Cortical Information Processing in Coma

Decoding Analyses Show Dynamic Waxing and Waning of Event-Related Potentials in Coma Patients

Background/Objectives: Coma prognosis is challenging, as patient presentation can be misleading or uninformative when using behavioral assessments only. Event-related potentials have been shown to provide valuable information about a patient's chance of survival and emergence from coma. Our prior work revealed that the mismatch negativity (MMN) in particular waxes and wanes across 24 h in some coma patients. This "cycling" aspect of the presence/absence of neurophysiological responses may require fine-grained tools to increase the chances of detecting levels of neural processing in coma. This study implements multivariate pattern analysis (MVPA) to automatically quantify patterns of neural discrimination between duration deviant and standard tones over time at the single-subject level in seventeen healthy controls and in three comatose patients. Methods: One EEG recording, containing up to five blocks of an auditory oddball paradigm, was performed in controls over a 12 h period. For patients, two EEG sessions were conducted 3 days apart for up to 24 h, denoted as day 0 and day 3, respectively. MVPA was performed using a support-vector machine classifier. Results: Healthy controls exhibited reliable discrimination or classification performance during the latency intervals associated with MMN and P3a components. Two patients showed some intervals with significant discrimination around the second half of day 0, and all had significant results on day 3. Conclusions: These findings suggest that decoding analyses can accurately classify neural responses at a single-subject level in healthy controls and provide evidence of small but significant changes in auditory discrimination over time in coma patients. Further research is needed to confirm whether this approach represents an improved technology for assessing cognitive processing in coma.

Neurophysiological measures of covert semantic processing in neurotypical adolescents actively ignoring spoken sentence inputs: A high-density event-related potential (ERP) study

Language comprehension requires semantic processing of individual words and their context within a sentence. Well-characterized event-related potential (ERP) components (the N400 and late positivity component (LPC/P600)) provide neuromarkers of semantic processing, and are robustly evoked when semantic errors are introduced into sentences. These measures are useful for evaluating semantic processing in clinical populations, but it is not known whether they can be evoked in more severe neurodevelopmental disorders where explicit attention to the sentence inputs cannot be objectively assessed (i.e., when sentences are passively listened to). We evaluated whether N400 and LPC/P600 could be detected in adolescents who were explicitly ignoring sentence inputs. Specifically, it was asked whether explicit attention to spoken inputs was required for semantic processing, or if a degree of automatic processing occurs when the focus of attention is directed elsewhere? High-density ERPs were acquired from twenty-two adolescents (12-17 years), under two experimental conditions: 1. individuals actively determined whether the final word in a sentence was congruent or incongruent with sentence context, or 2. passively listened to background sentences while watching a video. When sentences were ignored, N400 and LPC/P600 were robustly evoked to semantic errors, albeit with reduced amplitudes and protracted/delayed latencies. Statistically distinct topographic distributions during passive versus active paradigms pointed to distinct generator configurations for semantic processing as a function of attention. Covert semantic processing continues in neurotypical adolescents when explicit attention is withdrawn from sentence inputs. As such, this approach could be used to objectively investigate semantic processing in populations with communication deficits.

Tracking auditory mismatch negativity responses during full conscious state and coma

The mismatch negativity (MMN) is considered the electrophysiological change-detection response of the brain, and therefore a valuable clinical tool for monitoring functional changes associated with return to consciousness after severe brain injury. Using an auditory multi-deviant oddball paradigm, we tracked auditory MMN responses in seventeen healthy controls over a 12-h period, and in three comatose patients assessed over 24 h at two time points. We investigated whether the MMN responses show fluctuations in detectability over time in full conscious awareness, or whether such fluctuations are rather a feature of coma. Three methods of analysis were utilized to determine whether the MMN and subsequent event-related potential (ERP) components could be identified: traditional visual analysis, permutation t-test, and Bayesian analysis. The results showed that the MMN responses elicited to the duration deviant-stimuli are elicited and reliably detected over the course of several hours in healthy controls, at both group and single-subject levels. Preliminary findings in three comatose patients provide further evidence that the MMN is often present in coma, varying within a single patient from easily detectable to undetectable at different times. This highlights the fact that regular and repeated assessments are extremely important when using MMN as a neurophysiological predictor of coma emergence.

Complementary roles of neural synchrony and complexity for indexing consciousness and chances of surviving in acute coma

An open challenge in consciousness research is understanding how neural functions are altered by pathological loss of consciousness. To maintain consciousness, the brain needs synchronized communication of information across brain regions, and sufficient complexity in neural activity. Coordination of brain activity, typically indexed through measures of neural synchrony, has been shown to decrease when consciousness is lost and to reflect the clinical state of patients with disorders of consciousness. Moreover, when consciousness is lost, neural activity loses complexity, while the levels of neural noise, indexed by the slope of the electroencephalography (EEG) spectral exponent decrease. Although these properties have been well investigated in resting state activity, it remains unknown whether the sensory processing network, which has been shown to be preserved in coma, suffers from a loss of synchronization or information content. Here, we focused on acute coma and hypothesized that neural synchrony in response to auditory stimuli would reflect coma severity, while complexity, or neural noise, would reflect the presence or loss of consciousness. Results showed that neural synchrony of EEG signals was stronger for survivors than non-survivors and predictive of patients' outcome, but indistinguishable between survivors and healthy controls. Measures of neural complexity and neural noise were not informative of patients' outcome and had high or low values for patients compared to controls. Our results suggest different roles for neural synchrony and complexity in acute coma. Synchrony represents a precondition for consciousness, while complexity needs an equilibrium between high or low values to support conscious cognition.

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.

Combined Behavioral and Mismatch Negativity Evidence for the Effects of Long-Lasting High-Definition tDCS in Disorders of Consciousness: A Pilot Study

Objective

To evaluate the effects of long-term High-definition transcranial direct current stimulation (HD-tDCS) over precuneus on the level of consciousness (LOC) and the relationship between Mismatch negativity (MMN) and the LOC over the therapy period in patients with Disorders of consciousness (DOCs).

Methods

We employed a with-in group repeated measures design with an anode HD-tDCS protocol (2 mA, 20 min, the precuneus) on 11 (2 vegetative state and nine minimally conscious state) patients with DOCs. MMN and Coma Recovery Scale-Revised (CRS-R) scores were measured at four time points: before the treatment of HD-tDCS (T0), after a single session of HD-tDCS (T1), after the treatment of 7 days (T2) and 14 days (T3). A frequency-deviant oddball paradigm with two deviation magnitudes (standard stimulus: 1000 Hz, small deviant stimuli: 1050 Hz, large deviant stimuli: 1200 Hz) was adopted to elicit MMN.

Results

Significant improvements of CRS-R score were found after 7-day (T2) and 14-day (T3) treatment compared with baseline (T0). Regarding the MMN, significant improvements of MMN amplitudes were observed after a single session of stimulation (T1), 7-day (T2) and 14-day treatment (T3) compared with baseline (T0). Additionally, there were significant negative correlations between CRS-R scores and MMN amplitudes elicited by both large and small deviant stimuli.

Conclusion

Long-term HD-tDCS over precuneus might improve signs of consciousness in patients with DOCs as measured by CRS-R total scores, and MMN could be an assistant assessment in the course of tDCS treatment.

The N400 for brain computer interfacing: complexities and opportunities

The N400 is an event related potential that is evoked in response to conceptually meaningful stimuli. It is for instance more negative in response to incongruent than congruent words in a sentence, and more negative for unrelated than related words following a prime word. This sensitivity to semantic content of a stimulus in relation to the mental context of an individual makes it a signal of interest for Brain Computer Interfaces. A complicating aspect is the number of factors that can affect the N400 amplitude. In this paper, we provide an accessible overview of this range of N400 effects, and survey the three main BCI application areas that currently exploit the N400: (1) exploiting the semantic processing of faces to enhance matrix speller performance, (2) detecting language processing in patients with Disorders of Consciousness, and (3) using semantic stimuli to probe what is on a user's mind. Drawing on studies from these application areas, we illustrate that the N400 can successfully be exploited for BCI purposes, but that the signal-to-noise ratio is a limiting factor, with signal strength also varying strongly across subjects. Furthermore, we put findings in context of the general N400 literature, noting open questions and identifying opportunities for further research.

Development of a point of care system for automated coma prognosis: a prospective cohort study protocol

INTRODUCTION

Coma is a deep state of unconsciousness that can be caused by a variety of clinical conditions. Traditional tests for coma outcome prediction are based mainly on a set of clinical observations. Recently, certain event-related potentials (ERPs), which are transient electroencephalogram (EEG) responses to auditory, visual or tactile stimuli, have been introduced as useful predictors of a positive coma outcome (ie, emergence). However, such tests require the skills of clinical neurophysiologists, who are not commonly available in many clinical settings. Additionally, none of the current standard clinical approaches have sufficient predictive accuracies to provide definitive prognoses.

OBJECTIVE

The objective of this study is to develop improved machine learning procedures based on EEG/ERP for determining emergence from coma.

METHODS AND ANALYSIS

Data will be collected from 50 participants in coma. EEG/ERP data will be recorded for 24 consecutive hours at a maximum of five time points spanning 30 days from the date of recruitment to track participants' progression. The study employs paradigms designed to elicit brainstem potentials, middle-latency responses, N100, mismatch negativity, P300 and N400. In the case of patient emergence, data are recorded on that occasion to form an additional basis for comparison. A relevant data set will be developed from the testing of 20 healthy controls, each spanning a 15-hour recording period in order to formulate a baseline. Collected data will be used to develop an automated procedure for analysis and detection of various ERP components that are salient to prognosis. Salient features extracted from the ERP and resting-state EEG will be identified and combined to give an accurate indicator of prognosis.

ETHICS AND DISSEMINATION

This study is approved by the Hamilton Integrated Research Ethics Board (project number 4840). Results will be disseminated through peer-reviewed journal articles and presentations at scientific conferences.

TRIAL REGISTRATION NUMBER

NCT03826407.

Measuring Mindfulness: A Psychophysiological Approach

Mindfulness-based interventions have proved effective in reducing various clinical symptoms and in improving general mental health and well-being. The investigation of the mechanisms of therapeutic change needs methods for assessment of mindfulness. Existing self-report measures have, however, been strongly criticized on various grounds, including distortion of the original concept, response bias, and other. We propose a psychophysiological method for the assessment of the mindfulness learned through time-limited mindfulness-based therapy by people who undergo meditation training for the first time. We use the individual pre-post-therapy changes (dERPi) in the event-related brain potentials (ERPs) recorded in a passive meditation task as a measure of increased mindfulness. dERPi is computed through multivariate assessment of individual participant's ERPs. We tested the proposed method in a group of about 70 recurrently depressed participants, randomly assigned in 1.7:1 ratio to mindfulness-based cognitive therapy (MBCT) or cognitive therapy (CT). The therapy outcome was measured by the long-term change (dDS) relative to baseline in the depression symptoms (DS) assessed weekly, for 60 weeks, by an online self-report questionnaire. We found a strong, highly significant, negative correlation (r = -0.55) between dERPi (mean = 0.4) and dDS (mean = -0.7) in the MBCT group. Compared to this result, the relationship between dDS and the other (self-report) measures of mindfulness we used was substantially weaker and not significant. So was also the relationship between dERPi and dDS in the CT group. The interpretation of dERPi as a measure of increased mindfulness was further supported by positive correlations between dERPi and the other measures of mindfulness. In this study, we also replicated a previous result, namely, the increase (dLCNV) of the late contingent negative variation (LCNV) of the ERP in the MBCT group, but not in the control group (in this case, CT). We interpreted dLCNV as a measure of increased meditative concentration. The relationship between dLCNV and dDS was, however, very week, which suggests that concentration might be relatively unimportant for the therapeutic effect of mindfulness. The proposed psychophysiological method could become an important component of a "mindfulness test battery" together with self-report questionnaires and other newly developed instruments.

Preliminary Investigation of the Passively Evoked N400 as a Tool for Estimating Speech-in-Noise Thresholds

PURPOSE

Speech-in-noise testing relies on a number of factors beyond the auditory system, such as cognitive function, compliance, and motor function. It may be possible to avoid these limitations by using electroencephalography. The present study explored this possibility using the N400.

METHOD

Eleven adults with typical hearing heard high-constraint sentences with congruent and incongruent terminal words in the presence of speech-shaped noise. Participants ignored all auditory stimulation and watched a video. The signal-to-noise ratio (SNR) was varied around each participant's behavioral threshold during electroencephalography recording. Speech was also heard in quiet.

RESULTS

The amplitude of the N400 effect exhibited a nonlinear relationship with SNR. In the presence of background noise, amplitude decreased from high (+4 dB) to low (+1 dB) SNR but increased dramatically at threshold before decreasing again at subthreshold SNR (-2 dB).

CONCLUSIONS

The SNR of speech in noise modulates the amplitude of the N400 effect to semantic anomalies in a nonlinear fashion. These results are the first to demonstrate modulation of the passively evoked N400 by SNR in speech-shaped noise and represent a first step toward the end goal of developing an N400-based physiological metric for speech-in-noise testing.

Developing Brain Vital Signs: Initial Framework for Monitoring Brain Function Changes Over Time

Clinical assessment of brain function relies heavily on indirect behavior-based tests. Unfortunately, behavior-based assessments are subjective and therefore susceptible to several confounding factors. Event-related brain potentials (ERPs), derived from electroencephalography (EEG), are often used to provide objective, physiological measures of brain function. Historically, ERPs have been characterized extensively within research settings, with limited but growing clinical applications. Over the past 20 years, we have developed clinical ERP applications for the evaluation of functional status following serious injury and/or disease. This work has identified an important gap: the need for a clinically accessible framework to evaluate ERP measures. Crucially, this enables baseline measures before brain dysfunction occurs, and might enable the routine collection of brain function metrics in the future much like blood pressure measures today. Here, we propose such a framework for extracting specific ERPs as potential “brain vital signs.” This framework enabled the translation/transformation of complex ERP data into accessible metrics of brain function for wider clinical utilization. To formalize the framework, three essential ERPs were selected as initial indicators: (1) the auditory N100 (Auditory sensation); (2) the auditory oddball P300 (Basic attention); and (3) the auditory speech processing N400 (Cognitive processing). First step validation was conducted on healthy younger and older adults (age range: 22–82 years). Results confirmed specific ERPs at the individual level (86.81–98.96%), verified predictable age-related differences (P300 latency delays in older adults, p < 0.05), and demonstrated successful linear transformation into the proposed brain vital sign (BVS) framework (basic attention latency sub-component of BVS framework reflects delays in older adults, p < 0.05). The findings represent an initial critical step in developing, extracting, and characterizing ERPs as vital signs, critical for subsequent evaluation of dysfunction in conditions like concussion and/or dementia.

A rapid event-related potential (ERP) method for point-of-care evaluation of brain function: development of the Halifax Consciousness Scanner

BACKGROUND

Event-related potentials (ERPs) may provide a non-invasive index of brain function for a range of clinical applications. However, as a lab-based technique, ERPs are limited by technical challenges that prevent full integration into clinical settings.

NEW METHOD

To translate ERP capabilities from the lab to clinical applications, we have developed methods like the Halifax Consciousness Scanner (HCS). HCS is essentially a rapid, automated ERP evaluation of brain functional status. The present study describes the ERP components evoked from auditory tones and speech stimuli. ERP results were obtained using a 5-min test in 100 healthy individuals. The HCS sequence was designed to evoke the N100, the mismatch negativity (MMN), P300, the early negative enhancement (ENE), and the N400. These components reflected sensation, perception, attention, memory, and language perception, respectively. Component detection was examined at group and individual levels, and evaluated across both statistical and classification approaches.

RESULTS

All ERP components were robustly detected at the group level. At the individual level, nonparametric statistical analyses showed reduced accuracy relative to support vector (SVM) machine classification, particularly for speech-based ERPs. Optimized SVM results were MMN: 95.6%; P300: 99.0%; ENE: 91.8%; and N400: 92.3%.

CONCLUSIONS

A spectrum of individual-level ERPs can be obtained in a very short time. Machine learning classification improved detection accuracy across a large healthy control sample. Translating ERPs into clinical applications is increasingly possible at the individual level.

Robust discrimination between EEG responses to categories of environmental sounds in early coma

Humans can recognize categories of environmental sounds, including vocalizations produced by humans and animals and the sounds of man-made objects. Most neuroimaging investigations of environmental sound discrimination have studied subjects while consciously perceiving and often explicitly recognizing the stimuli. Consequently, it remains unclear to what extent auditory object processing occurs independently of task demands and consciousness. Studies in animal models have shown that environmental sound discrimination at a neural level persists even in anesthetized preparations, whereas data from anesthetized humans has thus far provided null results. Here, we studied comatose patients as a model of environmental sound discrimination capacities during unconsciousness. We included 19 comatose patients treated with therapeutic hypothermia (TH) during the first 2 days of coma, while recording nineteen-channel electroencephalography (EEG). At the level of each individual patient, we applied a decoding algorithm to quantify the differential EEG responses to human vs. animal vocalizations as well as to sounds of living vocalizations vs. man-made objects. Discrimination between vocalization types was accurate in 11 patients and discrimination between sounds from living and man-made sources in 10 patients. At the group level, the results were significant only for the comparison between vocalization types. These results lay the groundwork for disentangling truly preferential activations in response to auditory categories, and the contribution of awareness to auditory category discrimination.

Non-invasive EEG-based brain-computer interfaces in patients with disorders of consciousness

Disorders of consciousness (DoCs) are chronic conditions resulting usually from severe neurological deficits. The limitations of the existing diagnosis systems and methodologies cause a need for additional tools for relevant patients with DoCs assessment, including brain-computer interfaces (BCIs). Recent progress in BCIs' clinical applications may offer important breakthroughs in the diagnosis and therapy of patients with DoCs. Thus the clinical significance of BCI applications in the diagnosis of patients with DoCs is hard to overestimate. One of them may be brain-computer interfaces. The aim of this study is to evaluate possibility of non-invasive EEG-based brain-computer interfaces in diagnosis of patients with DOCs in post-acute and long-term care institutions.

Progression of auditory discrimination based on neural decoding predicts awakening from coma

Auditory evoked potentials are informative of intact cortical functions of comatose patients. The integrity of auditory functions evaluated using mismatch negativity paradigms has been associated with their chances of survival. However, because auditory discrimination is assessed at various delays after coma onset, it is still unclear whether this impairment depends on the time of the recording. We hypothesized that impairment in auditory discrimination capabilities is indicative of coma progression, rather than of the comatose state itself and that rudimentary auditory discrimination remains intact during acute stages of coma. We studied 30 post-anoxic comatose patients resuscitated from cardiac arrest and five healthy, age-matched controls. Using a mismatch negativity paradigm, we performed two electroencephalography recordings with a standard 19-channel clinical montage: the first within 24 h after coma onset and under mild therapeutic hypothermia, and the second after 1 day and under normothermic conditions. We analysed electroencephalography responses based on a multivariate decoding algorithm that automatically quantifies neural discrimination at the single patient level. Results showed high average decoding accuracy in discriminating sounds both for control subjects and comatose patients. Importantly, accurate decoding was largely independent of patients' chance of survival. However, the progression of auditory discrimination between the first and second recordings was informative of a patient's chance of survival. A deterioration of auditory discrimination was observed in all non-survivors (equivalent to 100% positive predictive value for survivors). We show, for the first time, evidence of intact auditory processing even in comatose patients who do not survive and that progression of sound discrimination over time is informative of a patient's chance of survival. Tracking auditory discrimination in comatose patients could provide new insight to the chance of awakening in a quantitative and automatic fashion during early stages of coma.

Unconscious knowledge: A survey

The concept of unconscious knowledge is fundamental for an understanding of human thought processes and mentation in general; however, the psychological community at large is not familiar with it. This paper offers a survey of the main psychological research currently being carried out into cognitive processes, and examines pathways that can be integrated into a discipline of unconscious knowledge. It shows that the field has already a defined history and discusses some of the features that all kinds of unconscious knowledge seem to share at a deeper level. With the aim of promoting further research, we discuss the main challenges which the postulation of unconscious cognition faces within the psychological community.

Towards brain first-aid: a diagnostic device for conscious awareness

When the brain is damaged, evaluating an individual's level of awareness can be a major diagnostic challenge (Is he or she in there?). Existing tests typically rely on behavioral indicators, which are incorrect in as many as one out of every two cases. The current paper presents a diagnostic device that addresses this problem. The technology circumvents behavioral limitations through noninvasive brain wave measurements (electroencephalography, or EEG). Unlike traditional EEG, the device is designed for point-of-care use by incorporating a portable, user-friendly, and stable design. It uses a novel software algorithm that automates subject stimulation, data acquisition/analysis, and the reporting of results. The test provides indicators for five identifiable levels of neural processing: sensation, perception, attention, memory, and language. The results are provided as rapidly obtained diagnostic, reliability, validity, and prognostic scores. The device can be applied to a wide variety of patients across a host of different environments. The technology is designed to be wireless-enabled for remote monitoring and assessment capabilities. In essence, the device is developed to scan for conscious awareness in order to optimize subsequent patient care.

Semantic processing in comatose patients with intact temporal lobes as reflected by the N400 event-related potential

The present study aimed at determining whether the N400 effect (an ERP index of semantic processing) for spoken words occurs in comatose patients. The patients, treated in an intensive care unit, scored less than 8 points in the glasgow coma score at the time of the recording. Semantically related and unrelated spoken word pairs were delivered to patients through headphones at a rate of 1/3s. Patients with an intact temporal lobe exhibited differential N400-like responses for semantically related and unrelated word pairs, which suggests that word semantics can be processed even in the comatose state. In contrast, patients with an injured temporal lobe showed no such effect.