Background
We investigated the relationship between three language-dependent behaviors (i.e., command-following, intelligible verbalization, and intentional communication) and the functional status ...of patients with disorders of consciousness (DoC). We hypothesized that patients in minimally conscious state (MCS) who retain behavioral evidence of preserved language function would have similar levels of functional disability, while patients who lack these behaviors would demonstrate significantly greater disability. We reasoned that these results could then be used to establish empirically-based diagnostic criteria for
MCS
+.
Methods
In this retrospective cohort study we included rehabilitation inpatients diagnosed with DoC following severe-acquired brain injury (MCS = 57; vegetative state/unresponsive wakefulness syndrome VS/UWS = 63); women: 46; mean age: 47 ± 19 years; traumatic etiology: 68; time post-injury: 40 ± 23 days). We compared the scores of the Disability Rating Scale score (DRS) at time of transition from VS/UWS to MCS or from
MCS
– to
MCS
+, and at discharge between groups.
Results
Level of disability on the DRS was similar in patients with any combination of the three language-related behaviors. MCS patients with no behavioral evidence of language function (i.e.,
MCS
–) were more functionally impaired than patients with
MCS
+ at time of transition and at discharge.
Conclusions
Command-following, intelligible verbalization, and intentional communication are not associated with different levels of functional disability. Thus, the
MCS
+ syndrome can be diagnosed based on the presence of any one of these language-related behaviors. Patients in
MCS
+ may evidence less functional disability compared to those in MCS who fail to demonstrate language function (i.e.,
MCS
–).
Summary Background Bedside clinical examinations can have high rates of misdiagnosis of unresponsive wakefulness syndrome (vegetative state) or minimally conscious state. The diagnostic and ...prognostic usefulness of neuroimaging-based approaches has not been established in a clinical setting. We did a validation study of two neuroimaging-based diagnostic methods: PET imaging and functional MRI (fMRI). Methods For this clinical validation study, we included patients referred to the University Hospital of Liège, Belgium, between January, 2008, and June, 2012, who were diagnosed by our unit with unresponsive wakefulness syndrome, locked-in syndrome, or minimally conscious state with traumatic or non-traumatic causes. We did repeated standardised clinical assessments with the Coma Recovery Scale–Revised (CRS–R), cerebral18 F-fluorodeoxyglucose (FDG) PET, and fMRI during mental activation tasks. We calculated the diagnostic accuracy of both imaging methods with CRS–R diagnosis as reference. We assessed outcome after 12 months with the Glasgow Outcome Scale–Extended. Findings We included 41 patients with unresponsive wakefulness syndrome, four with locked-in syndrome, and 81 in a minimally conscious state (48=traumatic, 78=non-traumatic; 110=chronic, 16=subacute).18 F-FDG PET had high sensitivity for identification of patients in a minimally conscious state (93%, 95% CI 85–98) and high congruence (85%, 77–90) with behavioural CRS–R scores. The active fMRI method was less sensitive at diagnosis of a minimally conscious state (45%, 30–61) and had lower overall congruence with behavioural scores (63%, 51–73) than PET imaging.18 F-FDG PET correctly predicted outcome in 75 of 102 patients (74%, 64–81), and fMRI in 36 of 65 patients (56%, 43–67). 13 of 41 (32%) of the behaviourally unresponsive patients (ie, diagnosed as unresponsive with CRS–R) showed brain activity compatible with (minimal) consciousness (ie, activity associated with consciousness, but diminished compared with fully conscious individuals) on at least one neuroimaging test; 69% of these (9 of 13) patients subsequently recovered consciousness. Interpretation Cerebral18 F-FDG PET could be used to complement bedside examinations and predict long-term recovery of patients with unresponsive wakefulness syndrome. Active fMRI might also be useful for differential diagnosis, but seems to be less accurate. Funding The Belgian National Funds for Scientific Research (FNRS), Fonds Léon Fredericq, the European Commission, the James McDonnell Foundation, the Mind Science Foundation, the French Speaking Community Concerted Research Action, the University of Copenhagen, and the University of Liège.
Summary Background Between pathologically impaired consciousness and normal consciousness exists a scarcely researched transition zone, referred to as emergence from minimally conscious state, in ...which patients regain the capacity for functional communication, object use, or both. We investigated neural correlates of consciousness in these patients compared with patients with disorders of consciousness and healthy controls, by multimodal imaging. Methods In this cross-sectional, multimodal imaging study, patients with unresponsive wakefulness syndrome, patients in a minimally conscious state, and patients who had emerged from a minimally conscious state, diagnosed with the Coma Recovery Scale–Revised, were recruited from the neurology department of the Centre Hospitalier Universitaire de Liège, Belgium. Key exclusion criteria were neuroimaging examination in an acute state, sedation or anaesthesia during scanning, large focal brain damage, motion parameters of more than 3 mm in translation and 3° in rotation, and suboptimal segmentation and normalisation. We acquired resting state functional and structural MRI data and18 F-fluorodeoxyglucose (FDG) PET data; we used seed-based functional MRI (fMRI) analysis to investigate positive default mode network connectivity (within-network correlations) and negative default mode network connectivity (between-network anticorrelations). We correlated FDG-PET brain metabolism with fMRI connectivity. We used voxel-based morphometry to test the effect of anatomical deformations on functional connectivity. Findings We recruited a convenience sample of 58 patients (21 36% with unresponsive wakefulness syndrome, 24 41% in a minimally conscious state, and 13 22% who had emerged from a minimally conscious state) and 35 healthy controls between Oct 1, 2009, and Oct 31, 2014. We detected consciousness-level-dependent increases (from unresponsive wakefulness syndrome, minimally conscious state, emergence from minimally conscious state, to healthy controls) for positive and negative default mode network connectivity, brain metabolism, and grey matter volume (p<0·05 false discovery rate corrected for multiple comparisons). Positive default mode network connectivity differed between patients and controls but not among patient groups ( F test p<0·0001). Negative default mode network connectivity was only detected in healthy controls and in those who had emerged from a minimally conscious state; patients with unresponsive wakefulness syndrome or in a minimally conscious state showed pathological between-network positive connectivity (hyperconnectivity; F test p<0·0001). Brain metabolism correlated with positive default mode network connectivity (Spearman's r =0·50 95% CI 0·26 to 0·61; p<0·0001) and negative default mode network connectivity (Spearman's r =–0·52 –0·35 to −0·67); p<0·0001). Grey matter volume did not differ between the studied groups ( F test p=0·06). Interpretation Partial preservation of between-network anticorrelations, which are seemingly of neuronal origin and cannot be solely explained by morphological deformations, characterise patients who have emerged from a minimally conscious state. Conversely, patients with disorders of consciousness show pathological between-network correlations. Apart from a deeper understanding of the neural correlates of consciousness, these findings have clinical implications and might be particularly relevant for outcome prediction and could inspire new therapeutic options. Funding Belgian National Funds for Scientific Research (FNRS), European Commission, Natural Sciences and Engineering Research Council of Canada, James McDonnell Foundation, European Space Agency, Mind Science Foundation, French Speaking Community Concerted Research Action, Fondazione Europea di Ricerca Biomedica, University and University Hospital of Liège (Liège, Belgium), and University of Western Ontario (London, ON, Canada).
Consciousness can be defined by two components: arousal (wakefulness) and awareness (subjective experience). However, neurophysiological consciousness metrics able to disentangle between these ...components have not been reported. Here, we propose an explainable consciousness indicator (ECI) using deep learning to disentangle the components of consciousness. We employ electroencephalographic (EEG) responses to transcranial magnetic stimulation under various conditions, including sleep (n = 6), general anesthesia (n = 16), and severe brain injury (n = 34). We also test our framework using resting-state EEG under general anesthesia (n = 15) and severe brain injury (n = 34). ECI simultaneously quantifies arousal and awareness under physiological, pharmacological, and pathological conditions. Particularly, ketamine-induced anesthesia and rapid eye movement sleep with low arousal and high awareness are clearly distinguished from other states. In addition, parietal regions appear most relevant for quantifying arousal and awareness. This indicator provides insights into the neural correlates of altered states of consciousness.
Abstract
Background: Spasticity following a stroke occurs in about 30% of patients. The mechanisms underlying this disorder, however, are not well understood.
Method: This review aims to define ...spasticity, describe hypotheses explaining its development after a stroke, give an overview of related neuroimaging studies as well as a description of the most common scales used to quantify the degree of spasticity and finally explore which treatments are currently being used to treat this disorder.
Results: The lack of consensus is highlighted on the basis of spasticity and the associated absence of guidelines for treatment, use of drugs and rehabilitation programmes.
Conclusions: Future studies require controlled protocols to determine the efficiency of pharmacological and non-pharmacological treatments for spasticity. Neuroimaging may help predict the occurrence of spasticity and could provide insight into its neurological basis.
Differentiation of the minimally conscious state (MCS) and the unresponsive wakefulness syndrome (UWS) is a persistent clinical challenge 1. Based on positron emission tomography (PET) studies with ...18F-fluorodeoxyglucose (FDG) during sleep and anesthesia, the global cerebral metabolic rate of glucose has been proposed as an indicator of consciousness 2, 3. Likewise, FDG-PET may contribute to the clinical diagnosis of disorders of consciousness (DOCs) 4, 5. However, current methods are non-quantitative and have important drawbacks deriving from visually guided assessment of relative changes in brain metabolism 4. We here used FDG-PET to measure resting state brain glucose metabolism in 131 DOC patients to identify objective quantitative metabolic indicators and predictors of awareness. Quantitation of images was performed by normalizing to extracerebral tissue. We show that 42% of normal cortical activity represents the minimal energetic requirement for the presence of conscious awareness. Overall, the cerebral metabolic rate accounted for the current level, or imminent return, of awareness in 94% of the patient population, suggesting a global energetic threshold effect, associated with the reemergence of consciousness after brain injury. Our data further revealed that regional variations relative to the global resting metabolic level reflect preservation of specific cognitive or sensory modules, such as vision and language comprehension. These findings provide a simple and objective metabolic marker of consciousness, which can readily be implemented clinically. The direct correlation between brain metabolism and behavior further suggests that DOCs can fundamentally be understood as pathological neuroenergetic conditions and provide a unifying physiological basis for these syndromes.
•Quantitative FDG-PET allows fine diagnosis and prognosis in disorders of consciousness•Level of consciousness after brain injury correlates with whole-brain energetic state•Emergence of awareness occurs above a sharply defined brain energy metabolic boundary
Stender et al. show that positron emission tomography measurement of whole-brain glucose metabolic state allows accurate diagnosis and prediction of disorders of consciousness. Recovery from the unresponsive wakefulness condition occurs above a sharply defined brain metabolic limit, reflecting the minimal energetic requirements of consciousness.
Patients with chronic disorders of consciousness face a significant lack of treatment options.
We aimed at investigating the feasibility and the behavioral effects of home-based transcranial direct ...current stimulation (tDCS), applied by relatives or caregivers, in chronic patients in minimally conscious state (MCS).
Each participant received, in a randomized order, 20 sessions of active and 20 sessions of sham tDCS applied over the prefrontal cortex for 4 weeks; separated by 8 weeks of washout. Level of consciousness was assessed using the Coma Recovery Scale-Revised before the first stimulation (baseline), at the end of the 20 tDCS sessions (direct effects) and 8 weeks after the end of each stimulation period (long-term effects). Reported adverse events and data relative to the adherence (i.e., amount of sessions effectively received) were collected as well.
Twenty-seven patients completed the study and 22 patients received at least 80% of the stimulation sessions. All patients tolerated tDCS well, no severe adverse events were noticed after real stimulation and the overall adherence (i.e., total duration of stimulation) was good. A moderate effect size (0.47 and 0.53, for modified intention to treat and per protocol analysis, respectively) was observed at the end of the 4 weeks of tDCS in favor of the active treatment.
We demonstrated that home-based tDCS can be used adequately outside a research facility or hospital by patients' relatives or caregivers. In addition, 4 weeks of tDCS moderately improved the recovery of signs of consciousness in chronic MCS patients.
•Feasibility, efficiency and safety of tDCS in minimally conscious state patients are investigated.•Repeated tDCS shows moderate efficacy along with excellent feasibility and safety.•tDCS is a valuable treatment option for patients with chronic minimally conscious state.
Transcranial direct current stimulation (tDCS) is a noninvasive neuromodulation technique that has been widely studied for the treatment of chronic pain. It is considered a promising and safe ...alternative pain therapy. Different targets have been tested, each having their own particular mechanisms for modulating pain perception.
We discuss the current state of the art of tDCS to manage pain and future strategies to optimize tDCS' effects. Current strategies include primary motor cortex tDCS, prefrontal tDCS and tDCS combined with behavioral interventions while future strategies, on the other hand, include high-intensity tDCS, transcutaneous spinal direct current stimulation, cerebellar tDCS, home-based tDCS, and tDCS with extended number of sessions.
It has been shown that the stimulation of the prefrontal and primary motor cortex is efficient for pain reduction while a few other new strategies, such as high-intensity tDCS and network-based tDCS, are believed to induce strong neuroplastic effects, although the underlying neural mechanisms still need to be fully uncovered. Hence, conventional tDCS approaches demonstrated promising effects to manage pain and new strategies are under development to enhance tDCS effects and make this approach more easily available by using, for instance, home-based devices.
Neuroimaging studies have suggested an important role for the default mode network (DMN) in disorders of consciousness (DoC). However, the extent to which DMN connectivity can discriminate DoC ...states–unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS)–is less evident. Particularly, it is unclear whether effective DMN connectivity, as measured indirectly with dynamic causal modelling (DCM) of resting EEG can disentangle UWS from healthy controls and from patients considered conscious (MCS+). Crucially, this extends to UWS patients with potentially “covert” awareness (minimally conscious star, MCS*) indexed by voluntary brain activity in conjunction with partially preserved frontoparietal metabolism as measured with positron emission tomography (PET+ diagnosis; in contrast to PET- diagnosis with complete frontoparietal hypometabolism). Here, we address this gap by using DCM of EEG data acquired from patients with traumatic brain injury in 11 UWS (6 PET- and 5 PET+) and in 12 MCS+ (11 PET+ and 1 PET-), alongside with 11 healthy controls. We provide evidence for a key difference in left frontoparietal connectivity when contrasting UWS PET- with MCS+ patients and healthy controls. Next, in a leave-one-subject-out cross-validation, we tested the classification performance of the DCM models demonstrating that connectivity between medial prefrontal and left parietal sources reliably discriminates UWS PET- from MCS+ patients and controls. Finally, we illustrate that these models generalize to an unseen dataset: models trained to discriminate UWS PET- from MCS+ and controls, classify MCS* patients as conscious subjects with high posterior probability (pp > .92). These results identify specific alterations in the DMN after severe brain injury and highlight the clinical utility of EEG-based effective connectivity for identifying patients with potential covert awareness.
PDF
