Minimally conscious state

Locked-in syndrome (LIS) represents one of the most clinically paradoxical and ethically compelling conditions in neurology. Patients retain full consciousness, cognitive function, and emotional capacity while being rendered nearly completely paralyzed, typically preserving only vertical eye movements and blinking. This dissociation between intact cortical function and efferent motor failure results from lesions to the ventral pons or caudal midbrain, most commonly due to basilar artery occlusion. The syndrome is substantially underrecognized in its early stages, with diagnosis often delayed by weeks, during which time family members are frequently the first to detect signs of purposeful behavior. This article provides a comprehensive, clinically grounded overview of LIS, beginning with its definition and classification-classical, incomplete, and total immobility forms. The etiological spectrum is reviewed, emphasizing the predominance of vascular causes, followed by trauma, masses, infections, and demyelinating disorders such as central pontine myelinolysis. Pathophysiological mechanisms are mapped to brainstem anatomy, explaining why consciousness and vertical gaze survive while all other voluntary motor functions are lost. The evaluation section integrates neuroimaging, CSF analysis, electrophysiology, and serum studies, highlighting the role of EEG in confirming cortical function in the most severe cases. Management is stratified into acute stabilization with thrombolysis or thrombectomy where indicated, treatment of the underlying cause, and long-term rehabilitation with assistive technologies including eye-tracking and brain-computer interfaces. The differential diagnosis is systematically compared with persistent vegetative state, akinetic mutism, coma, catatonia, and high cervical cord injury. Prognosis varies markedly by etiology: nonvascular causes carry lower mortality and better recovery potential, while vascular LIS remains a severe insult, though survivors beyond four months may achieve meaningful functional gains. Complications-including nosocomial infections, DVT, pressure ulcers, and persistent dysphagia-require proactive interdisciplinary management. Ultimately, early recognition, structured diagnostic algorithms, and aggressive rehabilitation improve outcomes. The locked-in patient is not a vegetable nor a ghost, but a person waiting for the world to learn how to listen. Keywords Locked-in syndrome; basilar artery occlusion; ventral pontine lesion; disorders of consciousness; de-efferentation; central pontine myelinolysis; brain-computer interface; akinetic mutism; quadriplegia with preserved cognition; neurorehabilitation Key Points Consciousness is the rule, not the exception. A patient who cannot move or speak but can blink upward on command is locked in, not unconscious. The single most common diagnostic error is assuming that immobility implies unawareness. The eyes are the window to the locked-in mind. Preserved vertical gaze and blinking are the clinical bedrock of LIS. If a patient with quadriplegia and anarthria can reliably signal

Background: There are few available therapeutic options to promote recovery among patients with chronic disorders of consciousness (DOC). Among pharmacological treatments, apomorphine, a dopamine agonist, has exhibited promising behavioral effects and safety of use in small-sample pilot studies. The true efficacy of the drug and its neural mechanism are still unclear. Apomorphine may act through a modulation of the anterior forebrain mesocircuit, but neuroimaging and neurophysiological investigations to test this hypothesis are scarce. This clinical trial aims to (1) assess the treatment effect of subcutaneous apomorphine infusions in patients with DOC, (2) better identify the phenotype of responders to treatment, (3) evaluate tolerance and side effects in this population, and (4) examine the neural networks underlying its modulating action on consciousness. Methods/Design: This study is a prospective double-blind randomized parallel placebo-controlled trial. Forty-eight patients diagnosed with DOC will be randomized to receive a 30-day regimen of either apomorphine hydrochloride or placebo subcutaneous infusions. Patients will be monitored at baseline 30 days before initiation of therapy, during treatment and for 30 days after treatment washout, using standardized behavioral scales (Coma Recovery Scale-Revised, Nociception Coma Scale-Revised), neurophysiological measures (electroencephalography, body temperature, actigraphy) and brain imaging (magnetic resonance imaging, positron emission tomography). Behavioral follow-up will be performed up to 2 years using structured phone interviews. Analyses will look for changes in behavioral status, circadian rhythmicity, brain metabolism, and functional connectivity at the individual level (comparing before and after treatment) and at the group level (comparing apomorphine and placebo arms, and comparing responder and non-responder groups). Sanz et al. Discussion: This study investigates the use of apomorphine for the recovery of consciousness in the first randomized placebo-controlled double-blind trial using multimodal assessments. The results will contribute to define the role of dopamine agonists for the treatment of these challenging conditions and identify the neural correlates to their action. Results will bring objective evidence to further assess the modulation of the anterior forebrain mesocircuit by pharmacological agents, which may open new therapeutic perspectives. Clinical Trial Registration: EudraCT n • 2018-003144-23; Clinicaltrials.gov n • NCT03623828 ().

Background: There are few available therapeutic options to promote recovery among patients with chronic disorders of consciousness (DOC). Among pharmacological treatments, apomorphine, a dopamine agonist, has exhibited promising behavioral effects and safety of use in small-sample pilot studies. The true efficacy of the drug and its neural mechanism are still unclear. Apomorphine may act through a modulation of the anterior forebrain mesocircuit, but neuroimaging and neurophysiological investigations to test this hypothesis are scarce. This clinical trial aims to (1) assess the treatment effect of subcutaneous apomorphine infusions in patients with DOC, (2) better identify the phenotype of responders to treatment, (3) evaluate tolerance and side effects in this population, and (4) examine the neural networks underlying its modulating action on consciousness. Methods/Design: This study is a prospective double-blind randomized parallel placebo-controlled trial. Forty-eight patients diagnosed with DOC will be randomized to receive a 30-day regimen of either apomorphine hydrochloride or placebo subcutaneous infusions. Patients will be monitored at baseline 30 days before initiation of therapy, during treatment and for 30 days after treatment washout, using standardized behavioral scales (Coma Recovery Scale-Revised, Nociception Coma Scale-Revised), neurophysiological measures (electroencephalography, body temperature, actigraphy) and brain imaging (magnetic resonance imaging, positron emission tomography). Behavioral follow-up will be performed up to 2 years using structured phone interviews. Analyses will look for changes in behavioral status, circadian rhythmicity, brain metabolism, and functional connectivity at the individual level (comparing before and after treatment) and at the group level (comparing apomorphine and placebo arms, and comparing responder and non-responder groups). Sanz et al. Discussion: This study investigates the use of apomorphine for the recovery of consciousness in the first randomized placebo-controlled double-blind trial using multimodal assessments. The results will contribute to define the role of dopamine agonists for the treatment of these challenging conditions and identify the neural correlates to their action. Results will bring objective evidence to further assess the modulation of the anterior forebrain mesocircuit by pharmacological agents, which may open new therapeutic perspectives. Clinical Trial Registration: EudraCT n • 2018-003144-23; Clinicaltrials.gov n • NCT03623828 ().

To update the 1995 American Academy of Neurology (AAN) practice parameter on persistent vegetative state and the 2002 case definition for the minimally conscious state (MCS) by reviewing the literature on the diagnosis, natural history, prognosis, and treatment of disorders of consciousness lasting at least 28 days. Articles were classified per the AAN evidence-based classification system. Evidence synthesis occurred through a modified Grading of Recommendations Assessment, Development and Evaluation process. Recommendations were based on evidence, related evidence, care principles, and inferences according to the AAN 2011 process manual, as amended. No diagnostic assessment procedure had moderate or strong evidence for use. It is possible that a positive EMG response to command, EEG reactivity to sensory stimuli, laser-evoked potentials, and the Perturbational Complexity Index can distinguish MCS from vegetative state/unresponsive wakefulness syndrome (VS/UWS). The natural history ...

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Despite advances in resting state functional magnetic resonance imaging investigations, clinicians remain with the challenge of how to implement this paradigm on an individualized basis. Here, we assessed the clinical relevance of resting state functional magnetic resonance imaging acquisitions in patients with disorders of consciousness by means of a systems-level approach. Three clinical centres collected data from 73 patients in minimally conscious state, vegetative state/unresponsive wakefulness syndrome and coma. The main analysis was performed on the data set coming from one centre (Liège) including 51 patients (26 minimally conscious state, 19 vegetative state/unresponsive wakefulness syndrome, six coma; 15 females; mean age 49 ± 18 years, range 11-87; 16 traumatic, 32 non-traumatic of which 13 anoxic, three mixed; 35 patients assessed >1 month post-insult) for whom the clinical diagnosis with the Coma Recovery Scale-Revised was congruent with positron emission tomography ...

In the past ten years, rapid technological developments in the field of neuroimaging have produced a cornucopia of new techniques for examining both the structure and function of the human brain in vivo. In specialized centers, many of these methods are now being employed routinely in the assessment of patients diagnosed with disorders of consciousness, mapping patterns of residual function and dysfunction and helping to reduce diagnostic errors between related conditions such as the vegetative and minimally conscious states. Moreover, such efforts are beginning to provide important new prognostic indicators, helping to disentangle differences in outcome on the basis of a greater understanding of the underlying mechanisms responsible and providing information that will undoubtedly contribute to improved therapeutic choices in these challenging populations. Of course, these emerging technologies and the new information that they provide will bring new ethical challenges to this area ...

Background Patients diagnosed as vegetative have periods of wakefulness, but seem to be unaware of themselves or their environment. Although functional MRI (fMRI) studies have shown that some of these patients are consciously aware, issues of expense and accessibility preclude the use of fMRI assessment in most of these individuals. We aimed to assess bedside detection of awareness with an electroencephalography (EEG) technique in patients in the vegetative state. Methods This study was undertaken at two European centres. We recruited patients with traumatic brain injury and non-traumatic brain injury who met the Coma Recovery Scale-Revised definition of vegtative state. We developed a novel EEG task involving motor imagery to detect command-following-a universally accepted clinical indicator of awareness-in the absence of overt behaviour. Patients completed the task in which they were required to imagine movements of their right-hand and toes to command. We analysed the command-specific EEG responses of each patient for robust evidence of appropriate, consistent, and statistically reliable markers of motor imagery, similar to those noted in healthy, conscious controls. We assessed 16 patients diagnosed in the vegetative state, and 12 healthy controls. Three (19%) of 16 patients could repeatedly and reliably generate appropriate EEG responses to two distinct commands, despite being behaviourally entirely unresponsive (classification accuracy 61-78%). We noted no significant relation between patients' clinical histories (age, time since injury, cause, and behavioural score) and their ability to follow commands. When separated according to cause, two (20%) of the five traumatic and one (9%) of the 11 non-traumatic patients were able to successfully complete this task. Interpretation Despite rigorous clinical assessment, many patients in the vegetative state are misdiagnosed. The EEG method that we developed is cheap, portable, widely available, and objective. It could allow the widespread use of this bedside technique for the rediagnosis of patients who behaviourally seem to be entirely vegetative, but who might have residual cognitive function and conscious awareness.

We discuss the problems of evidence-based neurorehabilitation in disorders of consciousness, and recent functional neuroimaging data obtained in the vegetative state and minimally conscious state. Published data are insufficient to make recommendations for or against any of the neurorehabilitative treatments in vegetative state and minimally conscious state patients. Electrophysiological and functional imaging studies have been shown to be useful in measuring residual brain function in noncommunicative brain-damaged patients. Despite the fact that such studies could in principle allow an objective quantification of the putative cerebral effect of rehabilitative treatment in the vegetative state and minimally conscious state, they have so far not been used in this context. Summary Without controlled studies and careful patient selection criteria it will not be possible to evaluate the potential of therapeutic interventions in disorders of consciousness. There also is a need to elucidate the neurophysiological effects of such treatments. Integration of multimodal neuroimaging techniques should eventually improve our ability to disentangle differences in outcome on the basis of underlying mechanisms and better guide our therapeutic options in the challenging patient populations encountered following severe acute brain damage.

of consciousness EEG evoked potentials event-related potentials vegetative state minimally conscious state coma h i g h l i g h t s We provide an overview of EEG-based techniques in the prognostic and diagnostic assessment of DoC. We highlight bridging principles between conventional and investigational approaches. We share expert opinions and considerations on the technical and conceptual caveats.

This paper proposes an interpretative model of brain rhythms based on the assumption of their interference nature. It is shown that the observed ranges of electroencephalographic (EEG) activity (delta, theta, alpha, beta, gamma) can be considered not as primary frequencies of consciousness generation, but as the result of interactions between processes at different frequency levels.
Within the framework of the model, it is assumed that the recorded EEG signals represent a low-frequency projection of a more complex dynamics formed through superposition and resonant interaction of these levels. It is shown that an approximate quadratic correspondence between the main ranges of brain waves may be observed, indicating a possible hierarchical structure of their interrelations.
The proposed approach does not introduce new measurable quantities and remains interpretative in nature; however, it allows for a new perspective on neurophysiological data and suggests directions for further analysis of coherence and the dynamics of brain rhythms.

A significant proportion of patients who survive traumatic or nontraumatic severe acquired brain injuries experiences disorders of consciousness. The vegetative state and the minimally conscious state may have different prognoses, and while some patients regain awareness, others have negative outcomes and die. The aim of this work is to identify age-related, medical and behavioural risk factors for mortality in those patients. Participants were enrolled from June 2009 to March 2012 in 107 Italian health care institutions. Univariate and multivariate Cox proportional hazard models were adopted to screen and test candidate risk factors. The study enrolled 600 subjects in vegetative and minimally conscious states for an overall mortality rate of 180.1 per 1,000 personyears. The following traits were associated with a significantly lower chance of survival: age at the acute event higher than 51 years, disease duration less than 1 year, post-anoxic aetiology, absence of visual fixation, and the presence of endocrine, nutritional, and metabolic diseases, and immunity disorders. Clinical history, behavioural assessment, and age-related factors provide important prognostic information on negative outcomes that helps clinicians and researchers to predict patients who are at higher risk of mortality. This knowledge has important clinical, managerial, and ethical implications.

Contributors VC drafted the first version of the manuscript. VC, SHA, THP, KBL, IP, LPK, HRS, KWA, KHM, KM and IA edited and approved the last version of the manuscript. HRS, IP and LPK designed the first version of the protocol, while VC, THP, KM and KHM worked on add-ons to the original design. VC, THP, KM, KHM and KWA wrote the data analysis section of the manuscript. SHA, LPK, IP, CPH and KBL are responsible for the clinical sections of the manuscript.

Contributors VC drafted the first version of the manuscript. VC, SHA, THP, KBL, IP, LPK, HRS, KWA, KHM, KM and IA edited and approved the last version of the manuscript. HRS, IP and LPK designed the first version of the protocol, while VC, THP, KM and KHM worked on add-ons to the original design. VC, THP, KM, KHM and KWA wrote the data analysis section of the manuscript. SHA, LPK, IP, CPH and KBL are responsible for the clinical sections of the manuscript.

Introduction Traumatic brain injury (TBI) is considered one of the most pervasive causes of disability in people under the age of 45. TBI often results in disorders of consciousness, and clinical assessment of the state of consciousness in these patients is challenging due to the lack of behavioural responsiveness. Functional neuroimaging offers a means to assess these patients without the need for behavioural signs, indicating that brain connectivity plays a major role in consciousness emergence and maintenance. However, little is known regarding how changes in connectivity during recovery from TBI accompany changes in the level of consciousness. Here, we aim to combine cutting-edge neuroimaging techniques to follow changes in brain connectivity in patients recovering from severe TBI. Methods and analysis A multimodal, longitudinal assessment of 30 patients in the subacute stage after severe TBI will be made comprising an MRI session combined with electroencephalography (EEG), a po...

Disorders of consciousness are impaired states of consciousness caused by severe brain injuries. Previous resting-state functional magnetic resonance imaging studies have reported abnormal brain network properties at different topological scales in patients with disorders of consciousness by using graph theoretical analysis. However, it is still unclear how inter-regional directed propagation activities affect the topological organization of functional brain networks in patients with disorders of consciousness. To reveal the altered topological organization in patients with disorders of consciousness, we constructed whole-brain directed functional networks by combining functional connectivity analysis and time delay estimation. Then we performed graph theoretical analysis based on the directed functional brain networks at three topological scales, from the nodal scale, the resting-state network scale to the global scale. Finally, the canonical correlation analysis was used to determine the correlations between altered topological properties and clinical scores in patients with disorders of consciousness. At the nodal scale, we observed decreased in-degree and increased outdegree in the precuneus in patients with disorders of consciousness. At the resting-state network scale, the patients with disorders of consciousness showed reorganized motif patterns within the default mode network and between the default mode network and other resting-state networks. At the global scale, we found a lower global clustering coefficient in the patients with disorders of consciousness than in the controls. The results of the canonical correlation analysis showed that the abnormal degree and the disrupted motif were significantly correlated with the clinical scores of the patients with disorders of consciousness. Our findings showed that consciousness impairment can be revealed by abnormal directed connection patterns at multiple topological scales in the whole brain, and the disrupted directed connection patterns may serve as clinical biomarkers to assess the dysfunction of patients with disorders of consciousness.

Existing evidence suggests that the default-mode network (DMN) and fronto-pariatal network (FPN) play an important role in altered states of consciousness. However, the brain mechanisms underlying impaired consciousness and the specific network interactions involved are not well understood. We studied the topological properties of brain functional networks using resting-state functional MRI data acquired from 18 patients (11 vegetative state/unresponsive wakefulness syndrome, VS/UWS, and 7 minimally conscious state, MCS) and compared these properties with those of healthy controls. We identified that the topological properties in DMN and FPN are anti-correlated which comes, in part, from the contribution of interactions between dorsolateral prefrontal cortex of the FPN and precuneus of the DMN. Notably, altered nodal connectivity strength was distance-dependent, with most disruptions appearing in long-distance connections within the FPN but in short-distance connections within the DMN. A multivariate pattern-classification analysis revealed that combination of topological patterns between the FPN and DMN could predict conscious state more effectively than connectivity within either network. Taken together, our results imply distinct interactions between the FPN and DMN, which may mediate conscious state. Previous neuroimaging studies have shown that a core set of brain regions within the fronto-parietal network (FPN) and the default mode network (DMN) is centrally involved in conscious processes 1,2 . Functional connectivity analyses have demonstrated internetwork coupling between networks is necessary to support conscious cognitive processes . How functional networks operate and interact with each other in pathological conditions characterized by impaired consciousness is not well understood. Unlike traditional task-evoked paradigms, functional magnetic resonance imaging in the resting state (R-fMRI) is particularly suitable for studying the brain functions of individuals with disorders of consciousness (DOC). Multiple R-fMRI studies demonstrated that nodal topology is disrupted in impaired consciousness . Specifically, whole-brain network efficiency, measured by the shortest path length and modularity, is altered in different brain regions depending on conscious state . For instance, Crone et al. found decreased local efficiency in several brain regions (e.g., medial parietal, frontal, thalamic) when comparing minimally conscious and unconscious patients 6 . Achard et al. examined functional networks in comatose patients shortly after brain injury and demonstrated extensive reorganization of central hubs, including precuneus of the DMN 5 . These studies, however, found no difference in global network topology between comatose patients and controls 5 or between patients in a minimally conscious state (MCS) and vegetative/unresponsive wakeful state (VS/UWS) 6 . Another

Over the last 20 years, studies have provided greater insight into disorders of consciousness (DOC), also known as altered state of consciousness. Increased brain residual functions have been identified in patients with DOC due to the successful application of novel next-generation imaging technologies. Many unconscious patients have now been confirmed to retain considerable cognitive functions. It is hoped that greater insight regarding the psychological state of patients may be achieved through the use of functional magnetic resonance imaging and brain-computer interfaces. However, issues surrounding the research and treatment of DOC remain problematic. These include differing opinions on the definition of consciousness, difficulties in diagnosis, assessment, prognosis and/or treatment, and newly emerging ethical, legal and social issues. To overcome these, appropriate care must be offered to patients with DOC by clinicians and families, as DOC patients may now be considered to live in more than just a vegetative state. The present article reviews the controversy surrounding the definition of consciousness and the reliability of novel technologies, prognostic prediction, communication with DOC patients and treatment methods. The ethical and social issues surrounding the treatment of DOC and future perspectives are also considered.

Deep brain stmulaton (DBS) has been proposed to enable consciousness recovery. We studied clinical effects of bilateral pallido-thalamic low frequency stmulaton intended to overdrive neuronal actvity. Five patents were included. Primary outcome was the analysis of scores of the Coma Recovery Scale Revised (CRS-R; 0-23). Statstcal analyses used random-effects models accountng between and within patent variability due to repeated measurements. We observed statstcally signifcant improvement of CRS-R during DBS-ON versus baseline (P1, P3) and CO-On versus baseline (P3). For the 5 patents auditory, visual, motor, oromotor-verbal, communicaton subscores of CRS-R were signifcantly improved.

Objective: The efficacy of deep brain stimulation in disorders of consciousness remains inconclusive. We investigated bilateral 30-Hz low-frequency stimulation designed to overdrive neuronal activity by dual pallido-thalamic targeting, using the Coma Recovery Scale Revised (CRS-R) to assess conscious behavior. Methods: We conducted a prospective, single center, observational 11-month pilot study comprising four phases: baseline (2 months); surgery and titration (1 month); blind, random, crossover, 1.5-month ON and OFF periods; and unblinded, 5-month stimulation ON. Five adult patients were included: one unresponsive-wakefulness-syndrome male (traumatic brain injury); and four patients in a minimally conscious state, one male (traumatic brain injury) and three females (two hemorrhagic strokes and one traumatic brain injury). Primary outcome measures focused on CRS-R scores. Secondary outcome measures focused notably on baseline brain metabolism and variation in activity (stimulation ONbaseline) using normalized fluorodeoxyglucose positron emission tomography maps. Statistical analysis used random-effect models. Results: The two male patients (one minimally conscious and one unresponsive wakefulness syndrome) showed improved mean CRS-R scores (stimulation ON vs. baseline), in auditory, visual and oromotor/verbal subscores, and visual subscores respectively. The metabolism of the medial cortices (low at baseline in all five patients) increased specifically in the two responders. Interpretation: Our findings show there were robust but limited individual clinical benefits, mainly in visual and auditory processes. Overall modifications seem linked to the modulation of thalamo-cortico-basal and tegmental loops activating default mode network cortices. Specifically, in the two responders there was an increase in medial cortex activity related to internal awareness.

Musical perception does not end when external sound stops. Many individuals, especially trained musicians, report experiencing melodies internally during rest, meditation, or the transition into sleep. Cognitive neuroscience describes this phenomenon as Involuntary Musical Imagery, in which fragments of music replay spontaneously in the mind without deliberate intention. This article explores the neurological basis of this experience and examines how rhythmic repetition in music may align with natural brainwave frequencies. Using the Carnatic raga Nalinakanthi as an illustrative example, the discussion integrates concepts from music theory, neuroscience, and auditory cognition to demonstrate how melodic structures can become deeply embedded in neural memory and reappear during transitional states of consciousness such as Hypnagogia.

Human dreams represent the brain's highest-bandwidth generative process unconstrained by sensory input, social filtering, or logical consistency. During REM sleep, neural activity encodes creative recombination, emotional processing, and abstract problem-solving in a form that is beginning to be experimentally decodable. This paper proposes a formal information-theoretic framework for dream neural decoding: we derive channel capacity bounds for the fMRI-to-content reconstruction pipeline, establish theoretical limits on dream sequence fidelity, and specify the architecture of a generative model trained on reconstructed dream data which we call DreamML. We connect this framework to the emerging literature on neural decoding during sleep (Kamitani, Gallant, Dehaene), to the author's prior work on Shannon channel characterization of physical systems, and to the open question of whether subconscious generative processes contain learnable structure that waking-state data does not. We identify three testable predictions and four open questions at the intersection of neuroscience, information theory, and machine learning.

BackgroundIn intensive care unit (ICU) patients with coma and other disorders of consciousness (DoC), outcome prediction is key to decision-making regarding prognostication, neurorehabilitation, and management of family expectations. Current prediction algorithms are largely based on chronic DoC, while multimodal data from acute DoC are scarce. Therefore, CONNECT-ME (Consciousness in neurocritical care cohort study using EEG and fMRI,NCT02644265) investigates ICU-patients with acute DoC due to traumatic and non-traumatic brain injuries, utilizing EEG (resting-state and passive paradigms), fMRI (resting-state) and systematic clinical examinations.MethodsWe previously presented results for a subset of patients (n=87) concerning prediction of consciousness levels at ICU discharge. Now, we report 3- and 12-month outcomes in an extended cohort (n=123). Favourable outcome was defined as modified Rankin Scale ≤3, Cerebral Performance Category ≤2, and Glasgow Outcome Scale-Extended ≥4. EEG-...

Article presents the materials of empirical research of life sense orientations, self-relation and level of claims of schizophrenic patients and patients with acute and transient psychotic disorders, who have committed socially hazardous actions and to whom forced measures of medical character are temporarily applied. Changes in the self- consciousness of patients with schizophrenia in dynamics were examined: in com­paring the results obtained at first and fourth stages of patients' stay in mental hospital with strict supervision (the first stage – adaptation and diagnostics, the fourth stage – the consolidation of treatment results and preparation of patient to be discharged). Research was done by D. Leontiev’s test of life sense orientations (LSO), by S. Pantileyev – V. Sto­lin’s techniques and by Shwarzlander’s “Motor test”. Statistical processing of the obtained results of differences by indices of life sense orientations, of selfattitude and level of claims between the grou...

Neuronal theories of conscious access tentatively relate conscious perception to the integration and global broadcasting of information across distant cortical and thalamic areas. Experiments contrasting visible and invisible stimuli support this view and suggest that global neuronal communication may be detectable using scalp electroencephalography (EEG). However, whether global information sharing across brain areas also provides a specific signature of conscious state in awake but noncommunicating patients remains an active topic of research. We designed a novel measure termed "weighted symbolic mutual information" (wSMI) and applied it to 181 high-density EEG recordings of awake patients recovering from coma and diagnosed in various states of consciousness. The results demonstrate that this measure of information sharing systematically increases with consciousness state, particularly across distant sites. This effect sharply distinguishes patients in vegetative state (...

Determining the state of consciousness in patients with disorders of consciousness is a challenging practical and theoretical problem. Recent findings suggest that multiple markers of brain activity extracted from the EEG may index the state of consciousness in the human brain. Furthermore, machine learning has been found to optimize their capacity to discriminate different states of consciousness in clinical practice. However, it is unknown how dependable these EEG markers are in the face of signal variability because of different EEG configurations, EEG protocols and subpopulations from different centres encountered in practice. In this study we analysed 327 recordings of patients with disorders of consciousness (148 unresponsive wakefulness syndrome and 179 minimally conscious state) and 66 healthy controls obtained in two independent research centres (Paris Pitié-Salpêtrière and Liège). We first show that a non-parametric classifier based on ensembles of decision trees provides ...

Severe brain injuries can lead to long-lasting disorders of consciousness (DoC) such as vegetative state/unresponsive wakefulness syndrome (VS/UWS) or minimally conscious state (MCS). While behavioral assessment remains the gold standard to determine conscious state, EEG has proven to be a promising complementary tool to monitor the effect of new therapeutics. Encouraging results have been obtained with invasive electrical stimulation of the brain, and recent studies identified transcranial direct current stimulation (tDCS) as an effective approach in randomized controlled trials. This non-invasive and inexpensive tool may turn out to be the preferred treatment option. However, its mechanisms of action and physiological effects on brain activity remain unclear and debated. Here, we stimulated 60 DoC patients with the anode placed over left-dorsolateral prefrontal cortex in a prospective open-label study. Clinical behavioral assessment improved in twelve patients (20%) and none deter...

Predicting the functional recovery of patients with severe neurological condition due to coronavirus disease 2019 (COVID-19) is a challenging task. Only limited outcome data are available, the pathophysiology is poorly understood, and the time-course of recovery is still largely unknown. Here, we report the case of a patient with COVID-19 associated encephalitis presenting as a prolonged state of unresponsiveness for two months, who finally fully recovered consciousness, functional communication, and autonomy after immunotherapy. In a multimodal approach, a high-density resting state EEG revealed a rich brain activity in spite of a severe clinical presentation. Using our previously validated algorithms, we could predict a possible improvement of consciousness in this patient. This case report illustrates the value of a multimodal approach capitalizing on advanced brain-imaging and bedside electrophysiology techniques to improve prognosis accuracy in this complex and new aetiology.

Despite advances in resting state functional magnetic resonance imaging investigations, clinicians remain with the challenge of how to implement this paradigm on an individualized basis. Here, we assessed the clinical relevance of resting state functional magnetic resonance imaging acquisitions in patients with disorders of consciousness by means of a systems-level approach. Three clinical centres collected data from 73 patients in minimally conscious state, vegetative state/unresponsive wakefulness syndrome and coma. The main analysis was performed on the data set coming from one centre (Liège) including 51 patients (26 minimally conscious state, 19 vegetative state/unresponsive wakefulness syndrome, six coma; 15 females; mean age 49 ± 18 years, range 11-87; 16 traumatic, 32 non-traumatic of which 13 anoxic, three mixed; 35 patients assessed >1 month post-insult) for whom the clinical diagnosis with the Coma Recovery Scale-Revised was congruent with positron emission tomography ...

Recovery of consciousness has been associated with connectivity in the frontal cortex and parietal regions modulated by the thalamus. To examine this model and to relate alterations to deficits in cognitive functioning and conscious processing, we investigated topological network properties in patients with chronic disorders of consciousness recovered from coma. Resting state fMRI data of 34 patients with unresponsive wakefulness syndrome and 25 in minimally conscious state were compared to 28 healthy controls. We investigated global and local network characteristics. Additionally, behavioral measures were correlated with the local metrics of 28 regions within the fronto-parietal network and the thalamus. In chronic disorders of consciousness, modularity at the global level was reduced suggesting a disturbance in the optimal balance between segregation and integration. Moreover, network properties were altered in several regions which are associated with conscious processing (particularly, in medial parietal, and frontal regions, as well as in the thalamus). Between minimally conscious and unconscious patients the local efficiency of medial parietal regions differed. Alterations in the thalamus were particularly evident in non-conscious patients. Most of the regions affected in patients with impaired consciousness belong to the so-called 'rich club' of highly interconnected central nodes. Disturbances in their topological characteristics have severe impact on information integration and are reflected in deficits in cognitive functioning probably leading to a total breakdown of consciousness.

Self-related stimuli activate anterior parts of cortical midline regions, which normally show task-induced deactivation. Deactivation in medial posterior and frontal regions is associated with the ability to focus attention on the demands of the task, and therefore, with consciousness. Studies investigating patients with impaired consciousness, that is, patients in minimally conscious state and patients with unresponsive wakefulness syndrome (formerly vegetative state), demonstrate that these patients show responses to self-related content in the anterior cingulate cortex. However, it remains unclear if these responses are an indication for conscious processing of stimuli or are due to automatic processing. To shed further light on this issue, we investigated responses of cortical midline regions to the own and another name in 27 patients with a disorder of consciousness and compared them to task-induced deactivation. While almost all of the control subjects responding to the own name demonstrated higher activation due to the self-related content in anterior midline regions and additional deactivation, none of the responding patients did so. Differences between groups showed a similar pattern of findings. Despite the relation between behavioral responsiveness in patients and activation in response to the own name, the findings of this study do not provide evidence for a direct association of activation in anterior midline regions and conscious processing. The deficits in processing of self-referential content in anterior midline regions may rather be due to general impairments in cognitive processing and not particularly linked to impaired consciousness.

Diagnosis of patients with a disorder of consciousness is very challenging. Previous studies investigating resting state networks demonstrate that 2 main features of the so-called default mode network (DMN), metabolism and functional connectivity, are impaired in patients with a disorder of consciousness. However, task-induced deactivation -a third main feature of the DMN -has not been explored in a group of patients. Deactivation of the DMN is supposed to reflect interruptions of introspective processes. Seventeen patients with unresponsive wakefulness syndrome (UWS, former vegetative state), 8 patients in minimally conscious state (MCS), and 25 healthy controls were investigated with functional magnetic resonance imaging during a passive sentence listening task. Results show that deactivation in medial regions is reduced in MCS and absent in UWS patients compared to healthy controls. Moreover, behavioral scores assessing the level of consciousness correlate with deactivation in patients. On single-subject level, all control subjects but only 2 patients in MCS and 6 with UWS exposed deactivation. Interestingly, all patients who deactivated during speech processing (except for one) showed activation in left frontal regions which are associated with conscious processing. Our results indicate that deactivation of the DMN can be associated with the level of consciousness by selecting those who are able to interrupt ongoing introspective processes. In consequence, deactivation of the DMN may function as a marker of consciousness.

Current research aims at identifying voluntary brain activation in patients who are behaviorally diagnosed as being unconscious, but are able to perform commands by modulating their brain activity patterns. This involves machine learning techniques and feature extraction methods such as applied in brain computer interfaces. In this study, we try to answer the question if features/classification methods which show advantages in healthy participants are also accurate when applied to data of patients with disorders of consciousness. A sample of healthy participants (N = 22), patients in a minimally conscious state (MCS; N = 5), and with unresponsive wakefulness syndrome (UWS; N = 9) was examined with a motor imagery task which involved imagery of moving both hands and an instruction to hold both hands firm. We extracted a set of 20 features from the electroencephalogram and used linear discriminant analysis, k-nearest neighbor classification, and support vector machines (SVM) as classification methods. In healthy participants, the best classification accuracies were seen with coherences (mean = .79; range = .532.94) and power spectra (mean = .69; range = .402.85). The coherence patterns in healthy participants did not match the expectation of central modulated m-rhythm. Instead, coherence involved mainly frontal regions. In healthy participants, the best classification tool was SVM. Five patients had at least one feature-classifier outcome with pv0.05 (none of which were coherence or power spectra), though none remained significant after falsediscovery rate correction for multiple comparisons. The present work suggests the use of coherences in patients with disorders of consciousness because they show high reliability among healthy subjects and patient groups. However, feature extraction and classification is a challenging task in unresponsive patients because there is no ground truth to validate the results.

Most resuscitated cardiac arrest patients are comatose and often die due to severe brain injury. With the uncertainty of which patient will survive or not, it is important for the right prognosis to be given. This would help decide which patient intensive care should be focused on. Machine learning, which is a revolutionary computer program that can work without explicit instructions, could be used to study neurological patterns, and make better prognosis. As part of the Predicting Neurological Recovery from Coma After Cardiac Arrest: The George B. Moody Physionet Challenge 2023, our team, Leicester Fox, focused on the comparison of the effectiveness of shallow and deep learning machine learning models in giving the right prognosis on chances of survival of cardiac arrest comatose patients. Features extracted from the electroencephalography (EEG) of 607 patients are used for this analysis. Three groups of features (18 features) were extracted and use for training. The official result was a challenge score of 51% for the shallow model. Locally, we had an accuracy of 76% and 65% for shallow and deep learning models respectively. In conclusion, when dealing with smaller number of patients and using features for analysis, shallow classifiers would usually give a better result.

Significant advances in the scientific investigation of the neurobiology of consciousness have been slow to be translated into clinical settings, limited by factors of conceptual (e.g., what is consciousness?), methodological (e.g., how to identify reliable indicators of consciousness?), and technical (e.g., how to improve sensitivity and specificity of the technological identification of consciousness?) nature. In the present paper we aim at reducing the gap between research, clinical practice, patients’ and their caregivers’ needs regarding disorders of consciousness. By implementing a multidisciplinary and multidimensional approach, the paper focuses on disorders of consciousness: it starts from the review of some of the most promising measures of consciousness from brain activity (i.e., spectral measures, measures of functional connectivity, complexity-based measures). Next the paper introduces brain responses to illusions as a new indicator of consciousness (i.e., a feature tha...

Predicting the functional recovery of patients with severe neurological condition due to coronavirus disease 2019 (COVID-19) is a challenging task. Only limited outcome data are available, the pathophysiology is poorly understood, and the time-course of recovery is still largely unknown. Here, we report the case of a patient with COVID-19 associated encephalitis presenting as a prolonged state of unresponsiveness for two months, who finally fully recovered consciousness, functional communication, and autonomy after immunotherapy. In a multimodal approach, a high-density resting state EEG revealed a rich brain activity in spite of a severe clinical presentation. Using our previously validated algorithms, we could predict a possible improvement of consciousness in this patient. This case report illustrates the value of a multimodal approach capitalizing on advanced brain-imaging and bedside electrophysiology techniques to improve prognosis accuracy in this complex and new aetiology.