Moving into the wide clinical spectrum of consciousness disorders: Pearls, perils and pitfalls

Task-based EEG and fMRI paradigms in a multimodal clinical diagnostic framework for disorders of consciousness

Disorders of consciousness (DoC) are generally diagnosed by clinical assessment, which is a predominantly motor-driven process and accounts for up to 40 % of non-communication being misdiagnosed as unresponsive wakefulness syndrome (UWS) (previously known as prolonged/persistent vegetative state). Given the consequences of misdiagnosis, a more reliable and objective multimodal protocol to diagnosing DoC is needed, but has not been produced due to concerns regarding their interpretation and reliability. Of the techniques commonly used to detect consciousness in DoC, task-based paradigms (active paradigms) produce the most unequivocal result when findings are positive. It is well-established that command following (CF) reliably reflects preserved consciousness. Task-based electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can detect motor-independent CF and reveal preserved covert consciousness in up to 14 % of UWS patients. Accordingly, to improve the diagnostic accuracy of DoC, we propose a practical multimodal clinical decision framework centered on task-based EEG and fMRI, and complemented by measures like transcranial magnetic stimulation (TMS-EEG).

A Recent Investigation on Detection and Classification of Epileptic Seizure Techniques Using EEG Signal

The benefits of early detection and classification of epileptic seizures in analysis, monitoring and diagnosis for the realization and actualization of computer-aided devices and recent internet of medical things (IoMT) devices can never be overemphasized. The success of these applications largely depends on the accuracy of the detection and classification techniques employed. Several methods have been investigated, proposed and developed over the years. This paper investigates various seizure detection algorithms and classifications in the last decade, including conventional techniques and recent deep learning algorithms. It also discusses epileptiform detection as one of the steps towards advanced diagnoses of disorders of consciousness (DOCs) and their understanding. A performance comparison was carried out on the different algorithms investigated, and their advantages and disadvantages were explored. From our survey, much attention has recently been paid to exploring the efficacy of deep learning algorithms in seizure detection and classification, which are employed in other areas such as image processing and classification. Hybrid deep learning has also been explored, with CNN-RNN being the most popular.

Noninvasive brain stimulation for patients with a disorder of consciousness: a systematic review and meta-analysis

Noninvasive brain stimulation (NIBS) techniques have been used to facilitate the recovery from prolonged unconsciousness as a result of brain injury. The aim of this study is to systematically assess the effects of NIBS in patients with a disorder of consciousness (DOC). We searched four databases for any randomized controlled trials on the effect of NIBS in patients with a DOC, which used the JFK Coma Recovery Scale-Revised (CRS-R) as the primary outcome measure. A random-effects meta-analysis was conducted to pool effect sizes. Fourteen studies with 273 participants were included in this review, of which 12 studies with sufficient data were included in the meta-analysis. Our meta-analysis showed a significant effect on increasing CRS-R scores in favor of real stimulation as compared to sham (Hedges' g = 0.522; 95% confidence interval [CI], 0.318-0.726; P < 0.0001, I2 = 0.00%). Subgroup analysis demonstrated that only anodal transcranial direct current stimulation (tDCS) of the left dorsolateral prefrontal cortex (DLPFC) significantly enhances the CRS-R scores in patients with a DOC, as compared to sham (Hedges' g = 0.703; 95% CI, 0.419-0.986; P < 0.001), and this effect was predominant in patients in a minimally conscious state (MCS) (Hedges' g = 0.815; 95% CI, 0.429-1.200; P < 0.001). Anodal tDCS of the left DLPFC appears to be an effective approach for patients with MCS.

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.

Peri-Personal Space Tracing by Hand-Blink Reflex Modulation in Patients with Chronic Disorders of Consciousness

The assessment of awareness in patients with chronic Disorders of Consciousness (DoC), including Unresponsive Wakefulness Syndrome (UWS) and Minimally Conscious State (MCS), is challenging. The level of awareness impairment may depend on the degree of deterioration of the large-scale cortical-thalamo-cortical networks induced by brain injury. Electrophysiological approaches may shed light on awareness presence in patients with DoC by estimating cortical functions related to the cortical-thalamo-cortical networks including, for example, the cortico-subcortical processes generating motor responses to the perturbation of the peri-personal space (PPS). We measured the amplitude, latency, and duration of the hand-blink reflex (HBR) responses by recording electromyography (EMG) signals from both the orbicularis oculi muscles while electrically stimulating the median nerve at the wrist. Such a BR is thought to be mediated by a neural circuit at the brainstem level. Despite its defensive-response nature, HBR can be modulated by the distance between the stimulated hand and the face. This suggests a functional top-down control of HBR as reflected by HBR features changes (latency, amplitude, and magnitude). We therefore estimated HBR responses in a sample of patients with DoC (8 MCS and 12 UWS, compared to 15 healthy controls -HC) while performing a motor task targeting the PPS. This consisted of passive movements in which the hand of the subject was positioned at different distances from the participant's face. We aimed at demonstrating a residual top-down modulation of HBR properties, which could be useful to differentiate patients with DoC and, potentially, demonstrate awareness preservation. We found a decrease in latency, and an increase in duration and magnitude of HBR responses, which were all inversely related to the hand-to-face distance in HC and patients with MCS, but not in individuals with UWS. Our data suggest that only patients with MCS have preserved, residual, top-down modulation of the processes related to the PPS from higher-order cortical areas to sensory-motor integration network. Although the sample size was relatively small, being thus our data preliminary, HBR assessment seems a rapid, easy, and first-level tool to differentiate patients with MCS from those with UWS. We may also hypothesize that such a HBR modulation suggests awareness preservation.

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

Consciousness arises from the functional interaction of multiple brain structures and their ability to integrate different complex patterns of internal communication. Although several studies demonstrated that the fronto-parietal and functional default mode networks play a key role in conscious processes, it is still not clear which topological network measures (that quantifies different features of whole-brain functional network organization) are altered in patients with disorders of consciousness. Herein, we investigate the functional connectivity of unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) patients from a topological network perspective, by using resting-state EEG recording. Network-based statistical analysis reveals a subnetwork of decreased functional connectivity in UWS compared to in the MCS patients, mainly involving the interhemispheric fronto-parietal connectivity patterns. Network topological analysis reveals increased values of local-community-paradigm correlation, as well as higher clustering coefficient and local efficiency in UWS patients compared to in MCS patients. At the nodal level, the UWS patients showed altered functional topology in several limbic and temporo-parieto-occipital regions. Taken together, our results highlight (i) the involvement of the interhemispheric fronto-parietal functional connectivity in the pathophysiology of consciousness disorders and (ii) an aberrant connectome organization both at the network topology level and at the nodal level in UWS patients compared to in the MCS patients.