alterations in brainstem arousal system functional connectivity (FC) and its involvement in these two types of vigilance decline following total sleep deprivation (TSD). Thirty-seven healthy male subjects underwent two counterbalanced resting-state fMRI scans, once in rested wakefulness (RW) and once after 36 h of TSD. The pontine tegmental area and caudal midbrain (PTA-cMidbrain), the core regions of the brainstem arousal system, were chosen as the seeds for FC analysis. The difference in PTA-cMidbrain FC between RW and TSD conditions was then investigated, as well as its associations with objective vigilance measured by psychomotor vigilance task (PVT) and subjective vigilance measured by Stanford Sleepiness Scale. The sleep-deprived subjects showed increased PTA-cMidbrain FC with the thalamus and cerebellum and decreased PTA-cMidbrain FC with the occipital, parietal, and sensorimotor regions. TSD-induced increases in PVT reaction time were negatively correlated with altered PTA-cMidbrain FC in the dorsolateral prefrontal cortex, extrastriate visual cortex, and precuneus. TSD-induced increases in subjective sleepiness were positively correlated with altered PTA-cMidbrain FC in default mode regions including the medial prefrontal cortex and precuneus. Our results suggest that different brainstem FC patterns underlie the objective and subjective vigilance declines induced by TSD.

Altered functional connectivity and regional brain activity in a triple-network model in minimally conscious state and vegetative-state/unresponsive wakefulness syndrome patients: A resting-state functional magnetic resonance imaging study

The purpose of this study was to investigate changes in functional connectivity and regional brain activity between and within the default mode network (DMN), salience network (SN), and executive control network (ECN) among individuals with disorders of consciousness (DOC) in the conditions of minimally conscious state (MCS) and vegetative-state/unresponsive wakefulness syndrome (VS/UWS). Twenty-five VS/UWS patients, 14 MCS patients, and 30 healthy individuals as normal control, completed resting-state fMRI scans. ROI-wise functional connectivity and fractional amplitude of low-frequency fluctuation (fALFF) were implemented to examine group differences. All ROI-wise and fALFF analyses masks were identified from the triple-network model. ROI-wise analyses indicated significantly decreased functional connectivity between posterior cingulate cortex (DMN)-left anterior insula (SN), right anterior insula (SN)-left dorsolateral prefrontal cortex (ECN), and right anterior insula (SN)-right amygdala (SN) in VS/UWS patients compared to MCS patients. Moreover, fALFF were observed reduced in the triple-network across all DOC patients, and as the clinical manifestations of DOC deteriorated from MCS to VS/UWS, fALFF in dorsal DMN, anterior/posterior SN, and left ECN became significantly reduced. Moreover, a positive correlation between fALFF of the left ECN and Coma Recovery Scale-Revised (CRS-R) total scores was found across all DOC patients. These findings contribute to a better understanding of the underlying neural mechanism of functional connectivity and regional brain activity in DOC patients, and this triple-network model provides new connectivity pattern changes that may be integrated in future diagnostic tools based on the neural signatures of conscious states.

Regional Homogeneity Alterations in Patients with Impaired Consciousness. An Observational Resting-State fMRI Study

PURPOSE

It is always challenging to correctly differentiate between minimally conscious state (MCS) and vegetative state/unresponsive wakefulness syndrome (VS/UWS) among disorders of consciousness (DOC) patients. However, the underlying neural mechanisms of awareness identification remain incompletely understood.

METHODS

Using regional homogeneity (ReHo) analysis, we evaluated how regional connectivity of brain regions is disrupted in MCS and VS/UWS patients. Resting-state functional magnetic resonance imaging was conducted in 14 MCS patients, 25 VS/UWS patients, and 30 age-matched healthy individuals.

RESULTS

We found that MCS and VS/UWS patients demonstrated DOC-dependent reduced ReHo within widespread brain regions including posterior cingulate cortices (PCC), medial prefrontal cortices (mPFC), and bilateral fronto-parieto-temporal cortices and showed increased ReHo in limbic structures. Moreover, a positive correlation between Coma Recovery Scale-Revised (CRS-R) total scores and reduced ReHo in the left precuneus was observed in VS/UWS patients, despite the linear trend was not found in MCS patients. In addition, ReHo were also observed reduced in three mainly intrinsic connectivity networks (ICNs), including default mode network (DMN), executive control network (ECN), and salience network (SN). Notably, as the clinical symptoms of consciousness disorders worsen from MCS to VS/UWS, ReHo in dorsal DMN, left ECN, and posterior SN became significantly reduced.

CONCLUSION

These findings make a further understanding of the underlying neural mechanism of regional connectivity among DOC patients and provide additional neuroimaging-based biomarkers for the clinical diagnosis of MCS and VS/UWS patients.

The neuroethics of disorders of consciousness: a brief history of evolving ideas

Neuroethical questions raised by recent advances in the diagnosis and treatment of disorders of consciousness are rapidly expanding, increasingly relevant and yet underexplored. The aim of this thematic review is to provide a clinically applicable framework for understanding the current taxonomy of disorders of consciousness and to propose an approach to identifying and critically evaluating actionable neuroethical issues that are frequently encountered in research and clinical care for this vulnerable population. Increased awareness of these issues and clarity about opportunities for optimizing ethically responsible care in this domain are especially timely given recent surges in critically ill patients with prolonged disorders of consciousness associated with coronavirus disease 2019 around the world. We begin with an overview of the field of neuroethics: what it is, its history and evolution in the context of biomedical ethics at large. We then explore nomenclature used in disorders of consciousness, covering categories proposed by the American Academy of Neurology, the American Congress of Rehabilitation Medicine and the National Institute on Disability, Independent Living and Rehabilitation Research, including definitions of terms such as coma, the vegetative state, unresponsive wakefulness syndrome, minimally conscious state, covert consciousness and the confusional state. We discuss why these definitions matter, and why there has been such evolution in this nosology over the years, from Jennett and Plum in 1972 to the Multi-Society Task Force in 1994, the Aspen Working Group in 2002 and the 2018 American and 2020 European Disorders of Consciousness guidelines. We then move to a discussion of clinical aspects of disorders of consciousness, the natural history of recovery and ethical issues that arise within the context of caring for people with disorders of consciousness. We conclude with a discussion of key challenges associated with assessing residual consciousness in disorders of consciousness, potential solutions and future directions, including integration of crucial disability rights perspectives.

Dopaminergic brainstem disconnection is common to pharmacological and pathological consciousness perturbation

Understanding the neural bases of consciousness is of basic scientific and clinical importance. Human neuroimaging has established that a network of interconnected brain regions known as the default mode network disintegrates in anesthesia and after brain damage that causes disorders of consciousness. However, the neurochemical underpinnings of this network change remain largely unknown. Motivated by preclinical animal work and clinical observations, we found that across pharmacological (sedation) and pathological (disorders of consciousness) consciousness perturbation, the dopaminergic source nucleus, the ventral tegmental area, disconnects from the main nodes of the default mode network. As the severity of this dopaminergic disconnection was associated with default mode network disintegration, we propose that dopaminergic modulation may be a central mechanism for consciousness maintenance.

Clinical research into consciousness has long focused on cortical macroscopic networks and their disruption in pathological or pharmacological consciousness perturbation. Despite demonstrating diagnostic utility in disorders of consciousness (DoC) and monitoring anesthetic depth, these cortico-centric approaches have been unable to characterize which neurochemical systems may underpin consciousness alterations. Instead, preclinical experiments have long implicated the dopaminergic ventral tegmental area (VTA) in the brainstem. Despite dopaminergic agonist efficacy in DoC patients equally pointing to dopamine, the VTA has not been studied in human perturbed consciousness. To bridge this translational gap between preclinical subcortical and clinical cortico-centric perspectives, we assessed functional connectivity changes of a histologically characterized VTA using functional MRI recordings of pharmacologically (propofol sedation) and pathologically perturbed consciousness (DoC patients). Both cohorts demonstrated VTA disconnection from the precuneus and posterior cingulate (PCu/PCC), a main default mode network node widely implicated in consciousness. Strikingly, the stronger VTA–PCu/PCC connectivity was, the more the PCu/PCC functional connectome resembled its awake configuration, suggesting a possible neuromodulatory relationship. VTA-PCu/PCC connectivity increased toward healthy control levels only in DoC patients who behaviorally improved at follow-up assessment. To test whether VTA–PCu/PCC connectivity can be affected by a dopaminergic agonist, we demonstrated in a separate set of traumatic brain injury patients without DoC that methylphenidate significantly increased this connectivity. Together, our results characterize an in vivo dopaminergic connectivity deficit common to reversible and chronic consciousness perturbation. This noninvasive assessment of the dopaminergic system bridges preclinical and clinical work, associating dopaminergic VTA function with macroscopic network alterations, thereby elucidating a critical aspect of brainstem–cortical interplay for consciousness.

The clinical effect of vagus nerve stimulation in the treatment of patients with a minimally conscious state

Objective:

Vagus nerve stimulation (VNS) has recently been used in neurorehabilitation and the recovery of consciousness based on its effects on cortical plasticity. The aim of this study was to examine the therapeutic effects of VNS on patients with a minimally conscious state (MCS).

Methods:

All patients included in the study were assessed more than 5 months after injury and were receiving regular rehabilitation at our hospital from August 2018 to October 2019. Ten patients diagnosed with MCS by Coma Recovery Scale-Revised (CRS-R) test who underwent VNS surgery were enrolled. The scores on CRS-R evaluation at baseline (before VNS implantation) and 1, 3, and 6 months after VNS treatment were recorded. The stimulation parameters were chosen according to a previous study. All clinical rehabilitation protocols remained unchanged during the study. Furthermore, safety was assessed by analyzing treatment-emergent adverse events (TEAEs).

Results:

No significant improvement in the total CRS-R scores at the end of the 1-month follow-up was observed (p > 0.05). After 3 months of stimulation, a significant difference (p = 0.0078) was observed in the total CRS-R scores compared with the baseline. After 6 months of VNS treatment, CRS-R assessments showed a continuous significant improvement (p = 0.0039); one patient emerged from the MCS and recovered functional communication and object use. Interestingly, one item of CRS-R scores on visual domain was sensitive to VNS treatment (p = 0.0039). Furthermore, no serious adverse event occurred throughout the study.

Conclusion:

This exploratory study provides preliminary evidence suggesting that VNS is a safe and effective tool for consciousness recovery in patients with MCS.

Structural and functional connectivity of ascending reticular activating system in a patient with impaired consciousness after a cardiac arrest: A case report

RATIONALE

Diffusion tensor imaging (DTI), diffusion tensor tractography (DTT), as well as resting-state-functional magnetic resonance imaging (rsfMRI) are promising methods for assessing patients with disorders of consciousness (DOCs).

PATIENT CONCERNS

This work describes the main findings using DTI, DTT, and rsfMRI in a patient with a DOC secondary to an anoxic encephalopathy who had a fatal outcome. She was an 85-year-old woman who presented a cardiac arrest and underwent cardiopulmonary resuscitation for 20 minutes then returning to spontaneous circulation. After sedation withdrawal, 2 days after the event, she remained with a Glasgow Coma Scale score of 3/15 and with an absence of brainstem reflexes.

DIAGNOSES

DOC secondary to an anoxic encephalopathy after cardiovascular resuscitation.

INTERVENTIONS

A complete brain MRI scan was performed 72 hours after the initial event, including DTI, DTT, and rsfMRI. DTT demonstrated disruption of both ventral and dorsal tegmental tracts bilaterally. DTI showed a reduction of fractional anisotropic level in the mesencephalic nuclei. Moreover, changes in the number of fiber tracts were not evidenced in any portions of the ascending reticular activating system (ARAS). Finally, an increase in the anticorrelated and correlated association among the nuclei in the ARAS and the cortex was evidenced.

OUTCOMES

Patient deceased.

LESSONS

Neuroimaging demonstrated low FA values in the ARAS, destruction of dorsal and ventral tegmental tracts, as well as hyper-connective (highly correlated or anti-correlated) association among ARAS and cortical nuclei compared with 3 healthy control subjects.

Spatial characteristics of spontaneous and stimulus-induced individual functional connectivity networks in severe disorders of consciousness

BACKGROUND

Functional connectivity (fcMRI) analyses of resting state functional magnetic resonance imaging (fMRI) data revealed substantial differences between states of consciousness. The underlying cause-effect linkage, however, remains unknown to the present day. The aim of this study was to examine the relationship between fcMRI measures and Disorders of Consciousness (DOC) in resting state and under adequate stimulation.

METHODS AND FINDINGS

fMRI data from thirteen patients with unresponsive wakefulness syndrome, eight patients in minimally conscious state, and eleven healthy controls were acquired in rest and during the application of nociceptive and emotional acoustic stimuli. We compared spatial characteristics and anatomical topography of seed-based fcMRI networks on group and individual levels. The anatomical topography of fcMRI networks of patients was altered in all three conditions as compared with healthy controls. Spread and distribution of individual fcMRI networks, however, differed significantly between patients and healthy controls in stimulation conditions only. The exploration of individual metric values identified two patients whose spatial metrics did not deviate from metric distributions of healthy controls in a statistically meaningful manner.

CONCLUSIONS

These findings suggest that the disturbance of consciousness in DOC is related to deficits in global topographical network organization rather than a principal inability to establish long-distance connections. In addition, the results question the claim that task-free measurements are particularly valuable as a tool for individual diagnostics in severe neurological disorders. Further studies comparing connectivity indices with outcome of DOC patients are needed to determine the clinical relevance of spatial metrics and stimulation paradigms for individual diagnosis, prognosis and treatment in DOC.