Robust EEG-based cross-site and cross-protocol classification of states of consciousness

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 robust out-of-sample performance on unseen data with a predictive area under the curve (AUC) of ~0.77 that was only marginally affected when using alternative EEG configurations (different numbers and positions of sensors, numbers of epochs, average AUC = 0.750 ± 0.014). In a second step, we observed that classifiers based on multiple as well as single EEG features generalize to recordings obtained from different patient cohorts, EEG protocols and different centres. However, the multivariate model always performed best with a predictive AUC of 0.73 for generalization from Paris 1 to Paris 2 datasets, and an AUC of 0.78 from Paris to Liège datasets. Using simulations, we subsequently demonstrate that multivariate pattern classification has a decisive performance advantage over univariate classification as the stability of EEG features decreases, as different EEG configurations are used for feature-extraction or as noise is added. Moreover, we show that the generalization performance from Paris to Liège remains stable even if up to 20% of the diagnostic labels are randomly flipped. Finally, consistent with recent literature, analysis of the learned decision rules of our classifier suggested that markers related to dynamic fluctuations in theta and alpha frequency bands carried independent information and were most influential. Our findings demonstrate that EEG markers of consciousness can be reliably, economically and automatically identified with machine learning in various clinical and acquisition contexts.

Detection of Brain Activation in Unresponsive Patients with Acute Brain Injury

BACKGROUND

Brain activation in response to spoken motor commands can be detected by electroencephalography (EEG) in clinically unresponsive patients. The prevalence and prognostic importance of a dissociation between commanded motor behavior and brain activation in the first few days after brain injury are not well understood.

METHODS

We studied a prospective, consecutive series of patients in a single intensive care unit who had acute brain injury from a variety of causes and who were unresponsive to spoken commands, including some patients with the ability to localize painful stimuli or to fixate on or track visual stimuli. Machine learning was applied to EEG recordings to detect brain activation in response to commands that patients move their hands. The functional outcome at 12 months was determined with the Glasgow Outcome Scale-Extended (GOS-E; levels range from 1 to 8, with higher levels indicating better outcomes).

RESULTS

A total of 16 of 104 unresponsive patients (15%) had brain activation detected by EEG at a median of 4 days after injury. The condition in 8 of these 16 patients (50%) and in 23 of 88 patients (26%) without brain activation improved such that they were able to follow commands before discharge. At 12 months, 7 of 16 patients (44%) with brain activation and 12 of 84 patients (14%) without brain activation had a GOS-E level of 4 or higher, denoting the ability to function independently for 8 hours (odds ratio, 4.6; 95% confidence interval, 1.2 to 17.1).

CONCLUSIONS

A dissociation between the absence of behavioral responses to motor commands and the evidence of brain activation in response to these commands in EEG recordings was found in 15% of patients in a consecutive series of patients with acute brain injury. (Supported by the Dana Foundation and the James S. McDonnell Foundation.).

Uncovering Consciousness in Unresponsive ICU Patients: Technical, Medical and Ethical Considerations

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2019. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2019. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901.

Wisdom of the caregivers: pooling individual subjective reports to diagnose states of consciousness in brain-injured patients, a monocentric prospective study

OBJECTIVES

The clinical distinction between vegetative state/unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) is a key step to elaborate a prognosis and formulate an appropriate medical plan for any patient suffering from disorders of consciousness (DoC). However, this assessment is often challenging and may require specialised expertise. In this study, we hypothesised that pooling subjective reports of the level of consciousness of a given patient across several nursing staff members can be used to clinically detect MCS.

SETTING AND PARTICIPANTS

Patients referred to consciousness assessment were prospectively screened. MCS (target condition) was defined according to the best Coma Recovery Scale-Revised score (CRS-R) obtained from expert physicians (reference standard). 'DoC-feeling' score was defined as the median of individual subjective reports pooled from multiple staff members during a week of hospitalisation (index test). Individual ratings were collected at the end of each shift using a 100 mm Visual Analogue Scale, blinded from the reference standard. Diagnostic accuracy was evaluated using area under the receiver operating characteristic curve (AUC), sensitivity and specificity metrics.

RESULTS

692 ratings performed by 83 nursing staff members were collected from 47 patients. Twenty patients were diagnosed with UWS and 27 with MCS. DoC-feeling scores obtained by pooling all individual ratings obtained for a given patient were significantly greater in patients with MCS than with UWS (59.2 mm (IQR: 27.3-77.3) vs 7.2 mm (IQR: 2.4-11.4); p<0.001) yielding an AUC of 0.92 (95% CI 0.84 to 0.99).

CONCLUSIONS

DoC-feeling capitalises on the expertise of nursing staff to evaluate patients' consciousness. Together with the CRS-R as well as with brain imaging, DoC-feeling might improve diagnostic and prognostic accuracy of patients with DoC.

Human consciousness is supported by dynamic complex patterns of brain signal coordination

Adopting the framework of brain dynamics as a cornerstone of human consciousness, we determined whether dynamic signal coordination provides specific and generalizable patterns pertaining to conscious and unconscious states after brain damage. A dynamic pattern of coordinated and anticoordinated functional magnetic resonance imaging signals characterized healthy individuals and minimally conscious patients. The brains of unresponsive patients showed primarily a pattern of low interareal phase coherence mainly mediated by structural connectivity, and had smaller chances to transition between patterns. The complex pattern was further corroborated in patients with covert cognition, who could perform neuroimaging mental imagery tasks, validating this pattern's implication in consciousness. Anesthesia increased the probability of the less complex pattern to equal levels, validating its implication in unconsciousness. Our results establish that consciousness rests on the brain's ability to sustain rich brain dynamics and pave the way for determining specific and generalizable fingerprints of conscious and unconscious states.

Mismatch negativity to predict subsequent awakening in deeply sedated critically ill patients

BACKGROUND

Mismatch negativity (MMN) is the neurophysiological correlate of cognitive integration of novel stimuli. Although MMN is a well-established predictor of awakening in non-sedated comatose patients, its prognostic value in deeply sedated critically ill patients remains unknown. The aim of this prospective, observational pilot study was to investigate the prognostic value of MMN for subsequent awakening in deeply sedated critically ill patients.

METHODS

MMN was recorded in 43 deeply sedated critically ill patients on Day 3 of ICU admission using a classical 'odd-ball' paradigm that delivers rare deviant sounds in a train of frequent standard sounds. Individual visual analyses and a group level analysis of recordings were performed. MMN amplitudes were then analysed according to the neurological status (awake vs not awake) at Day 28.

RESULTS

Median (inter-quartile range) Richmond Assessment Sedation Scale (RASS) at the time of recording was -5 (range, from -5 to -4.5). Visual detection of MMN revealed a poor inter-rater agreement [kappa=0.17, 95% confidence interval (0.07-0.26)]. On Day 28, 30 (70%) patients had regained consciousness while 13 (30%) had not. Quantitative group level analysis revealed a significantly greater MMN amplitude for patients who awakened compared with those who had not [mean (standard deviation) = -0.65 (1.4) vs 0.08 (0.17) μV, respectively; P=0.003).

CONCLUSIONS

MMN can be observed in deeply sedated critically ill patients and could help predict subsequent awakening. However, visual analysis alone is unreliable and should be systematically completed with individual level statistics.

Early myoclonus following anoxic brain injury

Background

It is unknown whether postanoxic cortical and subcortical myoclonus are distinct entities with different prognoses.

Methods

In this retrospective cohort study of 604 adult survivors of cardiac arrest over 8.5 years, we identified 111 (18%) patients with myoclonus. Basic demographics and clinical characteristics of myoclonus were collected. EEG reports, and, when available, raw video EEG, were reviewed, and all findings adjudicated by 3 authors blinded to outcomes. Myoclonus was classified as cortical if there was a preceding, time-locked electrographic correlate and otherwise as subcortical. Outcome at discharge was determined using Cerebral Performance Category.

Results

Patients with myoclonus had longer arrests with less favorable characteristics compared to patients without myoclonus. Cortical myoclonus occurred twice as often as subcortical myoclonus (59% vs 23%, respectively). Clinical characteristics during hospitalization did not distinguish the two. Rates of electrographic seizures were higher in patients with cortical myoclonus (43%, vs 8% with subcortical). Survival to discharge was worse for patients with myoclonus compared to those without (26% vs 39%, respectively), but did not differ between subcortical and cortical myoclonus (24% and 26%, respectively). Patients with cortical myoclonus were more likely to be discharged in a comatose state than those with subcortical myoclonus (82% vs 33%, respectively). Among survivors, good functional outcome at discharge was equally possible between those with cortical and subcortical myoclonus (12% and 16%, respectively).

Conclusions

Cortical and subcortical myoclonus are seen in every sixth patient with cardiac arrest and cannot be distinguished using clinical criteria. Either condition may have good functional outcomes.

Survival and consciousness recovery are better in the minimally conscious state than in the vegetative state

BACKGROUND

The prognosis value of early clinical diagnosis of consciousness impairment is documented by an extremely limited number of studies, whereas it may convey important information to guide medical decisions.

OBJECTIVE

We aimed at determining if patients diagnosed at an early stage (<90 days after brain injury) as being in the minimally conscious state (MCS) have a better prognosis than patients in the vegetative state/Unresponsive Wakefulness syndrome (VS/UWS), independent of care limitations or withdrawal decisions.

METHODS

Patients hospitalized in ICUs of the Pitié-Salpêtrière Hospital (Paris, France) from November 2008 to January 2011 were included and evaluated behaviourally with standardized assessment and with the Coma Recovery Scale-Revised as being either in the VS/UWS or in the MCS. They were then prospectively followed until 1July 2011 to evaluate their outcome with the GOSE. We compared survival function and outcomes of these two groups.

RESULTS

Both survival function and outcomes, including consciousness recovery, were significantly better in the MCS group. This difference of outcome still holds when considering only patients still alive at the end of the study.

CONCLUSIONS

Early accurate clinical diagnosis of VS/UWS or MCS conveys a strong prognostic value of survival and of consciousness recovery.

Brain-heart interactions reveal consciousness in noncommunicating patients

OBJECTIVE

We here aimed at characterizing heart-brain interactions in patients with disorders of consciousness. We tested how this information impacts data-driven classification between unresponsive and minimally conscious patients.

METHODS

A cohort of 127 patients in vegetative state/unresponsive wakefulness syndrome (VS/UWS; n = 70) and minimally conscious state (MCS; n = 57) were presented with the local-global auditory oddball paradigm, which distinguishes 2 levels of processing: short-term deviation of local auditory regularities and global long-term rule violations. In addition to previously validated markers of consciousness extracted from electroencephalograms (EEG), we computed autonomic cardiac markers, such as heart rate (HR) and HR variability (HRV), and cardiac cycle phase shifts triggered by the processing of the auditory stimuli.

RESULTS

HR and HRV were similar in patients across groups. The cardiac cycle was not sensitive to the processing of local regularities in either the VS/UWS or MCS patients. In contrast, global regularities induced a phase shift of the cardiac cycle exclusively in the MCS group. The interval between the auditory stimulation and the following R peak was significantly shortened in MCS when the auditory rule was violated. When the information for the cardiac cycle modulations and other consciousness-related EEG markers were combined, single patient classification performance was enhanced compared to classification with solely EEG markers.

INTERPRETATION

Our work shows a link between residual cognitive processing and the modulation of autonomic somatic markers. These results open a new window to evaluate patients with disorders of consciousness via the embodied paradigm, according to which body-brain functions contribute to a holistic approach to conscious processing. Ann Neurol 2017;82:578-591.

Encephalitis in a traveller with typhoid fever: efficacy of corticosteroids

Typhoid fever is a bacterial infection caused by Salmonella typhi or S. paratyphi, recognized as a classical cause of fever in returning travellers. However, neuropsychiatric presentations are rarely reported in travellers diagnosed in western countries, whereas they are more commonly described in patients treated in endemic areas. We describe such a case and discuss the pathophysiologic mechanisms of this complication.

Probing consciousness in a sensory-disconnected paralyzed patient

BACKGROUND

Diagnosis of consciousness can be very challenging in some clinical situations such as severe sensory-motor impairments.

CASE STUDY

We report the case study of a patient who presented a total "locked-in syndrome" associated with and a multi-sensory deafferentation (visual, auditory and tactile modalities) following a protuberantial infarction.

RESULT

In spite of this severe and extreme disconnection from the external world, we could detect reliable evidence of consciousness using a multivariate analysis of his high-density resting state electroencephalogram. This EEG-based diagnosis was eventually confirmed by the clinical evolution of the patient.

CONCLUSION

This approach illustrates the potential importance of functional brain-imaging data to improve diagnosis of consciousness and of cognitive abilities in critical situations in which the behavioral channel is compromised such as deafferented locked-in syndrome.

Early impairment of intracranial conduction time predicts mortality in deeply sedated critically ill patients: a prospective observational pilot study

Background

Somatosensory (SSEP) and brainstem auditory (BAEP) evoked potentials are neurophysiological tools which, respectively, explore the intracranial conduction time (ICCT) and the intrapontine conduction time (IPCT). The prognostic values of prolonged cerebral conduction times in deeply sedated patients have never been assessed. Sedated patients are at risk of developing new neurological complications, undetected. In this prospective observational bi-center pilot study, we investigated whether early impairment of SSEP’s ICCT and/or BAEP’s IPCT could predict in-ICU mortality or altered mental status (AMS), in deeply sedated critically ill patients.

Methods

SSEP by stimulation of the median nerve and BAEP were assessed in critically ill patients receiving deep sedation on day 3 following ICU admission. Deep sedation was defined by a Richmond Assessment sedation Scale (RASS) <−3. Mean left- and right-side ICCT and IPCT were measured for each patient. Primary and secondary outcomes were, respectively, in-ICU mortality and AMS defined as the occurrence of delirium and/or delayed awakening after discontinuation of sedation.

Results

Eighty-six patients were studied of which 49 (57%) were non-brain-injured and 37 (43%) were brain-injured. Impaired ICCT was a predictor of in-ICU mortality after adjustment on the global Sequential Organ Failure Assessment score (SOFA) [OR (95% CI) = 2.69 (1.05–6.85); p = 0.039] and on the non-neurological SOFA components [2.67 (1.05–6.81); p = 0.040]. IPCT was more frequently delayed in the subgroup of patients who developed post-sedation AMS (24%) compared those without AMS (0%). However, this difference did not reach statistical significance (p = 0.053). Impairment rates of ICCT and IPCT were not found to be significantly different between non-brain- and brain-injured subgroups of patients.

Conclusion

In critically ill patients receiving deep sedation, early ICCT impairment was associated with mortality. Somatosensory and brainstem auditory evoked potentials may be useful early warning indicators of brain dysfunction as well as prognostic markers in deeply sedated critically ill patients.

Brainstem response patterns in deeply-sedated critically-ill patients predict 28-day mortality

Background and purpose

Deep sedation is associated with acute brain dysfunction and increased mortality. We had previously shown that early-assessed brainstem reflexes may predict outcome in deeply sedated patients. The primary objective was to determine whether patterns of brainstem reflexes might predict mortality in deeply sedated patients. The secondary objective was to generate a score predicting mortality in these patients.

Methods

Observational prospective multicenter cohort study of 148 non-brain injured deeply sedated patients, defined by a Richmond Assessment sedation Scale (RASS) <-3. Brainstem reflexes and Glasgow Coma Scale were assessed within 24 hours of sedation and categorized using latent class analysis. The Full Outline Of Unresponsiveness score (FOUR) was also assessed. Primary outcome measure was 28-day mortality. A “Brainstem Responses Assessment Sedation Score” (BRASS) was generated.

Results

Two distinct sub-phenotypes referred as homogeneous and heterogeneous brainstem reactivity were identified (accounting for respectively 54.6% and 45.4% of patients). Homogeneous brainstem reactivity was characterized by preserved reactivity to nociceptive stimuli and a partial and topographically homogenous depression of brainstem reflexes. Heterogeneous brainstem reactivity was characterized by a loss of reactivity to nociceptive stimuli associated with heterogeneous brainstem reflexes depression. Heterogeneous sub-phenotype was a predictor of increased risk of 28-day mortality after adjustment to Simplified Acute Physiology Score-II (SAPS-II) and RASS (Odds Ratio [95% confidence interval] = 6.44 [2.63–15.8]; p<0.0001) or Sequential Organ Failure Assessment (SOFA) and RASS (OR [95%CI] = 5.02 [2.01–12.5]; p = 0.0005). The BRASS (and marginally the FOUR) predicted 28-day mortality (c-index [95%CI] = 0.69 [0.54–0.84] and 0.65 [0.49–0.80] respectively).

Conclusion

In this prospective cohort study, around half of all deeply sedated critically ill patients displayed an early particular neurological sub-phenotype predicting 28-day mortality, which may reflect a dysfunction of the brainstem.

Multidimensional cognitive evaluation of patients with disorders of consciousness using EEG: A proof of concept study

The use of cognitive evoked potentials in EEG is now part of the routine evaluation of non-communicating patients with disorders of consciousness in several specialized medical centers around the world. They typically focus on one or two cognitive markers, such as the mismatch negativity or the P3 to global auditory regularity. However it has become clear that none of these markers in isolation is at the same time sufficiently specific and sufficiently sensitive to be taken as the unique gold standard for diagnosing consciousness. A good way forward would be to combine several cognitive markers within the same test to improve evaluation. Furthermore, given the diversity of lesions leading to disorders of consciousness, it is important not only to probe whether a patient is conscious or not, but also to establish a more general and nuanced profile of the residual cognitive capacities of each patient using a combination of markers.

In the present study we built a unique EEG protocol that probed 8 dimensions of cognitive processing in a single 1.5 h session. This protocol probed variants of classical markers together with new markers of spatial attention, which has not yet been studied in these patients. The eight dimensions were: (1) own name recognition, (2) temporal attention, (3) spatial attention, (4) detection of spatial incongruence (5) motor planning, and (6,7,8) modulations of these effects by the global context, reflecting higher-level functions. This protocol was tested in 15 healthy control subjects and in 17 patients with various etiologies, among which 13 could be included in the analysis. The results in the control group allowed a validation and a specific description of the cognitive levels probed by each marker. At the single-subject level, this combined protocol allowed assessing the presence of both classical and newly introduced markers for each patient and control, and revealed that the combination of several markers increased diagnostic sensitivity. The presence of a high-level effect in any of the three tested domains distinguished between minimally conscious and vegetative patients, while the presence of low-level effects was similar in both groups. In summary, this study constitutes a validated proof of concept in favor of probing multiple cognitive dimensions to improve the evaluation of non-communicating patients. At a more conceptual level, this EEG tool can help achieve a better understanding of disorders of consciousness by exploring consciousness in its multiple cognitive facets.

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This new EEG protocol probes 8 cognitive functions within a single 1.5 h session.

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It allows a complete neuropsychological evaluation only based on brain activity.

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It increases sensitivity in detecting both low-level and high-level functions in patients.

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Only the high-level functions distinguish minimally conscious from vegetative states.

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Multidimensional EEG testing is feasible in patients and can improve evaluation.

Unconscious semantic processing of polysemous words is not automatic

Semantic processing of visually presented words can be identified both on behavioral and neurophysiological evidence. One of the major discoveries of the last decades is the demonstration that these signatures of semantic processing, initially observed for consciously perceived words, can also be detected for masked words inaccessible to conscious reports. In this context, the distinction between conscious and unconscious verbal semantic processing constitutes a challenging scientific issue. A prominent view considered that while conscious representations are subject to executive control, unconscious ones would operate automatically in a modular way, independent from control and top-down influences. Recent findings challenged this view by revealing that endogenous attention and task-setting can have a strong influence on unconscious processing. However, one of the major arguments supporting the automaticity of unconscious semantic processing still stands, stemming from a seminal observation reported by Marcel in 1980 about polysemous words. In the present study we reexamined this evidence. We present a combination of behavioral and event-related-potentials (ERPs) results that refute this view by showing that the current conscious semantic context has a major and similar influence on the semantic processing of both visible and masked polysemous words. In a classical lexical decision task, a polysemous word was preceded by a word which defined the current semantic context. Crucially, this context was associated with only one of the two meanings of the polysemous word, and was followed by a word/pseudo-word target. Behavioral and electrophysiological evidence of semantic priming of target words by masked polysemous words was strongly dependent on the conscious context. Moreover, we describe a new type of influence related to the response-code used to answer for target words in the lexical decision task: unconscious semantic priming constrained by the conscious context was present both in behavior and ERPs exclusively when right-handed subjects were instructed to respond to words with their right hand. The strong and respective influences of conscious context and response-code on semantic processing of masked polysemous words demonstrate that unconscious verbal semantic representations are not automatic.

Large scale screening of neural signatures of consciousness in patients in a vegetative or minimally conscious state

In recent years, numerous electrophysiological signatures of consciousness have been proposed. Here, we perform a systematic analysis of these electroencephalography markers by quantifying their efficiency in differentiating patients in a vegetative state from those in a minimally conscious or conscious state. Capitalizing on a review of previous experiments and current theories, we identify a series of measures that can be organized into four dimensions: (i) event-related potentials versus ongoing electroencephalography activity; (ii) local dynamics versus inter-electrode information exchange; (iii) spectral patterns versus information complexity; and (iv) average versus fluctuations over the recording session. We analysed a large set of 181 high-density electroencephalography recordings acquired in a 30 minutes protocol. We show that low-frequency power, electroencephalography complexity, and information exchange constitute the most reliable signatures of the conscious state. When combined, these measures synergize to allow an automatic classification of patients' state of consciousness.

Information sharing in the brain indexes consciousness in noncommunicative patients

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 (VS), minimally conscious state (MCS), and conscious state (CS) and is observed regardless of etiology and delay since insult. The present findings support distributed theories of conscious processing and open up the possibility of an automatic detection of conscious states, which may be particularly important for the diagnosis of awake but noncommunicating patients.

Single-trial decoding of auditory novelty responses facilitates the detection of residual consciousness

Detecting residual consciousness in unresponsive patients is a major clinical concern and a challenge for theoretical neuroscience. To tackle this issue, we recently designed a paradigm that dissociates two electro-encephalographic (EEG) responses to auditory novelty. Whereas a local change in pitch automatically elicits a mismatch negativity (MMN), a change in global sound sequence leads to a late P300b response. The latter component is thought to be present only when subjects consciously perceive the global novelty. Unfortunately, it can be difficult to detect because individual variability is high, especially in clinical recordings. Here, we show that multivariate pattern classifiers can extract subject-specific EEG patterns and predict single-trial local or global novelty responses. We first validate our method with 38 high-density EEG, MEG and intracranial EEG recordings. We empirically demonstrate that our approach circumvents the issues associated with multiple comparisons and individual variability while improving the statistics. Moreover, we confirm in control subjects that local responses are robust to distraction whereas global responses depend on attention. We then investigate 104 vegetative state (VS), minimally conscious state (MCS) and conscious state (CS) patients recorded with high-density EEG. For the local response, the proportion of significant decoding scores (M=60%) does not vary with the state of consciousness. By contrast, for the global response, only 14% of the VS patients' EEG recordings presented a significant effect, compared to 31% in MCS patients' and 52% in CS patients'. In conclusion, single-trial multivariate decoding of novelty responses provides valuable information in non-communicating patients and paves the way towards real-time monitoring of the state of consciousness.

Probing consciousness with event-related potentials in the vegetative state

OBJECTIVE

Probing consciousness in noncommunicating patients is a major medical and neuroscientific challenge. While standardized and expert behavioral assessment of patients constitutes a mandatory step, this clinical evaluation stage is often difficult and doubtful, and calls for complementary measures which may overcome its inherent limitations. Several functional brain imaging methods are currently being developed within this perspective, including fMRI and cognitive event-related potentials (ERPs). We recently designed an original rule extraction ERP test that is positive only in subjects who are conscious of the long-term regularity of auditory stimuli.

METHODS

In the present work, we report the results of this test in a population of 22 patients who met clinical criteria for vegetative state.

RESULTS

We identified 2 patients showing this neural signature of consciousness. Interestingly, these 2 patients showed unequivocal clinical signs of consciousness within the 3 to 4 days following ERP recording.

CONCLUSIONS

Taken together, these results strengthen the relevance of bedside neurophysiological tools to improve diagnosis of consciousness in noncommunicating patients.