Brain Network Studies in Chronic Disorders of Consciousness: Advances and Perspectives

Assessment of impaired consciousness using EEG-based connectivity features and convolutional neural networks

Growing electroencephalogram (EEG) studies have linked the abnormities of functional brain networks with disorders of consciousness (DOC). However, due to network data's high-dimensional and non-Euclidean properties, it is difficult to exploit the brain connectivity information that can effectively detect the consciousness levels of DOC patients via deep learning. To take maximum advantage of network information in assessing impaired consciousness, we utilized the functional connectivity with convolutional neural network (CNN) and employed three rearrangement schemes to improve the evaluation performance of brain networks. In addition, the gradient-weighted class activation mapping (Grad-CAM) was adopted to visualize the classification contributions of connections among different areas. We demonstrated that the classification performance was significantly enhanced by applying network rearrangement techniques compared to those obtained by the original connectivity matrix (with an accuracy of 75.0%). The highest classification accuracy (87.2%) was achieved by rearranging the alpha network based on the anatomical regions. The inter-region connections (i.e., frontal-parietal and frontal-occipital connectivity) played dominant roles in the classification of patients with different consciousness states. The effectiveness of functional connectivity in revealing individual differences in brain activity was further validated by the correlation between behavioral performance and connections among specific regions. These findings suggest that our proposed assessment model could detect the residual consciousness of patients.

Variability of large timescale functional networks in patients with disorders of consciousness

Objective

Most brain function assessments for disorders of consciousness (DOC) utilized quantified characteristics, measured only once, ignoring the variation of patients' brain states. The study aims to investigate the brain activities of patients with DOC from a new perspective: variability of a large timescale functional network.

Methods

Forty-nine patients were enrolled in this study and performed a 1-week behavioral assessment. Subsequently, each patient received electroencephalography (EEG) recordings five times daily at 2-h intervals. Functional connectivity and networks were measured by weighted phase lag index and complex network parameters (characteristic path length, cluster coefficient, and betweenness centrality). The relative coefficient of variation (CV) of network parameters was measured to evaluate functional network variability.

Results

Functional networks of patients with vegetative state/unresponsive wakefulness syndrome (VS/UWS) showed significantly higher segregation (characteristic path length) and lower centrality (betweenness centrality) than emerging from the minimal conscious state (EMCS) and minimal conscious state (MCS), as well as lower integration (cluster coefficient) than MCS. The functional networks of VS/UWS patients consistently presented the highest variability in segregation and integration (i.e., highest CV values of characteristic path length and cluster coefficient) on a larger time scale than MCS and EMCS. Moreover, the CV values of characteristic path length and cluster coefficient showed a significant inverse correlation with the Coma Recovery Scale-Revised scores (CRS-R). The CV values of network betweenness centrality, particularly of the cento-parietal region, showed a positive correlation with the CRS-R.

Conclusion

The functional networks of VS/UWS patients present the most invariant segregation and integration but divergent centrality on the large time scale networks than MCS and EMCS.

Significance

The variations observed within large timescale functional networks significantly correlate with the degree of consciousness impairment. This finding augments our understanding of the neurophysiological mechanisms underpinning disorders of consciousness.

The visual stimulation in disorders of consciousness

Severe brain damage usually leads to disorders of consciousness (DOC), which include coma, unresponsive wakefulness syndrome (UWS) and a minimally conscious state (MCS). Visual stimulation is widely used, especially in the diagnosis and treatment and treatment of DOC. Researchers have indicated that tests based on visual stimulation including visual pursuit, when used in conjunction with the Coma Recovery Scale-Revised, are able to differentiate between UWS from an MCS. Recently, targeting patients' circadian rhythms has been proposed to be a possible treatment target for DOC. Indeed, light therapy has been applied in some other fields, including treating seasonal affective disorder, sleep problems, and Parkinson's disease. However, at present, although visual stimulation and light therapy are frequently used in DOC, there is still no international unified standard. Therefore, we recommend the development of an international consensus in regard to the definitions, operational criteria and assessment procedures of visual stimulation and light therapy. This review combines visual stimulation, circadian rhythm recovery, and light therapy in DOC patients and presents the mechanisms and current advances in applications related to light therapy and visual stimulation in an attempt to provide additional ideas for future research and treatment of DOC.

Resting-state EEG microstates as electrophysiological biomarkers in post-stroke disorder of consciousness

Introduction

Ischemic stroke patients commonly experience disorder of consciousness (DOC), leading to poorer discharge outcomes and higher mortality risks. Therefore, the identification of applicable electrophysiological biomarkers is crucial for the rapid diagnosis and evaluation of post-stroke disorder of consciousness (PS-DOC), while providing supportive evidence for cerebral neurology.

Methods

In our study, we conduct microstate analysis on resting-state electroencephalography (EEG) of 28 post-stroke patients with awake consciousness and 28 patients with PS-DOC, calculating the temporal features of microstates. Furthermore, we extract the Lempel-Ziv complexity of microstate sequences and the delta/alpha power ratio of EEG on spectral. Statistical analysis is performed to examine the distinctions in features between the two groups, followed by inputting the distinctive features into a support vector machine for the classification of PS-DOC.

Results

Both groups obtain four optimal topographies of EEG microstates, but notable distinctions are observed in microstate C. Within the PS-DOC group, there is a significant increase in the mean duration and coverage of microstates B and C, whereas microstate D displays a contrasting trend. Additionally, noteworthy variations are found in the delta/alpha ratio and Lempel-Ziv complexity between the two groups. The integration of the delta/alpha ratio with microstates' temporal and Lempel-Ziv complexity features demonstrates the highest performance in the classifier (Accuracy = 91.07%).

Discussion

Our results suggest that EEG microstates can provide insights into the abnormal brain network dynamics in DOC patients post-stroke. Integrating the temporal and Lempel-Ziv complexity microstate features with spectral features offers a deeper understanding of the neuro mechanisms underlying brain damage in patients with DOC, holding promise as effective electrophysiological biomarkers for diagnosing PS-DOC.

The temporal dynamics of Large-Scale brain network changes in disorders of consciousness: A Microstate-Based study

BACKGROUND AND OBJECTIVES

The resting-state brain is composed of several discrete networks, which remain stable for 10-100 ms. These functional microstates are considered the building blocks of spontaneous consciousness. Electroencephalography (EEG) microstate analysis may provide insight into the altered brain dynamics underlying consciousness recovery in patients with disorders of consciousness (DOC). We aimed to analyze microstates in the resting-state EEG source space in patients with DOC, the relationship between state-specific features and consciousness levels, and the corresponding patterns of microstates and functional networks.

METHODS

We obtained resting-state EEG data from 84 patients with DOC (27 in a minimally conscious state [MCS] and 57 in a vegetative state [VS] or with unresponsive wakefulness syndrome). We conducted a microstate analysis of the resting-state (EEG) source space and developed a state-transition analysis protocol for patients with DOC.

RESULTS

We identified seven microstates with distinct spatial distributions of cortical activation. Multivariate pattern analyses revealed that different functional connectivity patterns were associated with source-level microstates. There were significant differences in the microstate properties, including spatial activation patterns, temporal dynamics, state shifts, and connectivity construction, between the MCS and VS groups.

DISCUSSION

Our findings suggest that consciousness depends on complex dynamics within the brain and may originate from the anterior cortex.

Targeting Affective Mood Disorders With Ketamine to Prevent Chronic Postsurgical Pain

The phencyclidine-derivative ketamine [2-(2-chlorophenyl)-2-(methylamino)cyclohexan-1-one] was added to the World Health Organization's Model List of Essential Medicines in 1985 and is also on the Model List of Essential Medicines for Children due to its efficacy and safety as an intravenous anesthetic. In sub-anesthetic doses, ketamine is an effective analgesic for the treatment of acute pain (such as may occur in the perioperative setting). Additionally, ketamine may have efficacy in relieving some forms of chronic pain. In 2019, Janssen Pharmaceuticals received regulatory-approval in both the United States and Europe for use of the S-enantiomer of ketamine in adults living with treatment-resistant major depressive disorder. Pre-existing anxiety/depression and the severity of postoperative pain are risk factors for development of chronic postsurgical pain. An important question is whether short-term administration of ketamine can prevent the conversion of acute postsurgical pain to chronic postsurgical pain. Here, we have reviewed ketamine's effects on the biopsychological processes underlying pain perception and affective mood disorders, focusing on non-NMDA receptor-mediated effects, with an emphasis on results from human trials where available.

Whole-brain modelling identifies distinct but convergent paths to unconsciousness in anaesthesia and disorders of consciousness

The human brain entertains rich spatiotemporal dynamics, which are drastically reconfigured when consciousness is lost due to anaesthesia or disorders of consciousness (DOC). Here, we sought to identify the neurobiological mechanisms that explain how transient pharmacological intervention and chronic neuroanatomical injury can lead to common reconfigurations of neural activity. We developed and systematically perturbed a neurobiologically realistic model of whole-brain haemodynamic signals. By incorporating PET data about the cortical distribution of GABA receptors, our computational model reveals a key role of spatially-specific local inhibition for reproducing the functional MRI activity observed during anaesthesia with the GABA-ergic agent propofol. Additionally, incorporating diffusion MRI data obtained from DOC patients reveals that the dynamics that characterise loss of consciousness can also emerge from randomised neuroanatomical connectivity. Our results generalise between anaesthesia and DOC datasets, demonstrating how increased inhibition and connectome perturbation represent distinct neurobiological paths towards the characteristic activity of the unconscious brain.

Perturbations in a large-scale whole-brain model suggest that anesthesia and injury may be imparting functionally similar effects in terms of brain dynamics.

Toward a coherent structuration of disorders of consciousness expertise at a country scale: A proposal for France

Probing consciousness and cognitive abilities in non-communicating patients is one of the most challenging diagnostic issues. A fast growing medical and scientific literature explores the various facets of this challenge, often coined under the generic expression of 'Disorders of Consciousness' (DoC). Crucially, a set of independent converging results demonstrated both (1) the diagnostic and prognostic importance of this expertise, and (2) the need to combine behavioural measures with brain structure and activity data to improve diagnostic and prognostication accuracy as well as potential therapeutic intervention. Thus, probing consciousness in DoC patients appears as a crucial activity rich of human, medical, economic and ethical consequences, but this activity needs to be organized in order to offer this expertise to each concerned patient. More precisely, diagnosis of consciousness differs in difficulty across patients: while a minimal set of data can be sufficient to reach a confident result, some patients need a higher level of expertise that relies on additional behavioural and brain activity and brain structure measures. In order to enable this service on a systematic mode, we present two complementary proposals in the present article. First, we sketch a structuration of DoC expertise at a country-scale, namely France. More precisely, we suggest that a 2-tiers network composed of local (Tier-1) and regional (Tier-2) centers backed by distant electronic databases and algorithmic centers could optimally enable the systematic implementation of DoC expertise in France. Second, we propose to create a national common register of DoC patients in order to better monitor this activity, to improve its performance on the basis of nation-wide collected evidence, and to promote rational decision-making.

Hypothermia selectively protects the anterior forebrain mesocircuit during global cerebral ischemia

Hypothermia is an important protective strategy against global cerebral ischemia following cardiac arrest. However, the mechanisms of hypothermia underlying the changes in different regions and connections of the brain have not been fully elucidated. This study aims to identify the metabolic nodes and connection integrity of specific brain regions in rats with global cerebral ischemia that are most affected by hypothermia treatment. ¹⁸F-fluorodeoxyglucose positron emission tomography was used to quantitatively determine glucose metabolism in different brain regions in a rat model of global cerebral ischemia established at 31–33°C. Diffusion tensor imaging was also used to reconstruct and explore the brain connections involved. The results showed that, compared with the model rats established at 37–37.5°C, the rat models of global cerebral ischemia established at 31–33°C had smaller hypometabolic regions in the thalamus and primary sensory areas and sustained no obvious thalamic injury. Hypothermia selectively preserved the integrity of the anterior forebrain mesocircuit, exhibiting protective effects on the brain during the global cerebral ischemia. The study was approved by the Institutional Animal Care and Use Committee at Capital Medical University (approval No. XW-AD318-97-019) on December 15, 2019.

Individualized Thalamic Parcellation Reveals Alterations in Shape and Microstructure of Thalamic Nuclei in Patients with Disorder of Consciousness

The thalamus plays crucial roles in consciousness generation and information processing. Previous evidence suggests that disorder of consciousness (DOC) caused by severe brain injury, is potentially related to thalamic abnormalities. However, how the morphology and microstructure change in thalamic subfields and thalamocortical fiber pathways in patients with DOC, and the relationships between these changes and the consciousness status remain unclear. Here, we generated the individual-specific thalamic parcellation in 10 DOC patients and 10 healthy controls (HC) via a novel thalamic segmentation framework based on the fiber orientation distribution (FOD) derived from 7-Tesla diffusion MRI, and investigated the shape deformation of thalamic nuclei as well as the microstructural changes associated with thalamic nuclei and thalamocortical pathways in patients with DOC. Enlargement of dorsal posterior nucleus and atrophy of anterior nucleus in the right thalamus were observed in DOC cohort relative to the HCs, and the former was closely linked to the consciousness level of the patients. We also found significant reductions of fiber density, but not fiber bundle cross-section, within several thalamic nuclei and most of the thalamocortical fiber pathways, suggesting that loss of axons might take primary responsibility for the impaired thalamocortical connections in patients with DOC rather than the change in fiber-bundle morphology. Furthermore, the individual-specific thalamic parcellation achieved 80% accuracy in classifying patients at the minimally conscious state from the vegetative state, compared with ~60% accuracy based on group-level parcellations. Our findings provide the first evidence for the shape deformation of thalamic nuclei in DOC patients and the microstructural basis of the disrupted thalamocortical connections.

Disrupted Pallido-Thalamo-Cortical Functional Connectivity in Chronic Disorders of Consciousness

Chronic disorders of consciousness (DOC) encompass unresponsive wakefulness syndrome and minimally conscious state. Their anatomo-functional correlates are not clearly defined yet, although impairments of functional cortical networks have been reported, as well as the implication of the thalamus and deep brain structures. However, the pallidal functional connectivity with the thalamus and the cortical networks has not been studied so far. Using resting-state functional MRI, we conducted a functional connectivity study between the pallidum, the thalamus and the cortical networks in 13 patients with chronic DOC and 19 healthy subjects. We observed in chronic DOC patients that the thalami were no longer connected to the cortical networks, nor to the pallidums. Concerning the functional connectivity of pallidums, we reported an abolition of the negative correlation with the default mode network, and of the positive correlation with the salience network. The disrupted functional connectivity observed in chronic DOC patients between subcortical structures and cortical networks could be related to the mesocircuit model. A better understanding of the DOC underlying physiopathology could provide food for thought for future therapeutic proposals.

A Review of Neuronal Pathways Associated With Consciousness

ABSTRACT

INTRODUCTION: Accurate communication of information regarding fluctuations in level of consciousness is critical. It is, important for nurses to understand terms related to consciousness to appropriately assess and implement plans of care. CONTENT: Although the neurobiology of consciousness is complex and multifaceted, consciousness can be conceptualized as having 2 distinct but interrelated dimensions: arousal and awareness. The different levels of consciousness are thought to fall on a continuum ranging from being fully awake to coma. CONCLUSION: This article focuses on the terms of consciousness, awareness, and arousal along with nursing implications where appropriate.

Fine-Grained Topography and Modularity of the Macaque Frontal Pole Cortex Revealed by Anatomical Connectivity Profiles

The frontal pole cortex (FPC) plays key roles in various higher-order functions and is highly developed in non-human primates. An essential missing piece of information is the detailed anatomical connections for finer parcellation of the macaque FPC than provided by the previous tracer results. This is important for understanding the functional architecture of the cerebral cortex. Here, combining cross-validation and principal component analysis, we formed a tractography-based parcellation scheme that applied a machine learning algorithm to divide the macaque FPC (2 males and 6 females) into eight subareas using high-resolution diffusion magnetic resonance imaging with the 9.4T Bruker system, and then revealed their subregional connections. Furthermore, we applied improved hierarchical clustering to the obtained parcels to probe the modular structure of the subregions, and found that the dorsolateral FPC, which contains an extension to the medial FPC, was mainly connected to regions of the default-mode network. The ventral FPC was mainly involved in the social-interaction network and the dorsal FPC in the metacognitive network. These results enhance our understanding of the anatomy and circuitry of the macaque brain, and contribute to FPC-related clinical research.

Multiplex and Multilayer Network EEG Analyses: A Novel Strategy in the Differential Diagnosis of Patients with Chronic Disorders of Consciousness

The deterioration of specific topological network measures that quantify different features of whole-brain functional network organization can be considered a marker for awareness impairment. Such topological measures reflect the functional interactions of multiple brain structures, which support the integration of different sensorimotor information subtending awareness. However, conventional, single-layer, graph theoretical analysis (GTA)-based approaches cannot always reliably differentiate patients with Disorders of Consciousness (DoC). Using multiplex and multilayer network analyses of frequency-specific and area-specific networks, we investigated functional connectivity during resting-state EEG in 17 patients with Unresponsive Wakefulness Syndrome (UWS) and 15 with Minimally Conscious State (MCS). Multiplex and multilayer network metrics indicated the deterioration and heterogeneity of functional networks and, particularly, the frontal-parietal (FP), as the discriminant between patients with MCS and UWS. These data were not appreciable when considering each individual frequency-specific network. The distinctive properties of multiplex/multilayer network metrics and individual frequency-specific network metrics further suggest the value of integrating the networks as opposed to analyzing frequency-specific network metrics one at a time. The hub vulnerability of these regions was positively correlated with the behavioral responsiveness, thus strengthening the clinically-based differential diagnosis. Therefore, it may be beneficial to adopt both multiplex and multilayer network analyses when expanding the conventional GTA-based analyses in the differential diagnosis of patients with DoC. Multiplex analysis differentiated patients at a group level, whereas the multilayer analysis offered complementary information to differentiate patients with DoC individually. Although further studies are necessary to confirm our preliminary findings, these results contribute to the issue of DoC differential diagnosis and may help in guiding patient-tailored management.

Altered inter-frequency dynamics of brain networks in disorder of consciousness

OBJECTIVE

Growing evidence have linked disorders of consciousness (DOC) with the changes in frequency-specific functional networks. However, the alteration of inter-frequency dynamics in brain networks remain largely unknown. In this study, we investigated the network integration and segregation across frequency bands in a multiplex network framework.

APPROACH

Resting-state EEG data were recorded and analysed from 19 patients in minimally conscious state, 35 patients in unresponsive wakefulness syndrome (UWS) and 23 healthy controls. Frequency-based multiplex (cross-frequency) networks were reconstructed by integrating the five frequency-specific networks. Multiplex graph metrics, named multiplex participation coefficient and multiplex clustering coefficient, were employed to assess the network topology of subjects with different levels of consciousness.

MAIN RESULTS

Results revealed DOC networks, compared to those of healthy controls, may work at a less optimal point (closer to complete disorder) with increased integration and decreased segregation considering inter-frequency dynamics. Both metrics show increased spatial and temporal variability with the consciousness levels. Moreover, significant correlation can be found between the alteration of cross-frequency networks in DOC patients and their behavioural performance at both local and global scales.

SIGNIFICANCE

These findings may contribute to the development of EEG network study and benefit our understanding of the processes of consciousness and their pathophysiology for DOC.

Toward Improving Diagnostic Strategies in Chronic Disorders of Consciousness: An Overview on the (Re-)Emergent Role of Neurophysiology

The differential diagnosis of patients with Disorder of Consciousness (DoC), in particular in the chronic phase, is significantly difficult. Actually, about 40% of patients with unresponsive wakefulness syndrome (UWS) and the minimally conscious state (MCS) are misdiagnosed. Indeed, only advanced paraclinical approaches, including advanced EEG analyses, can allow achieving a more reliable diagnosis, that is, discovering residual traces of awareness in patients with UWS (namely, functional Locked-In Syndrome (fLIS)). These approaches aim at capturing the residual brain network models, at rest or that may be activated in response to relevant stimuli, which may be appropriate for awareness to emerge (despite their insufficiency to generate purposeful motor behaviors). For this, different brain network models have been studied in patients with DoC by using sensory stimuli (i.e., passive tasks), probing response to commands (i.e., active tasks), and during resting-state. Since it can be difficult for patients with DoC to perform even simple active tasks, this scoping review aims at summarizing the current, innovative neurophysiological examination methods in resting state/passive modality to differentiate and prognosticate patients with DoC. We conclude that the electrophysiologically-based diagnostic procedures represent an important resource for diagnosis, prognosis, and, therefore, management of patients with DoC, using advance passive and resting state paradigm analyses for the patients who lie in the “greyzones” between MCS, UWS, and fLIS.

Point-of-care brain injury evaluation of conscious awareness: wide scale deployment of portable HCS EEG evaluation

Survivors of severe brain injury may remain in a decreased state of conscious awareness for an extended period of time. Clinical scales are used to describe levels of consciousness but rely on behavioural responses, precipitating misdiagnosis. We have previously utilized event-related potentials (ERPs) to circumvent reliance on behavioural responses. However, practical implementation barriers limit the clinical utility of ERP assessment at point-of-care (POC). To address this challenge, we developed the Halifax Consciousness Scanner (HCS)-a rapid, semi-automated electroencephalography system. The current study evaluated: (i) HCS feasibility in sub-acute, POC settings nationwide; (ii) ERP P300 responses in patients with acquired brain injury versus healthy controls; and (iii) correlations within and between clinical measures and P300 latencies. We assessed 28 patients with severe, chronic impairments from brain injuries and contrasted the results with healthy control data (n = 100). Correlational analyses examined relationships between P300 latencies and the commonly used clinical scales. P300 latencies were significantly delayed in patients compared to healthy controls (P < 0.05). Clinical assessment scores were significantly inter-correlated and correlated significantly with P300 latencies (P < 0.05). In sub-acute and chronic care settings, the HCS provided a physiological measure of neurocognitive processing at POC for patients with severe acquired brain injury, including those with disorders of consciousness.

Disorders of Consciousness in China

With the development of modern international medicine, the subject of disorders of consciousness (DOCs) has begun to be raised in mainland China. Much progress has been made to date in several specialties related to the management of chronic DOC patients in China. In this article, we briefly review the present status of DOC studies in China, specifically concerning diagnosis, prognosis, therapy, and rehabilitation. The development of DOC-related scientific organizations and activities in China are introduced. Some weaknesses that need improvement are also noted. The current program provides a good foundation for future development.