Determination of awareness in patients with severe brain injury using EEG power spectral analysis

Covert Speech Comprehension Predicts Recovery From Acute Unresponsive States

OBJECTIVE

Patients with traumatic brain injury who fail to obey commands after sedation-washout pose one of the most significant challenges for neurological prognostication. Reducing prognostic uncertainty will lead to more appropriate care decisions and ensure provision of limited rehabilitation resources to those most likely to benefit. Bedside markers of covert residual cognition, including speech comprehension, may reduce this uncertainty.

METHODS

We recruited 28 patients with acute traumatic brain injury who were 2 to 7 days sedation-free and failed to obey commands. Patients heard streams of isochronous monosyllabic words that built meaningful phrases and sentences while their brain activity via electroencephalography (EEG) was recorded. In healthy individuals, EEG activity only synchronizes with the rhythm of phrases and sentences when listeners consciously comprehend the speech. This approach therefore provides a measure of residual speech comprehension in unresponsive patients.

RESULTS

Seventeen and 16 patients were available for assessment with the Glasgow Outcome Scale Extended (GOSE) at 3 months and 6 months, respectively. Outcome significantly correlated with the strength of patients' acute cortical tracking of phrases and sentences (r > 0.6, p < 0.007), quantified by inter-trial phase coherence. Linear regressions revealed that the strength of this comprehension response (beta = 0.603, p = 0.006) significantly improved the accuracy of prognoses relative to clinical characteristics alone (eg, Glasgow Coma Scale [GCS], computed tomography [CT] grade).

INTERPRETATION

A simple, passive, auditory EEG protocol improves prognostic accuracy in a critical period of clinical decision making. Unlike other approaches to probing covert cognition for prognostication, this approach is entirely passive and therefore less susceptible to cognitive deficits, increasing the number of patients who may benefit. ANN NEUROL 2021;89:646-656.

End-of-life Decisions for Patients with Prolonged Disorders of Consciousness in England and Wales: Time for Neuroscience-informed Improvements

This article explores how the law of England and Wales1 has responded thus far to medical and clinical advances that have enabled patients with prolonged disorders of consciousness to survive. The authors argue that, although the courts have taken account of much of the science, they are now lagging behind, with the result that some patients are being denied their legal rights under the Mental Capacity Act 2005. The article further argues that English law does not comply with the United Kingdom's commitments under the United Nations Convention on the Rights of Persons with Disabilities. Stressing the need for the law to keep in step with advances in science, the article concludes with robust recommendations for improvements, based on the latest research in neuroscience, to the way in which life-sustaining treatment decisions are made. This would mean that the wishes of patients, including those with covert awareness, can be better reflected in best interests assessments.

EEG Assessment in a 2-Year-Old Child with Prolonged Disorders of Consciousness: 3 Years' Follow-up

A 2-year-old girl, diagnosed with traumatic brain injury and epilepsy following car trauma, was followed up for 3 years (a total of 15 recordings taken at 0, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 14, 19, 26, and 35 months). There is still no clear guidance on the diagnosis, treatment, and prognosis of children with disorders of consciousness. At each appointment, recordings included the child's height, weight, pediatric Glasgow Coma Scale (pGCS), Coma Recovery Scale-Revised (CRS-R), Gesell Developmental Schedule, computed tomography or magnetic resonance imaging, electroencephalogram, frequency of seizures, oral antiepileptic drugs, stimulation with subject's own name (SON), and median nerve electrical stimulation (MNS). Growth and development were deemed appropriate for the age of the child. The pGCS and Gesell Developmental Schedule provided a comprehensive assessment of consciousness and mental development; the weighted Phase Lag Index (wPLI ) in the β-band (13–25 Hz) can distinguish unresponsive wakefulness syndrome from minimally conscious state and confirm that the SON and MNS were effective. The continuous increase of delta-band power indicates a poor prognosis. Interictal epileptiform discharges (IEDs) have a cumulative effect and seizures seriously affect the prognosis.

Towards New Diagnostic Approaches in Disorders of Consciousness: A Proof of Concept Study on the Promising Use of Imagery Visuomotor Task

Background: advanced paraclinical approaches using functional neuroimaging and electroencephalography (EEG) allow identifying patients who are covertly aware despite being diagnosed as unresponsive wakefulness syndrome (UWS). Bedside detection of covert awareness employing motor imagery tasks (MI), which is a universally accepted clinical indicator of awareness in the absence of overt behavior, may miss some of these patients, as they could still have a certain level of awareness. We aimed at assessing covert awareness in patients with UWS using a visuomotor-guided motor imagery task (VMI) during EEG recording. Methods: nine patients in a minimally conscious state (MCS), 11 patients in a UWS, and 15 healthy individuals (control group—CG) were provided with an VMI (imagine dancing while watching a group dance video to command), a simple-MI (imagine squeezing their right hand to command), and an advanced-MI (imagine dancing without watching a group dance video to command) to detect command-following. We analyzed the command-specific EEG responses (event-related synchronization/desynchronization—ERS/ERD) of each patient, assessing whether these responses were appropriate, consistent, and statistically similar to those elicited in the CG, as reliable markers of motor imagery. Results: All patients in MCS, all healthy individuals and one patient in UWS repeatedly and reliably generated appropriate EEG responses to distinct commands of motor imagery with a classification accuracy of 60–80%. Conclusions: VMI outperformed significantly MI tasks. Therefore, patients in UWS may be still misdiagnosed despite a rigorous clinical assessment and an appropriate MI assessment. It is thus possible to suggest that motor imagery tasks should be delivered to patients with chronic disorders of consciousness in visuomotor-aided modality (also in the rehabilitation setting) to greatly entrain patient’s participation. In this regard, the EEG approach we described has the clear advantage of being cheap, portable, widely available, and objective. It may be thus considered as, at least, a screening tool to identify the patients who deserve further, advanced paraclinical approaches.

Electrophysiological and Neuroimaging Studies - During Resting State and Sensory Stimulation in Disorders of Consciousness: A Review

A severe brain injury may lead to a disorder of consciousness (DOC) such as coma, vegetative state (VS), minimally conscious state (MCS) or locked-in syndrome (LIS). Till date, the diagnosis of DOC relies only on clinical evaluation or subjective scoring systems such as Glasgow coma scale, which fails to detect subtle changes and thereby results in diagnostic errors. The high rate of misdiagnosis and inability to predict the recovery of consciousness for DOC patients have created a huge research interest in the assessment of consciousness. Researchers have explored the use of various stimulation and neuroimaging techniques to improve the diagnosis. In this article, we present the important findings of resting-state as well as sensory stimulation methods and highlight the stimuli proven to be successful in the assessment of consciousness. Primarily, we review the literature based on (a) application/non-use of stimuli (i.e., sensory stimulation/resting state-based), (b) type of stimulation used (i.e., auditory, visual, tactile, olfactory, or mental-imagery), (c) electrophysiological signal used (EEG/ERP, fMRI, PET, EMG, SCL, or ECG). Among the sensory stimulation methods, auditory stimulation has been extensively used, since it is easier to conduct for these patients. Olfactory and tactile stimulation have been less explored and need further research. Emotionally charged stimuli such as subject’s own name or narratives in a familiar voice or subject’s own face/family pictures or music result in stronger responses than neutral stimuli. Studies based on resting state analysis have employed measures like complexity, power spectral features, entropy and functional connectivity patterns to distinguish between the VS and MCS patients. Resting-state EEG and fMRI are the state-of-the-art techniques and have a huge potential in predicting the recovery of coma patients. Further, EMG and mental-imagery based studies attempt to obtain volitional responses from the VS patients and thus could detect their command-following capability. This may provide an effective means to communicate with these patients. Recent studies have employed fMRI and PET to understand the brain-activation patterns corresponding to the mental imagery. This review promotes our knowledge about the techniques used for the diagnosis of patients with DOC and attempts to provide ideas for future research.

EEG to Identify Attempted Movement in Unresponsive Wakefulness Syndrome

Assessment of consciousness following severe brain-injury is challenging. Our hypothesis is that electroencephalography (EEG) can provide information on awareness, in terms of oscillatory activity and network task-related modifications, in people with disorders of consciousness. Similar results were obtained with neuroimaging techniques; we aim at demonstrating the use of EEG, which is low cost and routinely implemented, to the same goal. Nineteen-channel EEG was recorded in 7 persons with unresponsive wakefulness syndrome (UWS) and in 10 healthy subjects during the execution of active (attempted movement) and passive motor tasks as well as 2 mental imagery tasks. Event-related synchronization/desynchronization (ERS/ERD), coherence and network parameters were calculated in delta (1-4 Hz), theta (4-8 Hz), alpha1 (8-10 Hz), alpha2 (10-12 Hz), and beta (13-30 Hz) ranges. In UWS subjects, passive movement induced a weak alpha2 ERD over contralateral sensorimotor area. During motor imagery, ERD was detected over the frontal and motor contralateral brain areas; during spatial imagery, ERS in lower alpha band over the right temporo-parietal regions was missing. In UWS, functional connectivity provided evidence of network disruption and isolation of the motor areas, which cannot dialog with adjacent network nodes, likely suggesting a diffuse structural alteration. Our findings suggest that people with a clinical diagnosis of UWS were able to modulate their brain activity when prompted to perform movement tasks and thus suggest EEG as a potential tool to support diagnosis of disorders of consciousness.

Clinical and advanced neurophysiology in the prognostic and diagnostic evaluation of disorders of consciousness: review of an IFCN-endorsed expert group

The analysis of spontaneous EEG activity and evoked potentialsis a cornerstone of the instrumental evaluation of patients with disorders of consciousness (DoC). Thepast few years have witnessed an unprecedented surge in EEG-related research applied to the prediction and detection of recovery of consciousness after severe brain injury,opening up the prospect that new concepts and tools may be available at the bedside. This paper provides a comprehensive, critical overview of bothconsolidated and investigational electrophysiological techniquesfor the prognostic and diagnostic assessment of DoC.We describe conventional clinical EEG approaches, then focus on evoked and event-related potentials, and finally we analyze the potential of novel research findings. In doing so, we (i) draw a distinction between acute, prolonged and chronic phases of DoC, (ii) attempt to relate both clinical and research findings to the underlying neuronal processes and (iii) discuss technical and conceptual caveats.The primary aim of this narrative review is to bridge the gap between standard and emerging electrophysiological measures for the detection and prediction of recovery of consciousness. The ultimate scope is to provide a reference and common ground for academic researchers active in the field of neurophysiology and clinicians engaged in intensive care unit and rehabilitation.

Propofol-induced loss of consciousness is associated with a decrease in thalamocortical connectivity in humans

Although the molecular effects of many anaesthetics have been well characterized, a network-level explanation for how these changes lead to loss of consciousness remains unclear. Studies using electroencephalography have characterized changes in neural oscillations in the cortex at specific frequency bands during propofol-induced anaesthesia and modelling work suggests these changes result from changes in thalamocortical functional connectivity. However, it is unclear if the neurophysiological changes seen at the cortex are due to enhanced or disrupted thalamocortical communication. Direct recordings from these sites during anaesthesia that could be used to confirm such models are rare. We recorded local field potentials from the ventral intermediate nucleus of the thalamus and electrocorticography signals from the ipsilateral sensorimotor cortex in 10 patients undergoing deep brain stimulation surgery. Signals were acquired during induction of propofol anaesthesia while subjects were resting. After confirming direct structural connectivity between the thalamus and the cortical recording site, we investigated propofol-associated changes in thalamic and cortical local power as well as thalamocortical functional connectivity, as measured with coherence, debiased weighted phase lag index, and phase amplitude coupling. Propofol anaesthesia resulted in local power increases at α frequencies (8-12 Hz) across both thalamic and cortical areas. At sensorimotor cortices, there was a broadband power increase (12-100 Hz), while the power of this same broad frequency band was suppressed within the thalamus. Despite the increase in local α power both within the thalamus and cortex, thalamocortical coherence and debiased weighted phase lag index in the α/low β frequencies (8-16 Hz, which was present in the awake state) significantly decreased with propofol administration (P < 0.05, two group test of coherence). Likewise, propofol administration resulted in decreased phase amplitude coupling between the phase of α/low β in the thalamus and the amplitude of broadband gamma (50-200 Hz) in the cortex (P = 0.031, Wilcoxon signed-rank test). We also report phase amplitude coupling between the phase of slow wave oscillations (0.1-1 Hz) and amplitude of broadband frequencies (8-200 Hz) within the cortex and across thalamocortical connections, during anaesthesia, both following a peak-max pattern. While confirming α-power increases with propofol administration both in thalamus and cortex, we observed decreased thalamocortical connectivity, contradicting models that suggest increasing cortical low frequency power is necessarily related to increased thalamocortical coherence but in support of the theory that propofol-induced loss of consciousness is associated with disrupted thalamocortical communication.

Detecting Epileptic Seizures in EEG Signals with Complementary Ensemble Empirical Mode Decomposition and Extreme Gradient Boosting

Epilepsy is a common nervous system disease that is characterized by recurrent seizures. An electroencephalogram (EEG) records neural activity, and it is commonly used for the diagnosis of epilepsy. To achieve accurate detection of epileptic seizures, an automatic detection approach of epileptic seizures, integrating complementary ensemble empirical mode decomposition (CEEMD) and extreme gradient boosting (XGBoost), named CEEMD-XGBoost, is proposed. Firstly, the decomposition method, CEEMD, which is capable of effectively reducing the influence of mode mixing and end effects, was utilized to divide raw EEG signals into a set of intrinsic mode functions (IMFs) and residues. Secondly, the multi-domain features were extracted from raw signals and the decomposed components, and they were further selected according to the importance scores of the extracted features. Finally, XGBoost was applied to develop the epileptic seizure detection model. Experiments were conducted on two benchmark epilepsy EEG datasets, named the Bonn dataset and the CHB-MIT (Children's Hospital Boston and Massachusetts Institute of Technology) dataset, to evaluate the performance of our proposed CEEMD-XGBoost. The extensive experimental results indicated that, compared with some previous EEG classification models, CEEMD-XGBoost can significantly enhance the detection performance of epileptic seizures in terms of sensitivity, specificity, and accuracy.

Neurosensory stimulation outdoors enhances cognition recovery in cognitive motor dissociation: A prospective crossover study

BACKGROUND:

Neurosensory stimulation is effective in enhancing the recovery process of severely brain-injured patients with disorders of consciousness. Multisensory environments are found in nature, recognized as beneficial to many medical conditions. Recent advances detected covert cognition in patients behaviorally categorized as un- or minimally responsive; a state described as cognitive motor dissociation (CMD).

OBJECTIVE:

To determine effectiveness of a neurosensory stimulation approach enhanced by outdoor therapy, in the early phases of recovery in patients presenting with CMD.

METHODS:

A prospective non-randomized crossover study was performed. A two-phase neurosensory procedure combined identical individually goal assessed indoor and outdoor protocols. All sessions were video-recorded and observations rated offline. The frequency of volitional behavior was measured using a behavioral grid.

RESULTS:

Fifteen patients participated in this study. The outdoor group patients had statistically significant higher number of intentional behaviors than the indoor group on seven features of the grid. Additionally, for all items assessed, total amount of behaviors in the outdoor condition where higher than those in the indoor condition.

CONCLUSIONS:

Although preliminary, this study provides robust evidence supporting the effectiveness and appropriateness of an outdoor neurosensory intervention in patients with covert cognition, to improve adaptive goal-oriented behavior. This may be a step towards helping to restore functional interactive communication.

Assessment of Covert Consciousness in the Intensive Care Unit: Clinical and Ethical Considerations

OBJECTIVE

To propose a practical ethical framework for how task-based functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) may be used in the intensive care unit (ICU) to identify covert consciousness in patients with acute severe traumatic brain injury (TBI).

METHODS

We present 2 clinical scenarios in which investigational task-based fMRI and EEG were performed in critically ill patients with acute severe TBI who appeared unconscious on the bedside behavioral assessment. From these cases, we consider the clinical and ethical challenges that emerge and suggest how to reconcile them. We also provide recommendations regarding communication with families about ICU patients with covert consciousness.

RESULTS

Covert consciousness was detected acutely in a patient who died in the ICU due to withdrawal of life-sustaining therapy, whereas covert consciousness was not detected in a patient who subsequently recovered consciousness, communication, and functional independence. These cases raise ethical challenges about how assessment of covert consciousness in the ICU might inform treatment decisions, prognostication, and perceptions about the benefits and burdens of ongoing care.

CONCLUSIONS

Given that covert consciousness can be detected acutely in the ICU, we recommend that clinicians reconsider evaluative norms for ICU patients. As our clinical appreciation of covert consciousness evolves and its ethical import unfolds, we urge prognostic humility and transparency when clinicians communicate with families in the ICU about goals of care.

Beta and gamma synchronous oscillations in neural network activity in mice-induced by food deprivation

Food deprivation is known to trigger hunger sensation and motivation to eat for energy replenishing. However, brain mechanisms associated with hunger and neural circuitries that mediate hunger driven responses remained to be investigated. To understand neural signaling of hunger, local field potentials (LFPs) in the lateral hypothalamus (LHa), nucleus accumbens (NAc), dorsal hippocampus (HP) and olfactory bulb (OB) and their interconnectivities were studied in freely moving adult male Albino mice during 18-20 h food deprivation and fed periods. Raw LFP signals were recorded and analyzed for mean values of spectral frequency power and coherence values. One-way repeated measures ANOVA revealed significant increases in spectral powers of beta and gamma frequency ranges induced by food deprivation in the LHa, HP, NAc but not OB. No change of spectral power in these brain regions was induced by food feeding. The analyses of coherent activity between brain regions also deliniated some distributed neural network activities correlated with hunger. In particular, coherent function indicated the increased beta and gamma phase synchrony between the pairs of LHa-HP and NAc-OB regions, and decreased gamma synchrony between the pairs of LHa-NAc and NAc-HP induced by food deprivation. It was found that plasma glucose level, locomotor count, travelled distance and time spent on moving were not altered by food deprivation. These results suggest that changes in LFP hallmarks in these brain regions were associated with hunger driven by negative energy balance.

Low- and medium-rate auditory steady-state responses in patients with prolonged disorders of consciousness correlate with Coma Recovery Scale - Revised score

Diagnosis of consciousness in patients with prolonged disorders of consciousness (PDOC) remains challenging since their responsiveness is often very impaired, while their assessment depends on observable behavior. The aim of this proof-of-concept study was to evaluate whether low- and medium-rate amplitude-modulated (AM) auditory steady-state responses (ASSRs) can be sensitive to the state of PDOC patients and may thus serve as a diagnostic tool which does not explicitly depend on a patient's cooperation. EEG was recorded from nine unresponsive wakefulness syndrome/vegetative state (UWS/VS) and eight minimally conscious state (MCS)/emergence from MCS patients during stimulation with two-minute trains of simple tones, amplitude modulated (AM) by 4 Hz, 6 Hz, 8 Hz, 12 Hz, 20 Hz, 40 Hz. The obtained ASSRs were then related to the Coma Recovery Scale - Revised (CRS-R) diagnosis and its total score. We observed significant correlations between mean inter-trial phase coherence (PC) (averaged across all stimulation frequencies) and total CRS-R score, as well as between 40 Hz relative power (RP) and total CRS-R score. Moreover, both parameters significantly differed between the patient groups. Our preliminary results suggest that a passive auditory stimulation protocol consisting of low- and medium-rate ASSRs might be used as an objective estimate of the level of neural dysfunction in PDOC patients. Consequently, the integrity of the auditory system appears to be an important predictor of the actual state of consciousness in PDOC patients.

Robust EEG-based cross-site and cross-protocol classification of states of consciousness

Determining the state of consciousness in patients with disorders of consciousness is a challenging practical and theoretical problem. Recent findings suggest that multiple markers of brain activity extracted from the EEG may index the state of consciousness in the human brain. Furthermore, machine learning has been found to optimize their capacity to discriminate different states of consciousness in clinical practice. However, it is unknown how dependable these EEG markers are in the face of signal variability because of different EEG configurations, EEG protocols and subpopulations from different centres encountered in practice. In this study we analysed 327 recordings of patients with disorders of consciousness (148 unresponsive wakefulness syndrome and 179 minimally conscious state) and 66 healthy controls obtained in two independent research centres (Paris Pitié-Salpêtrière and Liège). We first show that a non-parametric classifier based on ensembles of decision trees provides robust out-of-sample performance on unseen data with a predictive area under the curve (AUC) of ~0.77 that was only marginally affected when using alternative EEG configurations (different numbers and positions of sensors, numbers of epochs, average AUC = 0.750 ± 0.014). In a second step, we observed that classifiers based on multiple as well as single EEG features generalize to recordings obtained from different patient cohorts, EEG protocols and different centres. However, the multivariate model always performed best with a predictive AUC of 0.73 for generalization from Paris 1 to Paris 2 datasets, and an AUC of 0.78 from Paris to Liège datasets. Using simulations, we subsequently demonstrate that multivariate pattern classification has a decisive performance advantage over univariate classification as the stability of EEG features decreases, as different EEG configurations are used for feature-extraction or as noise is added. Moreover, we show that the generalization performance from Paris to Liège remains stable even if up to 20% of the diagnostic labels are randomly flipped. Finally, consistent with recent literature, analysis of the learned decision rules of our classifier suggested that markers related to dynamic fluctuations in theta and alpha frequency bands carried independent information and were most influential. Our findings demonstrate that EEG markers of consciousness can be reliably, economically and automatically identified with machine learning in various clinical and acquisition contexts.

Fractal dimension analysis of states of consciousness and unconsciousness using transcranial magnetic stimulation

BACKGROUND AND OBJECTIVE

Knowing whether a subject is conscious or not is a current challenge with a deep potential clinical impact. Recent theoretical considerations suggest that consciousness is linked to the complexity of distributed interactions within the corticothalamic system. The fractal dimension (FD) is a quantitative parameter that has been extensively used to analyse the complexity of structural and functional patterns of the human brain. In this study we investigate FD to assess whether it can discriminate between consciousness and different states of unconsciousness in healthy individuals.

METHODS

We study 69 high-density electroencephalogram (hd-EEG) measurements after transcranial magnetic stimulation (TMS) in 18 healthy subjects progressing from wakefulness to non-rapid eye movement (NREM) sleep and sedation induced by different anaesthetic agents (xenon and propofol). We quantify the integration of thalamocortical networks by calculating the FD of a spatiotemporal voxelization obtained from the locations of all sources that are significantly activated by the perturbation (4DFD). Moreover, we study the temporal evolution of the evoked spatial distributions and compute a measure of the differentiation of the response by means of the Higuchi FD (HFD). Finally, a Fractal Dimension Index (FDI) of perturbational complexity is computed as the product of both quantities: integration FD (4DFD) and differentiation FD (HFD).

RESULTS

We found that FDI is significantly lower in sleep and sedation when compared to wakefulness and provides an almost perfect intra-subject discrimination between conscious and unconscious states.

CONCLUSIONS

These results support the combination of FD measures of cortical integration and cortical differentiation as a novel paradigm of tracking complex spatiotemporal dynamics in the brain that could provide further insights into the link between complexity and the brain's capacity to sustain consciousness.

Detection of Brain Activation in Unresponsive Patients with Acute Brain Injury

BACKGROUND

Brain activation in response to spoken motor commands can be detected by electroencephalography (EEG) in clinically unresponsive patients. The prevalence and prognostic importance of a dissociation between commanded motor behavior and brain activation in the first few days after brain injury are not well understood.

METHODS

We studied a prospective, consecutive series of patients in a single intensive care unit who had acute brain injury from a variety of causes and who were unresponsive to spoken commands, including some patients with the ability to localize painful stimuli or to fixate on or track visual stimuli. Machine learning was applied to EEG recordings to detect brain activation in response to commands that patients move their hands. The functional outcome at 12 months was determined with the Glasgow Outcome Scale-Extended (GOS-E; levels range from 1 to 8, with higher levels indicating better outcomes).

RESULTS

A total of 16 of 104 unresponsive patients (15%) had brain activation detected by EEG at a median of 4 days after injury. The condition in 8 of these 16 patients (50%) and in 23 of 88 patients (26%) without brain activation improved such that they were able to follow commands before discharge. At 12 months, 7 of 16 patients (44%) with brain activation and 12 of 84 patients (14%) without brain activation had a GOS-E level of 4 or higher, denoting the ability to function independently for 8 hours (odds ratio, 4.6; 95% confidence interval, 1.2 to 17.1).

CONCLUSIONS

A dissociation between the absence of behavioral responses to motor commands and the evidence of brain activation in response to these commands in EEG recordings was found in 15% of patients in a consecutive series of patients with acute brain injury. (Supported by the Dana Foundation and the James S. McDonnell Foundation.).

Neural Speech Tracking in the Theta and in the Delta Frequency Band Differentially Encode Clarity and Comprehension of Speech in Noise

Humans excel at understanding speech even in adverse conditions such as background noise. Speech processing may be aided by cortical activity in the delta and theta frequency bands, which have been found to track the speech envelope. However, the rhythm of non-speech sounds is tracked by cortical activity as well. It therefore remains unclear which aspects of neural speech tracking represent the processing of acoustic features, related to the clarity of speech, and which aspects reflect higher-level linguistic processing related to speech comprehension. Here we disambiguate the roles of cortical tracking for speech clarity and comprehension through recording EEG responses to native and foreign language in different levels of background noise, for which clarity and comprehension vary independently. We then use a both a decoding and an encoding approach to relate clarity and comprehension to the neural responses. We find that cortical tracking in the theta frequency band is mainly correlated to clarity, whereas the delta band contributes most to speech comprehension. Moreover, we uncover an early neural component in the delta band that informs on comprehension and that may reflect a predictive mechanism for language processing. Our results disentangle the functional contributions of cortical speech tracking in the delta and theta bands to speech processing. They also show that both speech clarity and comprehension can be accurately decoded from relatively short segments of EEG recordings, which may have applications in future mind-controlled auditory prosthesis.

SIGNIFICANCE STATEMENT Speech is a highly complex signal whose processing requires analysis from lower-level acoustic features to higher-level linguistic information. Recent work has shown that neural activity in the delta and theta frequency bands track the rhythm of speech, but the role of this tracking for speech processing remains unclear. Here we disentangle the roles of cortical entrainment in different frequency bands and at different temporal lags for speech clarity, reflecting the acoustics of the signal, and speech comprehension, related to linguistic processing. We show that cortical speech tracking in the theta frequency band encodes mostly speech clarity, and thus acoustic aspects of the signal, whereas speech tracking in the delta band encodes the higher-level speech comprehension.

Mental imagery for brain-computer interface control and communication in non-responsive individuals

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 detecting neurophysiological correlates of conscious processing of information to enable communication with these individuals after the diagnosis.

OBJECTIVE

The goal of our study was to evaluate with a user-centered design approach the usability of a mental imagery task to detect signs of voluntary information processing and enabling communication in a group of severely disabled individuals.

METHODS

Five individuals with LIS participated in the study. Participants were instructed to imagine hand, arm or feet movements during electroencephalography (EEG) to detect patterns of event-related synchronization/desynchronization associated with each task. After the user-centered design, usability was evaluated (i.e., efficiency, effectiveness and satisfaction).

RESULTS

Two participants achieved significant levels of accuracy in 2 different tasks. The associated workload and levels of satisfaction perceived by the users were moderate and were mainly related to the time demand of the task.

CONCLUSION

Results showed lack of effectiveness of the task to detect voluntary brain activity and thus detect consciousness or communicate with non-responsive individuals. The application must be modified to be sufficiently satisfying for the intended end-users and suggestions are made in this regard.

Uncovering Consciousness in Unresponsive ICU Patients: Technical, Medical and Ethical Considerations

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2019. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2019. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901.

Cortical Response to the Natural Speech Envelope Correlates with Neuroimaging Evidence of Cognition in Severe Brain Injury

Recent studies identify severely brain-injured patients with limited or no behavioral responses who successfully perform functional magnetic resonance imaging (fMRI) or electroencephalogram (EEG) mental imagery tasks [1-5]. Such tasks are cognitively demanding [1]; accordingly, recent studies support that fMRI command following in brain-injured patients associates with preserved cerebral metabolism and preserved sleep-wake EEG [5, 6]. We investigated the use of an EEG response that tracks the natural speech envelope (NSE) of spoken language [7-22] in healthy controls and brain-injured patients (vegetative state to emergence from minimally conscious state). As audition is typically preserved after brain injury, auditory paradigms may be preferred in searching for covert cognitive function [23-25]. NSE measures are obtained by cross-correlating EEG with the NSE. We compared NSE latencies and amplitudes with and without consideration of fMRI assessments. NSE latencies showed significant and progressive delay across diagnostic categories. Patients who could carry out fMRI-based mental imagery tasks showed no statistically significant difference in NSE latencies relative to healthy controls; this subgroup included patients without behavioral command following. The NSE may stratify patients with severe brain injuries and identify those patients demonstrating "cognitive motor dissociation" (CMD) [26] who show only covert evidence of command following utilizing neuroimaging or electrophysiological methods that demand high levels of cognitive function. Thus, the NSE is a passive measure that may provide a useful screening tool to improve detection of covert cognition with fMRI or other methods and improve stratification of patients with disorders of consciousness in research studies.

Research on electroencephalogram to measure thermal pleasure in thermal alliesthesia in temperature step-change environment

Thermal pleasure is currently measured along psychological and physiological variables. However, in transient environments where temperatures change, it is hard to correlate psychological and physiological measures, because there is a delay in physiological changes. This study tests a method for correlating both measures using electroencephalogram (EEG), which can capture physiological feedback with a rapid response rate. In this experimental study, thermal pleasure was induced in a temperature step-change environment, one of non-uniform and transient environments. During the experiment, EEG was monitored and psychological responses of thermal sensation and thermal comfort votes were collected via survey questionnaire. A total of 50 males in their twenties participated in a climate chamber experiment. An experimental group of 25 men were exposed to temperature step-change between two different room conditions (32°C, 65% and 25°C, 50%), experiencing thermal pleasure. The control group of the remaining 25 men were exposed to an unchanging condition, experiencing thermal comfort close to thermal neutrality. The EEG spectral analysis demonstrated that EEG frequency band associated with pleasant emotional (theta) increased while frequency band related to pleasantness, satisfaction or relaxation (beta) decreased with thermal pleasure.

Responses of Patients with Disorders of Consciousness to Habit Stimulation: A Quantitative EEG Study

Whether habit stimulation is effective in DOC patient arousal has not been reported. In this paper, we analyzed the responses of DOC patients to habit stimulation. Nineteen DOC patients with alcohol consumption or smoking habits were recruited and 64-channel EEG signals were acquired both at the resting state and at three stimulation states. Wavelet transformation and nonlinear dynamics were used to extract the features of EEG signals and four brain lobes were selected to investigate the degree of EEG response to habit stimulation. Results showed that the highest degree of EEG response was from the call-name stimulation, followed by habit and music stimulations. Significant differences in EEG wavelet energy and response coefficient were found both between habit and music stimulation, and between habit and call-name stimulation. These findings prove that habit stimulation induces relatively more intense EEG responses in DOC patients than music stimulation, suggesting that it may be a relevant additional method for eliciting patient arousal.

Movement-Modulation of Local Power and Phase Amplitude Coupling in Bilateral Globus Pallidus Interna in Parkinson Disease

There is converging evidence that bilateral basal ganglia motor networks jointly support normal movement behaviors including unilateral movements. The extent and manner in which these networks interact during lateralized movement remains unclear. In this study, simultaneously recorded bilateral Globus Pallidus interna (GPi) local field potentials (LFP) were examined from 19 subjects with idiopathic Parkinson disease (PD), while undergoing awake deep brain stimulation (DBS) implantation. Recordings were carried out during two behavioral states; rest and cued left hand movement (finger tapping). The state-dependent effects on α- β oscillatory power and β phase-encoded phase amplitude coupling (PAC), including symmetrical and assymetrical changes between hemispheres, were identified. Unilateral hand movement resulted in symmetrical oscillatory power suppression within bilateral GPi at α (8-12 Hz) and high β (21-35 Hz) and increase in power of high frequency oscillations (HFO, 200-300 Hz) frequency bands. Asymmetrical attenuation was also observed at both low β (13-20 Hz) and low γ (40-80 Hz) bands within the contralateral GPi (P = 0.009). In addition, unilateral movement effects on PAC were confined to the contralateral GPi with attenuation of both low β-low γ and β-HFO PAC (P < 0.05). Further analysis showed that the lateralized attenuation of low β and low γ power did not correlate with low β-low γ PAC changes. The overall coherence between bilateral GPi was not significantly altered with unilateral movement, however the preferred phase difference in the high β range increased from 0.23 (±1.31) radians during rest to 1.99 (±0.78) radians during movement execution. Together, the present results suggest that unilateral motor control involves bilateral basal ganglia networks with movement features differentially encoded by distinct frequency bands. The lateralization of low β and low γ attenuation with movement suggests that these frequency bands are specific to the motor act whereas symmetrical expression of α, high β, and HFO oscillations best correspond to motor state. The restriction of movement-related PAC modulation to the contralateral GPi indicates that cross-frequency interactions appear to be associated with lateralized movements. Despite no significant movement-related changes in the interhemispheric coherence, the increase in phase difference suggests that the communication between bilateral GPi is altered with unilateral movement.

Towards using fNIRS recordings of mental arithmetic for the detection of residual cognitive activity in patients with disorders of consciousness (DOC)

BACKGROUND

Recently, fNIRS has been proposed as a promising approach for awareness detection, and a possible method to establish basic communication in patients with disorders of consciousness (DOC).

AIM

Using fNIRS, the present study evaluated the applicability of auditory presented mental-arithmetic tasks in this respect.

METHODS

We investigated the applicability of active attention to serial subtractions for awareness detection in ten healthy controls (HC, 21-32 y/o), by comparing the measured patterns to patterns induced by self-performance of the same task. Furthermore, we examined the suitability of ignoring the given task as additional control signal to implement a two-class brain-computer interface (BCI) paradigm. Finally, we compared our findings in HC with recordings in one DOC patient (78 y/o).

RESULTS AND CONCLUSION

Results of the HC revealed no differences between the self-performance and the attention condition, making the attention task suitable for awareness detection. However, there was no general difference between the ignore and attend condition, making the tasks less suitable for BCI control. Despite inconsistent correlations between the patient data and the HC group, single runs of the patient recordings revealed task-synchronous patterns - however, we cannot conclude whether the measured activation derives from instruction based task performance and thus awareness.

Characterization of EEG signals revealing covert cognition in the injured brain

See Boly and Laureys (doi:10.1093/brain/awy080) for a scientific commentary on this article.Patients with severe brain injury are difficult to assess and frequently subject to misdiagnosis. 'Cognitive motor dissociation' is a term used to describe a subset of such patients with preserved cognition as detected with neuroimaging methods but not evident in behavioural assessments. Unlike the locked-in state, cognitive motor dissociation after severe brain injury is prominently marked by concomitant injuries across the cerebrum in addition to limited or no motoric function. In the present study, we sought to characterize the EEG signals used as indicators of cognition in patients with disorders of consciousness and examine their reliability for potential future use to re-establish communication. We compared EEG-based assessments to the results of using similar methods with functional MRI. Using power spectral density analysis to detect EEG evidence of task performance (Two Group Test, P ≤ 0.05, with false discovery rate correction), we found evidence of the capacity to follow commands in 21 of 28 patients with severe brain injury and all 15 healthy individuals studied. We found substantial variability in the temporal and spatial characteristics of significant EEG signals among the patients in contrast to only modest variation in these domains across healthy controls; the majority of healthy controls showed suppression of either 8-12 Hz 'alpha' or 13-40 Hz 'beta' power during task performance, or both. Nine of the 21 patients with EEG evidence of command-following also demonstrated functional MRI evidence of command-following. Nine of the patients with command-following capacity demonstrated by EEG showed no behavioural evidence of a communication channel as detected by a standardized behavioural assessment, the Coma Recovery Scale - Revised. We further examined the potential contributions of fluctuations in arousal that appeared to co-vary with some patients' ability to reliably generate EEG signals in response to command. Five of nine patients with statistically indeterminate responses to one task tested showed a positive response after accounting for variations in overall background state (as visualized in the qualitative shape of the power spectrum) and grouping of trial runs with similar background state characteristics. Our findings reveal signal variations of EEG responses in patients with severe brain injuries and provide insight into the underlying physiology of cognitive motor dissociation. These results can help guide future efforts aimed at re-establishment of communication in such patients who will need customization for brain-computer interfaces.

Minimally conscious state or cortically mediated state?

Durable impairments of consciousness are currently classified in three main neurological categories: comatose state, vegetative state (also recently coined unresponsive wakefulness syndrome) and minimally conscious state. While the introduction of minimally conscious state, in 2002, was a major progress to help clinicians recognize complex non-reflexive behaviours in the absence of functional communication, it raises several problems. The most important issue related to minimally conscious state lies in its criteria: while behavioural definition of minimally conscious state lacks any direct evidence of patient's conscious content or conscious state, it includes the adjective 'conscious'. I discuss this major problem in this review and propose a novel interpretation of minimally conscious state: its criteria do not inform us about the potential residual consciousness of patients, but they do inform us with certainty about the presence of a cortically mediated state. Based on this constructive criticism review, I suggest three proposals aiming at improving the way we describe the subjective and cognitive state of non-communicating patients. In particular, I present a tentative new classification of impairments of consciousness that combines behavioural evidence with functional brain imaging data, in order to probe directly and univocally residual conscious processes.

Toward an Attention-Based Diagnostic Tool for Patients With Locked-in Syndrome

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 tool for patients with locked-in syndrome (LIS), answering the issues of accuracy and training requirement. Data from 20 healthy volunteers, 6 LIS patients, and 10 patients with a vegetative state/unresponsive wakefulness syndrome (VS/UWS) were included. Spectral entropy was computed during a gaze-independent 2-class (attention vs rest) paradigm, and compared with EEG rhythms (delta, theta, alpha, and beta) classification. Spectral entropy classification during the attention-rest paradigm showed 93% and 91% accuracy in healthy volunteers and LIS patients respectively. VS/UWS patients were at chance level. EEG rhythms classification reached a lower accuracy than spectral entropy. Resting-state EEG spectral entropy could not distinguish individual VS/UWS patients from LIS patients. The present study provides evidence that an EEG-based measure of attention could detect command-following in patients with severe motor disabilities. The entropy system could detect a response to command in all healthy subjects and LIS patients, while none of the VS/UWS patients showed a response to command using this system.

Pallidal deep brain stimulation modulates excessive cortical high β phase amplitude coupling in Parkinson disease

OBJECTIVE

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) and globus pallidus internus (GPi) are equally efficacious in the management of Parkinson disease (PD). Studies of STN-DBS have revealed a therapeutic reduction in excessive cortical β-γ phase-amplitude coupling (PAC). It is unclear whether this is specific to STN-DBS and potentially mediated by modulation of the hyperdirect pathway or if it is a generalizable mechanism seen with DBS of other targets. Moreover, it remains unclear how cortical signals are differentially modulated by movement versus therapy. To clarify, the effects of GPi-DBS and movement on cortical β power and β-γ PAC were examined.

METHODS

Right sensorimotor electrocorticographic signals were recorded in 10 PD patients undergoing GPi-DBS implantation surgery. We evaluated cortical β power and β-γ PAC during blocks of rest and contralateral hand movement (finger tapping) with GPi-DBS off and on.

RESULTS

Movement suppressed cortical low β power (P = 0.008) and high β-γ PAC (P = 0.028). Linear mixed effect modeling (LMEM) showed that power in low and high β bands are differentially modulated by movement (P = 0.022). GPi-DBS also results in a significant suppression of high β-γ PAC but without power modulation in either β sub-band (P = 0.008). Cortical high β-γ PAC is significantly correlated with severity of bradykinesia (Rho = 0.59, P = 0.045) and changes proportionally with therapeutic improvement (Rho = 0.61, P = 0.04).

CONCLUSIONS

Similar to STN-DBS, GPi-DBS reduces motor cortical β-γ PAC, like that also reported with dopaminergic mediations, suggesting it is a generalizable symptom biomarker in PD, independent of therapeutic target or proximity to the hyperdirect pathway.

Local changes in network structure contribute to late communication recovery after severe brain injury

Spontaneous recovery of brain function after severe brain injury may evolve over a long time period and is likely to involve both structural and functional reorganization of brain networks. We longitudinally tracked the recovery of communication in a patient with severe brain injury using multimodal brain imaging techniques and quantitative behavioral assessments measured at the bedside over a period of 2 years and 9 months (21 months after initial injury). Structural diffusion tensor imaging revealed changes in brain structure across interhemispheric connections and in local brain regions that support language and visuomotor function. These findings correlated with functional brain imaging using functional magnetic resonance imaging and positron emission tomography, which demonstrated increased language network recruitment in response to natural speech stimuli, graded increases in interhemispheric interactions of language-related frontal cortices, and increased cerebral metabolic activity in the language-dominant hemisphere. In addition, electrophysiological studies showed recovery of synchronization of sleep spindling activity. The observed changes suggest a specific mechanism for late recovery of communication after severe brain injury and provide support for the potential of activity-dependent structural and functional remodeling over long time periods.

Reforming the taxonomy in disorders of consciousness

This article examines the serious shortcomings that characterize the current taxonomy of postcomatose disorders of consciousness (DoC), and it provides guidelines for how an improved DoC taxonomy might be developed. In particular, it is argued that behavioral criteria for the application of DoC categories should be supplemented with brain-based criteria (eg, information derived from electroencephalography and functional magnetic resonance imaging), and that the categorical framework that currently characterizes DoC should be replaced by a multidimensional framework that better captures the performance of patients across a range of cognitive and behavioural tasks. Ann Neurol 2017;82:866-872.

Spectral signatures of activity-dependent neural feedback in the corticothalamic system

The modulation of neural quantities by presynaptic and postsynaptic activities via local feedback processes is investigated by incorporating nonlinear phenomena such as relative refractory period, synaptic enhancement, synaptic depression, and habituation. This is done by introducing susceptibilities, which quantify the response in either firing threshold or synaptic strength to unit change in either presynaptic or postsynaptic activity. Effects on the power spectra are then analyzed for a realistic corticothalamic model to determine the spectral signatures of various nonlinear processes and to what extent these are distinct. Depending on the feedback processes, there can be enhancements or reductions in low-frequency and/or alpha power, splitting of the alpha resonance, and/or appearance of new resonances at high frequencies. These features in the power spectra allow processes to be fully distinguished where they are unique, or partly distinguished if they are common to only a subset of feedbacks, and can potentially be used to constrain the types, strengths, and dynamics of feedbacks present.

Assessing pain in patients with chronic disorders of consciousness: Are we heading in the right direction?

The deterioration of sensory-motor integration within the pain matrix in patients with chronic Disorders of Consciousness (DoC) is one of the principal mechanisms responsible for non-conscious pain perception. The present study aimed to assess whether the variability in the inter-peak interval (IPI) between the N2 and P2 components of laser evoked potentials (LEP) could represent an objective marker of the behavioral responsiveness to nociceptive stimulation, as measured by the Nociception Coma Scale-Revised (NCS-R), and regardless of the sensory part of pain processing. We found that only IPI variability showed a significant correlation with NCS-R score, independently of the stimulation intensity (that influences the sensory part of pain processing). It was thus concluded that IPI variability might represent an objective measure of pain processing, which may help clinicians in the development of effective pain management strategies.

Group and individual analyses of pre-, peri-, and post-movement related alpha and beta oscillations during a single continuous monitoring task

Band power linked to lower and upper alpha (i.e. 8-10Hz; 10-12Hz) and lower and upper beta (i.e. 12-20Hz; 20-30Hz) were examined during response related stages, including anticipation, response execution (RE), response inhibition (RI) and post response recovery (PRR). Group and individual data from 34 participants were considered. The participant's objective was to press a response key immediately following 4 non-repeating, single integer odd digits. These were presented amongst a continuous stream of digits and Xs. Electroencephalogram (EEG) signals were recorded from 32 electrodes (pooled to 12 regions). In the group analyses, participant EEG response was compared to baseline revealing that upper alpha desynchronised during anticipation, RE and RI; lower beta during anticipation and RE; and upper beta just RE. Upper alpha desynchronisation during rapid, unplanned RI is novel. Also, upper alpha and lower/upper beta synchronised during PRR. For upper alpha, we speculate this indexes brief cortical deactivation; for beta we propose this indexes response set maintenance. Lastly, lower alpha fluctuations correlated negatively with RT, indexing neural efficiency. Individual analyses involved calculation of the proportion of individuals displaying the typical RE and PRR trends; these were not reflected by all participants. The former was displayed individually by the largest proportion in upper alpha recorded left fronto-centrally; the latter was most reliably displayed individually in lower beta recorded mid centro-parietally. Therefore, group analyses identified typical alpha and beta synchronisation/desynchronisation trends, whilst individual analyses identified their degree of representation in single participants. Attention is drawn to the clinical relevance of this issue.

Disorders of Consciousness

Disorder of consciousness (DOC) is a state of prolonged altered consciousness, which can be categorized into coma, vegetative state, or minimally conscious state based on neurobehavioral function. The pathophysiology of DOC is poorly understood but recent advances in neuroimaging and advanced electrophysiological techniques may provide an improved understanding for the neural network involved with consciousness. The primary aim of DOC rehabilitation programs is to promote arousal while preventing secondary medical complications while providing education and training to families. Treatment interventions include both pharmacologic and nonpharmacologic programs, but there are currently no consensus treatment guidelines for individuals with DOC.

Measures of metabolism and complexity in the brain of patients with disorders of consciousness

Background

Making an accurate diagnosis in patients with disorders of consciousness remains challenging. ¹⁸F-fluorodeoxyglucose (FDG)–PET has been validated as a diagnostic tool in this population, and allows identifying unresponsive patients with a capacity for consciousness. In parallel, the perturbational complexity index (PCI), a new measure based on the analysis of the electroencephalographic response to transcranial magnetic stimulation, has also been suggested as a tool to distinguish between unconscious and conscious states. The aim of the study was to cross-validate FDG–PET and PCI, and to identify signs of consciousness in otherwise unresponsive patients.

Methods

We jointly applied the Coma Recovery Scale-Revised, FDG–PET and PCI to assess 24 patients with non-acute disorders of consciousness or locked-in syndrome (13 male; 19–54 years old; 12 traumatic; 9 unresponsive wakefulness syndrome, 11 minimally conscious state; 2 emergence from the minimally conscious state, and 2 locked-in syndrome).

Results

FDG–PET and PCI provided congruent results in 22 patients, regardless of their behavioural diagnosis. Notably, FDG–PET and PCI revealed preserved metabolic rates and high complexity levels in four patients who were behaviourally unresponsive.

Conclusion

We propose that jointly measuring the metabolic activity and the electrophysiological complexity of cortical circuits is a useful complement to the diagnosis and stratification of patients with disorders of consciousness.

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A cross validation of brain complexity measures with metabolic imaging is proposed.

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TMS–EEG and ¹⁸F-FDG PET provided congruent result in post-comatose patients.

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Unresponsive patients with high complexity also show preserved metabolic activity.

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These patients thus probably have a specific cognitive-motor dissociation.

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TMS–EEG and PET have potential clinical impact in the diagnosis of these patients.

Executive attention deficits after traumatic brain injury reflect impaired recruitment of resources

Deficits in attention are a common and devastating consequence of traumatic brain injury (TBI), leading to functional impairments, rehabilitation barriers, and long-term disability. While such deficits are well documented, little is known about their underlying pathophysiology hindering development of effective and targeted interventions. Here we evaluate the integrity of brain systems specific to attentional functions using quantitative assessments of electroencephalography recorded during performance of the Attention Network Test (ANT), a behavioral paradigm that separates alerting, orienting, and executive components of attention. We studied 13 patients, at least 6 months post-TBI with cognitive impairments, and 24 control subjects. Based on performance on the ANT, TBI subjects showed selective impairment in executive attention. In TBI subjects, principal component analysis combined with spectral analysis of the EEG after target appearance extracted a pattern of increased frontal midline theta power (2.5–7.5 Hz) and suppression of frontal beta power (12.5–22.5 Hz). Individual expression of this pattern correlated (r = − 0.67, p < 0.001) with executive attention impairment. The grading of this pattern of spatiotemporal dynamics with executive attention deficits reflects impaired recruitment of anterior forebrain resources following TBI; specifically, deafferentation and variable disfacilitation of medial frontal neuronal populations is proposed as the basis of our findings.

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Electrophysiological correlate of impaired executive attention after Traumatic Brain Injury is derived.

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Theta increases in medial frontal and beta suppression in frontal regions is linked to behavioral performance.

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Individual-specific pathophysiology allows for tracking of recovery/interventions and studies of function-structure.

Multidimensional cognitive evaluation of patients with disorders of consciousness using EEG: A proof of concept study

The use of cognitive evoked potentials in EEG is now part of the routine evaluation of non-communicating patients with disorders of consciousness in several specialized medical centers around the world. They typically focus on one or two cognitive markers, such as the mismatch negativity or the P3 to global auditory regularity. However it has become clear that none of these markers in isolation is at the same time sufficiently specific and sufficiently sensitive to be taken as the unique gold standard for diagnosing consciousness. A good way forward would be to combine several cognitive markers within the same test to improve evaluation. Furthermore, given the diversity of lesions leading to disorders of consciousness, it is important not only to probe whether a patient is conscious or not, but also to establish a more general and nuanced profile of the residual cognitive capacities of each patient using a combination of markers.

In the present study we built a unique EEG protocol that probed 8 dimensions of cognitive processing in a single 1.5 h session. This protocol probed variants of classical markers together with new markers of spatial attention, which has not yet been studied in these patients. The eight dimensions were: (1) own name recognition, (2) temporal attention, (3) spatial attention, (4) detection of spatial incongruence (5) motor planning, and (6,7,8) modulations of these effects by the global context, reflecting higher-level functions. This protocol was tested in 15 healthy control subjects and in 17 patients with various etiologies, among which 13 could be included in the analysis. The results in the control group allowed a validation and a specific description of the cognitive levels probed by each marker. At the single-subject level, this combined protocol allowed assessing the presence of both classical and newly introduced markers for each patient and control, and revealed that the combination of several markers increased diagnostic sensitivity. The presence of a high-level effect in any of the three tested domains distinguished between minimally conscious and vegetative patients, while the presence of low-level effects was similar in both groups. In summary, this study constitutes a validated proof of concept in favor of probing multiple cognitive dimensions to improve the evaluation of non-communicating patients. At a more conceptual level, this EEG tool can help achieve a better understanding of disorders of consciousness by exploring consciousness in its multiple cognitive facets.

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This new EEG protocol probes 8 cognitive functions within a single 1.5 h session.

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It allows a complete neuropsychological evaluation only based on brain activity.

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It increases sensitivity in detecting both low-level and high-level functions in patients.

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Only the high-level functions distinguish minimally conscious from vegetative states.

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Multidimensional EEG testing is feasible in patients and can improve evaluation.

EEG and fMRI agree: Mental arithmetic is the easiest form of imagery to detect

fMRI and EEG during mental imagery provide alternative methods of detecting awareness in patients with disorders of consciousness (DOC) without reliance on behaviour. Because using fMRI in patients with DOC is difficult, studies increasingly employ EEG. However, there has been no verification that these modalities provide converging information at the individual subject level. The present study examined simultaneous EEG and fMRI in healthy volunteers during six mental imagery tasks to determine whether one mental imagery task generates more robust activation across subjects; whether activation can be predicted from familiarity with the imagined activity; and whether EEG and fMRI converge upon the same conclusions about individual imagery performance. Mental arithmetic generated the most robust activation in the majority of subjects for both EEG and fMRI, and level of activation could not be predicted from familiarity, with either modality. We conclude that overall, EEG and fMRI agree regarding individual mental imagery performance.

Bedside quantitative electroencephalography improves assessment of consciousness in comatose subarachnoid hemorrhage patients

OBJECTIVE

Accurate behavioral assessments of consciousness carry tremendous significance in guiding management, but are extremely challenging in acutely brain-injured patients. We evaluated whether electroencephalography (EEG) and multimodality monitoring parameters may facilitate assessment of consciousness in patients with subarachnoid hemorrhage.

METHODS

A retrospective analysis was performed of 83 consecutively treated adults with subarachnoid hemorrhage. All patients were initially comatose and had invasive brain monitoring placed. Behavioral assessments were performed during daily interruption of sedation and categorized into 3 groups based on their best examination as (1) comatose, (2) arousable (eye opening or attending toward a stimulus), and (3) aware (command following). EEG features included spectral power and complexity measures. Comparisons were made using bootstrapping methods and partial least squares regression.

RESULTS

We identified 389 artifact-free EEG clips following behavioral assessments. Increasing central gamma, posterior alpha, and diffuse theta-delta oscillations differentiated patients who were arousable from those in coma. Command following was characterized by a further increase in central gamma and posterior alpha, as well as an increase in alpha permutation entropy. These EEG features together with basic neurological examinations (eg, pupillary light reflex) contributed heavily to a linear model predicting behavioral state, whereas brain physiology measures (eg, brain oxygenation), structural injury, and clinical course added less.

INTERPRETATION

EEG measures of behavioral states provide distinctive signatures that complement behavioral assessments of patients with subarachnoid hemorrhage shortly after the injury. Our data support the hypothesis that impaired connectivity of cortex with both central thalamus and basal forebrain underlies decreasing levels of consciousness. Ann Neurol 2016;80:541-553.

Relative Values: Perspectives on a Neuroimaging Technology From Above and Within the Ethical Landscape

In this paper we contribute to "sociology in bioethics" and help clarify the range of ways sociological work can contribute to ethics scholarship. We do this using a case study of an innovative neurotechnology, functional magnetic resonance imaging, and its use to attempt to diagnose and communicate with severely brain-injured patients. We compare empirical data from interviews with relatives of patients who have a severe brain injury with perspectives from mainstream bioethics scholars. We use the notion of an "ethical landscape" as an analogy for the different ethical positions subjects can take-whereby a person's position relative to the landscape makes a difference to the way they experience and interact with it. We show that, in comparison to studying abstract ethics "from above" the ethical landscape, which involves universal generalizations and global judgements, studying ethics empirically "from the ground," within the ethical landscape foregrounds a more plural and differentiated picture. We argue it is important not to treat empirical ethics as secondary to abstract ethics, to treat on-the-ground perspectives as useful only insofar as they can inform ethics from above. Rather, empirical perspectives can illuminate the plural vantage points in ethical judgments, highlight the "lived" nature of ethical reasoning, and point to all ethical vantage points as being significant. This is of epistemic importance to normative ethics, since researchers who pay attention to the various positions in and trajectories through the ethical landscape are unlikely to think about ethics in terms of abstract agency-as can happen with top-down ethics-or to elide agency with the agency of policymakers. Moreover, empirical perspectives may have transformative implications for people on the ground, especially where focus on the potential harms and benefits they face brings their experiences and interests to the forefront of ethical and policy discussion.

Somatosensory attention identifies both overt and covert awareness in disorders of consciousness

OBJECTIVE

Some patients diagnosed with disorders of consciousness retain sensory and cognitive abilities beyond those apparent from their overt behavior. Characterizing these covert abilities is crucial for diagnosis, prognosis, and medical ethics. This multimodal study investigates the relationship between electroencephalographic evidence for perceptual/cognitive preservation and both overt and covert markers of awareness.

METHODS

Fourteen patients with severe brain injuries were evaluated with an electroencephalographic vibrotactile attention task designed to identify a hierarchy of residual somatosensory and cognitive abilities: (1) somatosensory steady-state evoked responses, (2) bottom-up attention orienting (P3a event-related potential), and (3) top-down attention (P3b event-related potential). Each patient was also assessed with a clinical behavioral scale and 2 functional magnetic resonance imaging assessments of covert command following.

RESULTS

Six patients produced only sensory responses, with no evidence of cognitive event-related potentials. A further 8 patients demonstrated reliable bottom-up attention-orienting responses (P3a). No patient showed evidence of top-down attention (P3b). Only those patients who followed commands, whether overtly with behavior or covertly with functional neuroimaging, also demonstrated event-related potential evidence of attentional orienting.

INTERPRETATION

Somatosensory attention-orienting event-related potentials differentiated patients who could follow commands from those who could not. Crucially, this differentiation was irrespective of whether command following was evident through overt external behavior, or through covert functional neuroimaging methods. Bedside electroencephalographic methods may corroborate more expensive and challenging methods such as functional neuroimaging, and thereby assist in the accurate diagnosis of awareness. Ann Neurol 2016;80:412-423.

Evaluation of induced and evoked changes in EEG during selective attention to verbal stimuli

BACKGROUND

Two challenges need to be addressed before bringing non-motor mental tasks for brain-computer interface (BCI) control to persons in a minimally conscious state (MCS), who can be behaviorally unresponsive even when proven to be consciously aware: first, keeping the cognitive demands as low as possible so that they could be fulfilled by persons with MCS. Second, increasing the control of experimental protocol (i.e. type and timing of the task performance).

NEW METHOD

The goal of this study is twofold: first goal is to develop an experimental paradigm that can facilitate the performance of brain-teasers (e.g. mental subtraction and word generation) on the one hand, and can increase the control of experimental protocol on the other hand. The second goal of this study is to exploit the similar findings for mentally attending to someone else's verbal performance of brain-teaser tasks and self-performing the same tasks to setup an online BCI, and to compare it in healthy participants to the current "state-of-the-art" motor imagery (MI, sports).

RESULTS

The response accuracies for the best performing healthy participants indicate that selective attention to verbal performance of mental subtraction (SUB) is a viable alternative to the MI. Time-frequency analysis of the SUB task in one participant with MCS did not reveal any significant (p<0.05) EEG changes, whereas imagined performance of one sport of participants' choice (SPORT) revealed task-related EEG changes over neurophysiological plausible cortical areas.

COMPARISON WITH EXISTING METHODS

We found that mentally attending to someone else's verbal performance of brain-teaser tasks leads to similar results as in self-performing the same tasks.

CONCLUSIONS

In this work we demonstrated that a single auditory selective attention task (i.e. mentally attending to someone else's verbal performance of mental subtraction) can modulate both induced and evoked changes in EEG, and be used for yes/no communication in an auditory scanning paradigm.

Isolation Syndrome after Cardiac Arrest and Therapeutic Hypothermia

Here, we present the first description of an isolation syndrome in a patient who suffered prolonged cardiac arrest and underwent a standard therapeutic hypothermia protocol. Two years after the arrest, the patient demonstrated no motor responses to commands, communication capabilities, or visual tracking at the bedside. However, resting neuronal metabolism and electrical activity across the entire anterior forebrain was found to be normal despite severe structural injuries to primary motor, parietal, and occipital cortices. In addition, using quantitative electroencephalography, the patient showed evidence for willful modulation of brain activity in response to auditory commands revealing covert conscious awareness. A possible explanation for this striking dissociation in this patient is that altered neuronal recovery patterns following therapeutic hypothermia may lead to a disproportionate preservation of anterior forebrain cortico-thalamic circuits even in the setting of severe hypoxic injury to other brain areas. Compared to recent reports of other severely brain-injured subjects with such dissociation of clinically observable (overt) and covert behaviors, we propose that this case represents a potentially generalizable mechanism producing an isolation syndrome of blindness, motor paralysis, and retained cognition as a sequela of cardiac arrest and therapeutic hypothermia. Our findings further support that highly-preserved anterior cortico-thalamic integrity is associated with the presence of conscious awareness independent from the degree of injury to other brain areas.