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See detailConsciousness and communication BCIs in severe brain-injured patients
Annen, Jitka ULiege; Laureys, Steven ULiege; Gosseries, Olivia ULiege

in Handbook Brain-Computer Interfacing: Neural Devices for paralysis in neurological practise and beyond (in press)

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See detailDiagnostic accuracy of a CRS-R modified score in patients with disorders of consciousness.
Annen, Jitka ULiege; Filippini, Maria Maddalena ULiege; Bonin, Estelle ULiege et al

in Brain Injury (2019, March 16)

Introduction The Coma Recovery Scale-Revised (CRS-R) is the gold standard diagnostic tool for assessing patients with disorders of consciousness (DOC) after severe acquired brain injury (Giacino, Kalmar ... [more ▼]

Introduction The Coma Recovery Scale-Revised (CRS-R) is the gold standard diagnostic tool for assessing patients with disorders of consciousness (DOC) after severe acquired brain injury (Giacino, Kalmar and Whyte, 2004; Seel et al., 2010). Differential diagnosis of DOC includes the unresponsive wakefulness syndrome (UWS;(Laureys et al., 2010)), characterized by the recovery of eye-opening but no behavioral evidence of self or environmental awareness, and the minimally conscious state (MCS; (Giacino et al., 2002)) defined by clearly discernible but inconsistent behavioral signs of conscious awareness. The CRS-R assesses reflexes and cognitively mediated behavior in six domains, namely auditory (4 items), visual (5 items), motor (6 items), oromotor (3 items), communication (2 items) and arousal (3 items). Items in every subscale are hierarchically ordered (i.e. reflexive to cognitively-mediated behaviors; higher level behaviors correspond to higher level of neurologic functioning and ability to demonstrate lower-level behaviors or disappearance of pathological behaviors as sign of recovery) and can be used to infer the patient’s level of consciousness (La Porta et al., 2013; Gerrard, Zafonte and Giacino, 2014). Several studies on DOC investigating markers of consciousness, recovery and treatment used the CRS-R total score (i.e. addition of the highest scores reached for each subscale) as regressor in neuroimaging analyses (Bruno et al., 2012; Thibaut et al., 2012; Margetis et al., 2014; Bagnato et al., 2015). However, ignoring the hierarchy of the subscales in the CRS-R total score reduces the sensitivity for the diagnosis of MCS patients (i.e., 100% specificity for UWS but false negative diagnostic error of 22%, with a cut-off CRS-R total score of 10 (Bodien et al., 2016)). In addition, the ordinal nature of the CRS-R total score make it limited to use with parametric statistical tests (e.g., requiring normal distribution). A solution to this problem has been proposed by Sattin and colleagues (2015) who computed a CRS-R modified score (CRS-R MS1), by considering reflexes and cognitively mediated behaviors separately, reliably distinguishing between UWS and MCS patients. These authors also argue that the interpretation of the total CRS-R scores is limited due to “the underlying assumption that if a patient is able to show higher-level behaviors, he/she is also able to show lower-level responses”. Sattin et al. (2015) propose to account for the number of presented responses in every subscale (i.e., every items in a subscale should be assessed and scored). One major drawback to this approach is that according to the CRS-R guidelines, the assessor should start assessing the highest item and move to the next subscale once an item is scored, in line with the hierarchical organization of the scale. This means that, if the CRS-R is performed according to the guidelines (for which the CRS-R has been validated), the CRS-R modified score cannot be calculated. Even if assessing all items might be valid, it is unlikely to be done in many clinical and research settings as it would increase assessment time and fatigue the patient. We here propose to adapt the CRS-R MS1 by considering only the highest score reached on every subscale, respecting the CRS-R guidelines. Methods One-hundred twenty-four patients admitted to the University Hospital of Liège were assessed multiple times with the CRS-R, at least once including the assessment of all items. Patients for whom the CRS-R assessment including all items provided the same diagnosis as the patient’s final diagnosis were selected. The study was approved by the ethics committee of the University Hospital of Liège and the legal guardians of patients gave written informed consent for participation in the study, in accordance with the Declaration of Helsinki. The CRS-R total score and two CRS-R MS were calculated for every patient. The CRS-R MS combines scores for reflexes and cognitive behaviors of every CRS-R subscale which can be used to obtain the CSR-R MS from a transposition matrix. The CRS-R MS1 was calculated as previously described (Sattin et al., 2015), and the CRS-R MS2 only used the highest score in every subscale (i.e., assuming that lower items were successful). Statistics were performed in R (R Core team, 2012). We assessed group differences in age (two sample t-test), time since injury (two sample t-test) and etiology (χ2 test). Receiver Operating Characteristic were calculated to obtain the sensitivity and specificity at several classification thresholds (package pROC (Robin et al., 2011)). We calculated the correlation between the CRSR MS1 and CRSR MS2 using Pearson correlation, and both scores with the CRS-R total score using Spearman correlation. Finally, we used a Kolmogorov-Smirnoff test to evaluate whether CRSR MS1 and CRSR MS2 come from different distributions (i.e., if one approach provides additional information over the other). Results Eighty-five MCS patients (26 females; mean age 40.4 (SD±17.4) years old; 43 traumatic; mean time since injury 2.7 (SD±4.0) years) and 39 UWS patients (14 females; mean age 50.6 (SD±16.5) years old; 29 traumatic; mean time since injury 1.2 (SD±1.8) years) were included in the study. MCS patients were older (t(77.6)-3.15, p<0.002 95%CI[-16.7, -3.7]), were in a more chronic stage (t(121.9)=2.9, p = 0.005, 95%CI[974,427]), and suffered more often from a traumatic brain injury (χ2=6.8, p = 0.01) than UWS patients. The ROC analysis for both MS showed an AUC of 1 (cut-off:8.315, 100% specificity and sensitivity). The ROC analysis for the CRS-R total score showed an AUC of 0.94 (cut-off:9, sensitivity = 100%, specificity = 67%). A correlation was found between the CRSR total score and both the CRSR MS1 (r = 0.94, p < 0.0001, figure 1A) and CRSR MS2 (r = 0.96, p < 0.0001, figure 1B). The two CRS-R MS correlated (r = 0.96, p = 0.0001, figure 1C). CRSR MS1 and CRSR MS2 were drawn from the same distribution (D(124)= 0.13, p = 0.25). Discussion CRSR MS2 correlated strongly with the CRSR MS1, and perfectly discriminated UWS from MCS patients. As for accurate diagnosis the CRS-R should be repeated (preferably five times (Wannez et al., 2018)) short assessments are preferred, and possibly also reduce effects of fatigue. Second, the CRSR MS2 can be calculated with CRS-R assessments performed according to the CRS-R guidelines, facilitating its use in clinical environments, and in research settings where CRSR MS2 can be used pro- and retrospectively for research protocols. Furthermore, the results indicate that the two modified scores share the same distribution. This suggests that assessing all CRS-R items as proposed previously does not significantly contribute to the stratification of patients. The CRSR MS2 code is available via: Github A remaining limitation of the proposed score is that it does not allow to distinguish MCS minus (i.e. showing language independent signs of awareness, like visual pursuit) from MCS plus (i.e. showing language dependent signs of awareness) patients, or emergence from MCS. However, a clear consensus about the diagnostic criteria is needed before an updated modified score can be provided. In conclusion, the current analyses show that the calculation of the CRS-R modified score using the highest item in every subscale is valid for clinical diagnosis, and provides perspective for its use for research. Figure Figure 1. Correlation between the CRS-R total score and the CRS-R MS1 (1A), CRSR MS2 (1B), and between the two modified CRS-R scores (1C). MCS plus patients are here characterized by command following, intelligible verbalization and/or intentional communication. Acknowledgements This project has received funding from the University and University Hospital of Liege, the Belgian National Funds for Scientific Research (FRS-FNRS), the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 785907 (Human Brain Project SGA2) the Luminous project (EU-H2020-fetopenga686764), the Center-TBI project (FP7-HEALTH- 602150), the Public Utility Foundation ‘Université Européenne du Travail’, “Fondazione Europea di Ricerca Biomedica”, the Bial Foundation, the Mind Science Foundation and the European Commission, the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 778234, European Space Agency (ESA) and the Belgian Federal Science Policy Office (BELSPO) for their support in the framework of the PRODEX Programme. CC is a post-doctoral Marie Sklodowska-Curie fellow (H2020-MSCA-IF-2016-ADOC-752686), and SL is research director at FRS-FNRS. We are highly grateful to the members of the Liège Coma Science Group for their assistance in clinical evaluations, and we thank all the patients and their families and the Neurology department of the University hospital of Liège. [less ▲]

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See detailInternational validation of the Phone Outcome Questionnaire for patients with Disorders Of Consciousness
Wolff, Audrey ULiege; Estraneo, Anna; Noé, Quique et al

Poster (2019, March 15)

Assessing the evolution of severely brain-injured patients with disorders of consciousness (DOC) with current tools like the Glasgow Outcome Scale-Extended (GOS-E) remains a challenge. At the bedside, the ... [more ▼]

Assessing the evolution of severely brain-injured patients with disorders of consciousness (DOC) with current tools like the Glasgow Outcome Scale-Extended (GOS-E) remains a challenge. At the bedside, the most reliable diagnostic tool is currently the Coma Recovery Scale-Revised. The CRS-R distinguishes patients with unresponsive wakefulness syndrome (UWS) from patients in minimally conscious state (MCS) and patients who have emerged from MCS (EMCS). This international multi-centric study aims to validate a phone outcome questionnaire (POQ) based on the CRS-R and compare it to the CRS-R performed at the bedside and to the GOS-E which evaluates the level of disability and assigns patient’s in outcomes categories. The POQ will allow clinicians to probe the evolution of patient’s state of consciousness based on caregivers feedback. This research project is part of the International Brain Injury Association, Disorders of Consciousness-Special Interest Group (DOCSIG) and DOCMA consortium. [less ▲]

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See detailBrain, behavior, and cognitive interplay in disorders of consciousness: A multiple case study
Aubinet, Charlène ULiege; Murphy, Leslie; Bahri, Mohamed Ali ULiege et al

in Frontiers in Neurology (2018), 9(665), 1-10

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See detailTutorial "Single-case evaluation of consciousness: same patient, different modalities": fMRI-based assessment of a single patient
Demertzi, Athina ULiege; Annen, Jitka ULiege; Chatelle, Camille ULiege et al

Conference (2018, June 24)

Tutorial: Patients with disorders of consciousness are by definition unable to communicate. This makes the evaluation of their state of consciousness a major challenge. To date, there are not standardized ... [more ▼]

Tutorial: Patients with disorders of consciousness are by definition unable to communicate. This makes the evaluation of their state of consciousness a major challenge. To date, there are not standardized guidelines as to how a post-comatose patient can be evaluated by means of assisting technologies. With this tutorial, we bring together specialists from three expert centers dealing with intensive evaluation of the state of consciousness in patients sustaining severe brain injuries. Our aim is to illustrate how we can infer a clinical diagnosis by integrating different data from behavioral and brain function as measured with different technological modalities. Specifically, we will discuss the case of a patient for whom behavioral, electrophysiological and neuroimaging data have been acquired with the aim to provide a global diagnosis of the state of consciousness. We will show how each of these evaluations are performed in step-by-step manner. Each presenter will further illustrate the methodological challenges and pragmatic solutions towards the inference of valid conclusions. In order to integrate the results into a global diagnostic category, we wish to engage the audience to participate interactively towards the composition of a final diagnostic report, as we typically do at our clinical sites [less ▲]

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See detailA comparison of the P300 and PET in patients with disorders of consciousness in absence of response to command
Annen, Jitka ULiege; Wolff, Audrey ULiege; Blandiaux, Séverine ULiege et al

in European Journal of Neurology (2018, June), 25(S2),

Detection and interpretation of signs of "covert command following" in patients with disorders of consciousness (DOC) remains a challenge for clinicians. In this study, we used a tactile P3-based BCI in ... [more ▼]

Detection and interpretation of signs of "covert command following" in patients with disorders of consciousness (DOC) remains a challenge for clinicians. In this study, we used a tactile P3-based BCI in 12 patients without behavioral command following, attempting to establish "covert command following." These results were then confronted to cerebral metabolism preservation as measured with glucose PET (FDG-PET). One patient showed "covert command following" (i.e., above-threshold BCI performance) during the active tactile paradigm. This patient also showed a higher cerebral glucose metabolism within the language network (presumably required for command following) when compared with the other patients without "covert command-following" but having a cerebral glucose metabolism indicative of minimally conscious state. Our results suggest that the P3-based BCI might probe "covert command following" in patients without behavioral response to command and therefore could be a valuable addition in the clinical assessment of patients with DOC. [less ▲]

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See detailPCI & Auditory ERPs for the diagnosis of disorders of consciousness: a EEG-based methods comparison study
Blandiaux, Séverine ULiege; Raimondo, Federico ULiege; Wolff, Audrey ULiege et al

in European Journal of Neurology (2018, June), 25(S2),

INTRODUCTION Diagnosing the level of consciousness in patients suffering from severe brain lesions is still a major challenge. EEG-based systems can help discriminate conscious from unconscious patients ... [more ▼]

INTRODUCTION Diagnosing the level of consciousness in patients suffering from severe brain lesions is still a major challenge. EEG-based systems can help discriminate conscious from unconscious patients. This study aims to confront the results from two of the most reliable methods: the Perturbational Complexity Index (PCI) which is based on Transcranial Magnetic Stimulation (TMS-EEG), and a recent machine learning approach using EEG-extracted markers from a standardized oddball auditory stimulation paradigm (EEG-ERP). METHODS Patients presenting either an unresponsive wakefulness syndrome (UWS), a minimally conscious state (MCS) or an emergence of MCS (EMCS) underwent both TMS-EEG and EEG-ERP. We computed PCI value by compressing the spatiotemporal pattern of cortical responses to the perturbation of the cortex with TMS. For EEG-ERP, we extracted 60 markers corresponding to quantification of power spectrum and complexity in individual EEG sensors and information sharing between them. Using machine-learning, we predicted the individual probability of being (minimally) conscious. RESULTS PCI and EEG markers, when considered categorically (i.e. UWS vs MCS), were consistent for all UWS and EMCS patients, whereas the results for MCS patients showed less consistency. Nevertheless, we found a significant correlation between PCI values and the probability of being conscious with the multivariate classifier. CONCLUSION PCI correlated positively with the combination of EEG markers in severely brain-injured patients. These findings imply that EEG signatures of consciousness can be reliably extracted from different contexts and combined into coherent predictive models, encouraging future efforts in large-scale data-driven clinical neuroscience. [less ▲]

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See detailVivid memories from hell: A systematic analysis of distressing near-death experiences accounts
Cassol, Helena ULiege; Martial, Charlotte ULiege; Annen, Jitka ULiege et al

Poster (2018, May 18)

Background: Near-death experiences (NDEs) are associated to positive affects, however, a small proportion is depicted as distressing. Only a few studies have addressed these frightening events, and yet ... [more ▼]

Background: Near-death experiences (NDEs) are associated to positive affects, however, a small proportion is depicted as distressing. Only a few studies have addressed these frightening events, and yet they could trigger long-lasting emotional trauma. Objectives: We aimed at 1) looking into the proportion of distressing NDEs in a sample of NDE narratives; 2) running a categorization of distressing narratives based on Greyson and Bush’s classification: “inverse”, “void” or “hellish” NDEs; and 3) comparing the content of distressing NDEs with “classical” NDEs (which include typical features and are not considered as negative). Methods: NDE experiencers were invited to write down their experience and complete the Memory Characteristics Questionnaire (to assess its phenomenological characteristics) as well as the Greyson NDE scale (to characterize the content of the NDE). Distressing narratives were identified and a text analysis was conducted to classify each narrative into one of the negative subcategories. Content and intensity of distressing and classical NDEs memories were then compared using Mann Whitney U tests based on answers to questionnaires. Results: First, we found that distressing NDEs represent 18% of our sample. Second, the text analysis confirmed Greyson and Bush’s classification and highlighted that our subsample includes 14 inverse (56%), 8 hellish (32%) and 3 void (12%) accounts. Finally, memories of distressing NDEs are considered as detailed as memories of classical NDEs. Apart from positive affects, distressing NDEs contain as much typical features as classical NDEs. Still poorly studied, distressing NDEs deserve careful consideration to ensure their integration into NDE experiencers’ identity. [less ▲]

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See detailRegional brain volumetry and brain function in severely brain-injured patients
Annen, Jitka ULiege; Frasso, Gianluca; Crone, Julia et al

in Annals of Neurology (2018)

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See detailGlobal structural integrity and effective connectivity in patients with disorders of consciousness
BODART, Olivier ULiege; Amico, Enrico; Gomez, Francisco et al

in Brain Stimulation (2018)

Background Previous studies have separately reported impaired functional, structural, and effective connectivity in patients with disorders of consciousness (DOC). The perturbational complexity index (PCI ... [more ▼]

Background Previous studies have separately reported impaired functional, structural, and effective connectivity in patients with disorders of consciousness (DOC). The perturbational complexity index (PCI) is a transcranial magnetic stimulation (TMS) derived marker of effective connectivity. The global fractional anisotropy (FA) is a marker of structural integrity. Little is known about how these parameters are related to each other. Objective We aimed at testing the relationship between structural integrity and effective connectivity. Methods We assessed 23 patients with severe brain injury more than 4 weeks post-onset, leading to DOC or locked-in syndrome, and 14 healthy subjects. We calculated PCI using repeated single pulse TMS coupled with high-density electroencephalography, and used it as a surrogate of effective connectivity. Structural integrity was measured using the global FA, derived from diffusion weighted imaging. We used linear regression modelling to test our hypothesis, and computed the correlation between PCI and FA in different groups. Results Global FA could predict 74% of PCI variance in the whole sample and 56% in the patients' group. No other predictors (age, gender, time since onset, behavioural score) improved the models. FA and PCI were correlated in the whole population (r = 0.86, p < 0.0001), the patients, and the healthy subjects subgroups. Conclusion We here demonstrated that effective connectivity correlates with structural integrity in brain-injured patients. Increased structural damage level decreases effective connectivity, which could prevent the emergence of consciousness. [less ▲]

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See detailMultifaceted Brain Networks Reconfiguration in Disorders of Consciousness Uncovered by Co-Activation Patterns
Di Perri, Carol ULiege; Amico, Enrico; Heine, Lizette ULiege et al

in Human Brain Mapping (2018)

Introduction: Given that recent research has shown that functional connectivity is not a static phenomenon, we aim to investigate the dynamic properties of the default mode network’s (DMN) connectivity in ... [more ▼]

Introduction: Given that recent research has shown that functional connectivity is not a static phenomenon, we aim to investigate the dynamic properties of the default mode network’s (DMN) connectivity in patients with disorders of consciousness. Methods: Resting-state fMRI volumes of a convenience sample of 17 patients in unresponsive wakefulness syndrome (UWS) and controls were reduced to a spatiotemporal point process by selecting critical time points in the posterior cingulate cortex (PCC). Spatial clustering was performed on the extracted PCC time frames to obtain 8 different co-activation patterns (CAPs). We investigated spatial connectivity patterns positively and negatively correlated with PCC using both CAPs and standard stationary method. We calculated CAPs occurrences and the total number of frames. Results: Compared to controls, patients showed (i) decreased within-network positive correlations and between-network negative correlations, (ii) emergence of “pathological” within-network negative correlations and between-network positive correlations (better defined with CAPs), and (iii) “pathological” increases in within-network positive correlations and between-network negative correlations (only detectable using CAPs). Patients showed decreased occurrence of DMN-like CAPs (1–2) compared to controls. No between-group differences were observed in the total number of frames Conclusion: CAPs reveal at a more fine-grained level the multifaceted spatial connectivity reconfiguration following the DMN disruption in UWS patients, which is more complex than previously thought and suggests alternative anatomical substrates for consciousness. BOLD fluctuations do not seem to differ between patients and controls, suggesting that BOLD response represents an intrinsic feature of the signal, and therefore that spatial configuration is more important for consciousness than BOLD activation itself. [less ▲]

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See detailPrevalence of coma-recovery scale-revised signs of consciousness in patients in minimally conscious state
Wannez, Sarah ULiege; Gosseries, Olivia ULiege; Azzolini, Deborah et al

in Neuropsychological Rehabilitation (2018), 28(8), 1350-1359

Different behavioural signs of consciousness can distinguish patients with an unresponsive wakefulness syndrome from patients in minimally conscious state (MCS). The Coma Recovery Scale-Revised (CRS-R) is ... [more ▼]

Different behavioural signs of consciousness can distinguish patients with an unresponsive wakefulness syndrome from patients in minimally conscious state (MCS). The Coma Recovery Scale-Revised (CRS-R) is the most sensitive scale to differentiate the different altered states of consciousness and eleven items detect the MCS. The aim of this study is to document the prevalence of these items. We analysed behavioural assessments of 282 patients diagnosed in MCS based on the CRS-R. Results showed that some items are particularly frequent among patients in MCS, namely fixation, visual pursuit, and reproducible movement to command, which were observed in more than 50% of patients. These responses were also the most probably observed items when the patients only showed one sign of consciousness. On the other hand, some items were rarely or never observed alone, e.g., object localisation (reaching), object manipulation, intelligible verbalisation, and object recognition. The results also showed that limiting the CRS-R assessment to the five most frequently observed items (i.e., fixation, visual pursuit, reproducible movement to command, automatic motor response and localisation to noxious stimulation) detected 99% of the patients in MCS. If clinicians have only limited time to assess patients with disorders of consciousness, we suggest to evaluate at least these five items of the CRS-R. © 2017, © 2017 Informa UK Limited, trading as Taylor & Francis Group. [less ▲]

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See detailClassifying disorders of consciousness across sites using Diffusion Tensor Imaging and machine learning
Reggenete, N; Zheng, Z.S; Annen, Jitka ULiege et al

Poster (2018)

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See detailDecreased integration of EEG source-space networks in disorders of consciousness
Rizkallah, Jennifer; Annen, Jitka ULiege; Modolo, Julien et al

E-print/Working paper (2018)

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See detailAssessing Command-Following and Communication With Vibro-Tactile P300 Brain-Computer Interface Tools in Patients With Unresponsive Wakefulness Syndrome.
Guger, Christoph; Spataro, Rossella; Pellas, Frederic et al

in Frontiers in Neuroscience (2018), 12

Persons diagnosed with disorders of consciousness (DOC) typically suffer from motor disablities, and thus assessing their spared cognitive abilities can be difficult. Recent research from several groups ... [more ▼]

Persons diagnosed with disorders of consciousness (DOC) typically suffer from motor disablities, and thus assessing their spared cognitive abilities can be difficult. Recent research from several groups has shown that non-invasive brain-computer interface (BCI) technology can provide assessments of these patients' cognitive function that can supplement information provided through conventional behavioral assessment methods. In rare cases, BCIs may provide a binary communication mechanism. Here, we present results from a vibrotactile BCI assessment aiming at detecting command-following and communication in 12 unresponsive wakefulness syndrome (UWS) patients. Two different paradigms were administered at least once for every patient: (i) VT2 with two vibro-tactile stimulators fixed on the patient's left and right wrists and (ii) VT3 with three vibro-tactile stimulators fixed on both wrists and on the back. The patients were instructed to mentally count either the stimuli on the left or right wrist, which may elicit a robust P300 for the target wrist only. The EEG data from -100 to +600 ms around each stimulus were extracted and sub-divided into 8 data segments. This data was classified with linear discriminant analysis (using a 10 x 10 cross validation) and used to calibrate a BCI to assess command following and YES/NO communication abilities. The grand average VT2 accuracy across all patients was 38.3%, and the VT3 accuracy was 26.3%. Two patients achieved VT3 accuracy >/=80% and went through communication testing. One of these patients answered 4 out of 5 questions correctly in session 1, whereas the other patient answered 6/10 and 7/10 questions correctly in sessions 2 and 4. In 6 other patients, the VT2 or VT3 accuracy was above the significance threshold of 23% for at least one run, while in 4 patients, the accuracy was always below this threshold. The study highlights the importance of repeating EEG assessments to increase the chance of detecting command-following in patients with severe brain injury. Furthermore, the study shows that BCI technology can test command following in chronic UWS patients and can allow some of these patients to answer YES/NO questions. [less ▲]

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See detailTheta network centrality correlates with tDCS response in disorders of consciousness
Thibaut, Aurore ULiege; Chennu, S.; Chatelle, Camille ULiege et al

in Brain Stimulation (2018), 11(6), 1407-1409

[No abstract available]

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See detailBrain Tissue-Volume Changes in Cosmonauts
Van Ombergen, A.; Jillings, S.; Jeurissen, B. et al

in The New England journal of medicine (2018), 379(17), 1678-1680

[No abstract available]

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See detailBrain-computer interfaces for motor rehabilitation, DOC assessment and communication.
Guger, Christophe; Spataro, Rosella; Annen, Jitka ULiege et al

in Brain–Computer Interfaces Handbook (2018)

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