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

Neuroimaging biomarkers for the diagnosis and prognosis of patients with disorders of consciousness

The progress in neuroimaging and electrophysiological techniques has shown substantial promise in improving the clinical assessment of disorders of consciousness (DOC). Through the examination of both stimulus-induced and spontaneous brain activity, numerous comprehensive investigations have explored variations in brain activity patterns among patients with DOC, yielding valuable insights for clinical diagnosis and prognostic purposes. Nonetheless, reaching a consensus on precise neuroimaging biomarkers for patients with DOC remains a challenge. Therefore, in this review, we begin by summarizing the empirical evidence related to neuroimaging biomarkers for DOC using various paradigms, including active, passive, and resting-state approaches, by employing task-based fMRI, resting-state fMRI (rs-fMRI), electroencephalography (EEG), and positron emission tomography (PET) techniques. Subsequently, we conducted a review of studies examining the neural correlates of consciousness in patients with DOC, with the findings holding potential value for the clinical application of DOC. Notably, previous research indicates that neuroimaging techniques have the potential to unveil covert awareness that conventional behavioral assessments might overlook. Furthermore, when integrated with various task paradigms or analytical approaches, this combination has the potential to significantly enhance the accuracy of both diagnosis and prognosis in DOC patients. Nonetheless, the stability of these neural biomarkers still needs additional validation, and future directions may entail integrating diagnostic and prognostic methods with big data and deep learning approaches.

Recovery of consciousness after acute brain injury: a narrative review

BACKGROUND

Disorders of consciousness (DoC) are frequently encountered in both, acute and chronic brain injuries. In many countries, early withdrawal of life-sustaining treatments is common practice for these patients even though the accuracy of predicting recovery is debated and delayed recovery can be seen. In this review, we will discuss theoretical concepts of consciousness and pathophysiology, explore effective strategies for management, and discuss the accurate prediction of long-term clinical outcomes. We will also address research challenges.

MAIN TEXT

DoC are characterized by alterations in arousal and/or content, being classified as coma, unresponsive wakefulness syndrome/vegetative state, minimally conscious state, and confusional state. Patients with willful modulation of brain activity detectable by functional MRI or EEG but not by behavioral examination is a state also known as covert consciousness or cognitive motor dissociation. This state may be as common as every 4th or 5th patient without behavioral evidence of verbal command following and has been identified as an independent predictor of long-term functional recovery. Underlying mechanisms are uncertain but intact arousal and thalamocortical projections maybe be essential. Insights into the mechanisms underlying DoC will be of major importance as these will provide a framework to conceptualize treatment approaches, including medical, mechanical, or electoral brain stimulation.

CONCLUSIONS

We are beginning to gain insights into the underlying mechanisms of DoC, identifying novel advanced prognostication tools to improve the accuracy of recovery predictions, and are starting to conceptualize targeted treatments to support the recovery of DoC patients. It is essential to determine how these advancements can be implemented and benefit DoC patients across a range of clinical settings and global societal systems. The Curing Coma Campaign has highlighted major gaps knowledge and provides a roadmap to advance the field of coma science with the goal to support the recovery of patients with DoC.

Covert Consciousness in the ICU

OBJECTIVES

For critically ill patients with acute severe brain injuries, consciousness may reemerge before behavioral responsiveness. The phenomenon of covert consciousness (i.e., cognitive motor dissociation) may be detected by advanced neurotechnologies such as task-based functional MRI (fMRI) and electroencephalography (EEG) in patients who appear unresponsive on the bedside behavioral examination. In this narrative review, we summarize the state-of-the-science in ICU detection of covert consciousness. Further, we consider the prognostic and therapeutic implications of diagnosing covert consciousness in the ICU, as well as its potential to inform discussions about continuation of life-sustaining therapy for patients with severe brain injuries.

DATA SOURCES

We reviewed salient medical literature regarding covert consciousness.

STUDY SELECTION

We included clinical studies investigating the diagnostic performance characteristics and prognostic utility of advanced neurotechnologies such as task-based fMRI and EEG. We focus on clinical guidelines, professional society scientific statements, and neuroethical analyses pertaining to the implementation of advanced neurotechnologies in the ICU to detect covert consciousness.

DATA EXTRACTION AND DATA SYNTHESIS

We extracted study results, guideline recommendations, and society scientific statement recommendations regarding the diagnostic, prognostic, and therapeutic relevance of covert consciousness to the clinical care of ICU patients with severe brain injuries.

CONCLUSIONS

Emerging evidence indicates that covert consciousness is present in approximately 15-20% of ICU patients who appear unresponsive on behavioral examination. Covert consciousness may be detected in patients with traumatic and nontraumatic brain injuries, including patients whose behavioral examination suggests a comatose state. The presence of covert consciousness in the ICU may predict the pace and extent of long-term functional recovery. Professional society guidelines now recommend assessment of covert consciousness using task-based fMRI and EEG. However, the clinical criteria for patient selection for such investigations are uncertain and global access to advanced neurotechnologies is limited.

Cognitive Motor Dissociation in Disorders of Consciousness

BACKGROUND

Patients with brain injury who are unresponsive to commands may perform cognitive tasks that are detected on functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). This phenomenon, known as cognitive motor dissociation, has not been systematically studied in a large cohort of persons with disorders of consciousness.

METHODS

In this prospective cohort study conducted at six international centers, we collected clinical, behavioral, and task-based fMRI and EEG data from a convenience sample of 353 adults with disorders of consciousness. We assessed the response to commands on task-based fMRI or EEG in participants without an observable response to verbal commands (i.e., those with a behavioral diagnosis of coma, vegetative state, or minimally conscious state-minus) and in participants with an observable response to verbal commands. The presence or absence of an observable response to commands was assessed with the use of the Coma Recovery Scale-Revised (CRS-R).

RESULTS

Data from fMRI only or EEG only were available for 65% of the participants, and data from both fMRI and EEG were available for 35%. The median age of the participants was 37.9 years, the median time between brain injury and assessment with the CRS-R was 7.9 months (25% of the participants were assessed with the CRS-R within 28 days after injury), and brain trauma was an etiologic factor in 50%. We detected cognitive motor dissociation in 60 of the 241 participants (25%) without an observable response to commands, of whom 11 had been assessed with the use of fMRI only, 13 with the use of EEG only, and 36 with the use of both techniques. Cognitive motor dissociation was associated with younger age, longer time since injury, and brain trauma as an etiologic factor. In contrast, responses on task-based fMRI or EEG occurred in 43 of 112 participants (38%) with an observable response to verbal commands.

CONCLUSIONS

Approximately one in four participants without an observable response to commands performed a cognitive task on fMRI or EEG as compared with one in three participants with an observable response to commands. (Funded by the James S. McDonnell Foundation and others.).

Impact of Aphasia on Brain Activation to Motor Commands in Patients with Acute Intracerebral Hemorrhage

BACKGROUND

Brain activation to motor commands is seen in 15% of clinically unresponsive patients with acute brain injury. This state called cognitive motor dissociation (CMD) is detectable by electroencephalogram (EEG) or functional magnetic resonance imaging, predicts long-term recovery, and is recommended by recent guidelines to support prognostication. However, false negative CMD results are a particular concern, and occult aphasia in clinically unresponsive patients may be a major factor. This study aimed to quantify the impact of aphasia on CMD testing.

METHODS

We prospectively studied 61 intensive care unit patients admitted with acute primary intracerebral hemorrhage (ICH) who had behavioral evidence of command following or were able to mimic motor commands. All patients underwent an EEG-based motor command paradigm used to detect CMD and comprehensive aphasia assessments. Logistic regression was used to identify predictors of brain activation, including aphasia types and associations with recovery of independence (Glasgow Outcome Scale-Extended score ≥ 4).

RESULTS

Of 61 patients, 50 completed aphasia and the EEG-based motor command paradigm. A total of 72% (n = 36) were diagnosed with aphasia. Patients with impaired comprehension (i.e., receptive or global aphasia) were less likely to show brain activation than those with intact comprehension (odds ratio [OR] 0.23 [95% confidence interval 0.05-0.89], p = 0.04). Brain activation was independently associated with Glasgow Outcome Scale-Extended ≥ 4 by 12 months (OR 2.4 [95% confidence interval 1.2-5.0], p = 0.01) accounting for the Functional Outcome in Patients with Primary ICH score (OR1.3 [95% confidence interval 1.0-1.8], p = 0.01).

CONCLUSIONS

Brain activation to motor commands is four times less likely for patients with primary ICH with impaired comprehension. False negative results due to occult receptive aphasia need to be considered when interpreting CMD testing. Early detection of brain activation may help predict long-term recovery in conscious patients with ICH.

Globus pallidus externus drives increase in network-wide alpha power with propofol-induced loss-of-consciousness in humans

States of consciousness are likely mediated by multiple parallel yet interacting cortico-subcortical recurrent networks. Although the mesocircuit model has implicated the pallidocortical circuit as one such network, this circuit has not been extensively evaluated to identify network-level electrophysiological changes related to loss of consciousness (LOC). We characterize changes in the mesocircuit in awake versus propofol-induced LOC in humans by directly simultaneously recording from sensorimotor cortices (S1/M1) and globus pallidus interna and externa (GPi/GPe) in 12 patients with Parkinson disease undergoing deep brain stimulator implantation. Propofol-induced LOC is associated with increases in local power up to 20 Hz in GPi, 35 Hz in GPe, and 100 Hz in S1/M1. LOC is likewise marked by increased pallidocortical alpha synchrony across all nodes, with increased alpha/low beta Granger causal (GC) flow from GPe to all other nodes. In contrast, LOC is associated with decreased network-wide beta coupling and beta GC from M1 to the rest of the network. Results implicate an important and possibly central role of GPe in mediating LOC-related increases in alpha power, supporting a significant role of the GPe in modulating cortico-subcortical circuits for consciousness. Simultaneous LOC-related suppression of beta synchrony highlights that distinct oscillatory frequencies act independently, conveying unique network activity.

Long-term HD-tDCS modulates dynamic changes of brain activity on patients with disorders of consciousness: A resting-state EEG study

OBJECTIVE

High-definition transcranial direct current stimulation (HD-tDCS) has been an effective neurostimulation method in the treatment of disorders of consciousness (DOC). However, the effects and mechanism of HD-tDCS are still unclear.

METHODS

This study recruited 8 DOC patients and applied 20-min sessions of 2 mA HD-tDCS (central anode electrode at Pz) for 14 consecutive days. We record DOC patients' EEG data and Coma Recovery Scale-Revised (CRS-R) values at four time point: baseline (T0), after 1 day's and 7,14 days' parietal HD-tDCS treatment (T1, T2, T3). Power spectral density (PSD), relative power (RP), spectral entropy and spectral exponent were calculated to evaluate the EEG dynamic changes of DOC patients during long-term parietal HD-tDCS. At last, we calculated the correlation between changes of EEG features and changes of CRS-R values.

RESULT

After 1 day's parietal HD-tDCS, DOC patients' CRS-R value had not changed (8.25 ± 1.91). HD-tDCS improved DOC patients' CRS-R value at T2 (9.75 ± 1.91, p < 0.05) and at T3 (11.38 ± 2.77, p < 0.05), compared with that at T0 (8.25 ± 1.91). As the treatment time increased, the EEG PSD decayed more slowly. Specifically, the delta frequency band RP decreased, while the alpha, beta, and gamma frequency bands RP increased. EEG oscillation characteristics changed but not significant at T1 (p > 0.05), and showed significant changes at T2 and T3 (p < 0.05). The spectral entropy continuously increased and the spectral exponent continuously decreased from T0 to T3. Specifically, the spectral entropy and spectral exponent of the parietal and occipital regions were significantly higher at T2 and T3 than that at T0 (p < 0.05). In addition, The changes in EEG features of the parietal and occipital lobes were correlated with changes in CRS-R value, especially between T2 and T0.

CONCLUSION

Long-term parietal HD-tDCS can improve the consciousness level and brain activity in DOC patients. Resting-state EEG can evaluate the dynamic changes of brain activity in DOC patients during HD-tDCS. EEG oscillation and non-oscillatory activity might be used to explain the mechanism of HD-tDCS on DOC patients.

Covert cortical processing: a diagnosis in search of a definition

Historically, clinical evaluation of unresponsive patients following brain injury has relied principally on serial behavioral examination to search for emerging signs of consciousness and track recovery. Advances in neuroimaging and electrophysiologic techniques now enable clinicians to peer into residual brain functions even in the absence of overt behavioral signs. These advances have expanded clinicians' ability to sub-stratify behaviorally unresponsive and seemingly unaware patients following brain injury by querying and classifying covert brain activity made evident through active or passive neuroimaging or electrophysiologic techniques, including functional MRI, electroencephalography (EEG), transcranial magnetic stimulation-EEG, and positron emission tomography. Clinical research has thus reciprocally influenced clinical practice, giving rise to new diagnostic categories including cognitive-motor dissociation (i.e. 'covert consciousness') and covert cortical processing (CCP). While covert consciousness has received extensive attention and study, CCP is relatively less understood. We describe that CCP is an emerging and clinically relevant state of consciousness marked by the presence of intact association cortex responses to environmental stimuli in the absence of behavioral evidence of stimulus processing. CCP is not a monotonic state but rather encapsulates a spectrum of possible association cortex responses from rudimentary to complex and to a range of possible stimuli. In constructing a roadmap for this evolving field, we emphasize that efforts to inform clinicians, philosophers, and researchers of this condition are crucial. Along with strategies to sensitize diagnostic criteria and disorders of consciousness nosology to these vital discoveries, democratizing access to the resources necessary for clinical identification of CCP is an emerging clinical and ethical imperative.

Cognitive Motor Dissociation: Gap Analysis and Future Directions

BACKGROUND

Patients with disorders of consciousness who are behaviorally unresponsive may demonstrate volitional brain responses to motor imagery or motor commands detectable on functional magnetic resonance imaging or electroencephalography. This state of cognitive motor dissociation (CMD) may have prognostic significance.

METHODS

The Neurocritical Care Society's Curing Coma Campaign identified an international group of experts who convened in a series of monthly online meetings between September 2021 and April 2023 to examine the science of CMD and identify key knowledge gaps and unmet needs.

RESULTS

The group identified major knowledge gaps in CMD research: (1) lack of information about patient experiences and caregiver accounts of CMD, (2) limited epidemiological data on CMD, (3) uncertainty about underlying mechanisms of CMD, (4) methodological variability that limits testing of CMD as a biomarker for prognostication and treatment trials, (5) educational gaps for health care personnel about the incidence and potential prognostic relevance of CMD, and (6) challenges related to identification of patients with CMD who may be able to communicate using brain-computer interfaces.

CONCLUSIONS

To improve the management of patients with disorders of consciousness, research efforts should address these mechanistic, epidemiological, bioengineering, and educational gaps to enable large-scale implementation of CMD assessment in clinical practice.

Covert consciousness

Covert consciousness is a state of residual awareness following severe brain injury or neurological disorder that evades routine bedside behavioral detection. Patients with covert consciousness have preserved awareness but are incapable of self-expression through ordinary means of behavior or communication. Growing recognition of the limitations of bedside neurobehavioral examination in reliably detecting consciousness, along with advances in neurotechnologies capable of detecting brain states or subtle signs indicative of consciousness not discernible by routine examination, carry promise to transform approaches to classifying, diagnosing, prognosticating and treating disorders of consciousness. Here we describe and critically evaluate the evolving clinical category of covert consciousness, including approaches to its diagnosis through neuroimaging, electrophysiology, and novel behavioral tools, its prognostic relevance, and open questions pertaining to optimal clinical management of patients with covert consciousness recovering from severe brain injury.

Relationship between individual differences in pain empathy and task- and resting-state EEG

Pain empathy is a complex form of psychological inference that enables us to understand how others feel in the context of pain. Since pain empathy may be grounded in our own pain experiences, it exhibits huge inter-individual variability. However, the neural mechanisms behind the individual differences in pain empathy and its association with pain perception are still poorly understood. In this study, we aimed to characterize brain mechanisms associated with individual differences in pain empathy in adult participants (n = 24). The 32-channel electroencephalography (EEG) was recorded at rest and during a pain empathy task, and participants viewed static visual stimuli of the limbs submitted to painful and nonpainful stimulation to solicit empathy. The pain sensitivity of each participant was measured using a series of direct current stimulations. In our results, the N2 of Fz and the LPP of P3 and P4 were affected by painful pictures. We found that both delta and alpha bands in the frontal and parietal cortex were involved in the regulation of pain empathy. For the delta band, a close relationship was found between average power, either in the resting or task state, and individual differences in pain empathy. It suggested that the spectral power in Fz's delta band may reflect subjective pain empathy across individuals. For the alpha band, the functional connectivity between Fz and P3 under painful picture stimulation was correlated to individuals' pain sensitivity. It indicated that the alpha band may reflect individual differences in pain sensitivity and be involved in pain empathy processing. Our results suggested the distinct role of the delta and alpha bands of EEG signals in pain empathy processing and may deepen our understanding of the neural mechanisms underpinning pain empathy.

Injury patterns associated with cognitive motor dissociation

In unconscious appearing patients with acute brain injury, wilful brain activation to motor commands without behavioural signs of command following, known as cognitive motor dissociation (CMD), is associated with functional recovery. CMD can be detected by applying machine learning to EEG recorded during motor command presentation in behaviourally unresponsive patients. Identifying patients with CMD carries clinical implications for patient interactions, communication with families, and guidance of therapeutic decisions but underlying mechanisms of CMD remain unknown. By analysing structural lesion patterns and network level dysfunction we tested the hypothesis that, in cases with preserved arousal and command comprehension, a failure to integrate comprehended motor commands with motor outputs underlies CMD. Manual segmentation of T2-fluid attenuated inversion recovery and diffusion weighted imaging sequences quantifying structural injury was performed in consecutive unresponsive patients with acute brain injury (n = 107) who underwent EEG-based CMD assessments and MRI. Lesion pattern analysis was applied to identify lesion patterns common among patients with (n = 21) and without CMD (n = 86). Thalamocortical and cortico-cortical network connectivity were assessed applying ABCD classification of power spectral density plots and weighted pairwise phase consistency (WPPC) to resting EEG, respectively. Two distinct structural lesion patterns were identified on MRI for CMD and three for non-CMD patients. In non-CMD patients, injury to brainstem arousal pathways including the midbrain were seen, while no CMD patients had midbrain lesions. A group of non-CMD patients was identified with injury to the left thalamus, implicating possible language comprehension difficulties. Shared lesion patterns of globus pallidus and putamen were seen for a group of CMD patients, which have been implicated as part of the anterior forebrain mesocircuit in patients with reversible disorders of consciousness. Thalamocortical network dysfunction was less common in CMD patients [ABCD-index 2.3 (interquartile range, IQR 2.1-3.0) versus 1.4 (IQR 1.0-2.0), P < 0.0001; presence of D 36% versus 3%, P = 0.0006], but WPPC was not different. Bilateral cortical lesions were seen in patients with and without CMD. Thalamocortical disruption did not differ for those with CMD, but long-range WPPC was decreased in 1-4 Hz [odds ratio (OR) 0.8; 95% confidence interval (CI) 0.7-0.9] and increased in 14-30 Hz frequency ranges (OR 1.2; 95% CI 1.0-1.5). These structural and functional data implicate a failure of motor command integration at the anterior forebrain mesocircuit level with preserved thalamocortical network function for CMD patients with subcortical lesions. Amongst patients with bilateral cortical lesions preserved cortico-cortical network function is associated with CMD detection. These data may allow screening for CMD based on widely available structural MRI and resting EEG.

Cerebral electrometabolic coupling in disordered and normal states of consciousness

We assess cerebral integrity with cortical and subcortical FDG-PET and cortical electroencephalography (EEG) within the mesocircuit model framework in patients with disorders of consciousness (DoCs). The mesocircuit hypothesis proposes that subcortical activation facilitates cortical function. We find that the metabolic balance of subcortical mesocircuit areas is informative for diagnosis and is associated with four EEG-based power spectral density patterns, cortical metabolism, and α power in healthy controls and patients with a DoC. Last, regional electrometabolic coupling at the cortical level can be identified in the θ and α ranges, showing positive and negative relations with glucose uptake, respectively. This relation is inverted in patients with a DoC, potentially related to altered orchestration of neural activity, and may underlie suboptimal excitability states in patients with a DoC. By understanding the neurobiological basis of the pathophysiology underlying DoCs, we foresee translational value for diagnosis and treatment of patients with a DoC.

Naturalistic auditory stimuli with fNIRS prefrontal cortex imaging: A potential paradigm for disorder of consciousness diagnostics (a study with healthy participants)

Disorder of consciousness (DOC) is a devastating condition due to brain damage. A patient in this condition is non-responsive, but nevertheless might be conscious at least at some level. Determining the conscious level of DOC patients is important for both medical and ethical reasons, but reliably achieving this has been a major challenge. Naturalistic stimuli in combination with neuroimaging have been proposed as a promising approach for DOC patient diagnosis. Capitalizing on and extending this proposal, the goal of the present study conducted with healthy participants was to develop a new paradigm with naturalistic auditory stimuli and functional near-infrared spectroscopy (fNIRS) - an approach that can be used at the bedside. Twenty-four healthy participants passively listened to 9 min of auditory story, scrambled auditory story, classical music, and scrambled classical music segments while their prefrontal cortex activity was recorded using fNIRS. We found much higher intersubject correlation (ISC) during story compared to scrambled story conditions both at the group level and in the majority of individual subjects, suggesting that fNIRS imaging of the prefrontal cortex might be a sensitive method to capture neural changes associated with narrative comprehension. In contrast, the ISC during the classical music segment did not differ reliably from scrambled classical music and was also much lower than the story condition. Our main result is that naturalistic auditory stories with fNIRS might be used in a clinical setup to identify high-level processing and potential consciousness in DOC patients.

The Current of Consciousness: Neural Correlates and Clinical Aspects

PURPOSE OF REVIEW

In this review, we summarize the current understanding of consciousness including its neuroanatomic basis. We discuss major theories of consciousness, physical exam-based and electroencephalographic metrics used to stratify levels of consciousness, and tools used to shed light on the neural correlates of the conscious experience. Lastly, we review an expanded category of 'disorders of consciousness,' which includes disorders that impact either the level or experience of consciousness.

RECENT FINDINGS

Recent studies have revealed many of the requisite EEG, ERP, and fMRI signals to predict aspects of the conscious experience. Neurological disorders that disrupt the reticular activating system can affect the level of consciousness, whereas cortical disorders from seizures and migraines to strokes and dementia may disrupt phenomenal consciousness. The recently introduced memory theory of consciousness provides a new explanation of phenomenal consciousness that may explain better than prior theories both experimental studies and the neurologist's clinical experience. Although the complete neurobiological basis of consciousness remains a mystery, recent advances have improved our understanding of the physiology underlying level of consciousness and phenomenal consciousness.

The effect of neural pre-stimulus oscillations on post-stimulus somatosensory event-related potentials in disorders of consciousness

Brain activity of people in a disorder of consciousness (DoC) is diffuse and different from healthy people. In order to get a better understanding of their cognitive processes and functions, electroencephalographic activity has often been examined in patients with DoC, including detection of event-related potentials (ERPs) and spectral power analysis. However, the relationship between pre-stimulus oscillations and post-stimulus ERPs has rarely been explored in DoC, although it is known from healthy participants that pre-stimulus oscillations predispose subsequent stimulus detection. Here, we examine to what extent pre-stimulus electroencephalography band power in DoC relates to post-stimulus ERPs in a similar way as previously documented in healthy people. 14 DoC patients in an unresponsive wakefulness syndrome (UWS, N = 2) or a minimally conscious state (MCS, N = 12) participated in this study. In an active oddball paradigm patients received vibrotactile stimuli. Significant post-stimulus differences between brain responses to deviant and standard stimulation could be found in six MCS patients (42.86%). Regarding relative pre-stimulus frequency bands, delta oscillations predominated in most patients, followed by theta and alpha, although two patients showed a relatively normal power spectrum. The statistical analysis of the relationship between pre-stimulus power and post-stimulus event-related brain response showed multiple significant correlations in five out of the six patients. Individual results sometimes showed similar correlation patterns as in healthy subjects primarily between the relative pre-stimulus alpha power and post-stimulus variables in later time-intervals. However, opposite effects were also found, indicating high inter-individual variability in DoC patients´ functional brain activity. Future studies should determine on an individual level to what extent the relationship between pre- and post-stimulus brain activity could relate to the course of the disorder.

Stability of mental motor-imagery classification in EEG depends on the choice of classifier model and experiment design, but not on signal preprocessing

Introduction

Modern consciousness research has developed diagnostic tests to improve the diagnostic accuracy of different states of consciousness via electroencephalography (EEG)-based mental motor imagery (MI), which is still challenging and lacks a consensus on how to best analyse MI EEG-data. An optimally designed and analyzed paradigm must detect command-following in all healthy individuals, before it can be applied in patients, e.g., for the diagnosis of disorders of consciousness (DOC).

Methods

We investigated the effects of two important steps in the raw signal preprocessing on predicting participant performance (F1) and machine-learning classifier performance (area-under-curve, AUC) in eight healthy individuals, that are based solely on MI using high-density EEG (HD-EEG): artifact correction (manual correction with vs. without Independent Component Analysis [ICA]), region of interest (ROI; motor area vs. whole brain), and machine-learning algorithm (support-vector machine [SVM] vs. k-nearest neighbor [KNN]).

Results

Results revealed no significant effects of artifact correction and ROI on predicting participant performance (F1) and classifier performance (AUC) scores (all ps > 0.05) in the SVM classification model. In the KNN model, ROI had a significant influence on the classifier performance [F(1,8.939) = 7.585, p = 0.023]. There was no evidence for artifact correction and ROI selection changing the prediction of participants performance and classifier performance in EEG-based mental MI if using SVM-based classification (71-100% correct classifications across different signal preprocessing methods). The variance in the prediction of participant performance was significantly higher when the experiment started with a resting-state compared to a mental MI task block [X2(1) = 5.849, p = 0.016].

Discussion

Overall, we could show that classification is stable across different modes of EEG signal preprocessing when using SVM models. Exploratory analysis gave a hint toward potential effects of the sequence of task execution on the prediction of participant performance, which should be taken into account in future studies.

The signs of computer tomography combined with artificial intelligence can indicate the correlation between status of consciousness and primary brainstem hemorrhage of patients

Background

For patients of primary brainstem hemorrhage (PBH), it is crucial to find a method that can quickly and accurately predict the correlation between status of consciousness and PBH.

Objective

To analyze the value of computer tomography (CT) signs in combination with artificial intelligence (AI) technique in predicting the correlation between status of consciousness and PBH.

Methods

A total of 120 patients with PBH were enrolled from August 2011 to March 2021 according to the criteria. Patients were divided into three groups [consciousness, minimally conscious state (MCS) and coma] based on the status of consciousness. Then, first, Mann–Whitney U test and Spearman rank correlation test were used on the factors: gender, age, stages of intracerebral hemorrhage, CT signs with AI or radiology physicians, hemorrhage involving the midbrain or ventricular system. We collected hemorrhage volumes and mean CT values with AI. Second, those significant factors were screened out by the Mann–Whitney U test and those highly or moderately correlated by Spearman’s rank correlation test, and a further ordinal multinomial logistic regression analysis was performed to find independent predictors of the status of consciousness. At last, receiver operating characteristic (ROC) curves were drawn to calculate the hemorrhage volume for predictively assessing the status of consciousness.

Results

Preliminary meaningful variables include hemorrhage involving the midbrain or ventricular system, hemorrhage volume, grade of hematoma shape and density, and CT value from Mann–Whitney U test and Spearman rank correlation test. It is further shown by ordinal multinomial logistic regression analysis that hemorrhage volume and hemorrhage involving the ventricular system are two major predictors of the status of consciousness. It showed from ROC that the hemorrhage volumes of &lt;3.040 mL, 3.040 ~ 6.225 mL and &gt;6.225 mL correspond to consciousness, MCS or coma, respectively. If the hemorrhage volume is the same, hemorrhage involving the ventricular system should be correlated with more severe disorders of consciousness (DOC).

Conclusion

CT signs combined with AI can predict the correlation between status of consciousness and PBH. Hemorrhage volume and hemorrhage involving the ventricular system are two independent factors, with hemorrhage volume in particular reaching quantitative predictions.

Classification of Level of Consciousness in a Neurological ICU Using Physiological Data

BACKGROUND

Impaired consciousness is common in intensive care unit (ICU) patients, and an individual's degree of consciousness is crucial to determining their care and prognosis. However, there are no methods that continuously monitor consciousness and alert clinicians to changes. We investigated the use of physiological signals collected in the ICU to classify levels of consciousness in critically ill patients.

METHODS

We studied 61 patients with subarachnoid hemorrhage (SAH) and 178 patients with intracerebral hemorrhage (ICH) from the neurological ICU at Columbia University Medical Center in a retrospective observational study of prospectively collected data. The level of consciousness was determined on the basis of neurological examination and mapped to comatose, vegetative state or unresponsive wakefulness syndrome (VS/UWS), minimally conscious minus state (MCS-), and command following. For each physiological signal, we extracted time-series features and performed classification using extreme gradient boosting on multiple clinically relevant tasks across subsets of physiological signals. We applied this approach independently on both SAH and ICH patient groups for three sets of variables: (1) a minimal set common to most hospital patients (e.g., heart rate), (2) variables available in most ICUs (e.g., body temperature), and (3) an extended set recorded mainly in neurological ICUs (absent for the ICH patient group; e.g., brain temperature).

RESULTS

On the commonly performed classification task of VS/UWS versus MCS-, we achieved an area under the receiver operating characteristic curve (AUROC) in the SAH patient group of 0.72 (sensitivity 82%, specificity 57%; 95% confidence interval [CI] 0.63-0.81) using the extended set, 0.69 (sensitivity 83%, specificity 51%; 95% CI 0.59-0.78) on the variable set available in most ICUs, and 0.69 (sensitivity 56%, specificity 78%; 95% CI 0.60-0.78) on the minimal set. In the ICH patient group, AUROC was 0.64 (sensitivity 56%, specificity 65%; 95% CI 0.55-0.74) using the minimal set and 0.61 (sensitivity 50%, specificity 80%; 95% CI 0.51-0.71) using the variables available in most ICUs.

CONCLUSIONS

We find that physiological signals can be used to classify states of consciousness for patients in the ICU. Building on this with intraday assessments and increasing sensitivity and specificity may enable alarm systems that alert physicians to changes in consciousness and frequent monitoring of consciousness throughout the day, both of which may improve patient care and outcomes.

miR-21, miR-93, miR-191, miR-let-7b, and miR-499 Expression Level in Plasma and Cerebrospinal Fluid in Patients with Prolonged Disorders of Consciousness

In recent decades, significant progress has been achieved in understanding the mechanisms of disturbance and restoration of consciousness in patients after severe brain damage resulting in prolonged disorders of consciousness (pDOC). MicroRNAs (miRs) may be potential candidates as possible biomarkers for the classification of disease subtypes, and prognosis in patients with pDOC. The aim of the study was to analyze miRs expression levels (hsa-miR-21-5p, hsa-miR-93-5p, hsa-miR-191-5p, mmu-miR-499-5p, hsa-let-7b-5p) by a real-time polymerase chain reaction in plasma and cerebrospinal fluid (CSF) from patients with pDOC and to identify a potential biomarker for dividing patients into groups according to disease severity. We analyzed the levels of investigated miRs in pDOC patients, divided by etiology, CRSI, and the total group compared with controls. Our results showed that dividing patients with pDOC into groups according to the etiology of the disease resulted in the most significant differences in the levels of miR-93, -21, and -191 in CSF and plasma samples between groups of patients. Among the analyzed miRs, we did not find a marker that would help to distinguish VS/UWS patient groups from MCS. Examining of miRs as possible prognostic markers in patients with pDOC, the starting point seems to be the cause that led to the development of the disease.

Cerebral cortical activity after withdrawal of life-sustaining measures in critically ill patients

Establishing when cerebral cortical activity stops relative to circulatory arrest during the dying process will enhance trust in donation after circulatory determination of death. We used continuous electroencephalography and arterial blood pressure monitoring prior to withdrawal of life sustaining measures and for 30 min following circulatory arrest to explore the temporal relationship between cessation of cerebral cortical activity and circulatory arrest. Qualitative and quantitative EEG analyses were completed. Among 140 screened patients, 52 were eligible, 15 were enrolled, 11 completed the full study, and 8 (3 female, median age 68 years) were included in the analysis. Across participants, EEG activity stopped at a median of 78 (Q1 = -387, Q3 = 111) seconds before circulatory arrest. Following withdrawal of life sustaining measures there was a progressive reduction in electroencephalographic amplitude (p = .002), spectral power (p = .008), and coherence (p = .003). Prospective recording of cerebral cortical activity in imminently dying patients is feasible. Our results from this small cohort suggest that cerebral cortical activity does not persist after circulatory arrest. Confirmation of these findings in a larger multicenter study are needed to help promote stakeholder trust in donation after circulatory determination of death.

Frequency-tuned electromagnetic field therapy improves post-stroke motor function: A pilot randomized controlled trial

BACKGROUND AND PURPOSE

Impaired upper extremity (UE) motor function is a common disability after ischemic stroke. Exposure to extremely low frequency and low intensity electromagnetic fields (ELF-EMF) in a frequency-specific manner (Electromagnetic Network Targeting Field therapy; ENTF therapy) is a non-invasive method available to a wide range of patients that may enhance neuroplasticity, potentially facilitating motor recovery. This study seeks to quantify the benefit of the ENTF therapy on UE motor function in a subacute ischemic stroke population.

METHODS

In a randomized, sham-controlled, double-blind trial, ischemic stroke patients in the subacute phase with moderately to severely impaired UE function were randomly allocated to active or sham treatment with a novel, non-invasive, brain computer interface-based, extremely low frequency and low intensity ENTF therapy (1-100 Hz, < 1 G). Participants received 40 min of active ENTF or sham treatment 5 days/week for 8 weeks; ~three out of the five treatments were accompanied by 10 min of concurrent physical/occupational therapy. Primary efficacy outcome was improvement on the Fugl-Meyer Assessment - Upper Extremity (FMA-UE) from baseline to end of treatment (8 weeks).

RESULTS

In the per protocol set (13 ENTF and 8 sham participants), mean age was 54.7 years (±15.0), 19% were female, baseline FMA-UE score was 23.7 (±11.0), and median time from stroke onset to first stimulation was 11 days (interquartile range (IQR) 8-15). Greater improvement on the FMA-UE from baseline to week 4 was seen with ENTF compared to sham stimulation, 23.2 ± 14.1 vs. 9.6 ± 9.0, p = 0.007; baseline to week 8 improvement was 31.5 ± 10.7 vs. 23.1 ± 14.1. Similar favorable effects at week 8 were observed for other UE and global disability assessments, including the Action Research Arm Test (Pinch, 13.4 ± 5.6 vs. 5.3 ± 6.5, p = 0.008), Box and Blocks Test (affected hand, 22.5 ± 12.4 vs. 8.5 ± 8.6, p < 0.0001), and modified Rankin Scale (-2.5 ± 0.7 vs. -1.3 ± 0.7, p = 0.0005). No treatment-related adverse events were reported.

CONCLUSIONS

ENTF stimulation in subacute ischemic stroke patients was associated with improved UE motor function and reduced overall disability, and results support its safe use in the indicated population. These results should be confirmed in larger multicenter studies.

CLINICAL TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT04039178, identifier: NCT04039178.

Objective Neurophysiologic Markers of Cognition After Pediatric Brain Injury

Background and Objectives

Following brain injury, clinical assessments of residual and emerging cognitive function are difficult and fraught with errors. In adults, recent American Academy of Neurology (AAN) practice guidelines recommend objective neuroimaging and neurophysiologic measures to support diagnosis. Equivalent measures are lacking in pediatrics-an especially great challenge due to the combined heterogeneity of both brain injury and pediatric development. Therefore, we aim to establish quantitative, clinically practicable measures of cognitive function following pediatric brain injury.

Methods

Participants with and without brain injury were aged 8-18 years, clinically classified according to cognitive recovery state: N = 8 in disorders of consciousness (DoC), N = 7 in confusional state, N = 19 cognitively impaired, and N = 13 typically developing uninjured controls. We prospectively measured electroencephalographic markers of sensory processing and attention in an auditory oddball paradigm, and of covert movement attempts in a command-following paradigm.

Results

In 3 participants with DoC, EEG markers of active attempted command following revealed cognitive function that clinical assessment had failed to detect. These same 3 individuals could also be distinguished from the rest of their group by 2 event-related potentials that correlate with sensory processing and orienting attention in the oddball paradigm. Considered across the whole participant group, magnitudes of these 2 ERP markers significantly increased as cognitive recovery progressed (ANOVA: each p < 0.001); viewed jointly, the 2 ERP markers cleanly delineated the 4 cognitive states.

Discussion

Despite heterogeneity of brain injuries and brain development, our objective EEG markers reflected cognitive recovery independent of motor function. Two of these markers required no active participation. Together, they allowed us to identify 3 individuals who meet the criteria for cognitive-motor dissociation. To diagnose, prognose, and track cognitive recovery accurately, such markers should be used in pediatrics.

How brain-computer interface technology may improve the diagnosis of the disorders of consciousness: A comparative study

Objective

Clinical assessment of consciousness relies on behavioural assessments, which have several limitations. Hence, disorder of consciousness (DOC) patients are often misdiagnosed. In this work, we aimed to compare the repetitive assessment of consciousness performed with a clinical behavioural and a Brain-Computer Interface (BCI) approach.

Materials and methods

For 7 weeks, sixteen DOC patients participated in weekly evaluations using both the Coma Recovery Scale-Revised (CRS-R) and a vibrotactile P300 BCI paradigm. To use the BCI, patients had to perform an active mental task that required detecting specific stimuli while ignoring other stimuli. We analysed the reliability and the efficacy in the detection of command following resulting from the two methodologies.

Results

Over repetitive administrations, the BCI paradigm detected command following before the CRS-R in seven patients. Four clinically unresponsive patients consistently showed command following during the BCI assessments.

Conclusion

Brain-Computer Interface active paradigms might contribute to the evaluation of the level of consciousness, increasing the diagnostic precision of the clinical bedside approach.

Significance

The integration of different diagnostic methods leads to a better knowledge and care for the DOC.

Proceedings of the Second Curing Coma Campaign NIH Symposium: Challenging the Future of Research for Coma and Disorders of Consciousness

This proceedings article presents actionable research targets on the basis of the presentations and discussions at the 2nd Curing Coma National Institutes of Health (NIH) symposium held from May 3 to May 5, 2021. Here, we summarize the background, research priorities, panel discussions, and deliverables discussed during the symposium across six major domains related to disorders of consciousness. The six domains include (1) Biology of Coma, (2) Coma Database, (3) Neuroprognostication, (4) Care of Comatose Patients, (5) Early Clinical Trials, and (6) Long-term Recovery. Following the 1st Curing Coma NIH virtual symposium held on September 9 to September 10, 2020, six workgroups, each consisting of field experts in respective domains, were formed and tasked with identifying gaps and developing key priorities and deliverables to advance the mission of the Curing Coma Campaign. The highly interactive and inspiring presentations and panel discussions during the 3-day virtual NIH symposium identified several action items for the Curing Coma Campaign mission, which we summarize in this article.

Electrophysiological correlates of thalamocortical function in acute severe traumatic brain injury

Tools assaying the neural networks that modulate consciousness may facilitate tracking of recovery after acute severe brain injury. The ABCD framework classifies resting-state EEG into categories reflecting levels of thalamocortical network function that correlate with outcome in post-cardiac arrest coma. In this longitudinal cohort study, we applied the ABCD framework to 20 patients with acute severe traumatic brain injury requiring intensive care (12 of whom were also studied at ≥6-months post-injury) and 16 healthy controls. We tested four hypotheses: 1) EEG ABCD classifications are spatially heterogeneous and temporally variable; 2) ABCD classifications improve longitudinally, commensurate with the degree of behavioral recovery; 3) ABCD classifications correlate with behavioral level of consciousness; and 4) the Coma Recovery Scale-Revised arousal facilitation protocol yields improved ABCD classifications. Channel-level EEG power spectra were classified based on spectral peaks within pre-defined frequency bands: 'A' = no peaks above delta (<4 Hz) range (complete thalamocortical disruption); 'B' = theta (4-8 Hz) peak (severe thalamocortical disruption); 'C' = theta and beta (13-24 Hz) peaks (moderate thalamocortical disruption); or 'D' = alpha (8-13 Hz) and beta peaks (normal thalamocortical function). Acutely, 95% of patients demonstrated 'D' signals in at least one channel but exhibited within-session temporal variability and spatial heterogeneity in the proportion of different channel-level ABCD classifications. By contrast, healthy participants and patients at follow-up consistently demonstrated signals corresponding to intact thalamocortical network function. Patients demonstrated longitudinal improvement in ABCD classifications (p < .05) and ABCD classification distinguished patients with and without command-following in the subacute-to-chronic phase of recovery (p < .01). In patients studied acutely, ABCD classifications improved after the Coma Recovery Scale-Revised arousal facilitation protocol (p < .05) but did not correspond with behavioral level of consciousness. These findings support the use of the ABCD framework to characterize channel-level EEG dynamics and track fluctuations in functional thalamocortical network integrity in spatial detail.

Dynamic Changes of Brain Activity in Patients With Disorders of Consciousness During Recovery of Consciousness

The disorder of brain activity dynamics is one of the main characteristics leading to disorders of consciousness (DOC). However, few studies have explored whether the dynamics of brain activity can be modulated, and whether the dynamics of brain activity can help to evaluate the state of consciousness and the recovery progress of consciousness. In current study, 20 patients with minimally conscious state (MCS) and 13 patients with vegetative state (VS) were enrolled, and resting state electroencephalogram (EEG) data and the coma recovery scale-revised (CRS-R) scores were collected three times before and after high-definition transcranial direct current stimulation (HD-tDCS) treatment. The patients were divided into the improved group and the unimproved group according to whether the CRS-R scores were improved after the treatment, and the dynamic changes of resting state EEG microstate parameters during treatment were analyzed. The results showed the occurrence per second (OPS) of microstate D was significantly different between the MCS group and VS group, and it was positively correlated with the CRS-R before the treatment. After 2 weeks of the treatment, the OPS of microstate D improved significantly in the improved group. Meanwhile, the mean microstate duration (MMD), ratio of time coverage (Cov) of microstate C and the Cov of microstate D were significantly changed after the treatment. Compared with the microstates parameters before the treatment, the dynamic changes of parameters with significant difference in the improved group showed a consistent trend after the treatment. In contrast, the microstates parameters did not change significantly after the treatment in the unimproved group. The results suggest that the dynamics of EEG brain activity can be modulated by HD-tDCS, and the improvement in brain activity dynamics is closely related to the recovery of DOC, which is helpful to evaluate the level of DOC and the progress of recovery of consciousness.

Cognitive-Motor Dissociation Following Pediatric Brain Injury: What About the Children?

Background and Objectives

Following severe brain injury, up to 16% of adults showing no clinical signs of cognitive function nonetheless have preserved cognitive capacities detectable via neuroimaging and neurophysiology; this has been designated cognitive-motor dissociation (CMD). Pediatric medicine lacks both practice guidelines for identifying covert cognition and epidemiologic data regarding CMD prevalence.

Methods

We applied a diverse battery of neuroimaging and neurophysiologic tests to evaluate 2 adolescents (aged 15 and 18 years) who had shown no clinical evidence of preserved cognitive function following brain injury at age 9 and 13 years, respectively. Clinical evaluations were consistent with minimally conscious state (minus) and vegetative state, respectively.

Results

Both participants' EEG, and 1 participant's fMRI, provided evidence that they could understand commands and make consistent voluntary decisions to follow them. Both participants' EEG demonstrated larger-than-expected responses to auditory stimuli and intact semantic processing of words in context.

Discussion

These converging lines of evidence lead us to conclude that both participants had preserved cognitive function dissociated from their motor output. Throughout the 5+ years since injury, communication attempts and therapy had remained uninformed by such objective evidence of their cognitive abilities. Proper diagnosis of CMD is an ethical imperative. Children with covert cognition reflect a vulnerable and isolated population; the methods outlined here provide a first step in identifying such persons to advance efforts to alleviate their condition.

Conventional and Investigational Approaches Leveraging Clinical EEG for Prognosis in Acute Disorders of Consciousness

Prediction of recovery of consciousness after severe brain injury is difficult and limited by a lack of reliable, standardized biomarkers. Multiple approaches for analysis of clinical electroencephalography (EEG) that shed light on prognosis in acute severe brain injury have emerged in recent years. These approaches fall into two major categories: conventional characterization of EEG background and quantitative measurement of resting state or stimulus-induced EEG activity. Additionally, a small number of studies have associated the presence of electrophysiologic sleep features with prognosis in the acute phase of severe brain injury. In this review, we focus on approaches for the analysis of clinical EEG that have prognostic significance and that could be readily implemented with minimal additional equipment in clinical settings, such as intensive care and intensive rehabilitation units, for patients with acute disorders of consciousness.

Language Assessment in Patients with Disorders of Consciousness

The assessment of residual language abilities in patients with disorders of consciousness (DoC) after severe brain injury is particularly challenging due to their limited behavioral repertoire. Moreover, associated language impairment such as receptive aphasia may lead to an underestimation of actual consciousness levels. In this review, we examine past research on the assessment of residual language processing in DoC patients, and we discuss currently available tools for identifying language-specific abilities and their prognostic value. We first highlight the need for validated and sensitive bedside behavioral assessment tools for residual language abilities in DoC patients. As regards neuroimaging and electrophysiological methods, the tasks involving higher level linguistic commands appear to be the most informative about level of consciousness and have the best prognostic value. Neuroimaging methods should be combined with the most appropriate behavioral tools in multimodal assessment protocols to assess receptive language abilities in DoC patients in the most complete and sensitive manner.

Flowchart for Implementing Advanced Imaging and Electrophysiology in Patients With Disorders of Consciousness: To fMRI or Not to fMRI?

The American Academy of Neurology and the European Academy of Neurology have recognized, for the first time, the value of advanced neuroimaging and electrophysiology techniques (AIEs) in the context of diagnosing patients with a disorder of consciousness (DOC). This recognition is part of an important agenda of promoting evidence-based competency in the management of patients with DOC. Nonetheless, considering that these techniques (and the required knowledge) are seldom available outside of advanced medical centers, it is important to provide physicians with a framework for balancing risks and benefits and deciding, on a single patient basis, whether AIEs are suitable. This issue is all the more urgent considering that family members are increasingly aware of the use of AIEs in patients with DOC, pressure for these assessments is likely to increase in the context of ethical and clinical imperatives to meet standards of care, and pathways for reimbursement for such assessments in DOC are yet to be established. The new guidelines, however, provide no guiding principle for physicians to decide when such assessments are appropriate, a limitation that impedes their wide adoption. We address this important gap by proposing an easy to use algorithmic flowchart that is based on the new guidelines and can be used to determine the appropriateness of AIEs for any given patient with DOC and ensure that evidence-based best practices are being followed. We also provide a brief context for understanding the main categories of AIEs available to clinicians, their advantages, and their limitations.

Ameliorative effects of alkaloid extract from Mitragyna speciosa (Korth.) Havil. Leaves on methamphetamine conditioned place preference in mice

ETHNOPHARMACOLOGICAL RELEVANCE

Mitragyna speciosa (Korth.) Havil., popularly known as Kratom (KT), is a medicinal plant used for pain suppression in Southeast Asia. It has been claimed to assist drug users withdraw from methamphetamine (METH) dependence. However, its use was controversial and not approved yet.

AIM OF THE STUDY

This study was conducted to characterize local field potential (LFP) patterns in the nucleus accumbens (NAc) and the hippocampus (HP) in mice with METH conditioned place preference (CPP) that were treated with KT alkaloid extract.

MATERIALS AND METHODS

Male Swiss albino ICR mice were implanted with intracraneal electrodes into the NAc and HP. To induce METH CPP, animals were injected intraperitoneally once a day with METH (1 mg/kg) and saline (0.9% w/v) alternately and put into METH/saline compartments to experience the associations between drug/saline injection and the unique environmental contexts for 10 sessions. Control group received saline injection paired with both saline/saline compartments. On post-conditioning day, effects of 40 (KT40), 80 (KT80) mg/kg KT alkaloid extract and 20 mg/kg bupropion (BP) on CPP scores and LFP powers and NAc-HP coherence were tested.

RESULTS

Two-way ANOVA revealed significant induction of CPP by METH sessions (P < 0.01). Multiple comparisons indicated that METH CPP was completely abolished by KT80 (P < 0.001). NAc gamma I (30.0-44.9 Hz) and HP delta (1.0-3.9 Hz) powers were significantly increased in mice with METH CPP (P < 0.01). The elevated NAc gamma I was significantly suppressed by KT80 (P < 0.05) and the increased HP delta was significantly reversed by KT40 (P < 0.01) and KT80 (P < 0.001). In addition, NAc-HP coherence was also significantly increased in gamma I (30.0-44.9 Hz) frequency range (P < 0.05) but it was reversed by KT80 (P < 0.05). Treatment with BP did not produce significant effect on these parameters.

CONCLUSIONS

These findings demonstrated that KT alkaloid extract significantly reversed CPP scores and LFP patterns induced by METH administration. The ameliorative effects of the extract might be beneficial for treatment of METH craving and addiction.

Investigating the relation between electroencephalogram, thermal comfort, and cognitive performance in neutral to hot indoor environment

The relation between electroencephalogram signals, thermal comfort, and cognitive performance in neutral to hot indoor environment was investigated. The experiments were carried out at four temperatures: 26ºC, 30ºC, 33ºC, and 37ºC, and two relative humidity levels: 50% and 70%. Thirty-two subjects were exposed for 175 min. The electroencephalogram signals were measured for 30 min 25 min after the onset of exposure while the recruited subjects performed neurobehavioral tests and rated their thermal comfort. The relative power of electroencephalogram signals has a significant correlation with thermal comfort and performance of neurobehavioral tests. The ratings of acceptability of thermal environment and thermal comfort, the speed, accuracy, and PI of completing the tests are negatively correlated with the relative power of δ-band, but positively correlated with θ-band, α-band, and β-band. The ratings of thermal sensation have a better correlation with the above four bands, but the correlation trend is opposite. A linear relation was found between electroencephalogram signals and the speed. The results showed that the relative power of P7 channel located in the occipital lobe is the most suitable as a single electroencephalogram channel to reflect joint thermal comfort and cognitive performance at high temperatures, especially its α-band.

Toward a coherent structuration of disorders of consciousness expertise at a country scale: A proposal for France

Probing consciousness and cognitive abilities in non-communicating patients is one of the most challenging diagnostic issues. A fast growing medical and scientific literature explores the various facets of this challenge, often coined under the generic expression of 'Disorders of Consciousness' (DoC). Crucially, a set of independent converging results demonstrated both (1) the diagnostic and prognostic importance of this expertise, and (2) the need to combine behavioural measures with brain structure and activity data to improve diagnostic and prognostication accuracy as well as potential therapeutic intervention. Thus, probing consciousness in DoC patients appears as a crucial activity rich of human, medical, economic and ethical consequences, but this activity needs to be organized in order to offer this expertise to each concerned patient. More precisely, diagnosis of consciousness differs in difficulty across patients: while a minimal set of data can be sufficient to reach a confident result, some patients need a higher level of expertise that relies on additional behavioural and brain activity and brain structure measures. In order to enable this service on a systematic mode, we present two complementary proposals in the present article. First, we sketch a structuration of DoC expertise at a country-scale, namely France. More precisely, we suggest that a 2-tiers network composed of local (Tier-1) and regional (Tier-2) centers backed by distant electronic databases and algorithmic centers could optimally enable the systematic implementation of DoC expertise in France. Second, we propose to create a national common register of DoC patients in order to better monitor this activity, to improve its performance on the basis of nation-wide collected evidence, and to promote rational decision-making.

The neuroethics of disorders of consciousness: a brief history of evolving ideas

Neuroethical questions raised by recent advances in the diagnosis and treatment of disorders of consciousness are rapidly expanding, increasingly relevant and yet underexplored. The aim of this thematic review is to provide a clinically applicable framework for understanding the current taxonomy of disorders of consciousness and to propose an approach to identifying and critically evaluating actionable neuroethical issues that are frequently encountered in research and clinical care for this vulnerable population. Increased awareness of these issues and clarity about opportunities for optimizing ethically responsible care in this domain are especially timely given recent surges in critically ill patients with prolonged disorders of consciousness associated with coronavirus disease 2019 around the world. We begin with an overview of the field of neuroethics: what it is, its history and evolution in the context of biomedical ethics at large. We then explore nomenclature used in disorders of consciousness, covering categories proposed by the American Academy of Neurology, the American Congress of Rehabilitation Medicine and the National Institute on Disability, Independent Living and Rehabilitation Research, including definitions of terms such as coma, the vegetative state, unresponsive wakefulness syndrome, minimally conscious state, covert consciousness and the confusional state. We discuss why these definitions matter, and why there has been such evolution in this nosology over the years, from Jennett and Plum in 1972 to the Multi-Society Task Force in 1994, the Aspen Working Group in 2002 and the 2018 American and 2020 European Disorders of Consciousness guidelines. We then move to a discussion of clinical aspects of disorders of consciousness, the natural history of recovery and ethical issues that arise within the context of caring for people with disorders of consciousness. We conclude with a discussion of key challenges associated with assessing residual consciousness in disorders of consciousness, potential solutions and future directions, including integration of crucial disability rights perspectives.

Residual implicit and explicit language abilities in patients with disorders of consciousness: A systematic review

Language assessment in post-comatose patients is difficult due to their limited behavioral repertoire; yet associated language deficits might lead to an underestimation of consciousness levels in unresponsive wakefulness syndrome (UWS) or minimally conscious state (MCS; -/+) diagnoses. We present a systematic review of studies from 2002 assessing residual language abilities with neuroimaging, electrophysiological or behavioral measures in patients with severe brain injury. Eighty-five articles including a total of 2278 patients were assessed for quality. The median percentages of patients showing residual implicit language abilities (i.e., cortical responses to specific words/sentences) were 33 % for UWS, 50 % for MCS- and 78 % for MCS + patients, whereas explicit language abilities (i.e., command-following using brain-computer interfaces) were reported in 20 % of UWS, 33 % of MCS- and 50 % of MCS + patients. Cortical responses to verbal stimuli increased along with consciousness levels and the progressive recovery of consciousness after a coma was paralleled by the reappearance of both implicit and explicit language processing. This review highlights the importance of language assessment in patients with disorders of consciousness.

Update on neuroimaging in disorders of consciousness

PURPOSE OF REVIEW

Neuroimaging has acquired a prominent place in the assessment of disorders of consciousness (DoC). Rapidly evolving technologies combined with state-of-the-art data analyses open new horizons to probe brain activity, but selecting appropriate imaging modalities from the plethora of available techniques can be challenging for clinicians. This update reviews selected advances in neuroimaging that demonstrate clinical relevance and translational potential in the assessment of severely brain-injured patients with DoC.

RECENT FINDINGS

Magnetic resonance imaging and high-density electroencephalography provide measurements of brain connectivity between functional networks, assessments of language function, detection of covert consciousness, and prognostic markers of recovery. Positron emission tomography can identify patients with preserved brain metabolism despite clinical unresponsiveness and can measure glucose consumption rates in targeted brain regions. Transcranial magnetic stimulation and near-infrared spectroscopy are noninvasive and practical tools with promising clinical applications.

SUMMARY

Each neuroimaging technique conveys advantages and pitfalls to assess consciousness. We recommend a multimodal approach in which complementary techniques provide diagnostic and prognostic information about brain function. Patients demonstrating neuroimaging evidence of covert consciousness may benefit from early adapted rehabilitation. Translating methodological advances to clinical care will require the implementation of recently published international guidelines and the integration of neuroimaging techniques into patient-centered decision-making algorithms.

Proceedings of the First Curing Coma Campaign NIH Symposium: Challenging the Future of Research for Coma and Disorders of Consciousness

Coma and disorders of consciousness (DoC) are highly prevalent and constitute a burden for patients, families, and society worldwide. As part of the Curing Coma Campaign, the Neurocritical Care Society partnered with the National Institutes of Health to organize a symposium bringing together experts from all over the world to develop research targets for DoC. The conference was structured along six domains: (1) defining endotype/phenotypes, (2) biomarkers, (3) proof-of-concept clinical trials, (4) neuroprognostication, (5) long-term recovery, and (6) large datasets. This proceedings paper presents actionable research targets based on the presentations and discussions that occurred at the conference. We summarize the background, main research gaps, overall goals, the panel discussion of the approach, limitations and challenges, and deliverables that were identified.

Pain Perception in Disorder of Consciousness: A Scoping Review on Current Knowledge, Clinical Applications, and Future Perspective

Pain perception in individuals with prolonged disorders of consciousness (PDOC) is still a matter of debate. Advanced neuroimaging studies suggest some cortical activations even in patients with unresponsive wakefulness syndrome (UWS) compared to those with a minimally conscious state (MCS). Therefore, pain perception has to be considered even in individuals with UWS. However, advanced neuroimaging assessment can be challenging to conduct, and its findings are sometimes difficult to be interpreted. Conversely, multichannel electroencephalography (EEG) and laser-evoked potentials (LEPs) can be carried out quickly and are more adaptable to the clinical needs. In this scoping review, we dealt with the neurophysiological basis underpinning pain in PDOC, pointing out how pain perception assessment in these individuals might help in reducing the misdiagnosis rate. The available literature data suggest that patients with UWS show a more severe functional connectivity breakdown among the pain-related brain areas compared to individuals in MCS, pointing out that pain perception increases with the level of consciousness. However, there are noteworthy exceptions, because some UWS patients show pain-related cortical activations that partially overlap those observed in MCS individuals. This suggests that some patients with UWS may have residual brain functional connectivity supporting the somatosensory, affective, and cognitive aspects of pain processing (i.e., a conscious experience of the unpleasantness of pain), rather than only being able to show autonomic responses to potentially harmful stimuli. Therefore, the significance of the neurophysiological approach to pain perception in PDOC seems to be clear, and despite some methodological caveats (including intensity of stimulation, multimodal paradigms, and active vs. passive stimulation protocols), remain to be solved. To summarize, an accurate clinical and neurophysiological assessment should always be performed for a better understanding of pain perception neurophysiological underpinnings, a more precise differential diagnosis at the level of individual cases as well as group comparisons, and patient-tailored management.

Statement in Support of Revising the Uniform Determination of Death Act and in Opposition to a Proposed Revision

Discrepancies between the Uniform Determination of Death Act (UDDA) and the adult and pediatric diagnostic guidelines for brain death (BD) (the "Guidelines") have motivated proposals to revise the UDDA. A revision proposed by Lewis, Bonnie and Pope (the RUDDA), has received particular attention, the three novelties of which would be: (1) to specify the Guidelines as the legally recognized "medical standard," (2) to exclude hypothalamic function from the category of "brain function," and (3) to authorize physicians to conduct an apnea test without consent and even over a proxy's objection. One hundred seven experts in medicine, bioethics, philosophy, and law, spanning a wide variety of perspectives, have come together in agreement that while the UDDA needs revision, the RUDDA is not the way to do it. Specifically, (1) the Guidelines have a non-negligible risk of false-positive error, (2) hypothalamic function is more relevant to the organism as a whole than any brainstem reflex, and (3) the apnea test carries a risk of precipitating BD in a non-BD patient, provides no benefit to the patient, does not reliably accomplish its intended purpose, and is not even absolutely necessary for diagnosing BD according to the internal logic of the Guidelines; it should at the very least require informed consent, as do many procedures that are much more beneficial and less risky. Finally, objections to a neurologic criterion of death are not based only on religious belief or ignorance. People have a right to not have a concept of death that experts vigorously debate imposed upon them against their judgment and conscience; any revision of the UDDA should therefore contain an opt-out clause for those who accept only a circulatory-respiratory criterion.

What Justifies the Allocation of Health Care Resources to Patients with Disorders of Consciousness?

This paper critically engages ethical issues in the allocation of novel, and potentially costly, health care resources to patients with disorders of consciousness. First, we review potential benefits of novel health care resources for patients and their families and outline preliminary considerations to address concerns about cost. We then address two problems regarding the allocation of health care resources to patients with disorders of consciousness: (1) the problem of uncertain moral status; and (2) the problem of accurately measuring the welfare burdens these resources would relieve. We conclude by suggesting that opportunity-based frameworks might complement standard approaches for justifying resources allocation to patients with disorders of consciousness.

The prognostic value of resting-state EEG in acute post-traumatic unresponsive states

Accurate early prognostication is vital for appropriate long-term care decisions after traumatic brain injury. While measures of resting-state EEG oscillations and their network properties, derived from graph theory, have been shown to provide clinically useful information regarding diagnosis and recovery in patients with chronic disorders of consciousness, little is known about the value of these network measures when calculated from a standard clinical low-density EEG in the acute phase post-injury. To investigate this link, we first validated a set of measures of oscillatory network features between high-density and low-density resting-state EEG in healthy individuals, thus ensuring accurate estimation of underlying cortical function in clinical recordings from patients. Next, we investigated the relationship between these features and the clinical picture and outcome of a group of 18 patients in acute post-traumatic unresponsive states who were not following commands 2 days+ after sedation hold. While the complexity of the alpha network, as indexed by the standard deviation of the participation coefficients, was significantly related to the patients' clinical picture at the time of EEG, no network features were significantly related to outcome at 3 or 6 months post-injury. Rather, mean relative alpha power across all electrodes improved the accuracy of outcome prediction at 3 months relative to clinical features alone. These results highlight the link between the alpha rhythm and clinical signs of consciousness and suggest the potential for simple measures of resting-state EEG band power to provide a coarse snapshot of brain health for stratification of patients for rehabilitation, therapy and assessments of both covert and overt cognition.

Recovery from disorders of consciousness: mechanisms, prognosis and emerging therapies

Substantial progress has been made over the past two decades in detecting, predicting and promoting recovery of consciousness in patients with disorders of consciousness (DoC) caused by severe brain injuries. Advanced neuroimaging and electrophysiological techniques have revealed new insights into the biological mechanisms underlying recovery of consciousness and have enabled the identification of preserved brain networks in patients who seem unresponsive, thus raising hope for more accurate diagnosis and prognosis. Emerging evidence suggests that covert consciousness, or cognitive motor dissociation (CMD), is present in up to 15-20% of patients with DoC and that detection of CMD in the intensive care unit can predict functional recovery at 1 year post injury. Although fundamental questions remain about which patients with DoC have the potential for recovery, novel pharmacological and electrophysiological therapies have shown the potential to reactivate injured neural networks and promote re-emergence of consciousness. In this Review, we focus on mechanisms of recovery from DoC in the acute and subacute-to-chronic stages, and we discuss recent progress in detecting and predicting recovery of consciousness. We also describe the developments in pharmacological and electrophysiological therapies that are creating new opportunities to improve the lives of patients with DoC.

Neural reactivity parameters of awareness predetermine one-year survival in patients with disorders of consciousness

Objective: The current investigation evaluated the sensitivity of neural-reactivity markers of awareness versus standard clinical assessments in predicting 1-year survival in nonresponsive-awake patients with disorders of consciousness (DOC).Methods: Pre-attentive auditory mismatch-negativity (MMN) event-related potentials (ERP's), globally induced electroencephalography (EEG) spectral power following verbal command, and clinical parameters were assessed. The study included 10 patients with DOC with mixed etiology and 10 healthy controls (HC) at baseline. The clinical status of patients with DOC was reassessed after 1 year.Results: Unlike baseline clinical assessment scores, baseline MMN amplitudes of non-survivors and induced theta-power following verbal-command clearly distinguished the non-surviving patients versus surviving patients. Baseline MMN peak-amplitude latencies in survivors with DOC were significantly related to clinical outcome over a 1-year period.Conclusion: Current findings underscore the increased sensitivity of EEG-reactivity markers of awareness versus standard clinical scores in predicting 1-year clinical outcome and survival in patients with DOC. Further longitudinal research in larger DOC samples is needed to confirm the prognostic-reliability, and validity of neural reactivity parameters of awareness in patients with DOC. Current finding may have implications for clinical care and medical-legal decisions in unresponsive-awake patients, and could assist clinicians to predict their survival up to 1 year from admission.

Frontotemporal EEG to guide sedation in COVID-19 related acute respiratory distress syndrome

Objective

To study if limited frontotemporal electroencephalogram (EEG) can guide sedation changes in highly infectious novel coronavirus disease 2019 (COVID-19) patients receiving neuromuscular blocking agent.

Methods

98 days of continuous frontotemporal EEG from 11 consecutive patients was evaluated daily by an epileptologist to recommend reduction or maintenance of the sedative level. We evaluated the need to increase sedation in the 6 h following this recommendation. Post-hoc analysis of the quantitative EEG was correlated with the level of sedation using a machine learning algorithm.

Results

Eleven patients were studied for a total of ninety-eight sedation days. EEG was consistent with excessive sedation on 57 (58%) and adequate sedation on 41 days (42%). Recommendations were followed by the team on 59% (N = 58; 19 to reduce and 39 to keep the sedation level). In the 6 h following reduction in sedation, increases of sedation were needed in 7 (12%). Automatized classification of EEG sedation levels reached 80% (±17%) accuracy.

Conclusions

Visual inspection of a limited EEG helped sedation depth guidance. In a secondary analysis, our data supported that this determination may be automated using quantitative EEG analysis.

Significance

Our results support the use of frontotemporal EEG for guiding sedation in patients with COVID-19.