Quentin Noirhomme

Brain Innovation, Maastricht, Netherlands

We introduce a mean-field model for analysing the dynamics of human consciousness. In particular, inspired by the Giulio Tononi's Integrated Information Theory and by the Max Tegmark's representation of consciousness, we study order–disorder phase transitions on Curie–Weiss models generated by processing EEG signals. The latter have been recorded o...

We introduce a mean-field model for analysing the dynamics of human consciousness. In particular, inspired by the Giulio Tononi's Integrated Information Theory and by the Max Tegmark's representation of consciousness, we study order-disorder phase transitions on Curie-Weiss models generated by processing EEG signals. The latter have been recorded o...

A bstract Background Clinical assessment of patients with disorders of consciousness (DOC) relies on the clinician’s ability to detect a behavioral response to an instruction (e.g., “squeeze my hand”). However, recent studies have shown that some of these patients can produce volitional brain responses to command while no behavioral response is pr...

Traumatic brain injury patients frequently undergo tracheal intubation. We aimed to assess current intubationpractice in Europe and identify variation in practice. We analysed data from patients with traumatic brain injuryincluded in the prospective cohort study collaborative European neurotrauma effectiveness research intraumatic brain injury (CEN...

Background: People who survive severe brain damage may eventually develop a prolonged consciousness disorder. Others can regain full consciousness but remain unable to speak or move because of the severity of the lesions, as for those with locked-in syndrome (LIS). Brain-computer interface techniques can be useful to disentangle these states by de...

Schizophrenia is a severe mental disorder characterized by numerous subtle changes in brain structure and function. Machine learning allows exploring the utility of combining structural and functional brain magnetic resonance imaging (MRI) measures for diagnostic application, but this approach has been hampered by sample size limitations and lack o...

Despite the common use of anesthetics to modulate consciousness in the clinic, brain-based monitoring of consciousness is uncommon. We combined electroencephalographic measurement of brain activity with deep neural networks to automatically discriminate anesthetic states induced by propofol. Our results with leave-one-participant-out-cross-validati...

Introduction: In a previous study exploring central pain modulation with heterotopic stimuli in healthy volunteers, we found that transitions between sustained noxious and innocuous thermal stimulations on the foot activated the ‘‘salience matrix’’. Knowing that central sensory processing is abnormal in migraine, we searched in the present study fo...

Electroencephalography can offer many insights into brain activity useful for the study of disorders of consciousness. In this chapter, we will focus on the state of knowledge regarding the implementation of such a technique for diagnosis and prognosis in clinical setting, as well as the current effort for developing more reliable methods for asses...

Patients diagnosed with complete locked in syndrome (CLIS) or a disorder of consciousness (DOC) have no reliable control of voluntary movements. Hence, assessing their cognitive functions and cognitive awareness can be challenging. The “gold standard” for such assessments relies on behavioral responses, and recent work using different neuroimaging...

The current study is a first exploration of real-time self-regulation of functional magnetic resonance imaging (fMRI) activation based on several different visual neurofeedback presentations. Six healthy participants were engaged in self-regulation of regional fMRI activation in the posterior parietal cortex (PPC), by performing a mental calculatio...

Introduction: Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non-contiguous regions. To date, the spatial patterns of the net...

Electroencephalography (EEG) has been proposed as a supplemental tool for reducing clinical misdiagnosis in severely brain-injured populations helping to distinguish conscious from unconscious patients. We studied the use of spectral entropy as a measure of focal attention in order to develop a motor-independent, portable, and objective diagnostic...

Event-related potentials (ERP) have been proposed to improve the differential diagnosis of non-responsive patients. We investigated the potential of the P300 as a reliable marker of conscious processing in patients with locked-in syndrome (LIS). Eleven chronic LIS patients and 10 healthy subjects (HS) listened to a complex-tone auditory oddball par...

Objective: To propose a new methodology based on single-trial analysis for detecting residual response to command with EMG in patients with disorders of consciousness (DOC), overcoming the issue of trial dependency and decreasing the influence of a patient's fluctuation of vigilance or arousal over time on diagnostic accuracy. Methods: Forty-fiv...

Figure S1. Scatter plots for all the 11 VS/UWS patients showing the correlation between the FDG‐PET after partial volume correction versus the fMRI‐total neuronal activity for voxels belonging to gray matter. Solid line indicates the best linear fit to the data and on the upper left corner of each scatter plot the linear correlation value is report...

Figure S3. Correlation between FDG‐PET, after partial volume correction, and fMRI total neuronal versus total number of neuronal components combining all subjects, healthy controls (CTR), locked‐in (LIS) syndrome patients and vegetative state/unresponsive wakeful syndrome (VS/UWS) patients. Solid line indicates the best linear fit to the data and o...

Figure S2. Same as for Figure S1 for the four LIS patients.

Given the fact that clinical bedside examinations can have a high rate of misdiagnosis, machine learning techniques based on neuroimaging and electrophysiological measurements are increasingly being considered for comatose patients and patients with unresponsive wakefulness syndrome, a minimally conscious state or locked-in syndrome. Machine learni...

Propofol is one of the most commonly used anesthetics in the world, but much remains unknown about the mechanisms by which it induces loss of consciousness. In this resting state functional magnetic resonance imaging study, we examined qualitative and quantitative changes of resting state networks, 'total brain connectivity', and mean oscillation f...

Brain-computer interfaces (BCIs) are tools that allow overcoming motor disability in patients with brain injury, allowing them to communicate with the environment. This chapter reviews studies on BCI applications in patients with disorders of consciousness, including EEG and fMRI applications, with a critical appraisal regarding false-positive and...

Introduction: The mildly invasive 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established imaging technique to measure 'resting state' cerebral metabolism. This technique made it possible to assess changes in metabolic activity in clinical applications, such as the study of severe brain injury and disorders of conscious...

In altered subjective states, the behavioral quantification of external and internal awareness remains challenging due to the need for reports on the subjects' behalf. With the aim to characterize the behavioral counterpart of external and internal awareness in a modified subjective condition, we used hypnosis during which subjects remain fully res...

Loss of cortical integration and changes in the dynamics of electrophysiological brain signals characterize the transition from wakefulness towards unconsciousness. The common mechanism underlying these observations remains unknown. In this study we arrive at a basic model, which explains these empirical observations based on the theory of phase tr...

The diagnosis of patients with Disorders Of Consciousness represents a challenge in the clinical routine. Recently, Brain Computer Interfaces based in Electroencephalography (EEG-BCI) have been used to detect signs of consciousness in these patients. This approach allows to discover brain responses to command following. Nevertheless, a reliable BCI...

Emerging neural theories of consciousness suggest a correlation between a specific type of neural dynamical complexity and the level of consciousness: When awake and aware, causal interactions between brain regions are both integrated (all regions are to a certain extent connected) and differentiated (there is inhomogeneity and variety in the inter...

Background The cerebral network termed the ”pain matrix” includes areas such as anterior cingulate cortex, insula, SI, SII, medial temporal cortex and prefrontal cortex shown to respond to noxious stimuli, but also to other highly salient stimulations. We have previously shown in healthy volunteers that switching between noxious and innocuous susta...

Detecting signs of consciousness in patients in a vegetative state/unresponsive wakefulness syndrome (UWS/VS) or minimally conscious state (MCS) is known to be very challenging. Plotkin et al. (2010) recently showed the possibility of using a breathing-controlled communication device in patients with locked in syndrome. We here aim to test a breath...

The mechanisms underlying conditioned pain modulation (CPM) are multifaceted. We searched for a link between individual differences in prefrontal cortex activity during multi-trial heterotopic noxious cold conditioning and modulation of the cerebral response to phasic heat pain. In 24 healthy female subjects we conditioned laser heat stimuli to the...

In this study we report on the improvement of classification accuracy in an auditory P300 paradigm, by using stepwise linear discriminant analysis (SWLDA) with an increased number of channels and analytic shrinkage-regularized LDA (sLDA) as classifier. The investigations were evaluated on recordings of 10 healthy subjects and 12 patients in a minim...

Bauernfeind G, Pokorny C, Steyrl D, Wriessnegger SC, Pichler G, Schippinger W, Noirhomme Q, Real RG, Kübler A, Mattia D, Müller-Putz GR (2014) Improved Classification of Auditory Evoked Event-Related Potentials, Proceedings of the 6th International Brain-Computer Interface Conference, September 16th – 19th, 2014, Graz, Austria, pp.248-251, doi:10.3...

Objective: 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 diagnos...

Recent electrophysiological and neuroimaging studies showed the possibility to detect command-specific changes in electroencephalography (EEG) or functional magnetic resonance imaging (fMRI) signals independent of any motor pathway. These techniques could help in the improvement of the diagnosis in patients with disorders of consciousness (DOC; oft...

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-inju...

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. We here simulated classification results of generated random data to assess the influence of the cross-validation scheme on the signifi...

Brain-Computer Interfaces (BCI) for communication purposes are usually controlled via a P300 paradigm. There, a high number of different classes is presented to the user, thus enhancing the information transfer rate in comparison to e.g. motor imagery based BCIs. During the last years several P300 speller, based on visual stimulation, were develope...

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, w...

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 elic...

The neural mechanisms underlying electrophysiological changes observed in patients with disorders of consciousness following a coma remain poorly understood. The aim of this study is to investigate the mechanisms underlying the differences in spontaneous electroencephalography (EEG) between patients in vegetative/unresponsive wakefulness syndrome,...

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...

The Default Mode Network (DMN) is a resting state network widely used for the analysis and diagnosis of mental disorders. It is normally detected in fMRI data, but for its detection in data corrupted by motion artefacts or low neuronal activity, the use of a robust analysis method is mandatory. In fMRI it has been shown that the signal-to-noise rat...

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 sh...

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. Starting with matching pursuit (MP) decomposition, we automatically detect and parametrize sleep s...

Whether unique to humans or not, consciousness is a central aspect of our experience of the world. The neural fingerprint of this experience, however, remains one of the least understood aspects of the human brain. In this paper we employ graph-theoretic measures and support vector machine classification to assess, in 12 healthy volunteers, the dyn...

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 presen...

Estimated exceedance probabilities for different fMRI-DCM families in each consciousness state. (PDF)

Family level inference. (PDF)

P300 based Brain-Computer Interfaces (BCIs) for communication are well known since many years. Most of them use visual stimuli to elicit evoked potentials because it is easy to integrate a high number of different classes into the paradigm. Nevertheless, a BCI that depends on visual stimuli is sometimes not feasible due to the presence of visual im...

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 importan...

Many patients with Disorders of Consciousness (DOC) are misdiagnosed for a variety of reasons. These patients typically cannot communicate. Because such patients are not provided with the needed tools, one of their basic human needs remains unsatisfied, leaving them truly locked in to their bodies. This chapter first reviews current methods and pro...

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 co...