Frédéric Faugeras

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.

Neural detection of complex sound sequences or of statistical regularities in the absence of consciousness

Sir, We read with interest the article by Tzovara et al. (2015), recently published in Brain . In this study the authors adapted a paradigm we previously designed (Bekinschtein et al. , 2009) to probe the EEG of comatose patients in response to two types of violations of auditory regularities. Unfortunately, several important problems mitigate the reliability of their conclusions. In the local-global paradigm, local auditory irregularities correspond to a change of sound within a trial, whereas global irregularities correspond to a change of sound sequence across trials. The authors showed with a decoding algorithm a significant difference in EEG responses to global violations in 10 of 24 comatose patients. Observing such a global effect in unconscious subjects challenges our previous conclusion that this global effect can only be observed in conscious and attentive subjects (Bekinschtein et al. , 2009; Wacongne et al. , 2012; El Karoui et al. , 2014) and systematically disappears in inattentive subjects (Bekinschtein et al. , 2009; King et al. , 2013), sleeping subjects (Strauss et al. , 2015), and clinically unconscious patients in vegetative state (Faugeras et al. , 2011, 2012). Converging findings from multiple functional brain imaging tools [high-density EEG, magnetoencephalography (MEG), intracranial stereoelectroencephalography (SEEG), functional MRI] demonstrated that the global effect is characterized by a late (>300 ms after violation onset) and sustained brain response (King et al. , 2014) typical of conscious access (Dehaene and Naccache 2001; Dehaene et al. , 2011). In our data, the only two patients in a vegetative state showing a late global effect recovered clinical signs of minimally conscious state within the next …

Reply: Replicability and impact of statistics in the detection of neural responses of consciousness

Sir, We read with interest the letter by Gabriel and colleagues (2016) addressing the major issue of replicability when probing conscious processing in non-communicating patients. This question—as well as the choice of the optimal statistical methodology—concerns the whole field of functional brain imaging in cognitive neuroscience (Kriegeskorte et al. , 2009), but its importance obviously culminates in single-subject analyses of non-communicating patients (see for instance the recent debate in Cruse et al. , 2011, 2013; Goldfine et al. , 2012). Gabriel et al. reacted to a recent discussion (Naccache et al. , 2015; Tzovara et al. , 2015 a , b ) following a report by Tzovara et al. (2015 a ), who adapted our auditory ‘local-global’ bedside EEG test (Bekinschtein et al. , 2009) to test comatose patients. Briefly, in the local-global paradigm two levels of regularities are manipulated: local auditory irregularities correspond to a change of sound within a trial, whereas global irregularities correspond to a change of sound sequence across trials. When analysing data according to the local irregularities, one can typically extract a mismatch negativity response observable even in unconscious states. In sharp contrast, when analysing event-related potentials (ERPs) to violations of global irregularities, we previously showed that a late global effect was present only in conscious or minimally conscious patients (Bekinschtein et al. , 2009; Faugeras et al. , 2011, 2012). Two problems emerged from the study of Tzovara et al. (2015 a ), first, this ERP global effect was found positive in the vast majority of conscious controls we tested at two distinct sites using high-density EEG: 18/18 (100%) in Paris, France (with 256 electrodes), and 7 to 10/10 (70 to 100%) with the monaural and binaural versions of the task, respectively in Cambridge, UK …

Dissociating temporal attention from spatial attention and motor response preparation: A high-density EEG study.

Engagement of various forms of attention and response preparation determines behavioral performance during stimulus-response tasks. Many studies explored the respective properties and neural signatures of each of these processes. However, very few experiments were conceived to explore their interaction. In the present work we used an auditory target detection task during which both temporal attention on the one side, and spatial attention and motor response preparation on the other side could be explicitly cued. Both cueing effects speeded response times, and showed strictly additive effects. Target ERP analysis revealed modulations of N1 and P3 responses by these two forms of cueing. Cue-target interval analysis revealed two main effects paralleling behavior. First, a typical contingent negative variation (CNV), induced by the cue and resolved immediately after target onset, was found larger for temporal attention cueing than for spatial and motor response cueing. Second, a posterior and late cue-P3 complex showed the reverse profile. Analyses of lateralized readiness potentials (LRP) revealed both patterns of motor response inhibition and activation. Taken together these results help to clarify and disentangle the respective effects of temporal attention on the one hand, and of the combination of spatial attention and motor response preparation on the other hand on brain activity and behavior.

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

ABSTRACT 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.

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.

\"DoC-feeling\": a new behavioural tool to help diagnose the Minimally Conscious State.

Background 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 specialized expertise. In this study, we hypothesized that pooling subjective reports of the level of consciousness of a given patient across several nursing staff members can help improving clinical diagnosis of MCS. Methods Patients referred for consciousness assessment were prospectively screened. MCS (target condition) was defined according to the best Coma Recovery Scale-Revised (CRS-R) obtained from expert physicians (reference standard). “DoC-feeling” score consisted in the median value of multiple ratings of patient’s behavior observation pooled from multiple staff members during a week of hospitalisation (index test). Individual ratings were collected at the end of each shift using a 100mm visual analog 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 in a UWS and 27 in a MCS. DoC-feeling scores obtained by pooling all individual ratings obtained for a given patient were significantly greater in MCS than in UWS patients (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: 0.84-0.99) and, using a 16.7 mm cut-off value, a sensitivity of 89% (95%CI: 71-98) and a specificity of 85% (95%CI: 62-97) for the diagnostic of MCS. Conclusion DoC-feeling capitalizes on the expertise of nursing staff to evaluate patients’s consciousness. Together with the CRS-R as well as with brain imaging, DoC-feeling might improve diagnostic and prognostic accuracy of DoC patients.

Corrigendum to “Dissociating temporal attention from spatial attention and motor response preparation: A high-density EEG study” [NeuroImage 124 (2016) 947–957]

a INSERM, ICM Research Center, UMRS 975, Paris, France b Institut du Cerveau et de la Moëlle épinière, Paris, France c University Hospital Dupuytren, Limoges, France d University Paris 6, Faculté de Médecine Pitié-Salpêtrière, Paris, France e AP-HP, Groupe hospitalier Pitié-Salpêtrière, Department of Neurology, Paris, France f AP-HP, Groupe hospitalier Pitié-Salpêtrière, Department of Neurophysiology, Paris, France