Wakefulness and loss of awareness: brain and brainstem interaction in the vegetative state

Multimodal MRI reveals brainstem connections that sustain wakefulness in human consciousness

Consciousness is composed of arousal (i.e., wakefulness) and awareness. Substantial progress has been made in mapping the cortical networks that underlie awareness in the human brain, but knowledge about the subcortical networks that sustain arousal in humans is incomplete. Here, we aimed to map the connectivity of a proposed subcortical arousal network that sustains wakefulness in the human brain, analogous to the cortical default mode network (DMN) that has been shown to contribute to awareness. We integrated data from ex vivo diffusion magnetic resonance imaging (MRI) of three human brains, obtained at autopsy from neurologically normal individuals, with immunohistochemical staining of subcortical brain sections. We identified nodes of the proposed default ascending arousal network (dAAN) in the brainstem, hypothalamus, thalamus, and basal forebrain. Deterministic and probabilistic tractography analyses of the ex vivo diffusion MRI data revealed projection, association, and commissural pathways linking dAAN nodes with one another and with DMN nodes. Complementary analyses of in vivo 7-tesla resting-state functional MRI data from the Human Connectome Project identified the dopaminergic ventral tegmental area in the midbrain as a widely connected hub node at the nexus of the subcortical arousal and cortical awareness networks. Our network-based autopsy methods and connectivity data provide a putative neuroanatomic architecture for the integration of arousal and awareness in human consciousness.

EEG Microstate Analysis in Patients with Disorders of Consciousness and Its Clinical Significance

Disorders of Consciousness are divided into two major categories such as vegetative and minimally conscious states. Objective measures that allow correct identification of patients with vegetative and minimally conscious state are needed. EEG microstate analysis is a promising approach that we believe has the potential to be effective in examining the resting state activities of the brain in different stages of consciousness by allowing the proper identification of vegetative and minimally conscious patients. As a result, we try to identify clinical evaluation scales and microstate characteristics with resting state EEGs from individuals with disorders of consciousness. Our prospective observational study included 28 individuals with a disorder of consciousness. Control group included 18 healthy subjects with proper EEG data. We made clinical evaluations using patient behavior scales. We also analyzed the EEGs using microstate analysis. In our study, microstate D coverage differed substantially between vegetative and minimally conscious state patients. Also, there was a strong connection between microstate D characteristics and clinical scale scores. Consequently, we have demonstrated that the most accurate parameter for representing consciousness level is microstate D. Microstate analysis appears to be a strong option for future use in the diagnosis, follow-up, and treatment response of patients with Disorders of Consciousness.

Neurophysiology of male sexual arousal-Behavioral perspective

In the presented review, we analyzed the physiology of male sexual arousal and its relation to the motivational aspects of this behavior. We highlighted the distinction between these processes based on observable physiological and behavioral parameters. Thus, we proposed the experimentally applicable differentiation between sexual arousal (SA) and sexual motivation (SM). We propose to define sexual arousal as an overall autonomic nervous system response leading to penile erection, triggered selectively by specific sexual cues. These autonomic processes include both spinal and supraspinal neuronal networks, activated by sensory pathways including information from sexual partner and sexual context, as well as external and internal genital organs. To avoid misinterpretation of experimental data, we also propose to precise the term "sexual motivation" as all actions performed by the individual that increase the probability of sexual interactions or increase the probability of exposition to sexual context cues. Neuronal structures such as the amygdala, bed nucleus of stria terminalis, hypothalamus, nucleus raphe, periaqueductal gray, and nucleus paragigantocellularis play crucial roles in controlling the level of arousal and regulating peripheral responses via specific autonomic effectors. On the highest level of CNS, the activity of cortical structures involved in the regulation of the autonomic nervous system, such as the insula and anterior cingulate cortex, can visualize an elevated level of SA in both animal and human brains. From a preclinical perspective, we underlie the usefulness of the non-contact erection test (NCE) procedure in understanding factors influencing sexual arousal, including studies of sexual preference in animal models. Taken together results obtained by different methods, we wanted to focus attention on neurophysiological aspects that are distinctly related to sexual arousal and can be used as an objective parameter, leading to higher translational transparency between basic, preclinical, and clinical studies.

Sustaining wakefulness: Brainstem connectivity in human consciousness

Consciousness is comprised of arousal (i.e., wakefulness) and awareness. Substantial progress has been made in mapping the cortical networks that modulate awareness in the human brain, but knowledge about the subcortical networks that sustain arousal is lacking. We integrated data from ex vivo diffusion MRI, immunohistochemistry, and in vivo 7 Tesla functional MRI to map the connectivity of a subcortical arousal network that we postulate sustains wakefulness in the resting, conscious human brain, analogous to the cortical default mode network (DMN) that is believed to sustain self-awareness. We identified nodes of the proposed default ascending arousal network (dAAN) in the brainstem, hypothalamus, thalamus, and basal forebrain by correlating ex vivo diffusion MRI with immunohistochemistry in three human brain specimens from neurologically normal individuals scanned at 600-750 μm resolution. We performed deterministic and probabilistic tractography analyses of the diffusion MRI data to map dAAN intra-network connections and dAAN-DMN internetwork connections. Using a newly developed network-based autopsy of the human brain that integrates ex vivo MRI and histopathology, we identified projection, association, and commissural pathways linking dAAN nodes with one another and with cortical DMN nodes, providing a structural architecture for the integration of arousal and awareness in human consciousness. We release the ex vivo diffusion MRI data, corresponding immunohistochemistry data, network-based autopsy methods, and a new brainstem dAAN atlas to support efforts to map the connectivity of human consciousness.

Effectiveness on level of consciousness of non-invasive neuromodulation therapy in patients with disorders of consciousness: a systematic review and meta-analysis

Background

Disorders of consciousness (DoC) commonly occurs secondary to severe neurological injury. A considerable volume of research has explored the effectiveness of different non-invasive neuromodulation therapy (NINT) on awaking therapy, however, equivocal findings were reported.

Objective

The aim of this study was to systematically investigate the effectiveness on level of consciousness of different NINT in patients with DoC and explore optimal stimulation parameters and characteristics of patients.

Methods

PubMed, Embase, Web of Science, Scopus, and Cochrane central register of controlled trials were searched from their inception through November 2022. Randomized controlled trials, that investigated effectiveness on level of consciousness of NINT, were included. Mean difference (MD) with 95% confidence interval (CI) was evaluated as effect size. Risk of bias was assessed with revised Cochrane risk-of-bias tool.

Results

A total of 15 randomized controlled trials with 345 patients were included. Meta-analysis was performed on 13 out of 15 reviewed trials indicating that transcranial Direct Current Stimulation (tDCS), Transcranial Magnetic Stimulation (TMS), and median nerve stimulation (MNS) all had a small but significant effect (MD 0.71 [95% CI 0.28, 1.13]; MD 1.51 [95% CI 0.87, 2.15]; MD 3.20 [95%CI: 1.45, 4.96]) on level of consciousness. Subgroup analyses revealed that patients with traumatic brain injury, higher initial level of consciousness (minimally conscious state), and shorter duration of prolonged DoC (subacute phase of DoC) reserved better awaking ability after tDCS. TMS also showed encouraging awaking effect when stimulation was applied on dorsolateral prefrontal cortex in patients with prolonged DoC.

Conclusion

tDCS and TMS appear to be effective interventions for improving level of consciousness of patients with prolonged DoC. Subgroup analyses identified the key parameters required to enhance the effects of tDCS and TMS on level of consciousness. Etiology of DoC, initial level of consciousness, and phase of DoC could act as significant characteristics of patients related to the effectiveness of tDCS. Stimulation site could act as significant stimulation parameter related to the effectiveness of TMS. There is insufficient evidence to support the use of MNS in clinical practice to improve level of consciousness in patients with coma.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=337780, identifier: CRD42022337780.

Responses to stimuli in the 'snoezelen' room in unresponsive wakefulness or in minimally responsive state

BACKGROUND

Sensory stimulation in Snoezelen room increased responsiveness after brain injury and dementia.

OBJECTIVE

To explore the physiological and clinical effects of Snoezelen stimulation in persons with unresponsive wakefulness syndrome or minimally conscious state (UWS or MCS).

DESIGN

A comparative prospective observational cohort study.

METHODS

Ten patients with UWS and 25 in MCS were exposed to consecutive stimuli involving the 5 senses in a Snoezelen room. Heart rate (HR) and cerebral blood flow velocity (CBFV), and scores of the Loewenstein communication scale (LCS) were obtained before and during or after the stimuli.

RESULTS

The stimuli increased HR values and decreased left hemisphere CBFV values in patients with MCS (p < 0.05). Stimulation increased LCS scores (from 28.48 ± 6.55 to 31.13 ± 7.14; p < 0.001) in patients with MCS, but not in the UWS group. LCS gain correlated with HR and right hemisphere CBFV gains in patients with MCS (r = 0.439 and 0.636 respectively, p < 0.05).

CONCLUSIONS

Snoezelen stimulation induced immediate improvement in communication and physiological changes in patients with MSC, and had a minor physiological effect in patients with UWS. If additional studies support these findings, it will be possible to suggest that Snoezelen stimulation can affect arousal, and possibly improve functioning.

Mapping the Unconscious Brain: Insights From Advanced Neuroimaging

SUMMARY

Recent advances in neuroimaging have been a preeminent factor in the scientific effort to unravel mechanisms of conscious awareness and the pathophysiology of disorders of consciousness. In the first part of this review, we selectively discuss operational models of consciousness, the biophysical signal that is measured using different imaging modalities, and knowledge on disorders of consciousness that has been gleaned with each neuroimaging modality. Techniques considered include diffusion-weighted imaging, diffusion tensor imaging, different types of nuclear medicine imaging, functional MRI, magnetoencephalography, and the combined transcranial magnetic stimulation-electroencephalography approach. In the second part of this article, we provide an overview of how advanced neuroimaging can be leveraged to support neurological prognostication, the use of machine learning to process high-dimensional imaging data, potential applications in clinical practice, and future directions.

The Potential Role of fNIRS in Evaluating Levels of Consciousness

Over the last few decades, neuroimaging techniques have transformed our understanding of the brain and the effect of neurological conditions on brain function. More recently, light-based modalities such as functional near-infrared spectroscopy have gained popularity as tools to study brain function at the bedside. A recent application is to assess residual awareness in patients with disorders of consciousness, as some patients retain awareness albeit lacking all behavioural response to commands. Functional near-infrared spectroscopy can play a vital role in identifying these patients by assessing command-driven brain activity. The goal of this review is to summarise the studies reported on this topic, to discuss the technical and ethical challenges of working with patients with disorders of consciousness, and to outline promising future directions in this field.

How Energy Supports Our Brain to Yield Consciousness: Insights From Neuroimaging Based on the Neuroenergetics Hypothesis

Consciousness is considered a result of specific neuronal processes and mechanisms in the brain. Various suggested neuronal mechanisms, including the information integration theory (IIT), global neuronal workspace theory (GNWS), and neuronal construction of time and space as in the context of the temporospatial theory of consciousness (TTC), have been laid forth. However, despite their focus on different neuronal mechanisms, these theories neglect the energetic-metabolic basis of the neuronal mechanisms that are supposed to yield consciousness. Based on the findings of physiology-induced (sleep), pharmacology-induced (general anesthesia), and pathology-induced [vegetative state/unresponsive wakeful syndrome (VS/UWS)] loss of consciousness in both human subjects and animals, we, in this study, suggest that the energetic-metabolic processes focusing on ATP, glucose, and γ-aminobutyrate/glutamate are indispensable for functional connectivity (FC) of normal brain networks that renders consciousness possible. Therefore, we describe the energetic-metabolic predispositions of consciousness (EPC) that complement the current theories focused on the neural correlates of consciousness (NCC).

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.

Functional and Structural Integrity of Frontoparietal Connectivity in Traumatic and Anoxic Coma

OBJECTIVES

Recovery from coma might critically depend on the structural and functional integrity of frontoparietal networks. We aimed to measure this integrity in traumatic brain injury and anoxo-ischemic (cardiac arrest) coma patients by using an original multimodal MRI protocol.

DESIGN

Prospective cohort study.

SETTING

Three Intensive Critical Care Units affiliated to the University in Toulouse (France).

PATIENTS

We longitudinally recruited 43 coma patients (Glasgow Coma Scale at the admission < 8; 29 cardiac arrest and 14 traumatic brain injury) and 34 age-matched healthy volunteers. Exclusion criteria were disorders of consciousness lasting more than 30 days and focal brain damage within the explored brain regions. Patient assessments were conducted at least 2 days (5 ± 2 d) after complete withdrawal of sedation. All patients were followed up (Coma Recovery Scale-Revised) 3 months after acute brain injury.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Functional and structural MRI data were recorded, and the analysis was targeted on the posteromedial cortex, the medial prefrontal cortex, and the cingulum. Univariate analyses and machine learning techniques were used to assess diagnostic and predictive values. Coma patients displayed significantly lower medial prefrontal cortex-posteromedial cortex functional connectivity (area under the curve, 0.94; 95% CI, 0.93-0.95). Cardiac arrest patients showed specific structural disturbances within posteromedial cortex. Significant cingulum architectural disturbances were observed in traumatic brain injury patients. The machine learning medial prefrontal cortex-posteromedial cortex multimodal classifier had a significant predictive value (area under the curve, 0.96; 95% CI, 0.95-0.97), best combination of subregions that discriminates a binary outcome based on Coma Recovery Scale-Revised).

CONCLUSIONS

This exploratory study suggests that frontoparietal functional disconnections are specifically observed in coma and their structural counterpart provides information about brain injury mechanisms. Multimodal MRI biomarkers of frontoparietal disconnection predict 3-month outcome in our sample. These findings suggest that fronto-parietal disconnection might be particularly relevant for coma outcome prediction and could inspire innovative precision medicine approaches.

Cortical lesions causing loss of consciousness are anticorrelated with the dorsal brainstem

Brain lesions can provide unique insight into the neuroanatomical substrate of human consciousness. For example, brainstem lesions causing coma map to a specific region of the tegmentum. Whether specific lesion locations outside the brainstem are associated with loss of consciousness (LOC) remains unclear. Here, we investigate the topography of cortical lesions causing prolonged LOC (N = 16), transient LOC (N = 91), or no LOC (N = 64). Using standard voxel lesion symptom mapping, no focus of brain damage was associated with LOC. Next, we computed the network of brain regions functionally connected to each lesion location using a large normative connectome dataset (N = 1,000). This technique, termed lesion network mapping, can test whether lesions causing LOC map to a connected brain circuit rather than one brain region. Connectivity between cortical lesion locations and an a priori coma-specific region of brainstem tegmentum was an independent predictor of LOC (B = 1.2, p = .004). Connectivity to the dorsal brainstem was the only predictor of LOC in a whole-brain voxel-wise analysis. This relationship was driven by anticorrelation (negative correlation) between lesion locations and the dorsal brainstem. The map of regions anticorrelated to the dorsal brainstem thus defines a distributed brain circuit that, when damaged, is most likely to cause LOC. This circuit showed a slight posterior predominance and had peaks in the bilateral claustrum. Our results suggest that cortical lesions causing LOC map to a connected brain circuit, linking cortical lesions that disrupt consciousness to brainstem sites that maintain arousal.

Pharmacologically informed machine learning approach for identifying pathological states of unconsciousness via resting-state fMRI

Determining the level of consciousness in patients with disorders of consciousness (DOC) remains challenging. To address this challenge, resting-state fMRI (rs-fMRI) has been widely used for detecting the local, regional, and network activity differences between DOC patients and healthy controls. Although substantial progress has been made towards this endeavor, the identification of robust rs-fMRI-based biomarkers for level of consciousness is still lacking. Recent developments in machine learning show promise as a tool to augment the discrimination between different states of consciousness in clinical practice. Here, we investigated whether machine learning models trained to make a binary distinction between conscious wakefulness and anesthetic-induced unconsciousness would then be capable of reliably identifying pathologically induced unconsciousness. We did so by extracting rs-fMRI-based features associated with local activity, regional homogeneity, and interregional functional activity in 44 subjects during wakefulness, light sedation, and unresponsiveness (deep sedation and general anesthesia), and subsequently using those features to train three distinct candidate machine learning classifiers: support vector machine, Extra Trees, artificial neural network. First, we show that all three classifiers achieve reliable performance within-dataset (via nested cross-validation), with a mean area under the receiver operating characteristic curve (AUC) of 0.95, 0.92, and 0.94, respectively. Additionally, we observed comparable cross-dataset performance (making predictions on the DOC data) as the anesthesia-trained classifiers demonstrated a consistent ability to discriminate between unresponsive wakefulness syndrome (UWS/VS) patients and healthy controls with mean AUC's of 0.99, 0.94, 0.98, respectively. Lastly, we explored the potential of applying the aforementioned classifiers towards discriminating intermediate states of consciousness, specifically, subjects under light anesthetic sedation and patients diagnosed as having a minimally conscious state (MCS). Our findings demonstrate that machine learning classifiers trained on rs-fMRI features derived from participants under anesthesia have potential to aid the discrimination between degrees of pathological unconsciousness in clinical patients.

Feasibility of Non-Gaussian Diffusion Metrics in Chronic Disorders of Consciousness

Diagnostic accuracy of different chronic disorders of consciousness (DOC) can be affected by the false negative errors in up to 40% cases. In the present study, we aimed to investigate the feasibility of a non-Gaussian diffusion approach in chronic DOC and to estimate a sensitivity of diffusion kurtosis imaging (DKI) metrics for the differentiation of vegetative state/unresponsive wakefulness syndrome (VS/UWS) and minimally conscious state (MCS) from a healthy brain state. We acquired diffusion MRI data from 18 patients in chronic DOC (11 VS/UWS, 7 MCS) and 14 healthy controls. A quantitative comparison of the diffusion metrics for grey (GM) and white (WM) matter between the controls and patient group showed a significant (p < 0.05) difference in supratentorial WM and GM for all evaluated diffusion metrics, as well as for brainstem, corpus callosum, and thalamus. An intra-subject VS/UWS and MCS group comparison showed only kurtosis metrics and fractional anisotropy differences using tract-based spatial statistics, owing mainly to macrostructural differences on most severely lesioned hemispheres. As a result, we demonstrated an ability of DKI metrics to localise and detect changes in both WM and GM and showed their capability in order to distinguish patients with a different level of consciousness.

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

Clinical patients in a vegetative state or unresponsive wakefulness syndrome (VS/UWS) demonstrate distinct arousal-awareness dissociation; the neuropathological mechanisms underlying such dissociation remain poorly understood. Here, we systematically examined how functional connectivity from the brainstem areas regulating arousal to the cortical networks supporting internal and external awareness is disrupted in minimally conscious state (MCS) and VS/UWS patients. Resting-state functional imaging was conducted in 23 MCS patients, 31 VS/UWS patients, and 20 age-matched healthy individuals. A hierarchical cluster analysis was conducted using all voxel-based signals in the brainstem to identify the specific areas for arousal. We found that the pontine tegmentum area (PTA) and caudal midbrain area persistently formed a distinct cluster that exclusively showed extensive connections with the cortical networks supporting internal and external awareness in healthy individuals, confirming their role in arousal. We show that functional connectivity from the PTA and caudal midbrain area to the cortical-awareness-supporting networks were significantly reduced in MCS and VS/UWS patients; importantly, as the clinical symptoms of consciousness disorders deepen from MCS to VS/UWS, functional connectivity strength became significantly reduced, changing from presenting no significant connections in MCS to widespread negative connections in VS/UWS. Additionally, we observed increased connectivity from the PTA and caudal midbrain area to limbic structures, the brainstem areas, and the cerebellum in MCS and VS/UWS patients, consistent with prior studies. These findings offer important insights into the neural network mechanisms underlying the long-observed arousal-awareness dissociation in VS/UWS patients and provide additional neuroimaging-based biomarkers for the clinical diagnosis of MCS and VS/UWS patients.

The value of midbrain morphology in predicting prognosis in chronic disorders of consciousness: A preliminary ultrasound study

Transcranial sonography (TCS) of the brainstem is currently used to support the clinical diagnosis of movement disorders. The aim of the study was to assess the usefulness of midbrain TCS in assessing outcome in patients with Chronic Disorders of Consciousness (DOC). Eleven patients with Minimally Conscious State (MCS) and Unresponsive Wakefulness Syndrome (UWS) were included in the study. We measured the area and echogenicity of the midbrain by encoding and digitally analyzing the corresponding images from the orbitomeatal plane, the morphology of brain parenchyma from the thalamic and cella media plane, and the intracranial circulation. All the patients showed an increase of pulsatility index and numerous morphological alterations on all the scan planes. In particular, we found a loss of the characteristic butterfly-shape of the midbrain, which appeared hypoechoic in the UWS but not in the MCS patients. After six months, the patients were clinically assessed by using Glasgow Outcome Scale Extended (GOSE). We found that a higher increase in GOSE scoring at follow-up was correlated with larger area and higher echogenicity of the midbrain at baseline. The present study suggests that TCS data of the midbrain may support clinical assessment of patients with chronic DOC to estimate their outcome.

Brain Gray Matter MRI Morphometry for Neuroprognostication After Cardiac Arrest

OBJECTIVES

We hypothesize that the combined use of MRI cortical thickness measurement and subcortical gray matter volumetry could provide an early and accurate in vivo assessment of the structural impact of cardiac arrest and therefore could be used for long-term neuroprognostication in this setting.

DESIGN

Prospective cohort study.

SETTING

Five Intensive Critical Care Units affiliated to the University in Toulouse (France), Paris (France), Clermont-Ferrand (France), Liège (Belgium), and Monza (Italy).

PATIENTS

High-resolution anatomical T1-weighted images were acquired in 126 anoxic coma patients ("learning" sample) 16 ± 8 days after cardiac arrest and 70 matched controls. An additional sample of 18 anoxic coma patients, recruited in Toulouse, was used to test predictive model generalization ("test" sample). All patients were followed up 1 year after cardiac arrest.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Cortical thickness was computed on the whole cortical ribbon, and deep gray matter volumetry was performed after automatic segmentation. Brain morphometric data were employed to create multivariate predictive models using learning machine techniques. Patients displayed significantly extensive cortical and subcortical brain volumes atrophy compared with controls. The accuracy of a predictive classifier, encompassing cortical and subcortical components, has a significant discriminative power (learning area under the curve = 0.87; test area under the curve = 0.96). The anatomical regions which volume changes were significantly related to patient's outcome were frontal cortex, posterior cingulate cortex, thalamus, putamen, pallidum, caudate, hippocampus, and brain stem.

CONCLUSIONS

These findings are consistent with the hypothesis of pathologic disruption of a striatopallidal-thalamo-cortical mesocircuit induced by cardiac arrest and pave the way for the use of combined brain quantitative morphometry in this setting.

Potential benefits of zolpidem in disorders of consciousness

INTRODUCTION

It has been suggested that zolpidem may arouse patients with decreased level of consciousness. Zolpidem may partially or even completely reverse abnormal cell metabolism following brain damage. In this article, available evidences regarding effects of zolpidem on disorders of consciousness were reviewed. Areas covered: A literature review was conducted using PubMed, Scopus, Medline, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews and Google Scholar as online databases. Search Keywords were 'vegetative state', 'minimally conscious state', 'semi-comatose', 'arousal', 'zolpidem', 'wakefulness', 'awareness', and 'loss of consciousness'. All English language studies that evaluated the effects of zolpidem on disorders of consciousness as a main surrogate endpoint were included. Finally 21 articles within this subject were included. Expert commentary: Zolpidem showed positive effects in several conditions with decreased level of consciousness. However, benefits of zolpidem were not detected in all patients with disorders of consciousness. Patients with post-anoxic encephalopathy or traumatic brain injury did not experience benefits of zolpidem. Available evidences support positive effects of zolpidem on brain functions in patients with non-brain stem injuries.

Neural signature of coma revealed by posteromedial cortex connection density analysis

Posteromedial cortex (PMC) is a highly segregated and dynamic core, which appears to play a critical role in internally/externally directed cognitive processes, including conscious awareness. Nevertheless, neuroimaging studies on acquired disorders of consciousness, have traditionally explored PMC as a homogenous and indivisible structure. We suggest that a fine-grained description of intrinsic PMC topology during coma, could expand our understanding about how this cortical hub contributes to consciousness generation and maintain, and could permit the identification of specific markers related to brain injury mechanism and useful for neurological prognostication.

To explore this, we used a recently developed voxel-based unbiased approach, named functional connectivity density (CD). We compared 27 comatose patients (15 traumatic and 12 anoxic), to 14 age-matched healthy controls. The patients' outcome was assessed 3 months later using Coma Recovery Scale-Revised (CRS-R).

A complex pattern of decreased and increased connections was observed, suggesting a network imbalance between internal/external processing systems, within PMC during coma. The number of PMC voxels with hypo-CD positive correlation showed a significant negative association with the CRS-R score, notwithstanding aetiology. Traumatic injury specifically appeared to be associated with a greater prevalence of hyper-connected (negative correlation) voxels, which was inversely associated with patient neurological outcome. A logistic regression model using the number of hypo-CD positive and hyper-CD negative correlations, accurately permitted patient's outcome prediction (AUC = 0.906, 95%IC = 0.795–1). These points might reflect adaptive plasticity mechanism and pave the way for innovative prognosis and therapeutics methods.

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A twofold pattern of decreased and increased connections within PMC was observed during coma.

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The number of PMC voxels with decreased positive connections, was significantly associated with patient's outcome.

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Greater prevalence of hyperconnected PMC voxels in traumatic brain injury was correlated to outcome in this subgroup.

Change of ascending reticular activating system with recovery from vegetative state to minimally conscious state in a stroke patient

RATIONALE

We report on a stroke patient who showed change of the ascending reticular activating system (ARAS) concurrent with recovery from a vegetative state (VS) to a minimally conscious state (MCS), which was demonstrated on diffusion tensor tractography (DTT).

PATIENT CONCERNS

A 59-year-old male patient underwent CT-guided stereotactic drainage 3 times for management of intracerebral hemorrhage and intraventricular hemorrhage.

DIAGNOSIS

After 4 months from onset, when starting rehabilitation, the patient showed impaired consciousness, with a Glasgow Coma Scale (GCS) score of 6 and a Coma Recovery Scale-Revised score of 2. At 10 months after onset, his GCS score had recovered to 11 with a GRS-R score of 20, and he was able to perform rock-scissors-paper using his right hand according to verbal command.

INTERVENTIONS

On 10-month DTT, marked increased neural connectivity of the thalamic intralaminar nucleus (ILN) to the cerebral cortex was observed in both prefrontal cortexes and the right thalamus compared with 4-month DTT. However, no significant change was observed in the lower dorsal ARAS between the pontine reticular formation (PRF) and the thalamic ILN. In addition, the reconstructed lower ventral ARAS between the PRF and hypothalamus had disappeared in both hemispheres on 10-month DTT.

OUTCOMES

Change of the ARAS was demonstrated in a stroke patient who showed recovery from a VS to an MCS.

LESSONS

It appeared that the prefrontal cortex and thalamus, which showed increased neural connectivity, contributed to recovery from a VS to an MCS in this patient.

Neurofeedback in three patients in the state of unresponsive wakefulness

Some severely brain injured patients remain unresponsive, only showing reflex movements without any response to command. This syndrome has been named unresponsive wakefulness syndrome (UWS). The objective of the present study was to determine whether UWS patients are able to alter their brain activity using neurofeedback (NFB) technique. A small sample of three patients received a daily session of NFB for 3 weeks. We applied the ratio of theta and beta amplitudes as a feedback variable. Using an automatic threshold function, patients heard their favourite music whenever their theta/beta ratio dropped below the threshold. Changes in awareness were assessed weekly with the JFK Coma Recovery Scale-Revised for each treatment week, as well as 3 weeks before and after NFB. Two patients showed a decrease in their theta/beta ratio and theta-amplitudes during this period. The third patient showed no systematic changes in his EEG activity. The results of our study provide the first evidence that NFB can be used in patients in a state of unresponsive wakefulness.

Disruption of posteromedial large-scale neural communication predicts recovery from coma

Objective:

We hypothesize that the major consciousness deficit observed in coma is due to the breakdown of long-range neuronal communication supported by precuneus and posterior cingulate cortex (PCC), and that prognosis depends on a specific connectivity pattern in these networks.

Methods:

We compared 27 prospectively recruited comatose patients who had severe brain injury (Glasgow Coma Scale score <8; 14 traumatic and 13 anoxic cases) with 14 age-matched healthy participants. Standardized clinical assessment and fMRI were performed on average 4 ± 2 days after withdrawal of sedation. Analysis of resting-state fMRI connectivity involved a hypothesis-driven, region of interest–based strategy. We assessed patient outcome after 3 months using the Coma Recovery Scale–Revised (CRS-R).

Results:

Patients who were comatose showed a significant disruption of functional connectivity of brain areas spontaneously synchronized with PCC, globally notwithstanding etiology. The functional connectivity strength between PCC and medial prefrontal cortex (mPFC) was significantly different between comatose patients who went on to recover and those who eventually scored an unfavorable outcome 3 months after brain injury (Kruskal-Wallis test, p < 0.001; linear regression between CRS-R and PCC-mPFC activity coupling at rest, Spearman ρ = 0.93, p < 0.003).

Conclusion:

In both etiology groups (traumatic and anoxic), changes in the connectivity of PCC-centered, spontaneously synchronized, large-scale networks account for the loss of external and internal self-centered awareness observed during coma. Sparing of functional connectivity between PCC and mPFC may predict patient outcome, and further studies are needed to substantiate this potential prognosis biomarker.

Promoting the use of personally relevant stimuli for investigating patients with disorders of consciousness

Sensory stimuli are used to evaluate and to restore cognitive functions and consciousness in patients with a disorder of consciousness (DOC) following a severe brain injury. Although sophisticated protocols can help assessing higher order cognitive functions and awareness, one major drawback is their lack of sensitivity. The aim of the present review is to show that stimulus selection is crucial for an accurate evaluation of the state of patients with disorders of consciousness as it determines the levels of processing that the patient can have with stimulation from his/her environment. The probability to observe a behavioral response or a cerebral response is increased when her/his personal history and/or her/his personal preferences are taken into account. We show that personally relevant stimuli (i.e., with emotional, autobiographical, or self-related characteristics) are associated with clearer signs of perception than are irrelevant stimuli in patients with DOC. Among personally relevant stimuli, music appears to be a promising clinical tool as it boosts perception and cognition in patients with DOC and could also serve as a prognostic tool. We suggest that the effect of music on cerebral processes in patients might reflect the music's capacity to act both on the external and internal neural networks supporting consciousness.

The Autonomic System Functional State Predicts Responsiveness in Disorder of Consciousness

Diagnosis and early prognosis of the vegetative state/unresponsive wakefulness syndrome (VS/UWS) and its differentiation from the minimally-conscious state still rest on the clinical observation of responsiveness. The incidence of established clinical indicators of responsiveness also has proven variable in the single subject and is correlated to measures of heart rate variability (HRV) describing the sympathetic/parasympathetic balance. We tested responsiveness when the HRV descriptors nuLF and peakLF were or were not in the ranges with highest incidence of response based on findings from previous studies (10.0-70.0 and 0.05-0.11 Hz, respectively). Testing was blind by The Coma Recovery Scale-revised in the two conditions and in two experimental sessions with a one-week interval. The incidence of responses was not randomly distributed in the "response" and "no-response" conditions (McNemar test; p < 0.0001). The observed incidence in the "response" condition (visual: 55.1%; auditory: 51.5%) was higher than predicted statistically (32.1%) or described in previous clinical studies; responses were only occasional in the "no-response" condition (visual, 15.9%; auditory, 13.4%). Models validated the predictability with high accuracy. The current clinical criteria for diagnosis and prognosis based on neurological signs should be reconsidered, including variability over time and the autonomic system functional state, which could also qualify per se as an independent indicator for diagnosis and prognosis.

Resting brain activity in disorders of consciousness: a systematic review and meta-analysis

OBJECTIVE

To quantitatively synthesize results from neuroimaging studies that evaluated patterns of resting functional activity in patients with disorders of consciousness (DOC).

METHODS

We performed a systematic review and coordinate-based meta-analysis of studies published up to May 2014. Studies were included if they compared resting-state functional neuroimaging data acquired in patients with DOC (coma, minimally conscious state, emergence from minimally conscious state, or vegetative state) with a group of healthy controls. Coordinate-based meta-analysis was performed in studies that included voxel-based comparisons at the whole-brain level and if analysis was accomplished with data-driven approaches.

RESULTS

A total of 36 studies (687 patients, 637 healthy controls) were included in the systematic review. Reported DOC were vegetative state (43.2%), coma (23.4%), minimally conscious state (22.8%), and emergence from minimally conscious state (1.6%); the most common etiologies of DOC were traumatic brain injury (37.7%) and anoxic brain injury (36.9%). Functional neuroimaging was accomplished using fMRI (16 studies), PET (15 studies), SPECT (4 studies), and both PET and SPECT in one study. Meta-analysis in 13 studies (272 patients, 259 healthy controls) revealed consistently reduced activity in patients with DOC in bilateral medial dorsal nucleus of the thalamus, left cingulate, posterior cingulate, precuneus, and middle frontal and medial temporal gyri.

CONCLUSIONS

In patients with DOC evaluated in the resting state, functional neuroimaging indicates markedly reduced activity within midline cortical and subcortical sites, anatomical structures that have been linked to the default-mode network. Studies are needed to determine the relation between activation (and coherence) within these structures and the emergence of conscious awareness.

Neural correlates of consciousness: what we know and what we have to learn!

Consciousness is a multifaceted concept with two major components: awareness of environment and of self (i.e., the content of consciousness) and wakefulness (i.e., the level of consciousness). Medically speaking, consciousness is the state of the patient's awareness of self and environment and his responsiveness to external stimulation and inner need. A basic understanding of consciousness and its neural correlates is of major importance for all clinicians, especially those involved with patients suffering from altered states of consciousness. To this end, in this review it is shown that consciousness is dependent on the brainstem and thalamus for arousal; that basic cognition is supported by recurrent electrical activity between the cortex and the thalamus at gamma band frequencies; and that some kind of working memory must, at least fleetingly, be present for awareness to occur. New advances in neuroimaging studies are also presented in order to better understand and demonstrate the neurophysiological basis of consciousness. In particular, recent functional magnetic resonance imaging studies have offered the possibility to measure directly and non-invasively normal and severely brain damaged subjects' brain activity, whilst diffusion tensor imaging studies have allowed evaluating white matter integrity in normal subjects and patients with disorder of consciousness.

Quantitative rates of brain glucose metabolism distinguish minimally conscious from vegetative state patients

The differentiation of the vegetative or unresponsive wakefulness syndrome (VS/UWS) from the minimally conscious state (MCS) is an important clinical issue. The cerebral metabolic rate of glucose (CMRglc) declines when consciousness is lost, and may reveal the residual cognitive function of these patients. However, no quantitative comparisons of cerebral glucose metabolism in VS/UWS and MCS have yet been reported. We calculated the regional and whole-brain CMRglc of 41 patients in the states of VS/UWS (n=14), MCS (n=21) or emergence from MCS (EMCS, n=6), and healthy volunteers (n=29). Global cortical CMRglc in VS/UWS and MCS averaged 42% and 55% of normal, respectively. Differences between VS/UWS and MCS were most pronounced in the frontoparietal cortex, at 42% and 60% of normal. In brainstem and thalamus, metabolism declined equally in the two conditions. In EMCS, metabolic rates were indistinguishable from those of MCS. Ordinal logistic regression predicted that patients are likely to emerge into MCS at CMRglc above 45% of normal. Receiver-operating characteristics showed that patients in MCS and VS/UWS can be differentiated with 82% accuracy, based on cortical metabolism. Together these results reveal a significant correlation between whole-brain energy metabolism and level of consciousness, suggesting that quantitative values of CMRglc reveal consciousness in severely brain-injured patients.

The mesencephalic nucleus of the trigeminal nerve and the SIDS

Sudden infant death syndrome (SIDS) is a major cause of infant mortality throughout the world, yet its cause and mechanism of action remain poorly understood. Here, we discuss a novel model of the etiology of SIDS which ties together what is known about the brain regions thought to be affected in SIDS infants with a defined neuroanatomical circuit and a documented preventative factor in young children. We propose that SIDS occurs due to a lack of sufficient development and plasticity of glutamatergic synapses in the mesencephalic nucleus of the trigeminal nerve (Me5) and reticular formation (RF) of the brainstem. This model is supported by evidence of brainstem dysfunction in SIDS as well as evidence of signaling through the Me5 and RF in another means of regulating cortical arousal. Furthermore, long-term plasticity of glutamatergic synapses is well known to play a critical role in learning and memory in other regions of the brain, implying that those mechanisms may also be relevant in the development of brainstem circuitry. This model clearly explains why SIDS deaths appear so suddenly with little pathological explanation and suggests a potentially novel way to prevent these deaths from occurring.

Using brain stimulation to disentangle neural correlates of conscious vision

Research into the neural correlates of consciousness (NCCs) has blossomed, due to the advent of new and increasingly sophisticated brain research tools. Neuroimaging has uncovered a variety of brain processes that relate to conscious perception, obtained in a range of experimental paradigms. But methods such as functional magnetic resonance imaging or electroencephalography do not always afford inference on the functional role these brain processes play in conscious vision. Such empirical NCCs could reflect neural prerequisites, neural consequences, or neural substrates of a conscious experience. Here, we take a closer look at the use of non-invasive brain stimulation (NIBS) techniques in this context. We discuss and review how NIBS methodology can enlighten our understanding of brain mechanisms underlying conscious vision by disentangling the empirical NCCs.

Measuring consciousness in coma and related states

Consciousness is a prismatic and ambiguous concept that still eludes any universal definition. Severe acquired brain injuries resulting in a disorder of consciousness (DOC) provide a model from which insights into consciousness can be drawn. A number of recent studies highlight the difficulty in making a diagnosis in patients with DOC based only on behavioral assessments. Here we aim to provide an overview of how neuroimaging techniques can help assess patients with DOC. Such techniques are expected to facilitate a more accurate understanding of brain function in states of unconsciousness and to improve the evaluation of the patient’s cognitive abilities by providing both diagnostic and prognostic indicators.

Resting brain activity varies with dream recall frequency between subjects

Dreaming is still poorly understood. Notably, its cerebral underpinning remains unclear. Neuropsychological studies have shown that lesions in the temporoparietal junction (TPJ) and/or the white matter of the medial prefrontal cortex (MPFC) lead to the global cessation of dream reports, suggesting that these regions of the default mode network have key roles in the dreaming process (forebrain 'dream-on' hypothesis). To test this hypothesis, we measured regional cerebral blood flow (rCBF) using [(15)O]H2O positron emission tomography in healthy subjects with high and low dream recall frequencies (DRFs) during wakefulness (rest) and sleep (rapid eye movement (REM) sleep, N2, and N3). Compared with Low recallers (0.5 ± 0.3 dream recall per week in average), High recallers (5.2 ± 1.4) showed higher rCBF in the TPJ during REM sleep, N3, and wakefulness, and in the MPFC during REM sleep and wakefulness. We demonstrate that the resting states of High recallers and Low recallers differ during sleep and wakefulness. It coheres with previous ERP results and confirms that a high/low DRF is associated with a specific functional organization of the brain. These results support the forebrain 'dream-on' hypothesis and suggest that TPJ and MPFC are not only involved in dream recall during wakefulness but also have a role in dreaming during sleep (production and/or encoding). Increased activity in the TPJ and MPFC might promote the mental imagery and/or memory encoding of dreams. Notably, increased activity in TPJ might facilitate attention orienting toward external stimuli and promote intrasleep wakefulness, facilitating the encoding of the dreams in memory.

Functional MRI and outcome in traumatic coma

Advances in task-based functional MRI (fMRI), resting-state fMRI (rs-fMRI), and arterial spin labeling (ASL) perfusion MRI have occurred at a rapid pace in recent years. These techniques for measuring brain function have great potential to improve the accuracy of prognostication for civilian and military patients with traumatic coma. In addition, fMRI, rs-fMRI, and ASL perfusion MRI have provided novel insights into the pathophysiology of traumatic disorders of consciousness, as well as the mechanisms of recovery from coma. However, functional neuroimaging techniques have yet to achieve widespread clinical use as prognostic tests for patients with traumatic coma. Rather, a broad spectrum of methodological hurdles currently limits the feasibility of clinical implementation. In this review, we discuss the basic principles of fMRI, rs-fMRI, and ASL perfusion MRI and their potential applications as prognostic tools for patients with traumatic coma. We also discuss future strategies for overcoming the current barriers to clinical implementation.

Spectral parameters modulation and source localization of blink-related alpha and low-beta oscillations differentiate minimally conscious state from vegetative state/unresponsive wakefulness syndrome

Recently, the cortical source of blink-related delta oscillations (delta BROs) in resting healthy subjects has been localized in the posterior cingulate cortex/precuneus (PCC/PCu), one of the main core-hubs of the default-mode network. This has been interpreted as the electrophysiological signature of the automatic monitoring of the surrounding environment while subjects are immersed in self-reflecting mental activities. Although delta BROs were directly correlated to the degree of consciousness impairment in patients with disorders of consciousness, they failed to differentiate vegetative state/unresponsive wakefulness syndrome (VS/UWS) from minimally conscious state (MCS). In the present study, we have extended the analysis of BROs to frequency bands other than delta in the attempt to find a biological marker that could support the differential diagnosis between VS/UWS and MCS. Four patients with VS/UWS, 5 patients with MCS, and 12 healthy matched controls (CTRL) underwent standard 19-channels EEG recordings during resting conditions. Three-second-lasting EEG epochs centred on each blink instance were submitted to time-frequency analyses in order to extract the normalized Blink-Related Synchronization/Desynchronization (nBRS/BRD) of three bands of interest (low-alpha, high-alpha and low-beta) in the time-window of 50–550 ms after the blink-peak and to estimate the corresponding cortical sources of electrical activity. VS/UWS nBRS/BRD levels of all three bands were lower than those related to both CTRL and MCS, thus enabling the differential diagnosis between MCS and VS/UWS. Furthermore, MCS showed an intermediate signal intensity on PCC/PCu between CTRL and VS/UWS and a higher signal intensity on the left temporo-parieto-occipital junction and inferior occipito-temporal regions when compared to VS/UWS. This peculiar pattern of activation leads us to hypothesize that resting MCS patients have a bottom-up driven activation of the task positive network and thus are tendentially prone to respond to environmental stimuli, even though in an almost unintentional way.

Oxytocin effects on complex brain networks are moderated by experiences of maternal love withdrawal

The neuropeptide oxytocin has been implicated in a variety of social processes. However, recent studies indicate that oxytocin does not enhance prosocial behavior in all people in all circumstances. Here, we investigate effects of intranasal oxytocin administration on intrinsic functional brain connectivity with resting state functional magnetic resonance imaging. Participants were 42 women who received a nasal spray containing either 16 IU of oxytocin or a placebo and reported how often their mother used love withdrawal as a disciplinary strategy involving withholding love and affection after a failure or misbehavior. We found that oxytocin changes functional connectivity between the posterior cingulate cortex (PCC) and the brainstem. In the oxytocin group there was a positive connectivity between these regions, whereas the placebo group showed negative connectivity. In addition, oxytocin induced functional connectivity changes between the PCC, the cerebellum and the postcentral gyrus, but only for those participants who experienced low levels of maternal love withdrawal. We speculate that oxytocin enhances prosocial behavior by influencing complex brain networks involved in self-referential processing and affectionate touch, most prominently in individuals with supportive family backgrounds.

The Human Connectome Project and beyond: initial applications of 300 mT/m gradients

The engineering of a 3 T human MRI scanner equipped with 300 mT/m gradients - the strongest gradients ever built for an in vivo human MRI scanner - was a major component of the NIH Blueprint Human Connectome Project (HCP). This effort was motivated by the HCP's goal of mapping, as completely as possible, the macroscopic structural connections of the in vivo healthy, adult human brain using diffusion tractography. Yet, the 300 mT/m gradient system is well suited to many additional types of diffusion measurements. Here, we present three initial applications of the 300 mT/m gradients that fall outside the immediate scope of the HCP. These include: 1) diffusion tractography to study the anatomy of consciousness and the mechanisms of brain recovery following traumatic coma; 2) q-space measurements of axon diameter distributions in the in vivo human brain and 3) postmortem diffusion tractography as an adjunct to standard histopathological analysis. We show that the improved sensitivity and diffusion-resolution provided by the gradients are rapidly enabling human applications of techniques that were previously possible only for in vitro and animal models on small-bore scanners, thereby creating novel opportunities to map the microstructure of the human brain in health and disease.

Sleep in the unresponsive wakefulness syndrome and minimally conscious state

The goal of our study was to investigate different aspects of sleep, namely the sleep-wake cycle and sleep stages, in the vegetative state/unresponsive wakefulness syndrome (VS/UWS), and minimally conscious state (MCS). A 24-h polysomnography was performed in 20 patients who were in a UWS (n=10) or in a MCS (n=10) because of brain injury. The data were first tested for the presence of a sleep-wake cycle, and the observed sleep patterns were compared with standard scoring criteria. Sleep spindles, slow wave sleep, and rapid eye movement sleep were quantified and their clinical value was investigated. According to our results, an electrophysiological sleep-wake cycle was identified in five MCS and three VS/UWS patients. Sleep stages did not always match the standard scoring criteria, which therefore needed to be adapted. Sleep spindles were present more in patients who clinically improved within 6 months. Slow wave sleep was present in eight MCS and three VS/UWS patients but never in the ischemic etiology. Rapid eye movement sleep, and therefore dreaming that is a form of consciousness, was present in all MCS and three VS/UWS patients. In conclusion, the presence of alternating periods of eyes-open/eyes-closed cycles does not necessarily imply preserved electrophysiological sleep architecture in the UWS and MCS, contrary to previous definition. The investigation of sleep is a little studied yet simple and informative way to evaluate the integrity of residual brain function in patients with disorders of consciousness with possible clinical diagnostic and prognostic implications.

Advanced neuroimaging in traumatic brain injury

Advances in structural and functional neuroimaging have occurred at a rapid pace over the past two decades. Novel techniques for measuring cerebral blood flow, metabolism, white matter connectivity, and neural network activation have great potential to improve the accuracy of diagnosis and prognosis for patients with traumatic brain injury (TBI), while also providing biomarkers to guide the development of new therapies. Several of these advanced imaging modalities are currently being implemented into clinical practice, whereas others require further development and validation. Ultimately, for advanced neuroimaging techniques to reach their full potential and improve clinical care for the many civilians and military personnel affected by TBI, it is critical for clinicians to understand the applications and methodological limitations of each technique. In this review, we examine recent advances in structural and functional neuroimaging and the potential applications of these techniques to the clinical care of patients with TBI. We also discuss pitfalls and confounders that should be considered when interpreting data from each technique. Finally, given the vast amounts of advanced imaging data that will soon be available to clinicians, we discuss strategies for optimizing data integration, visualization, and interpretation.

What about pain in disorders of consciousness?

The management and treatment of acute pain is very difficult in non-communicative patients with disorders of consciousness (i.e., vegetative state/unresponsive wakefulness syndrome (VS/UWS) and minimally conscious state), creating an ethical dilemma for caregivers and an emotional burden among both relatives and caregivers. In this review, we summarize recent findings about the neural substrates of nociception and pain in VS/UWS patients as well as recent behavioral assessment methods of nociception specifically designed for patients in altered states of consciousness. We will finally discuss implications for pain treatment in these patients.

Cortical source of blink-related delta oscillations and their correlation with levels of consciousness

Recently, blink-related delta oscillations (delta BROs) have been observed in healthy subjects during spontaneous blinking at rest. Delta BROs have been linked with continuous gathering of information from the surrounding environment, which is classically attributed to the precuneus. Furthermore, fMRI studies have shown that precuneal activity is reduced or missing when consciousness is low or absent. We therefore hypothesized that the source of delta BROs in healthy subjects could be located in the precuneus and that delta BROs could be absent or reduced in patients with disorders of consciousness (DOC). To test these hypotheses, electroencephalographic (EEG) activity at rest was recorded in 12 healthy controls and nine patients with DOC (four vegetative states, and five minimally conscious states). Three-second-lasting EEG epochs centred on each blink instance were analyzed in both time- (BROs) and frequency domains (event-related spectral perturbation or ERSP and intertrial coherence or ITC). Cortical sources of the maximum blink-related delta power, corresponding to the positive peak of the delta BROs, were estimated by standardized Low Resolution Electromagnetic Tomography. In control subjects, as expected, the source of delta BROs was located in the precuneus, whereas in DOC patients, delta BROs were not recognizable and no precuneal localization was possible. Furthermore, we observed a direct relationship between spectral indexes and levels of cognitive functioning in all subjects participating in the study. This reinforces the hypothesis that delta BROs reflect neural processes linked with awareness of the self and of the environment.

Measuring the fading consciousness in the human brain

PURPOSE OF REVIEW

Recent neuroimaging studies have provided novel insights on residual brain function in patients with disorders of consciousness, but also raised a number of ethical issues concerning the clinical management of these patients.

RECENT FINDINGS

Clinical studies have rated the Coma Recovery Scale as the most appropriate scale to accurately differentiate patients in a vegetative state from patients in a minimally conscious state. At the population level, a number of neuroimaging studies have provided evidence for more preserved brain activity patterns and cerebral tissue integrity in minimally conscious as compared to vegetative-state patients. However, the use of neuroimaging techniques to diagnose consciousness at the single-patient level remains challenging. In particular, it has been shown that whereas command-following functional MRI paradigms may sometimes detect residual awareness in patients that are behaviorally unresponsive, they can also produce negative results in patients that are communicative at the bedside.

SUMMARY

There is an urgent need of validation of functional MRI active paradigms on larger patient populations before they can be used in clinical routine. Further research on neural correlates of consciousness should hopefully allow using passive paradigms to assess the patients' conscious state without requiring their active collaboration.

Assessment of consciousness with electrophysiological and neurological imaging techniques

PURPOSE OF REVIEW

Brain MRI (diffusion tensor imaging and spectroscopy) and functional neuroimaging (PET, functional MRI, EEG and evoked potential studies) are changing our understanding of patients with disorders of consciousness encountered after coma such as the 'vegetative' or minimally conscious states.

RECENT FINDINGS

Increasing evidence from functional neuroimaging and electrophysiology demonstrates some residual cognitive processing in a subgroup of patients who clinically fail to show any response to commands, leading to the recent proposal of 'unresponsive wakefulness syndrome' as an alternative name for patients previously coined 'vegetative' or 'apallic'.

SUMMARY

Consciousness can be viewed as the emergent property of the collective behavior of widespread thalamocortical frontoparietal network connectivity. Data from physiological, pharmacological and pathological alterations of consciousness provide evidence in favor of this hypothesis. Increasing our understanding of the neural correlates of consciousness is helping clinicians to do a better job in terms of diagnosis, prognosis and finally treatment and drug development for these severely brain-damaged patients. The current challenge remains to continue translating this research from the bench to the bedside. Only well controlled large multicentric neuroimaging and electrophysiology studies will enable to identify which paraclinical diagnostic or prognostic test is necessary for our routine evidence-based assessment of individuals with disorders of consciousness.

Neurotransmitters in disorders of consciousness and brain damage

Restorations from disorders of consciousness such as the minimally conscious state and the vegetative state have been achieved spontaneously or by pharmacological agents such as zolpidem, baclofen, dopaminergic agents and tricyclic antidepressants in some patients. Other restoration methods have included electric and magnetic nerve stimulation, oxygen, Kreb's cycle constituent substitution and axonal re-growth. Although apparently unrelated, these methods all influence neurotransmitter availability or production within the brain. This review proposes depleted neurotransmitter function as a cause for long term brain suppression and disorders of consciousness. It unifies fundamentally different treatment approaches and explores the restoration of neurotransmitter function as a common theme to improve brain function after brain damage.

Visual pursuit in the severe disorder of consciousness

Visual pursuit is a key descriptor of the minimally conscious state (above 80% of cases). It is also observable in about 20% of subjects in vegetative state. Its reappearance after severe brain damage anticipates a favorable outcome, with recovery of consciousness in 73% of subjects (45% in the absence of it). We considered retrospectively 395 subjects in vegetative state because of traumatic (63%), massive acute vascular (30%), or diffuse anoxic-hypoxic (7%) brain damage consecutively admitted to one dedicated unit during the years 1998-2008. Visual tracking was observed in 290 subjects (73.4%) and was already detectable within 50 days from brain injury in about 60% of post-traumatic or vascular subjects and 21% of anoxic-hypoxic patients. After 230 days of follow-up or more, it was observed in 89% and 88% of post-traumatic and vascular subjects and in 67% of anoxic-hypoxic patients. Rating with the Glasgow Outcome Scale (GOS) was better in those subjects with recovered visual tracking and inversely correlated with the time of reappearance in post-traumatic and vascular subjects; also the subjects with late recovery of eye tracking (230 days or more) had better GOS outcome than those without it. The observation of visual tracking reappearing in subjects in vegetative state would reflect recuperation of the brainstem-cortical interaction and overall brain functional organization that are thought to sustain consciousness and are interfered with by the "functional disconnection," resulting in the vegetative state.