Life or death: prognostic value of a resting EEG with regards to survival in patients in vegetative and minimally conscious States

EEG connectivity and network analyses predict outcome in patients with disorders of consciousness - A systematic review and meta-analysis

Outcome prediction in prolonged disorders of consciousness (DOC) remains challenging. This can result in either inappropriate withdrawal of treatment or unnecessary prolongation of treatment. Electroencephalography (EEG) is a cheap, portable, and non-invasive device with various opportunities for complex signal analysis. Computational EEG measures, such as EEG connectivity and network metrics, might be ideal candidates for the investigation of DOC, but their capacity in prognostication is still undisclosed. We conducted a meta-analysis aiming to compare the prognostic power of the widely used clinical scale, Coma Recovery Scale-Revised - CRS-R and EEG connectivity and network metrics. We found that the prognostic power of the CRS-R scale was moderate (AUC: 0.67 (0.60-0.75)), but EEG connectivity and network metrics predicted outcome with significantly (p = 0.0071) higher accuracy (AUC:0.78 (0.70-0.86)). We also estimated the prognostic capacity of EEG spectral power, which was not significantly (p = 0.3943) inferior to that of the EEG connectivity and graph-theory measures (AUC:0.75 (0.70-0.80)). Multivariate automated outcome prediction tools seemed to outperform clinical and EEG markers.

Use of magnetic source imaging to assess recovery after severe traumatic brain injury-an MEG pilot study

Rationale

Severe TBI (sTBI) is a devastating neurological injury that comprises a significant global trauma burden. Early comprehensive neurocritical care and rehabilitation improve outcomes for such patients, although better diagnostic and prognostic tools are necessary to guide personalized treatment plans.

Methods

In this study, we explored the feasibility of conducting resting state magnetoencephalography (MEG) in a case series of sTBI patients acutely after injury (~7 days), and then about 1.5 and 8 months after injury. Synthetic aperture magnetometry (SAM) was utilized to localize source power in the canonical frequency bands of delta, theta, alpha, beta, and gamma, as well as DC-80 Hz.

Results

At the first scan, SAM source maps revealed zones of hypofunction, islands of preserved activity, and hemispheric asymmetry across bandwidths, with markedly reduced power on the side of injury for each patient. GCS scores improved at scan 2 and by scan 3 the patients were ambulatory. The SAM maps for scans 2 and 3 varied, with most patients showing increasing power over time, especially in gamma, but a continued reduction in power in damaged areas and hemispheric asymmetry and/or relative diminishment in power at the site of injury. At the group level for scan 1, there was a large excess of neural generators operating within the delta band relative to control participants, while the number of neural generators for beta and gamma were significantly reduced. At scan 2 there was increased beta power relative to controls. At scan 3 there was increased group-wise delta power in comparison to controls.

Conclusion

In summary, this pilot study shows that MEG can be safely used to monitor and track the recovery of brain function in patients with severe TBI as well as to identify patient-specific regions of decreased or altered brain function. Such MEG maps of brain function may be used in the future to tailor patient-specific rehabilitation plans to target regions of altered spectral power with neurostimulation and other treatments.

Developing a novel prediction model in opioid overdose using machine learning; a pilot analytical study

Background and Aims

The opioid epidemic has extended to many countries. Data regarding the accuracy of conventional prediction models including the Simplified Acute Physiologic Score (SAPS) II and acute physiology and chronic health evaluation (APACHE) II are scarce in opioid overdose cases. We evaluate the efficacy of adding quantitative electroencephalogram (qEEG) data to clinical and paraclinical data in the prediction of opioid overdose mortality using machine learning.

Methods

In a prospective study, we collected clinical/paraclinical, and qEEG data of 32 opioid-poisoned patients. After preprocessing and Fast Fourier Transform analysis, absolute power was computed. Also, SAPS II was calculated. Eventually, data analysis was performed using SAPS II as a benchmark at three levels to predict the patient's course in comparison with SAPS II. First, the qEEG data set was used alone, secondly, the combination of the clinical/paraclinical, SAPS II, qEEG datasets, and the SAPS II-based model was included in the pool of classifier models.

Results

Seven out of 32 (22%) died. SAPS II (cut-off of 50.5) had a sensitivity/specificity/positive/negative predictive values of 85.7%, 84.0%, 60.0%, and 95.5% in predicting mortality, respectively. Adding majority voting on random forest with qEEG and clinical data, improved the model sensitivity, specificity, and positive and negative predictive values to 71.4%, 96%, 83.3%, and 92.3% (not significant). The model fusion level has 40% less prediction error.

Conclusion

Considering the higher specificity and negative predictive value in our proposed model, it could predict survival much better than mortality. The model would constitute an indicator for better care of opioid poisoned patients in low resources settings, where intensive care unit beds are limited.

Brain Activity Characteristics of Patients With Disorders of Consciousness in the EEG Resting State Paradigm: A Review

The assessment of the level of consciousness in disorders of consciousness (DoC) is still one of the most challenging problems in contemporary medicine. Nevertheless, based on the multitude of studies conducted over the last 20 years on resting states based on electroencephalography (EEG) in DoC, it is possible to outline the brain activity profiles related to both patients without preserved consciousness and minimally conscious ones. In the case of patients without preserved consciousness, the dominance of low, mostly delta, frequency, and the marginalization of the higher frequencies were observed, both in terms of the global power of brain activity and in functional connectivity patterns. In turn, the minimally conscious patients revealed the opposite brain activity pattern—the characteristics of higher frequency bands were preserved both in global power and in functional long-distance connections. In this short review, we summarize the state of the art of EEG-based research in the resting state paradigm, in the context of providing potential support to the traditional clinical assessment of the level of consciousness.

Risk factors for 2-year mortality in patients with prolonged disorders of consciousness: An international multicentre study

BACKGROUND AND PURPOSE

Patients with prolonged disorders of consciousness (pDoC) have a high mortality rate due to medical complications. Because an accurate prognosis is essential for decision-making on patients' management, we analysed data from an international multicentre prospective cohort study to evaluate 2-year mortality rate and bedside predictors of mortality.

METHODS

We enrolled adult patients in prolonged vegetative state/unresponsive wakefulness syndrome (VS/UWS) or minimally conscious state (MCS) after traumatic and nontraumatic brain injury within 3 months postinjury. At enrolment, we collected demographic (age, sex), anamnestic (aetiology, time postinjury), clinical (Coma Recovery Scale-Revised [CRS-R], Disability Rating Scale, Nociception Coma Scale-Revised), and neurophysiologic (electroencephalogram [EEG], somatosensory evoked and event-related potentials) data. Patients were followed up to gather data on mortality up to 24 months postinjury.

RESULTS

Among 143 traumatic (n = 55) and nontraumatic (n = 88) patients (VS/UWS, n = 68, 19 females; MCS, n = 75, 22 females), 41 (28.7%) died within 24 months postinjury. Mortality rate was higher in VS/UWS (42.6%) than in MCS (16%; p < 0.001). Multivariate regression in VS/UWS showed that significant predictors of mortality were older age and lower CRS-R total score, whereas in MCS female sex and absence of alpha rhythm on EEG at study entry were significant predictors.

CONCLUSIONS

This study demonstrated that a feasible multimodal assessment in the postacute phase can help clinicians to identify patients with pDoC at higher risk of mortality within 24 months after brain injury. This evidence can help clinicians and patients' families to navigate the complex clinical decision-making process and promote an international standardization of prognostic procedures for patients with pDoC.

Narrative Review: Quantitative EEG in Disorders of Consciousness

In this narrative review, we focus on the role of quantitative EEG technology in the diagnosis and prognosis of patients with unresponsive wakefulness syndrome and minimally conscious state. This paper is divided into two main parts, i.e., diagnosis and prognosis, each consisting of three subsections, namely, (i) resting-state EEG, including spectral power, functional connectivity, dynamic functional connectivity, graph theory, microstates and nonlinear measurements, (ii) sleep patterns, including rapid eye movement (REM) sleep, slow-wave sleep and sleep spindles and (iii) evoked potentials, including the P300, mismatch negativity, the N100, the N400 late positive component and others. Finally, we summarize our findings and conclude that QEEG is a useful tool when it comes to defining the diagnosis and prognosis of DOC patients.

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.

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.

On the Hierarchical Organization of Oscillatory Assemblies: Layered Superimposition and a Global Bioelectric Framework

Bioelectric oscillations occur throughout the nervous system of nearly all animals, revealed to play an important role in various aspects of cognitive activity such as information processing and feature binding. Modern research into this dynamic and intrinsic bioelectric activity of neural cells continues to raise questions regarding their role in consciousness and cognition. In this theoretical article, we assert a novel interpretation of the hierarchical nature of "brain waves" by identifying that the superposition of multiple oscillations varying in frequency corresponds to the superimposing of the contents of consciousness and cognition. In order to describe this isomorphism, we present a layered model of the global functional oscillations of various frequencies which act as a part of a unified metastable continuum described by the Operational Architectonics theory and suggested to be responsible for the emergence of the phenomenal mind. We detail the purposes, functions, and origins of each layer while proposing our main theory that the superimposition of these oscillatory layers mirrors the superimposition of the components of the integrated phenomenal experience as well as of cognition. In contrast to the traditional view that localizations of high and low-frequency activity are spatially distinct, many authors have suggested a hierarchical nature to oscillations. Our theoretical interpretation is founded in four layers which correlate not only in frequency but in evolutionary development. As other authors have done, we explore how these layers correlate to the phenomenology of human experience. Special importance is placed on the most basal layer of slow oscillations in coordinating and grouping all of the other layers. By detailing the isomorphism between the phenomenal and physiologic aspects of how lower frequency layers provide a foundation for higher frequency layers to be organized upon, we provide a further means to elucidate physiological and cognitive mechanisms of mind and for the well-researched outcomes of certain voluntary breathing patterns and meditative practices which modulate the mind and have therapeutic effects for psychiatric and other disorders.

Animal-assisted therapy for patients in a minimally conscious state: A randomized two treatment multi-period crossover trial

Objective

To investigate if animal-assisted therapy (AAT) leads to higher consciousness in patients in a minimally conscious state during a therapy session, measured via behavioral reactions, heart rate and heart rate variability.

Methods

In a randomized two treatment multi-period crossover trial, 10 patients in a minimally conscious state participated in eight AAT sessions and eight paralleled conventional therapy sessions, leading to 78 AAT and 73 analyzed control sessions. Patients’ responses during sessions were assessed via behavioral video coding and the Basler Vegetative State Assessment (BAVESTA), heart rate and heart rate variability (SDNN, RMSSD, HF and LF). Data were analyzed with generalized linear mixed models.

Results

Patients showed more eye movements (IRR = 1.31, 95% CI: 1.23 to 1.40, p < 0.001) and active movements per tactile input during AAT compared to control sessions (IRR = 1.13, 95% CI: 1.02 to 1.25, p = 0.018). No difference was found for positive emotions. With BAVESTA, patients’ overall behavioral reactions were rated higher during AAT (b = 0.11, 95% CI: 0.01 to 0.22, p = 0.038). AAT led to significantly higher LF (b = 5.82, 95% CI: 0.55 to 11.08, p = 0.031) and lower HF (b = -5.80, 95% CI: -11.06 to -0.57, p = 0.030), while heart rate, SDNN, RMSSD did not differ.

Conclusions

Patients in a minimally conscious state showed more behavioral reactions and increased physiological arousal during AAT compared to control sessions. This might indicate increased consciousness during therapeutic sessions in the presence of an animal.

Trial registration

ClinicalTrials.gov NCT02629302.

A Primer on Electroencephalography and Event-Related Potentials for Organizational Neuroscience

Electroencephalography (EEG) was the first of the noninvasive brain measures in neuroscience. Technical advances over the last 100 years or so have rendered EEG a true brain imaging technique. Here, we provide an accessible primer on the biophysics of EEG, on measurement aspects, and on the analysis of EEG data. We use the example of event-related potentials (ERPs), although the issues apply equally to other varieties of EEG signals, and provide an overview of analytic methods at the base of the so-called electrical neuroimaging framework. We detail the interpretational strengths of electrical neuroimaging for organizational researchers and describe some domains of ongoing technical developments. We likewise emphasize practical considerations with the use of EEG in more real-world settings. This primer is intended to provide organizational researchers specifically, and novices more generally, an access point to understanding how EEG may be applied in their research.

Effect of acoustic stimuli in patients with disorders of consciousness: a quantitative electroencephalography study

Auditory stimuli are proposed as beneficial neurorehabilitation methods in patients with disorders of consciousness. However, precise and accurate quantitative indices to estimate their potential effect remain scarce. Fourteen patients were recruited from the Neuro-Rehabilitation Unit of Hangzhou Hospital of Zhejiang Armed Police Corps of China. Altogether, there were seven cases of unresponsive wakefulness syndrome (five males and two females, aged 45.7 ± 16.8 years) and seven cases of minimally conscious state (six males and one female, aged 42.3 ± 20.8 years). Simultaneously, fourteen healthy controls (10 males and 4 females, aged 51.7 ± 9.7 years) also participated in this case-control experiment. Brain response to music, subjects’ own name, and noise was monitored by quantitative electroencephalography (QEEG) in the resting state and with acoustic stimulation. Predictive QEEG values in various brain regions were investigated. Our results show that cerebral activation was high in subjects stimulated by their own name, especially in the temporal lobe in patients with disorders of consciousness, and the frontal lobe in the control group. Further, during resting and stimulation, QEEG index (δ + θ/α + β ratio) negatively correlated with the Coma Recovery Scale-Revised score in traumatic disorders of consciousness patients. Hence, we speculate that a subject's own name might be an effective awakening therapy for patients with disorders of consciousness. Moreover, QEEG index in specific stimulation states may be used as a prognostic indicator for disorders of consciousness patients (sensitivity, 75%; specificity, 50%). This clinical study has been registered at ClinicalTrials.gov (identifier: NCT03385291).

A Review of Resting-State Electroencephalography Analysis in Disorders of Consciousness

Recently, neuroimaging technologies have been developed as important methods for assessing the brain condition of patients with disorders of consciousness (DOC). Among these technologies, resting-state electroencephalography (EEG) recording and analysis has been widely applied by clinicians due to its relatively low cost and convenience. EEG reflects the electrical activity of the underlying neurons, and it contains information regarding neuronal population oscillations, the information flow pathway, and neural activity networks. Some features derived from EEG signal processing methods have been proposed to describe the electrical features of the brain with DOC. The computation of these features is challenging for clinicians working to comprehend the corresponding physiological meanings and then to put them into clinical applications. This paper reviews studies that analyze spontaneous EEG of DOC, with the purpose of diagnosis, prognosis, and evaluation of brain interventions. It is expected that this review will promote our understanding of the EEG characteristics in DOC.

How far can we go in chronic disorders of consciousness differential diagnosis? The use of neuromodulation in detecting internal and external awareness

Awareness generation and modulation may depend on a balanced information integration and differentiation across default mode network (DMN) and external awareness networks (EAN). Neuromodulation approaches, capable of shaping information processing, may highlight residual network activities supporting awareness, which are not detectable through active paradigms, thus allowing to differentiate chronic disorders of consciousness (DoC). We studied aftereffects of repetitive transcranial magnetic stimulation (rTMS) by applying graph theory within canonical frequency bands to compare the markers of these networks in the electroencephalographic data from 20 patients with DoC. We found that patients' high-frequency networks suffered from a large-scale connectivity breakdown, paralleled by a local hyperconnectivity, whereas low-frequency networks showed a preserved but dysfunctional large-scale connectivity. There was a correlation between metrics and the behavioral awareness. Interestingly, two persons with UWS showed a residual rTMS-induced modulation of the functional correlations between the DMN and the EAN, as observed in patients with MCS. Hence, we may hypothesize that the patients with UWS who demonstrate evidence of residual DMN-EAN functional correlation may be misdiagnosed, given that such residual network correlations could support covert consciousness.

Changes in Standard Electroencephalograms Parallel Consciousness Improvements in Patients With Unresponsive Wakefulness Syndrome

OBJECTIVE

To identify changes in the standard electroencephalograms (EEGs) of patients with unresponsive wakefulness syndrome (UWS) who did or did not recover consciousness 6 months after admission to a rehabilitation department.

DESIGN

Prospective cohort study.

SETTING

Unit for severe acquired brain injuries.

PARTICIPANTS

Consecutive patients with UWS (N=28).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

EEG amplitude (reduced or normal), dominant frequency (alpha, theta, or delta), and reactivity (absent or present) were scored at admission and 6 months later. The cumulative Amplitude-Frequency-Reactivity score was evaluated. Clinical assessments were made using the Coma Recovery Scale-Revised.

RESULTS

Sixteen (57.1%) of the 28 patients with UWS recovered consciousness after 6 months, while 12 patients (42.9%) did not recover consciousness. EEG improvements occurred in 14 patients with consciousness recovery (87.5%) and 2 patients without consciousness recovery (16.7%) only. Improvements in EEG dominant frequency (from the theta to the alpha band or from the delta to the theta band), reappearance of EEG reactivity, and Amplitude-Frequency-Reactivity score increase (P<.01) differentiated patients with consciousness improvement from those without consciousness improvement. Six months after admission for rehabilitation, patients with EEG improvements showed higher Coma Recovery Scale-Revised scores than did those without EEG changes (P<.01).

CONCLUSIONS

Most patients who emerge from UWS demonstrate improvement in basic EEG characteristics over time. EEG changes in patients with UWS may aid in the timely recognition of patients transitioning into a minimally conscious state.

Long-Term (Six Years) Clinical Outcome Discrimination of Patients in the Vegetative State Could be Achieved Based on the Operational Architectonics EEG Analysis: A Pilot Feasibility Study

Electroencephalogram (EEG) recordings are increasingly used to evaluate patients with disorders of consciousness (DOC) or assess their prognosis outcome in the short-term perspective. However, there is a lack of information concerning the effectiveness of EEG in classifying long-term (many years) outcome in chronic DOC patients. Here we tested whether EEG operational architectonics parameters (geared towards consciousness phenomenon detection rather than neurophysiological processes) could be useful for distinguishing a very long-term (6 years) clinical outcome of DOC patients whose EEGs were registered within 3 months post-injury. The obtained results suggest that EEG recorded at third month after sustaining brain damage, may contain useful information on the long-term outcome of patients in vegetative state: it could discriminate patients who remain in a persistent vegetative state from patients who reach a minimally conscious state or even recover a full consciousness in a long-term perspective (6 years) post-injury. These findings, if confirmed in further studies, may be pivotal for long-term planning of clinical care, rehabilitative programs, medical-legal decisions concerning the patients, and policy makers.

Polysomnographic Sleep Patterns in Children and Adolescents in Unresponsive Wakefulness Syndrome

OBJECTIVES

We aimed (i) to search for qualitative sleep patterns for pediatric unresponsive wakefulness syndrome (SPPUWS) in prolonged polysomnographic (PSG) recordings in children and adolescents with subacute severe disorders of consciousness due to an acquired brain damage; (ii) to investigate the clinical relevance of SPPUWS and of possible neurophysiological markers (rapid eye movement sleep and sleep spindles) in PSG recordings of pediatric patients with unresponsive wakefulness syndrome (UWS).

METHODS

We performed a PSG study in 27 children with UWS due to acquired brain damage in the subacute phase. Patients received a full neurological examination and a clinical assessment with standardized scales. In addition, outcome was assessed after 36 months.

RESULTS

We identified 6 PSG patterns (SPPUWS) corresponding to increasing neuroelectrical complexity. The presence of an organized sleep pattern, as well as rapid eye movement sleep and sleep spindles, in the subacute stage appeared highly predictive of a more favorable outcome. Correlation was found between SPPUWS and recovery, as assessed by several clinical and rehabilitation scales.

CONCLUSIONS

Polysomnography can be used as a prognostic tool, as it can help determine the capability to recover from a pediatric UWS and predict outcome well before the confirmation provided by suitable clinical scales.

Brain swelling and death in children with cerebral malaria

BACKGROUND

Case fatality rates among African children with cerebral malaria remain in the range of 15 to 25%. The key pathogenetic processes and causes of death are unknown, but a combination of clinical observations and pathological findings suggests that increased brain volume leading to raised intracranial pressure may play a role. Magnetic resonance imaging (MRI) became available in Malawi in 2009, and we used it to investigate the role of brain swelling in the pathogenesis of fatal cerebral malaria in African children.

METHODS

We enrolled children who met a stringent definition of cerebral malaria (one that included the presence of retinopathy), characterized them in detail clinically, and obtained MRI scans on admission and daily thereafter while coma persisted.

RESULTS

Of 348 children admitted with cerebral malaria (as defined by the World Health Organization), 168 met the inclusion criteria, underwent all investigations, and were included in the analysis. A total of 25 children (15%) died, 21 of whom (84%) had evidence of severe brain swelling on MRI at admission. In contrast, evidence of severe brain swelling was seen on MRI in 39 of 143 survivors (27%). Serial MRI scans showed evidence of decreasing brain volume in the survivors who had had brain swelling initially.

CONCLUSIONS

Increased brain volume was seen in children who died from cerebral malaria but was uncommon in those who did not die from the disease, a finding that suggests that raised intracranial pressure may contribute to a fatal outcome. The natural history indicates that increased intracranial pressure is transient in survivors. (Funded by the National Institutes of Health and Wellcome Trust U.K.).

Questioning the dichotomy between vegetative state and minimally conscious state: a review of the statistical evidence

Given the enormous consequences that the diagnosis of vegetative state (VS) vs. minimally conscious state (MCS) may have for the treatment of patients with disorders of consciousness, it is particularly important to empirically legitimate the distinction between these two discrete levels of consciousness. Therefore, the aim of this contribution is to review all the articles reporting statistical evidence concerning the performance of patients in VS vs. patients in MCS, on behavioral or neurophysiological measures. Twenty-three articles matched these inclusion criteria, and comprised behavioral, electroencephalographic (EEG), positron emission tomography (PET) and magnetic resonance imaging (MRI) measures. The analysis of these articles yielded 47 different statistical findings. More than half of these findings (n = 24) did not reveal any statistically significant difference between VS and MCS. Overall, there was no combination of variables that allowed reliably discriminating between VS and MCS. This pattern of results casts doubt on the empirical validity of the distinction between VS and MCS.

Repetitive transcranial magnetic stimulation improves consciousness disturbance in stroke patients: A quantitative electroencephalography spectral power analysis

Repetitive transcranial magnetic stimulation is a noninvasive treatment technique that can directly alter cortical excitability and improve cerebral functional activity in unconscious patients. To investigate the effects and the electrophysiological changes of repetitive transcranial magnetic stimulation cortical treatment, 10 stroke patients with non-severe brainstem lesions and with disturbance of consciousness were treated with repetitive transcranial magnetic stimulation. A quantitative electroencephalography spectral power analysis was also performed. The absolute power in the alpha band was increased immediately after the first repetitive transcranial magnetic stimulation treatment, and the energy was reduced in the delta band. The alpha band relative power values slightly decreased at 1 day post-treatment, then increased and reached a stable level at 2 weeks post-treatment. Glasgow Coma Score and JFK Coma Recovery Scale-Revised score were improved. Relative power value in the alpha band was positively related to Glasgow Coma Score and JFK Coma Recovery Scale-Revised score. These data suggest that repetitive transcranial magnetic stimulation is a noninvasive, safe, and effective treatment technology for improving brain functional activity and promoting awakening in unconscious stroke patients.

CRS-R score in disorders of consciousness is strongly related to spectral EEG at rest

Patients suffering from disorders of consciousness still present a diagnostic challenge due to the fact that their assessment is mainly based on behavioral scales with their motor responses often being strongly impaired. We therefore focused on resting electroencephalography (EEG) in order to reveal potential alternative measures of the patient's current state independent of rather complex abilities (e.g., language comprehension). Resting EEG was recorded in nine minimally conscious state (MCS) and eight vegetative state/unresponsive wakefulness syndrome (VS/UWS) patients. Behavioral assessments were conducted using the Coma-Recovery Scale-Revised (CRS-R). The signal was analyzed in the frequency domain and association between resting EEG and CRS-R score as well as clinical diagnosis were calculated using Pearson correlation and repeated-measures ANOVAs. The analyses revealed robust positive correlations between CRS-R score and ratios between frequencies above 8 Hz and frequencies below 8 Hz. Furthermore, the frequency of the spectral peak was also highly indicative of the patient's CRS-R score. Concerning differences between clinical diagnosis and healthy controls, it could be revealed that while VS/UWS patients showed higher delta and theta activity than controls, MCS did not differ from controls in this frequency range. Alpha activity, on the other hand, was strongly decreased in both patient groups as compared to controls. The strong relationship between various resting EEG parameters and CRS-R score provides significant clinical relevance. Not only is resting activity easily acquired at bedside, but furthermore, it does not depend on explicit cooperation of the patient. Especially in cases where behavioral assessment is difficult or ambiguous, spectral analysis of resting EEG can therefore complement clinical diagnosis.

Vegetative versus minimally conscious states: a study using TMS-EEG, sensory and event-related potentials

Differential diagnoses between vegetative and minimally conscious states (VS and MCS, respectively) are frequently incorrect. Hence, further research is necessary to improve the diagnostic accuracy at the bedside. The main neuropathological feature of VS is the diffuse damage of cortical and subcortical connections. Starting with this premise, we used electroencephalography (EEG) recordings to evaluate the cortical reactivity and effective connectivity during transcranial magnetic stimulation (TMS) in chronic VS or MCS patients. Moreover, the TMS-EEG data were compared with the results from standard somatosensory-evoked potentials (SEPs) and event-related potentials (ERPs). Thirteen patients with chronic consciousness disorders were examined at their bedsides. A group of healthy volunteers served as the control group. The amplitudes (reactivity) and scalp distributions (connectivity) of the cortical potentials evoked by TMS (TEPs) of the primary motor cortex were measured. Short-latency median nerve SEPs and auditory ERPs were also recorded. Reproducible TEPs were present in all control subjects in both the ipsilateral and the contralateral hemispheres relative to the site of the TMS. The amplitudes of the ipsilateral and contralateral TEPs were reduced in four of the five MCS patients, and the TEPs were bilaterally absent in one MCS patient. Among the VS patients, five did not manifest ipsilateral or contralateral TEPs, and three of the patients exhibited only ipsilateral TEPs with reduced amplitudes. The SEPs were altered in five VS and two MCS patients but did not correlate with the clinical diagnosis. The ERPs were impaired in all patients and did not correlate with the clinical diagnosis. These TEP results suggest that cortical reactivity and connectivity are severely impaired in all VS patients, whereas in most MCS patients, the TEPs are preserved but with abnormal features. Therefore, TEPs may add valuable information to the current clinical and neurophysiological assessment of chronic consciousness disorders.

Prognostic Value of Resting-State Electroencephalography Structure in Disentangling Vegetative and Minimally Conscious States

Background. Patients in a vegetative state pose problems in diagnosis, prognosis, and treatment. Currently, no prognostic markers predict the chance of recovery, which has serious consequences, especially in end-of-life decision making. Objective. We aimed to assess an objective measurement of prognosis using advanced electroencephalography (EEG). Methods. EEG data (19 channels) were collected in 14 patients who were diagnosed to be persistently vegetative based on repeated clinical evaluations at 3 months following brain damage. EEG structure parameters (amplitude, duration, and variability within quasi-stationary segments, as well as the spatial synchrony between such segments and the strength of this synchrony) were used to predict recovery of consciousness 3 months later. Results. The number and strength of cortical functional connections between EEG segments were higher in patients who recovered consciousness ( P < .05 to P < .001) compared with those who did not recover. Linear regression analysis confirms that EEG structure parameters are capable of predicting ( P = .0025) recovery of consciousness 6 months postinjury, whereas the same analysis failed to significantly predict patient outcome based on aspects of their clinical history alone ( P = .629) or conventional EEG spectrum power ( P = .473). Conclusions. The result of this preliminary study demonstrates that structural strategy of EEG analysis is better suited for providing prognosis of consciousness recovery than existing methods of clinical assessment and of conventional EEG. Our results may be a starting point for developing reliable prognosticators in patients who are in a vegetative state, with the potential to improve their day-to-day management, quality of life, and access to early interventions.