References of "Noirhomme, Quentin"
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See detailVolitional electromyographic responses in disorders of consciousness
Habbal, Dina; Gosseries, Olivia ULg; Noirhomme, Quentin ULg et al

in Brain Injury (2014)

The aim of the study was to validate the use of electromyography (EMG) for detecting responses to command in patients in vegetative state/unresponsive wakefulness syndrome (VS/UWS) or in minimally ... [more ▼]

The aim of the study was to validate the use of electromyography (EMG) for detecting responses to command in patients in vegetative state/unresponsive wakefulness syndrome (VS/UWS) or in minimally conscious state (MCS). Methods: Thirty-eight patients were included in the study (23 traumatic, 25 patients >1 year post-onset), 10 diagnosed as being in VS/UWS, eight in MCS- (no response to command) and 20 in MCS+ (response to command). Eighteen age-matched controls participated in the experiment. The paradigm consisted of three commands (i.e. 'Move your hands', 'Move your legs' and 'Clench your teeth') and one control sentence (i.e. 'It is a sunny day') presented in random order. Each auditory stimulus was repeated 4-times within one block with a stimulus-onset asynchrony of 30 seconds. Results: Post-hoc analyses with Bonferroni correction revealed that EMG activity was higher solely for the target command in one patient in permanent VS/UWS and in three patients in MCS+. Conclusion: The use of EMG could help clinicians to detect conscious patients who do not show any volitional response during standard behavioural assessments. However, further investigations should determine the sensitivity of EMG as compared to neuroimaging and electrophysiological assessments. [less ▲]

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See detailAn independent SSVEP-based brain-computer interface in locked-in-syndrome
Lesenfants, Damien ULg; Habbal, Dina; Lugo et al

in Journal of Neural Engineering (2014)

OBJECTIVE: Steady-state visually evoked potential (SSVEP)-based brain-computer interfaces (BCIs) allow healthy subjects to communicate. However, their dependence on gaze control prevents their use with ... [more ▼]

OBJECTIVE: Steady-state visually evoked potential (SSVEP)-based brain-computer interfaces (BCIs) allow healthy subjects to communicate. However, their dependence on gaze control prevents their use with severely disabled patients. Gaze-independent SSVEP-BCIs have been designed but have shown a drop in accuracy and have not been tested in brain-injured patients. In the present paper, we propose a novel independent SSVEP-BCI based on covert attention with an improved classification rate. We study the influence of feature extraction algorithms and the number of harmonics. Finally, we test online communication on healthy volunteers and patients with locked-in syndrome (LIS). APPROACH: Twenty-four healthy subjects and six LIS patients participated in this study. An independent covert two-class SSVEP paradigm was used with a newly developed portable light emitting diode-based 'interlaced squares' stimulation pattern. MAIN RESULTS: Mean offline and online accuracies on healthy subjects were respectively 85 ± 2% and 74 ± 13%, with eight out of twelve subjects succeeding to communicate efficiently with 80 ± 9% accuracy. Two out of six LIS patients reached an offline accuracy above the chance level, illustrating a response to a command. One out of four LIS patients could communicate online. SIGNIFICANCE: We have demonstrated the feasibility of online communication with a covert SSVEP paradigm that is truly independent of all neuromuscular functions. The potential clinical use of the presented BCI system as a diagnostic (i.e., detecting command-following) and communication tool for severely brain-injured patients will need to be further explored. [less ▲]

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See detailBiased binomial assessment of cross-validated estimation of classification accuracies illustrated in diagnosis predictions
Noirhomme, Quentin ULg; Lesenfants, Damien ULg; Gomez, Francisco et al

in NeuroImage: Clinical (2014), 4

Multivariate classification is used in neuroimaging studies to infer brain activation or in medical applications to infer diagnosis. Their results are often assessed through either a binomial or a ... [more ▼]

Multivariate classification is used in neuroimaging studies to infer brain activation or in medical applications to infer diagnosis. Their results are often assessed through either a binomial or a permutation test. Here, we simulated classification results of generated random data to assess the influence of the cross-validation scheme on the significance of results. Distributions built from classification of random data with crossvalidation did not follow the binomial distribution. The binomial test is therefore not adapted. On the contrary, the permutation test was unaffected by the cross-validation scheme. The influence of the crossvalidation was further illustrated on real-data from a brain–computer interface experiment in patients with disorders of consciousness and from an fMRI study on patients with Parkinson disease. Three out of 16 patients with disorders of consciousness had significant accuracy on binomial testing, but only one showed significant accuracy using permutation testing. In the fMRI experiment, the mental imagery of gait could discriminate significantly between idiopathic Parkinson’s disease patients and healthy subjects according to the permutation test but not according to the binomial test. Hence, binomial testing could lead to biased estimation of significance and false positive or negative results. In our view, permutation testing is thus recommended for clinical application of classification with cross-validation. [less ▲]

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See detailConsciousness and Unconsciousness: An EEG Perspective
Noirhomme, Quentin ULg; Laureys, Steven ULg

in Clinical EEG and Neuroscience (2014), 45

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See detailDIRECTED INFORMATION TRANSFER IN SCALP ELECTROENCEPHALOGRAPHIC RECORDINGS: INSIGHTS ON DISORDERS OF CONSCIOUSNESS
Marinazzo, Daniele; Gosseries, Olivia ULg; Boly, Mélanie ULg et al

in Clinical EEG and Neuroscience : Official Journal of the EEG and Clinical Neuroscience Society (ENCS) (2014)

Introduction: The neural mechanisms underlying electrophysiological changes observed in patients with disorders of consciousness following a coma remain poorly understood. The aim of this article is to ... [more ▼]

Introduction: The neural mechanisms underlying electrophysiological changes observed in patients with disorders of consciousness following a coma remain poorly understood. The aim of this article is to investigate the mechanisms underlying the differences in spontaneous electroencephalography between patients in vegetative/unresponsive wakefulness syndrome, minimally conscious state, emergence of the minimally conscious state and age-matched healthy control subjects. <br />Methods: Forty recording of spontaneous scalp electroencephalography were performed in 27 patients who were comatose on admission, and on healthy controls. Multivariate Granger Causality and Transfer Entropy were applied on the data. <br />Results: Distinctive patterns of putative bottlenecks of information were associated to each conscious state. Healthy controls are characterized by a greater amount of synergetic contributions from duplets of variables. <br />Conclusion: A novel set of measures was tested to get a novel insight on the pattern of information transfer in a network of scalp electrodes in patients with disorders of consciousness. [less ▲]

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See detailAutomated analysis of background EEG and reactivity during therapeutic hypothermia in comatose patients after cardiac arrest
Noirhomme, Quentin ULg; Lehembre, Rémy; Lugo, Zulay et al

in Clinical EEG and Neuroscience : Official Journal of the EEG and Clinical Neuroscience Society (ENCS) (2014)

Visual analysis of electroencephalography (EEG) background and reactivity during therapeutic hypothermia provides important outcome information, but is time-consuming and not always consistent between ... [more ▼]

Visual analysis of electroencephalography (EEG) background and reactivity during therapeutic hypothermia provides important outcome information, but is time-consuming and not always consistent between reviewers. Automated EEG analysis may help quantify the brain damage. Forty-six comatose patients in therapeutic hypothermia, after cardiac arrest, were included in the study. EEG background was quantified with burst-suppression ratio (BSR) and approximate entropy, both used to monitor anesthesia. Reactivity was detected through change in the power spectrum of signal before and after stimulation. Automatic results obtained almost perfect agreement (discontinuity) to substantial agreement (background reactivity) with a visual score from EEG-certified neurologists. Burst-suppression ratio was more suited to distinguish continuous EEG background from burst-suppression than approximate entropy in this specific population. Automatic EEG background and reactivity measures were significantly related to good and poor outcome. We conclude that quantitative EEG measurements can provide promising information regarding current state of the patient and clinical outcome, but further work is needed before routine application in a clinical setting. [less ▲]

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See detailA vibrotactile P300-based BCI for consciousness detection and communication
Lugo, Zulay; Rodriguez, Javi; Lechner, Alexander et al

in Clinical EEG and Neuroscience : Official Journal of the EEG and Clinical Neuroscience Society (ENCS) (2014)

Brain–computer interface (BCI) has been used for many years for communication in severely disabled patients. BCI based on electrophysiological signals has enabled communication, using auditory or visual ... [more ▼]

Brain–computer interface (BCI) has been used for many years for communication in severely disabled patients. BCI based on electrophysiological signals has enabled communication, using auditory or visual stimuli to elicit event-related potentials (ERPs). The aim of this study was to determine whether patients with locked-in syndrome (LIS) could elicit a P300 wave, using a vibrotactile oddball paradigm for establishing somatosensory BCI-based communication. Six chronic LIS patients performed 2electroencephalography (EEG)-based vibrotactile P300 oddball tasks. After a simple mental counting task of the target stimuli, participants were instructed to answer 5 questions by counting the vibration on either the right wrist for “yes” or the left wrist for “no.” All participants were able to elicit a P300 wave using the vibrotactile oddball paradigm BCI task. In the counting task, 4 patients got accuracies of 100% (average above chance). In the communication task, one patient achieved 100% accuracy (average above chance). We have shown the feasibility of eliciting a P300 response using vibrotactile stimulation in patients with LIS. The present study provides evidence that this approach can be used for EEG-based BCI communications in this patient group. This is the first study to prove the feasibility of a BCI based on somatosensory (vibratory) stimulation in a group of braininjured patients. Furthermore, this approach could be used for the detection of consciousness in non-communicating patients due to severe brain injuries. [less ▲]

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See detailMultiple fMRI system-level baseline connectivity is disrupted in patients with consciousness alterations
Demertzi, Athina ULg; Gomez, Francisco; Crone, Julia-Sophia et al

in Cortex : A Journal Devoted to the Study of the Nervous System & Behavior (2014), 52

Introduction: In healthy conditions, group-level fMRI resting state analyses identify ten resting state networks (RSNs) of cognitive relevance. Here, we aim to assess the tennetwork model in severely ... [more ▼]

Introduction: In healthy conditions, group-level fMRI resting state analyses identify ten resting state networks (RSNs) of cognitive relevance. Here, we aim to assess the tennetwork model in severely brain-injured patients suffering from disorders of consciousness and to identify those networks which will be most relevant to discriminate between patients and healthy subjects. Methods: 300 fMRI volumes were obtained in 27 healthy controls and 53 patients in minimally conscious state (MCS), vegetative state/unresponsive wakefulness syndrome (VS/ UWS) and coma. Independent component analysis (ICA) reduced data dimensionality. The ten networks were identified by means of a multiple template-matching procedure and were tested on neuronality properties (neuronal vs non-neuronal) in a data-driven way. Univariate analyses detected between-group differences in networks’ neuronal properties and estimated voxel-wise functional connectivity in the networks, which were significantly less identifiable in patients. A nearest-neighbor “clinical” classifier was used to determine the networks with high between-group discriminative accuracy. Results: Healthy controls were characterized by more neuronal components compared to patients in VS/UWS and in coma. Compared to healthy controls, fewer patients in MCS and VS/UWS showed components of neuronal origin for the left executive control network, default mode network (DMN), auditory, and right executive control network. The “clinical” classifier indicated the DMN and auditory network with the highest accuracy (85.3%) in discriminating patients from healthy subjects. [less ▲]

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See detailElectroencephalogram approximate entropy influenced by both age and sleep
Lee, Gerick; Fattinger, Sara; Mouthon, Anne-Laure et al

in Frontiers in Neuroinformatics (2013), 7(33),

The use of information-based measures to assess changes in conscious state is an increasingly popular topic. Though recent results have seemed to justify the merits of such methods, little has been done ... [more ▼]

The use of information-based measures to assess changes in conscious state is an increasingly popular topic. Though recent results have seemed to justify the merits of such methods, little has been done to investigate the applicability of such measures to children. For our work, we used the approximate entropy (ApEn), a measure previously shown to correlate with changes in conscious state when applied to the electroencephalogram (EEG), and sought to confirm whether previously reported trends in adult ApEn values across wake and sleep were present in children. Besides validating the prior findings that ApEn decreases from wake to sleep (including wake, rapid eye movement (REM) sleep, and non-REM sleep) in adults, we found that previously reported ApEn decreases across vigilance states in adults were also present in children (ApEn trends for both age groups: wake > REM sleep > non-REM sleep). When comparing ApEn values between age groups, adults had significantly larger ApEn values than children during wakefulness. After the application of an 8 Hz high-pass filter to the EEG signal, ApEn values were recalculated. The number of electrodes with significant vigilance state effects dropped from all 109 electrodes with the original 1 Hz filter to 1 electrode with the 8 Hz filter. The number of electrodes with significant age effects dropped from 10 to 4. Our results support the notion that ApEn can reliably distinguish between vigilance states, with low-frequency sleep-related oscillations implicated as the driver of changes between vigilance states. We suggest that the observed differences between adult and child ApEn values during wake may reflect differences in connectivity between age groups, a factor which may be important in the use of EEG to measure consciousness. [less ▲]

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See detailOn the statistical assessment of small sample classification
Noirhomme, Quentin ULg; Lesenfants, Damien ULg; Gomez, Francisco et al

Conference (2013, December)

Classifiers start to be used in medical application to infer diagnosis. Their results are assessed through either a binomial or a permutation test. Distributions built from classification of random data ... [more ▼]

Classifiers start to be used in medical application to infer diagnosis. Their results are assessed through either a binomial or a permutation test. Distributions built from classification of random data with cross-validation, did not follow the theoretical binomial distribution, showing that binomial test was not conservative enough. A permutation test is thus recommended. [less ▲]

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See detailCommon resting brain dynamics indicate a possible mechanism underlying zolpidem response in severe brain injury
Williams, Shawniqua; Conte, Mary; Goldfine, Andrew et al

in eLife (2013)

Zolpidem produces paradoxical recovery of speech, cognitive and motor functions in select subjects with severe brain injury but underlying mechanisms remain unknown. In three diverse patients with known ... [more ▼]

Zolpidem produces paradoxical recovery of speech, cognitive and motor functions in select subjects with severe brain injury but underlying mechanisms remain unknown. In three diverse patients with known zolpidem responses we identify a distinctive pattern of EEG dynamics that suggests a mechanistic model. In the absence of zolpidem, all subjects show a strong low frequency oscillatory peak ∼6–10 Hz in the EEG power spectrum most prominent over frontocentral regions and with high coherence (∼0.7–0.8) within and between hemispheres. Zolpidem administration sharply reduces EEG power and coherence at these low frequencies. The ∼6–10 Hz activity is proposed to arise from intrinsic membrane properties of pyramidal neurons that are passively entrained across the cortex by locally-generated spontaneous activity. Activation by zolpidem is proposed to arise from a combination of initial direct drug effects on cortical, striatal, and thalamic populations and further activation of underactive brain regions induced by restoration of cognitively-mediated behaviors. [less ▲]

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See detailElectroencephalographic profiles for differentiation of disorders of consciousness.
Malinowska, U; Chatelle, Camille ULg; Bruno, Marie-Aurélie ULg et al

in BioMedical Engineering OnLine (2013), 12

BACKGROUND: Electroencephalography (EEG) is best suited for long-term monitoring of brain functions in patients with disorders of consciousness (DOC). Mathematical tools are needed to facilitate efficient ... [more ▼]

BACKGROUND: Electroencephalography (EEG) is best suited for long-term monitoring of brain functions in patients with disorders of consciousness (DOC). Mathematical tools are needed to facilitate efficient interpretation of long-duration sleep-wake EEG recordings. METHODS: Starting with matching pursuit (MP) decomposition, we automatically detect and parametrize sleep spindles, slow wave activity, K-complexes and alpha, beta and theta waves present in EEG recordings, and automatically construct profiles of their time evolution, relevant to the assessment of residual brain function in patients with DOC. RESULTS: Above proposed EEG profiles were computed for 32 patients diagnosed as minimally conscious state (MCS, 20 patients), vegetative state/unresponsive wakefulness syndrome (VS/UWS, 11 patients) and Locked-in Syndrome (LiS, 1 patient). Their interpretation revealed significant correlations between patients' behavioral diagnosis and: (a) occurrence of sleep EEG patterns including sleep spindles, slow wave activity and light/deep sleep cycles, (b) appearance and variability across time of alpha, beta, and theta rhythms. Discrimination between MCS and VS/UWS based upon prominent features of these profiles classified correctly 87 % of cases. CONCLUSIONS: Proposed EEG profiles offer user-independent, repeatable, comprehensive and continuous representation of relevant EEG characteristics, intended as an aid in differentiation between VS/UWS and MCS states and diagnostic prognosis. To enable further development of this methodology into clinically usable tests, we share user-friendly software for MP decomposition of EEG (http://braintech.pl/svarog) and scripts used for creation of the presented profiles (attached to this article). [less ▲]

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See detailThe auditory P300-based single-switch brain–computer interface:Paradigm transition from healthy subjects to minimally consciouspatients
Pokorny, Christoph; Klobassa, Daniela; Pichler, Gerald et al

in Artificial Intelligence in Medicine (2013), 59(2), 81-90

Objective: Within this work an auditory P300 brain–computer interface based on tone stream segregation,which allows for binary decisions, was developed and evaluated.Methods and materials: Two tone ... [more ▼]

Objective: Within this work an auditory P300 brain–computer interface based on tone stream segregation,which allows for binary decisions, was developed and evaluated.Methods and materials: Two tone streams consisting of short beep tones with infrequently appearingdeviant tones at random positions were used as stimuli. This paradigm was evaluated in 10 healthysubjects and applied to 12 patients in a minimally conscious state (MCS) at clinics in Graz, Würzburg,Rome, and Liège. A stepwise linear discriminant analysis classifier with 10 × 10 cross-validation was usedto detect the presence of any P300 and to investigate attentional modulation of the P300 amplitude.Results: The results for healthy subjects were promising and most classification results were better thanrandom. In 8 of the 10 subjects, focused attention on at least one of the tone streams could be detectedon a single-trial basis. By averaging 10 data segments, classification accuracies up to 90.6 % could bereached. However, for MCS patients only a small number of classification results were above chance leveland none of the results were sufficient for communication purposes. Nevertheless, signs of consciousnesswere detected in 9 of the 12 patients, not on a single-trial basis, but after averaging of all correspondingdata segments and computing significant differences. These significant results, however, strongly variedacross sessions and conditions.Conclusion: This work shows the transition of a paradigm from healthy subjects to MCS patients. Promisingresults with healthy subjects are, however, no guarantee of good results with patients. Therefore, moreinvestigations are required before any definite conclusions about the usability of this paradigm for MCSpatients can be drawn. Nevertheless, this paradigm might offer an opportunity to support bedside clinicalassessment of MCS patients and eventually, to provide them with a means of communication. [less ▲]

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See detailDynamic change of global and local information processing in Propofol-induced loss and recovery of consciousness
Monti, Martin; Lutkenoff, Evan; Rubinov, Mikail et al

in PLoS Computational Biology (2013), 9

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See detailChanges in Effective Connectivity by Propofol Sedation
Gomez Jaramillo, Francisco Albeiro ULg; Phillips, Christophe ULg; Soddu, Andrea ULg et al

in PLoS ONE (2013), 8(8), 71370

Mechanisms of propofol-induced loss of consciousness remain poorly understood. Recent fMRI studies have shown decreases in functional connectivity during unconsciousness induced by this anesthetic agent ... [more ▼]

Mechanisms of propofol-induced loss of consciousness remain poorly understood. Recent fMRI studies have shown decreases in functional connectivity during unconsciousness induced by this anesthetic agent. Functional connectivity does not provide information of directional changes in the dynamics observed during unconsciousness. The aim of the present study was to investigate, in healthy humans during an auditory task, the changes in effective connectivity resulting from propofol induced loss of consciousness. We used Dynamic Causal Modeling for fMRI (fMRI-DCM) to assess how causal connectivity is influenced by the anesthetic agent in the auditory system. Our results suggest that the dynamic observed in the auditory system during unconsciousness induced by propofol, can result in a mixture of two effects: a local inhibitory connectivity increase and a decrease in the effective connectivity in sensory cortices. [less ▲]

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See detailReanalysis of “Bedside detection of awareness in the vegetative state: a cohort study”
Goldfine, Andrew; Bardin, Jonathan; Noirhomme, Quentin ULg et al

in Lancet (2013), 381

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See detailA multiscale method for a robust detection of the default mode network.
Baquero, Katherine; Gómez, Francisco; Cifuentes, Christian et al

Poster (2013)

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See detailThalamus, Brainstem and Salience Network Connectivity Changes During Propofol-Induced Sedation and Unconsciousness
Guldenmund, Justus Pieter ULg; Demertzi, Athina ULg; BOVEROUX, Pierre ULg et al

in Brain connectivity (2013), 3

In this functional magnetic resonance imaging study, we examined the effect of mild propofol sedation and propofol-induced unconsciousness on resting state brain connectivity, using graph analysis based ... [more ▼]

In this functional magnetic resonance imaging study, we examined the effect of mild propofol sedation and propofol-induced unconsciousness on resting state brain connectivity, using graph analysis based on independent component analysis and a classical seed-based analysis. Contrary to previous propofol research, which mainly emphasized the importance of connectivity in the default mode network (DMN) and external control network (ECN), we focused on the salience network, thalamus, and brainstem. The importance of these brain regions in brain arousal and organization merits a more detailed examination of their connectivity response to propofol. We found that the salience network disintegrated during propofol-induced unconsciousness. The thalamus decreased connectivity with the DMN, ECN, and salience network, while increasing connectivity with sensorimotor and auditory/insular cortices. Brainstem regions disconnected from the DMN with unconsciousness, while the pontine tegmental area increased connectivity with the insulae during mild sedation. These findings illustrate that loss of consciousness is associated with a wide variety of decreases and increases of both cortical and subcortical connectivity. It furthermore stresses the necessity of also examining resting state connectivity in networks representing arousal, not only those associated with awareness. [less ▲]

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See detailProbing command following in patients with disorders of consciousness using a brain-computer interface.
Lule, Dorothee; Noirhomme, Quentin ULg; Kleih, Sonja C. et al

in Clinical Neurophysiology (2013), 124(1), 101-6

OBJECTIVE: To determine if brain-computer interfaces (BCIs) could serve as supportive tools for detecting consciousness in patients with disorders of consciousness by detecting response to command and ... [more ▼]

OBJECTIVE: To determine if brain-computer interfaces (BCIs) could serve as supportive tools for detecting consciousness in patients with disorders of consciousness by detecting response to command and communication. METHODS: We tested a 4-choice auditory oddball EEG-BCI paradigm on 16 healthy subjects and 18 patients in a vegetative state/unresponsive wakefulness syndrome, in a minimally conscious state (MCS), and in locked-in syndrome (LIS). Subjects were exposed to 4 training trials and 10 -12 questions. RESULTS: Thirteen healthy subjects and one LIS patient were able to communicate using the BCI. Four of those did not present with a P3. One MCS patient showed command following with the BCI while no behavioral response could be detected at bedside. All other patients did not show any response to command and could not communicate with the BCI. CONCLUSION: The present study provides evidence that EEG based BCI can detect command following in patients with altered states of consciousness and functional communication in patients with locked-in syndrome. However, BCI approaches have to be simplified to increase sensitivity. SIGNIFICANCE: For some patients without any clinical sign of consciousness, a BCI might bear the potential to employ a "yes-no" spelling device offering the hope of functional interactive communication. [less ▲]

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See detailDetecting Consciousness with a Brain-computer Interface
Noirhomme, Quentin ULg; Lesenfants, Damien ULg; Lehembre, Remy ULg et al

in Pons, J. L.; Torricelli, D.; Pajaro, M. (Eds.) Converging Clinical and Engineering Research on Neurorehabilitation (2012, November)

Recent electrophysiological and neuroimaging studies showed command-specific changes in EEG or fMRI signals of unresponsive patients providing motor-independent evidence of conscious thoughts. These ... [more ▼]

Recent electrophysiological and neuroimaging studies showed command-specific changes in EEG or fMRI signals of unresponsive patients providing motor-independent evidence of conscious thoughts. These promising results have paved the way for a new application for Brain-computer Interface (BCI): detecting consciousness in patients with disorders of consciousness (DOC). In the present abstract, we review the first results obtained by BCI-like applications in patients with DOC and discuss the challenges facing BCI research. We believe that patients with DOC may benefit from BCI based diagnosis. BCIs may detect changes in the signal in response to command and, in some cases, may permit communication. [less ▲]

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