References of "Carrière, Manon"
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See detailFrom unconscious to conscious: a spectrum of states
Barra, Alice ULiege; Carrière, Manon ULiege; LAUREYS, Steven ULiege et al

in Overgaard, M; Mogensen, J; Kirkeby-Hinrup, A (Eds.) Beyond the Neural Correlates of Consciousness (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 detailIs auditory localization a sign of consciousness? Evidence from neuroimaging and electrophysiology
Carrière, Manon ULiege; Cassol, Helena ULiege; Aubinet, Charlène ULiege et al

Conference (2019, March 16)

Background Auditory localization is often part of the clinical evaluation of patients recovering from coma. There is however no clear consensus whether it should be considered as a reflex or as a ... [more ▼]

Background Auditory localization is often part of the clinical evaluation of patients recovering from coma. There is however no clear consensus whether it should be considered as a reflex or as a conscious behavior. For example, auditory localisation corresponds to the diagnosis of unresponsive wakefulness syndrome (UWS) in the Coma Recovery Scale-Revised, while it is considered a sign of consciousness in other post-coma scales. This study aims to determine if auditory localization reflects conscious processing in patients with disorders of consciousness. Methods We first evaluated the proportion of patients with and without auditory localisation in 186 patients with severe brain injury, including 64 UWS, 28 minimally conscious minus (MCS-), 71 minimally conscious plus (MCS+), i.e., language relatively preserved) and 23 who emerged from MCS (EMCS). We then measured brain metabolism using fluorine-18 fluorodeoxyglucose positron emission tomography, functional connectivity using magnetic resonance imaging (MRI) and high-density electroencephalography (EEG) in patients in UWS with and without auditory localization. Findings Auditory localization was observed in 12% of patients in UWS, 46% of patients in MCS-, 62% of patients in MCS+ and 78% of patients in EMCS. Brain metabolism of patients in UWS without auditory localization was mostly restricted to primary areas, whereas a more widespread activity, including associative areas, was observed in patients in UWS with auditory localisation. Brain functional connectivity was also higher in patients in UWS with auditory localisation in the frontoparietal fMRI resting state network, along with higher EEG connectivity in alpha frequency band, compared to patients without auditory localization. Finally, differences were also found regarding the outcome, as the survival rate at two years appeared to be significantly higher in UWS patients with auditory localization as compared to those without auditory localization. Interpretation. Both clinical data in post-comatose patients and neuroimaging examinations in UWS patients with and without auditory localization support the idea that auditory localization should be considered as a sign of consciousness. [less ▲]

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See detailNeurophysiological effects and behavioral outcomes after tPCS and tDCS in a patient in minimally conscious state
Barra, Alice ULiege; Mortaheb, Sepehr ULiege; Carrière, Manon ULiege et al

Conference (2019, March 15)

Introduction: Non-invasive brain stimulation (NIBS)(1-4) is a promising path in the search for treatments of patients with disorders of consciousness (DOC). Transcranial pulsed-current stimulation (tPCS ... [more ▼]

Introduction: Non-invasive brain stimulation (NIBS)(1-4) is a promising path in the search for treatments of patients with disorders of consciousness (DOC). Transcranial pulsed-current stimulation (tPCS) has been used to modulate cortical and subcortical neural connectivity within 6-10Hz(5). It was successfully employed to enhance motor and cognitive functions in healthy volunteers (6) and it is theoretically able to reach deeper brain structures(7) . On the other hand, transcranial direct-current stimulation (tDCS) over left dorsolateral prefrontal cortex (DLPFC) has shown to improve cognitive functions in DOC patients as measured by the Coma Recovery Scale-Revised (CRS-R) in about 50% of patients in minimally conscious state (MCS) (8,9). These are preliminary results of an ongoing study that aim to investigate the effects of tPCS and tDCS on one patient with DOC. Methods: This was a randomized double-blind sham-controlled clinical trial on a patient with DOC. The Subject received 3 sessions of stimulation: active tPCS sham tDCS, sham tPCS with active tDCS, and sham tPCS with sham tDCS. Before and after each session we evaluated the patient with the CRS-R and recorded 10 minutes of resting EEG. The stimulation target for tPCS was the bimastoid line with a random frequency of 6-10Hz (2mA peak to peak), whereas the target for tDCS was the left DLPFC with 2mA of intensity. EEG data were pre-processed and the power of signal was calculated for each frequency band: Delta (0-4 Hz), Theta (4-8 Hz), Alpha (8-12 Hz) and Beta (12-25 Hz). A non-parametric corrected cluster permutation test(10) was used to statistically compare the power maps before and after each session. Electrode clusters with p-value below 0.01 were considered as significantly different. Results and Discussion: An increase of Alpha and Beta power and decrease of Theta and Delta power was observed after anodal tDCS together with an increase of behavioural responsiveness as measured by the CRS-R score. After active tPCS, a significant increase was observed in Theta power consistently with the frequency of the stimulation (6-10Hz). However, this increase did not result in any measurable behavioural improvement maybe due to insufficient number of sessions or inadequate frequency of stimulation. Nevertheless, it could be relevant to mention that the patient’s caregivers noticed longer periods of wakefullness and higher arousal after tPCS. Therefore, it may be hypothesized that the CRS-R was not sensitive enough to capture these behavioural changes. Conclusion: In conclusion, here tDCS and tPCS induced distinct neurophysiological and clinical effects. So far, tDCS seems to be confirmed as a promising tool to improve behavioural responsiveness of patients with DOC. On the other hand, tPCS should be explored in larger cohorts to understand if this type of stimulation can reach similar results as the ones observed for tDCS. [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 detailImproving responsiveness to non-invasive brain stimulation in minimally conscious state patients: a closed-loop approach
Martens, Géraldine ULiege; Barra, Alice ULiege; Carrière, Manon ULiege et al

Poster (2019, February)

Transcranial direct current stimulation (tDCS) applied on the left dorsolateral prefrontal cortex has already been shown to efficiently promote the recovery of conscious awareness in patients with ... [more ▼]

Transcranial direct current stimulation (tDCS) applied on the left dorsolateral prefrontal cortex has already been shown to efficiently promote the recovery of conscious awareness in patients with disorders of consciousness following severe brain injury, especially those in minimally conscious state (MCS)1. However, one potential barrier to clinically respond to tDCS is accounting for the timing of the stimulation with regard to the fluctuations of vigilance that characterize this population2. Indeed, the vigilance of MCS patients has periodic average cycles of 70 minutes (range 57-80 minutes)3, potentially preventing them to be in an optimal neural state to benefit from tDCS when applied at random moments. To tackle this issue, we propose a new protocol to optimize the application of tDCS by selectively stimulating at high vigilance and low vigilance states, as measured by real-time spectral entropy (as a marker of vigilance3) and based on pre-identified individual thresholds, in a closed-loop fashion. We will conduct a clinical trial on 36 patients in MCS who will undergo a 4-hour EEG recording beforehand to set individual vigilance thresholds. The patients will then be randomized in three groups based on the moment of tDCS application: high vigilance, low vigilance and sham. These EEG-tDCS sessions will last for 6 hours with a maximum of two tDCS sessions of 20 min at 2 mA. Behavioral effects will be assessed using the Coma Recovery Scale-Revised4 at baseline, after 3 and 6 hours. The device used will be provided by Starlab and enable real-time analysis of EEG dynamics and spectral entropy as well as control of the tDCS stimulator (a customized version of Neuroelectrics’ Startsim 8). This unique and novel approach will provide new insights for the identification of tDCS responders and provide treatment options for the challenging population of patients with disorders of consciousness. [less ▲]

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See detailA Heartbeat Away From Consciousness: Heart Rate Variability Entropy can discriminate disorders of consciousness and is correlated with resting-state fMRI brain connectivity of the Central Autonomic Network
Riganello, Francesco ULiege; Larroque, Stephen Karl ULiege; Bahri, Mohamed Ali ULiege et al

Poster (2018, October)

Motivation: Heart rate variability (HRV) reflects the heart-brain two-way dynamic interactions[1-5]. HRV entropy analysis quantifies the unpredictability and complexity of the heart rate beats intervals ... [more ▼]

Motivation: Heart rate variability (HRV) reflects the heart-brain two-way dynamic interactions[1-5]. HRV entropy analysis quantifies the unpredictability and complexity of the heart rate beats intervals and over multiple time scales using multiscale entropy (MSE)[6-8]. The complexity index (CI) provides a score of a system’s complexity by aggregating the MSE measures over a range of time scales[8]. Most HRV entropy studies have focused on acute traumatic patients using task-based designs[9]. We here investigate the CI and its discriminative power in chronic patients with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) at rest, and its relation to brain functional connectivity. Methods: We investigated the CI in short (CIs) and long (CIl) time scales in 16 UWS and 17 MCS sedated. CI for MCS and UWS groups were compared using a Mann-Whitney exact test. Spearman’s correlation tests were conducted between the Coma Recovery Scale-revised (CRS-R) and both CI. Discriminative power of both CI was assessed with One-R machine learning model. Correlation between CI and brain connectivity (detected with functional magnetic resonance imagery using seed-based and hypothesis-free intrinsic connectivity) was investigated using a linear regression in a subgroup of 12 UWS and 12 MCS patients with sufficient image quality. Results and Discussion: Significant differences were found between MCS and UWS for CIs and CIl (0.0001≤p≤0.006). Significant correlations were found between CRS-R and CIs and CIl (0.0001≤p≤0.026). The One-R classifier selected CIl as the best discriminator between UWS and MCS with 85% accuracy, 19% false positive rate and 12% false negative rate after a 10-fold cross-validation test. Positive correlations were observed between CI and brain areas belonging to the autonomic system. CI was found to be significantly higher in MCS compared to UWS patients, with high discriminative power and lower false negative rate than the reported misdiagnosis rate of human assessors, providing an easy, inexpensive and non-invasive diagnosis tool. CI is correlated to functional connectivity changes in brain regions belonging to the autonomic nervous system, suggesting that CI can provide an indirect way to screen and monitor connectivity changes in this neural system. Future studies should investigate further the extent of CI’s predictive power for other pathologies in the disorders of consciousness spectrum. [less ▲]

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See detailA Heartbeat Away From Consciousness: Heart Rate Variability Entropy Can Discriminate Disorders of Consciousness and Is Correlated With Resting-State fMRI Brain Connectivity of the Central Autonomic Network
Riganello, Francesco ULiege; Larroque, Stephen Karl ULiege; Bahri, Mohamed Ali ULiege et al

in Frontiers in Neurology (2018), 9

Background: Disorders of consciousness are challenging to diagnose, with inconsistent behavioral responses, motor and cognitive disabilities, leading to approximately 40% misdiagnoses. Heart rate ... [more ▼]

Background: Disorders of consciousness are challenging to diagnose, with inconsistent behavioral responses, motor and cognitive disabilities, leading to approximately 40% misdiagnoses. Heart rate variability (HRV) reflects the complexity of the heart-brain two-way dynamic interactions. HRV entropy analysis quantifies the unpredictability and complexity of the heart rate beats intervals. We here investigate the complexity index (CI), a score of HRV complexity by aggregating the non-linear multi-scale entropies over a range of time scales, and its discriminative power in chronic patients with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS), and its relation to brain functional connectivity. Methods: We investigated the CI in short (CIs) and long (CIl) time scales in 14 UWS and 16 MCS sedated. CI for MCS and UWS groups were compared using a Mann-Whitney exact test. Spearman's correlation tests were conducted between the Coma Recovery Scale-revised (CRS-R) and both CI. Discriminative power of both CI was assessed with One-R machine learning model. Correlation between CI and brain connectivity (detected with functional magnetic resonance imagery using seed-based and hypothesis-free intrinsic connectivity) was investigated using a linear regression in a subgroup of 10 UWS and 11 MCS patients with sufficient image quality. Results: Higher CIs and CIl values were observed in MCS compared to UWS. Positive correlations were found between CRS-R and both CI. The One-R classifier selected CIl as the best discriminator between UWS and MCS with 90% accuracy, 7% false positive and 13% false negative rates after a 10-fold cross-validation test. Positive correlations were observed between both CI and the recovery of functional connectivity of brain areas belonging to the central autonomic networks (CAN). Conclusion: CI of MCS compared to UWS patients has high discriminative power and low false negative rate at one third of the estimated human assessors' misdiagnosis, providing an easy, inexpensive and non-invasive diagnostic tool. CI reflects functional connectivity changes in the CAN, suggesting that CI can provide an indirect way to screen and monitor connectivity changes in this neural system. Future studies should assess the extent of CI's predictive power in a larger cohort of patients and prognostic power in acute patients. [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 detailA Heartbeat Away From Consciousness: Heart Rate Variability Entropy can discriminate disorders of consciousness and is correlated with resting-state fMRI brain connectivity of the Central Autonomic Network
Riganello, Francesco ULiege; Larroque, Stephen Karl ULiege; Bahri, Mohamed Ali ULiege et al

Poster (2018, June 21)

Motivation: Heart rate variability (HRV) reflects the heart-brain two-way dynamic interactions[1-5]. HRV entropy analysis quantifies the unpredictability and complexity of the heart rate beats intervals ... [more ▼]

Motivation: Heart rate variability (HRV) reflects the heart-brain two-way dynamic interactions[1-5]. HRV entropy analysis quantifies the unpredictability and complexity of the heart rate beats intervals and over multiple time scales using multiscale entropy (MSE)[6-8]. The complexity index (CI) provides a score of a system’s complexity by aggregating the MSE measures over a range of time scales[8]. Most HRV entropy studies have focused on acute traumatic patients using task-based designs[9]. We here investigate the CI and its discriminative power in chronic patients with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) at rest, and its relation to brain functional connectivity. Methods: We investigated the CI in short (CIs) and long (CIl) time scales in 16 UWS and 17 MCS sedated. CI for MCS and UWS groups were compared using a Mann-Whitney exact test. Spearman’s correlation tests were conducted between the Coma Recovery Scale-revised (CRS-R) and both CI. Discriminative power of both CI was assessed with One-R machine learning model. Correlation between CI and brain connectivity (detected with functional magnetic resonance imagery using seed-based and hypothesis-free intrinsic connectivity) was investigated using a linear regression in a subgroup of 12 UWS and 12 MCS patients with sufficient image quality. Results and Discussion: Significant differences were found between MCS and UWS for CIs and CIl (0.0001≤p≤0.006). Significant correlations were found between CRS-R and CIs and CIl (0.0001≤p≤0.026). The One-R classifier selected CIl as the best discriminator between UWS and MCS with 85% accuracy, 19% false positive rate and 12% false negative rate after a 10-fold cross-validation test. Positive correlations were observed between CI and brain areas belonging to the autonomic system. CI was found to be significantly higher in MCS compared to UWS patients, with high discriminative power and lower false negative rate than the reported misdiagnosis rate of human assessors, providing an easy, inexpensive and non-invasive diagnosis tool. CI is correlated to functional connectivity changes in brain regions belonging to the autonomic nervous system, suggesting that CI can provide an indirect way to screen and monitor connectivity changes in this neural system. Future studies should investigate further the extent of CI’s predictive power for other pathologies in the disorders of consciousness spectrum. [less ▲]

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See detailTranscranial direct current stimulation unveils covert consciousness
Thibaut, Aurore ULiege; Chatelle, Camille ULiege; VANHAUDENHUYSE, Audrey ULiege et al

in Brain Stimulation (2018), 11(3), 642-644

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See detailFluctuation in behavioral responsiveness in severely brain-injured patients
Chatelle, Camille ULiege; Thibaut, Aurore ULiege; Gosseries, Olivia ULiege et al

in European Journal of Neurology (2018), 25(2), 90276

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