Functional Brain Network Topology Discriminates between Patients with Minimally Conscious State and Unresponsive Wakefulness Syndrome

Combined behavioral and EEG evidence for the 70 Hz frequency selection of short-term spinal cord stimulation in disorders of consciousness

OBJECTIVES

This study investigated the prognostic effect of electroencephalography (EEG) instant effects of single spinal cord stimulation (SCS) on clinical outcome in disorders of consciousness (DOC) and the time-dependent brain response during the recovery of consciousness prompted by SCS.

METHODS

Twenty three patients with DOC underwent short-term SCS (stSCS) implantation operation. Then, all patients received the postoperative EEG test including EEG record before (T1) and after (T2) single SCS session. Subsequently, 2 weeks stSCS treatment was performed and revised coma recovery scale (CRS-R) and EEG data were collected. Finally, they were classified into effective and ineffective groups at 3-month follow-up (T6).

RESULTS

The parietal-occipital (PO) connectivity and clustering coefficients (CC) in the beta band of the effective group at the 1 week after the treatment (T5) were found to be higher than preoperative assessment (T0). Correlation analysis showed that the change in beta CC at T1/T2 was correlated with the change in CRS-R at T0/T6. In addition, the change in PO connectivity and CC in the beta at T0/T5 were also correlated with the change in CRS-R at T0/T5.

CONCLUSION

SCS may facilitate the recovery of consciousness by enhancing local information interaction in posterior brain regions. And the recovery can be predicted by beta CC in the EEG test.

Movement-related ERS and connectivity in the gamma frequency decrease with practice

Previous work showed that movements are accompanied by modulation of electroencephalographic (EEG) activity in both beta (13-30 Hz) and gamma (>30 Hz) ranges. The amplitude of beta event-related synchronization (ERS) is not linked to movement characteristics, but progressively increases with motor practice, returning to baseline after a period of rest. Conversely, movement-related gamma ERS amplitude is proportional to movement distance and velocity. Here, high-density EEG was recorded in 51 healthy subjects to investigate whether i) three-hour practice in two learning tasks, one with a motor component and one without, affects gamma ERS amplitude and connectivity during a motor reaching test, and ii) 90-minutes of either sleep or quiet rest have an effect on gamma oscillatory activity. We found that, while gamma ERS was appropriately scaled to the target extent at all testing points, its amplitude decreased after practice, independently of the type of interposed learning, and after both quiet wake and nap, with partial correlations with subjective fatigue scores. During movement execution, connectivity patterns within fronto-parieto-occipital electrodes, over areas associated with attentional networks, decreased after both practice and after 90-minute rest. While confirming the prokinetic nature of movement-related gamma ERS, these findings demonstrated the preservation of gamma ERS scaling to movement velocity with practice, despite constant amplitude reduction. We thus speculate that such decreases, differently from the practice-related increases of beta ERS, are related to reduced attention or working memory mechanisms due to fatigue or a switch of strategy toward automatization of movement execution and do not specifically reflect plasticity phenomena.

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.

The current and future contribution of neuroimaging to the understanding of disorders of consciousness

Patients with disorders of consciousness (DoC) represent a group of severely brain-injured patients with varying capacities for consciousness in terms of both wakefulness and awareness. The current state-of-the-art for assessing these patients is through standardised behavioural examinations, but inaccuracies are commonplace. Neuroimaging and electrophysiological techniques have revealed vast insights into the relationships between neural alterations, andcognitive and behavioural features of consciousness in patients with DoC. This has led to the establishment of neuroimaging paradigms for the clinical assessment of DoC patients. Here, we review selected neuroimaging findings on the DoC population, outlining key findings of the dysfunction underlying DoC and presenting the current clinical utility of neuroimaging tools. We discuss that whilst individual brain areas play instrumental roles in generating and supporting consciousness, activation of these areas alone is not sufficient for conscious experience. Instead, for consciousness to arise, we need preserved thalamo-cortical circuits, in addition to sufficient connectivity between distinctly differentiated brain networks, underlined by connectivity both within, and between such brain networks. Finally, we present recent advances and future perspectives in computational methodologies applied to DoC, supporting the notion that progress in the science of DoC will be driven by a symbiosis of these data-driven analyses, and theory-driven research. Both perspectives will work in tandem to provide mechanistic insights contextualised within theoretical frameworks which ultimately inform the practice of clinical neurology.

Olfactory response is a potential sign of consciousness: electroencephalogram findings

Objective

This study aimed to explore whether olfactory response can be a sign of consciousness and represent higher cognitive processing in patients with disorders of consciousness (DoC) using clinical and electroencephalogram data.

Methods

Twenty-eight patients with DoC [13 vegetative states (VS)/unresponsive wakefulness syndrome (UWS) and 15 minimally conscious states (MCS)] were divided into two groups: the presence of olfactory response (ORES) group and the absence of olfactory response (N-ORES) group according to behavioral signs from different odors, i.e., vanillin, decanoic acid, and blank stimuli. We recorded an olfactory task-related electroencephalogram (EEG) and analyzed the relative power and functional connectivity at the whole-brain level in patients with DoC and healthy controls (HCs). After three months, the outcomes of DoC patients were followed up using the coma recovery scale-revised (CRS-R).

Results

A significant relationship was found between olfactory responses and the level of consciousness (χ²(1) = 6.892, p = 0.020). For olfactory EEG, N-ORES patients showed higher theta functional connectivity than ORES patients after stimulation with vanillin (p = 0.029; p = 0.027). Patients with N-ORES showed lower alpha and beta relative powers than HCs at the group level (p = 0.019; p = 0.033). After three months, 62.5% (10/16) of the ORES patients recovered consciousness compared to 16.7% (2/12) in the N-ORES group. The presence of olfactory response was significantly associated with an improvement in consciousness (χ²(1) = 5.882, p = 0.023).

Conclusion

Olfactory responses should be considered signs of consciousness. The differences in olfactory processing between DoC patients with and without olfactory responses may be a way to explore the neural correlates of olfactory consciousness in these patients. The olfactory response may help in the assessment of consciousness and may contribute to therapeutic orientation.

Disturbed functional connectivity and topological properties of the frontal lobe in minimally conscious state based on resting-state fNIRS

Background

Patients in minimally conscious state (MCS) exist measurable evidence of consciousness. The frontal lobe is a crucial part of the brain that encodes abstract information and is closely related to the conscious state. We hypothesized that the disturbance of the frontal functional network exists in MCS patients.

Methods

We collected the resting-state functional near-infrared spectroscopy (fNIRS) data of fifteen MCS patients and sixteen age- and gender-matched healthy controls (HC). The Coma Recovery Scale-Revised (CRS-R) scale of MCS patients was also composed. The topology of the frontal functional network was analyzed in two groups.

Results

Compared with HC, the MCS patients showed widely disrupted functional connectivity in the frontal lobe, especially in the frontopolar area and right dorsolateral prefrontal cortex. Moreover, the MCS patients displayed lower clustering coefficient, global efficiency, local efficiency, and higher characteristic path length. In addition, the nodal clustering coefficient and nodal local efficiency in the left frontopolar area and right dorsolateral prefrontal cortex were significantly reduced in MCS patients. Furthermore, the nodal clustering coefficient and nodal local efficiency in the right dorsolateral prefrontal cortex were positively correlated to auditory subscale scores.

Conclusion

This study reveals that MCS patients' frontal functional network is synergistically dysfunctional. And the balance between information separation and integration in the frontal lobe is broken, especially the local information transmission in the prefrontal cortex. These findings help us to understand the pathological mechanism of MCS patients better.

Stimulation-related modifications of evolving functional brain networks in unresponsive wakefulness

Recent advances in neurophysiological brain network analysis have demonstrated novel potential for diagnosis and prognosis of disorders of consciousness. While most progress has been achieved on the population-sample level, time-economic and easy-to-apply personalized solutions are missing. This prospective controlled study combined EEG recordings, basal stimulation, and daily behavioral assessment as applied routinely during complex early rehabilitation treatment. We investigated global characteristics of EEG-derived evolving functional brain networks during the repeated (3–6 weeks apart) evaluation of brain dynamics at rest as well as during and after multisensory stimulation in ten patients who were diagnosed with an unresponsive wakefulness syndrome (UWS). The age-corrected average clustering coefficient C* allowed to discriminate between individual patients at first (three patients) and second assessment (all patients). Clinically, only two patients changed from UWS to minimally conscious state. Of note, most patients presented with significant changes of C* due to stimulations, along with treatment, and with an increasing temporal distance to injury. These changes tended towards the levels of nine healthy controls. Our approach allowed to monitor both, short-term effects of individual therapy sessions and possibly long-term recovery. Future studies will need to assess its full potential for disease monitoring and control of individualized treatment decisions.

tDCS-EEG for Predicting Outcome in Patients With Unresponsive Wakefulness Syndrome

Objectives

We aimed to assess the role of transcranial direct current stimulation (tDCS) combined with electroencephalogram (EEG) for predicting prognosis in UWS cases.

Methods

This was a historical control study that enrolled 85 patients with UWS. The subjects were assigned to the control (without tDCS) and tDCS groups. Conventional treatments were implemented in both the control and tDCS groups, along with 40 multi-target tDCS sessions only in the tDCS group. Coma Recovery Scale-Revised (CRS-R) was applied at admission. The non-linear EEG index was evaluated after treatment. The modified Glasgow Outcome Scale (mGOS) was applied 12 months after disease onset.

Results

The mGOS improvement rate in the tDCS group (37.1%) was higher than the control value (22.0%). Linear regression analysis revealed that the local and remote cortical networks under unaffected pain stimulation conditions and the remote cortical network under affected pain stimulation conditions were the main relevant factors for mGOS improvement. Furthermore, the difference in prefrontal-parietal cortical network was used to examine the sensitivity of prognostic assessment in UWS patients. The results showed that prognostic sensitivity could be increased from 54.5% (control group) to 84.6% (tDCS group).

Conclusions

This study proposes a tDCS-EEG protocol for predicting the prognosis of UWS. With multi-target tDCS combined with EEG, the sensitivity of prognostic assessment in patients with UWS was improved. The recovery might be related to improved prefrontal-parietal cortical networks of the unaffected hemisphere.

Network analysis shows decreased ipsilesional structural connectivity in glioma patients

Gliomas that infiltrate networks and systems, such as the motor system, often lead to substantial functional impairment in multiple systems. Network-based statistics (NBS) allow to assess local network differences and graph theoretical analyses enable investigation of global and local network properties. Here, we used network measures to characterize glioma-related decreases in structural connectivity by comparing the ipsi- with the contralesional hemispheres of patients and correlated findings with neurological assessment. We found that lesion location resulted in differential impairment of both short and long connectivity patterns. Network analysis showed reduced global and local efficiency in the ipsilesional hemisphere compared to the contralesional hemispheric networks, which reflect the impairment of information transfer across different regions of a network.

Tumors and their location distinctly alter both local and global brain connectivity within the ipsilesional hemisphere of glioma patients.

Diagnostic Developments in Differentiating Unresponsive Wakefulness Syndrome and the Minimally Conscious State

When treating patients with a disorder of consciousness (DOC), it is essential to obtain an accurate diagnosis as soon as possible to generate individualized treatment programs. However, accurately diagnosing patients with DOCs is challenging and prone to errors when differentiating patients in a Vegetative State/Unresponsive Wakefulness Syndrome (VS/UWS) from those in a Minimally Conscious State (MCS). Upwards of ~40% of patients with a DOC can be misdiagnosed when specifically designed behavioral scales are not employed or improperly administered. To improve diagnostic accuracy for these patients, several important neuroimaging and electrophysiological technologies have been proposed. These include Positron Emission Tomography (PET), functional Magnetic Resonance Imaging (fMRI), Electroencephalography (EEG), and Transcranial Magnetic Stimulation (TMS). Here, we review the different ways in which these techniques can improve diagnostic differentiation between VS/UWS and MCS patients. We do so by referring to studies that were conducted within the last 10 years, which were extracted from the PubMed database. In total, 55 studies met our criteria (clinical diagnoses of VS/UWS from MCS as made by PET, fMRI, EEG and TMS- EEG tools) and were included in this review. By summarizing the promising results achieved in understanding and diagnosing these conditions, we aim to emphasize the need for more such tools to be incorporated in standard clinical practice, as well as the importance of data sharing to incentivize the community to meet these goals.

Frontal and parietal lobes play crucial roles in understanding the disorder of consciousness: A perspective from electroencephalogram studies

Background

Electroencephalogram (EEG) studies have established many characteristics relevant to consciousness levels of patients with disorder of consciousness (DOC). Although the frontal and parietal brain regions were often highlighted in DOC studies, their electro-neurophysiological roles in constructing human consciousness remain unclear because of the fragmented information from literatures and the complexity of EEG characteristics.

Methods

Existing EEG studies of DOC patients were reviewed and summarized. Relevant findings and results about the frontal and parietal regions were filtered, compared, and concluded to clarify their roles in consciousness classification and outcomes. The evidence covers multi-dimensional EEG characteristics including functional connectivity, non-linear dynamics, spectrum power, transcranial magnetic stimulation-electroencephalography (TMS-EEG), and event-related potential.

Results and conclusion

Electroencephalogram characteristics related to frontal and parietal regions consistently showed high relevance with consciousness: enhancement of low-frequency rhythms, suppression of high-frequency rhythms, reduction of dynamic complexity, and breakdown of networks accompanied with decreasing consciousness. Owing to the limitations of EEG, existing studies have not yet clarified which one between the frontal and parietal has priority in consciousness injury or recovery. Source reconstruction with high-density EEG, machine learning with large samples, and TMS-EEG mapping will be important approaches for refining EEG awareness locations.

Consciousness and complexity: a consilience of evidence

Over the last years, a surge of empirical studies converged on complexity-related measures as reliable markers of consciousness across many different conditions, such as sleep, anesthesia, hallucinatory states, coma, and related disorders. Most of these measures were independently proposed by researchers endorsing disparate frameworks and employing different methods and techniques. Since this body of evidence has not been systematically reviewed and coherently organized so far, this positive trend has remained somewhat below the radar. The aim of this paper is to make this consilience of evidence in the science of consciousness explicit. We start with a systematic assessment of the growing literature on complexity-related measures and identify their common denominator, tracing it back to core theoretical principles and predictions put forward more than 20 years ago. In doing this, we highlight a consistent trajectory spanning two decades of consciousness research and provide a provisional taxonomy of the present literature. Finally, we consider all of the above as a positive ground to approach new questions and devise future experiments that may help consolidate and further develop a promising field where empirical research on consciousness appears to have, so far, naturally converged.

Narrative Review: Quantitative EEG in Disorders of Consciousness

In this narrative review, we focus on the role of quantitative EEG technology in the diagnosis and prognosis of patients with unresponsive wakefulness syndrome and minimally conscious state. This paper is divided into two main parts, i.e., diagnosis and prognosis, each consisting of three subsections, namely, (i) resting-state EEG, including spectral power, functional connectivity, dynamic functional connectivity, graph theory, microstates and nonlinear measurements, (ii) sleep patterns, including rapid eye movement (REM) sleep, slow-wave sleep and sleep spindles and (iii) evoked potentials, including the P300, mismatch negativity, the N100, the N400 late positive component and others. Finally, we summarize our findings and conclude that QEEG is a useful tool when it comes to defining the diagnosis and prognosis of DOC patients.

Identification of the Key Regulators of Spina Bifida Through Graph-Theoretical Approach

Spina Bifida (SB) is a congenital spinal cord malformation. Efforts to discern the key regulators (KRs) of the SB protein-protein interaction (PPI) network are requisite for developing its successful interventions. The architecture of the SB network, constructed from 117 manually curated genes was found to self-organize into a scale-free fractal state having a weak hierarchical organization. We identified three modules/motifs consisting of ten KRs, namely, TNIP1, TNF, TRAF1, TNRC6B, KMT2C, KMT2D, NCOA3, TRDMT1, DICER1, and HDAC1. These KRs serve as the backbone of the network, they propagate signals through the different hierarchical levels of the network to conserve the network’s stability while maintaining low popularity in the network. We also observed that the SB network exhibits a rich-club organization, the formation of which is attributed to our key regulators also except for TNIP1 and TRDMT1. The KRs that were found to ally with each other and emerge in the same motif, open up a new dimension of research of studying these KRs together. Owing to the multiple etiology and mechanisms of SB, a combination of several biomarkers is expected to have higher diagnostic accuracy for SB as compared to using a single biomarker. So, if all the KRs present in a single module/motif are targetted together, they can serve as biomarkers for the diagnosis of SB. Our study puts forward some novel SB-related genes that need further experimental validation to be considered as reliable future biomarkers and therapeutic targets.

Outcome Prediction in Unresponsive Wakefulness Syndrome and Minimally Conscious State by Non-linear Dynamic Analysis of the EEG

Objectives: This study aimed to investigate the role of non-linear dynamic analysis (NDA) of the electroencephalogram (EEG) in predicting patient outcome in unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS).

Methods: This was a prospective longitudinal cohort study. A total of 98 and 64 UWS and MCS cases, respectively, were assessed. During admission, EEGs were acquired under eyes-closed and pain stimulation conditions. EEG nonlinear indices, including approximate entropy (ApEn) and cross-ApEn, were calculated. The modified Glasgow Outcome Scale (mGOS) was employed to assess functional prognosis 1 year following brain injury.

Results: The mGOS scores were improved in 25 (26%) patients with UWS and 42 (66%) with MCS. Under the painful stimulation condition, both non-linear indices were lower in patients with UWS than in those with MCS. The frontal region, periphery of the primary sensory area (S1), and forebrain structure might be the key points modulating disorders of consciousness. The affected local cortical networks connected to S1 and unaffected distant cortical networks connecting S1 to the prefrontal area played important roles in mGOS score improvement.

Conclusions: NDA provides an objective assessment of cortical excitability and interconnections of residual cortical functional islands. The impaired interconnection of the residual cortical functional island meant a poorer prognosis. The activation in the affected periphery of the S1 and the increase in the interconnection of affected local cortical areas around the S1 and unaffected S1 to the prefrontal and temporal areas meant a relatively favorable prognosis.

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.

Electrophysiological and Neuroimaging Studies - During Resting State and Sensory Stimulation in Disorders of Consciousness: A Review

A severe brain injury may lead to a disorder of consciousness (DOC) such as coma, vegetative state (VS), minimally conscious state (MCS) or locked-in syndrome (LIS). Till date, the diagnosis of DOC relies only on clinical evaluation or subjective scoring systems such as Glasgow coma scale, which fails to detect subtle changes and thereby results in diagnostic errors. The high rate of misdiagnosis and inability to predict the recovery of consciousness for DOC patients have created a huge research interest in the assessment of consciousness. Researchers have explored the use of various stimulation and neuroimaging techniques to improve the diagnosis. In this article, we present the important findings of resting-state as well as sensory stimulation methods and highlight the stimuli proven to be successful in the assessment of consciousness. Primarily, we review the literature based on (a) application/non-use of stimuli (i.e., sensory stimulation/resting state-based), (b) type of stimulation used (i.e., auditory, visual, tactile, olfactory, or mental-imagery), (c) electrophysiological signal used (EEG/ERP, fMRI, PET, EMG, SCL, or ECG). Among the sensory stimulation methods, auditory stimulation has been extensively used, since it is easier to conduct for these patients. Olfactory and tactile stimulation have been less explored and need further research. Emotionally charged stimuli such as subject’s own name or narratives in a familiar voice or subject’s own face/family pictures or music result in stronger responses than neutral stimuli. Studies based on resting state analysis have employed measures like complexity, power spectral features, entropy and functional connectivity patterns to distinguish between the VS and MCS patients. Resting-state EEG and fMRI are the state-of-the-art techniques and have a huge potential in predicting the recovery of coma patients. Further, EMG and mental-imagery based studies attempt to obtain volitional responses from the VS patients and thus could detect their command-following capability. This may provide an effective means to communicate with these patients. Recent studies have employed fMRI and PET to understand the brain-activation patterns corresponding to the mental imagery. This review promotes our knowledge about the techniques used for the diagnosis of patients with DOC and attempts to provide ideas for future research.

Managing disorders of consciousness: the role of electroencephalography

Disorders of consciousness (DOC) are an important but still underexplored entity in neurology. Novel electroencephalography (EEG) measures are currently being employed for improving diagnostic classification, estimating prognosis and supporting medicolegal decision-making in DOC patients. However, complex recording protocols, a confusing variety of EEG measures, and complicated analysis algorithms create roadblocks against broad application. We conducted a systematic review based on English-language studies in PubMed, Medline and Web of Science databases. The review structures the available knowledge based on EEG measures and analysis principles, and aims at promoting its translation into clinical management of DOC patients.

EEG to Identify Attempted Movement in Unresponsive Wakefulness Syndrome

Assessment of consciousness following severe brain-injury is challenging. Our hypothesis is that electroencephalography (EEG) can provide information on awareness, in terms of oscillatory activity and network task-related modifications, in people with disorders of consciousness. Similar results were obtained with neuroimaging techniques; we aim at demonstrating the use of EEG, which is low cost and routinely implemented, to the same goal. Nineteen-channel EEG was recorded in 7 persons with unresponsive wakefulness syndrome (UWS) and in 10 healthy subjects during the execution of active (attempted movement) and passive motor tasks as well as 2 mental imagery tasks. Event-related synchronization/desynchronization (ERS/ERD), coherence and network parameters were calculated in delta (1-4 Hz), theta (4-8 Hz), alpha1 (8-10 Hz), alpha2 (10-12 Hz), and beta (13-30 Hz) ranges. In UWS subjects, passive movement induced a weak alpha2 ERD over contralateral sensorimotor area. During motor imagery, ERD was detected over the frontal and motor contralateral brain areas; during spatial imagery, ERS in lower alpha band over the right temporo-parietal regions was missing. In UWS, functional connectivity provided evidence of network disruption and isolation of the motor areas, which cannot dialog with adjacent network nodes, likely suggesting a diffuse structural alteration. Our findings suggest that people with a clinical diagnosis of UWS were able to modulate their brain activity when prompted to perform movement tasks and thus suggest EEG as a potential tool to support diagnosis of disorders of consciousness.

Virtual Reality Based Cognitive Rehabilitation in Minimally Conscious State: A Case Report with EEG Findings and Systematic Literature Review

Chronic disorders of consciousness cause a total or partial and fluctuating unawareness of the surrounding environment. Virtual reality (VR) can be useful as a diagnostic and/or a neurorehabilitation tool, and its effects can be monitored by means of both clinical and electroencephalography (EEG) data recording of brain activity. We reported on the case of a 17-year-old patient with a disorder of consciousness (DoC) who was provided with VR training to improve her cognitive-behavioral outcomes, which were assessed using clinical scales (the Coma Recovery Scale-Revised, the Disability Rating Scale, and the Rancho Los Amigos Levels of Cognitive Functioning), as well as EEG recording, during VR training sessions. At the end of the training, significant improvements in both clinical and neurophysiological outcomes were achieved. Then, we carried out a systematic review of the literature to investigate the role of EEG and VR in the management of patients with DoC. A search on PubMed, Web of Science, Scopus, and Google Scholar databases was performed, using the keywords: “disorders of consciousness” and “virtual reality”, or “EEG”. The results of the literature review suggest that neurophysiological data in combination with VR could be useful in evaluating the reactions induced by different paradigms in DoC patients, helping in the differential diagnosis. In conclusion, the EEG plus VR approach used with our patient could be promising to define the most appropriate stimulation protocol, so as to promote a better personalization of the rehabilitation program. However, further clinical trials, as well as meta-analysis of the literature, are needed to be affirmative on the role of VR in patients with DoC.

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.

Stereotactic body radiation therapy and radiofrequency ablation for the treatment of liver metastases: How and when?

Limited liver metastases represent a clinical challenge. Surgical approach is the most frequently reported treatment option, however, some patients are not eligible for surgical interventions. Relatively recent technologic advances have permitted the safe use of ablative techniques employed in the cure of hepatic metastases. Among these, radiofrequency ablation (RFA) and stereotactic body radiotherapy (SBRT) have emerged as valid treatments in a significant proportion of patients with intrahepatic oligometastatic disease. This review offers an up-to-date of current available literature on this issue focusing on the use and outcomes of RFA and SBRT, according to the PICO (Population, Intervention, Comparison and Outcomes) criteria.

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.

Reconfiguration of large-scale functional connectivity in patients with disorders of consciousness

INTRODUCTION

Functional connectivity alterations within individual resting state networks (RSNs) are linked to disorders of consciousness (DOC). If these alterations influence the interaction quality with other RNSs, then, brain alterations in patients with DOC would be characterized by connectivity changes in the large-scale model composed of RSNs. How are functional interactions between RSNs influenced by internal alterations of individual RSNs? Do the functional alterations induced by DOC change some key properties of the large-scale network, which have been suggested to be critical for the consciousness emergence? Here, we use network analysis to measure functional connectivity in patients with DOC and address these questions. We hypothesized that network properties provide descriptions of brain functional reconfiguration associated with consciousness alterations.

METHODS

We apply nodal and global network measurements to study the reconfiguration linked with the disease severity. We study changes in integration, segregation, and centrality properties of the functional connectivity between the RSNs in subjects with different levels of consciousness.

RESULTS

Our analysis indicates that nodal measurements are more sensitive to disease severity than global measurements, particularly, for functional connectivity of sensory and cognitively related RSNs.

CONCLUSION

The network property alterations of functional connectivity in different consciousness levels suggest a whole-brain topological reorganization of the large-scale functional connectivity in patients with DOC.

Vocal cord surgery and pharmacological treatment of a patient with HPV and recurrent respiratory papillomatosis

Recurrent respiratory papillomatosis (RRP) is caused by persistent infection of the respiratory epithelium by human papillomavirus (HPV), especially HPV 6 and 11. We present a case of surgically treated RRP. The main purpose of our protocol is to remove the lesions with a non-aggressive surgical technique and prevent recurrences with the use of cidofovir for local infiltrations in multiple sessions. We use low-power energy CO₂ laser, directed towards the upper part of the vocal cord, to determine a retraction of the mucosa with consequent coverage of the epithelium of the free edge. The aim of this technique is to treat and stop the formation of synechia of the anterior commissure and the free margin of the vocal cords in the anterior commissure. After 8 years follow-up, there are no signs of recurrence of the disease. The voice had a net improvement confirming the effectiveness of the protocol.

Hyperbaric oxygen therapy in a case of cervical abscess extending to anterior mediastinum, with isolation of Prevotella corporis

We present a case of an odontogenic abscess, first spreading at the lateral cervical level and then in mediastinum. We isolated an anaerobic bacterium, Prevotella corporis, rarely documented in literature. The mortality rates of cervical abscesses secondary to odontogenic infections and complicated by mediastinitis vary from 10% to 40%. Treatment of descending mediastinitis involves multidisciplinary teams such as otorhinolaryngology, thoracic surgeons, infectious disease physicians, anesthetists and intensivists. Due to the combined treatment with surgical drainage within 48 hours of hospitalisation, antibiotics and subsequent hyperbaric oxygen therapy, we have achieved complete recovery of the patient.