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

Bai, Yang; Xia, Xiaoyu; Li, Xiaoli

doi:10.3389/fneur.2017.00471

Cited by 78 publications

(67 citation statements)

References 77 publications

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“…While resting state-EEG records mainly spontaneous neural activity, indicating a rather fundamental brain state (Bai et al 2017), Event-Related Potentials (ERP) are induced by a stimulus representing associated sensory, cognitive, affective and motor processes (Kappenman and Luck 2011).…”

Section: Electrophysiologymentioning

confidence: 99%

Biomarkers and neuromodulation techniques in substance use disorders

et al. 2020

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Addictive disorders are a severe health concern. Conventional therapies have just moderate success and the probability of relapse after treatment remains high. Brain stimulation techniques, such as transcranial Direct Current Stimulation (tDCS) and Deep Brain Stimulation (DBS), have been shown to be effective in reducing subjectively rated substance craving. However, there are few objective and measurable parameters that reflect neural mechanisms of addictive disorders and relapse. Key electrophysiological features that characterize substance related changes in neural processing are Event-Related Potentials (ERP). These high temporal resolution measurements of brain activity are able to identify neurocognitive correlates of addictive behaviours. Moreover, ERP have shown utility as biomarkers to predict treatment outcome and relapse probability. A future direction for the treatment of addiction might include neural interfaces able to detect addiction-related neurophysiological parameters and deploy neuromodulation adapted to the identified pathological features in a closed-loop fashion. Such systems may go beyond electrical recording and stimulation to employ sensing and neuromodulation in the pharmacological domain as well as advanced signal analysis and machine learning algorithms. In this review, we describe the state-of-the-art in the treatment of addictive disorders with electrical brain stimulation and its effect on addiction-related neurophysiological markers. We discuss advanced signal processing approaches and multi-modal neural interfaces as building blocks in future bioelectronics systems for treatment of addictive disorders.

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Section: Electrophysiologymentioning

confidence: 99%

Biomarkers and neuromodulation techniques in substance use disorders

et al. 2020

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“…Given that a patient’s state of conscious awareness hinges on many factors and can change over time; it makes sense to assess and monitor these patients once they are medically stable in the sub-acute phase. In recent years, several measures for capturing task related neural activity such as alpha band power, spectral edge frequency and mean spectral frequency have been identified ( Bai et al 2017 ; Song et al 2018 ). Additional measures have also been reported for evaluating blink related oscillation effects, with some demonstrated efficacy in differentiating between vegetative and minimally conscious state patients ( Bonfiglio et al 2013 , 2014 ; Liu et al 2017 ).…”

Section: Discussionmentioning

confidence: 99%

Point-of-care brain injury evaluation of conscious awareness: wide scale deployment of portable HCS EEG evaluation

Fleck-Prediger

Hajra

Liu

et al. 2018

Neuroscience of Consciousness

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Survivors of severe brain injury may remain in a decreased state of conscious awareness for an extended period of time. Clinical scales are used to describe levels of consciousness but rely on behavioural responses, precipitating misdiagnosis. We have previously utilized event-related potentials (ERPs) to circumvent reliance on behavioural responses. However, practical implementation barriers limit the clinical utility of ERP assessment at point-of-care (POC). To address this challenge, we developed the Halifax Consciousness Scanner (HCS)—a rapid, semi-automated electroencephalography system. The current study evaluated: (i) HCS feasibility in sub-acute, POC settings nationwide; (ii) ERP P300 responses in patients with acquired brain injury versus healthy controls; and (iii) correlations within and between clinical measures and P300 latencies. We assessed 28 patients with severe, chronic impairments from brain injuries and contrasted the results with healthy control data (n = 100). Correlational analyses examined relationships between P300 latencies and the commonly used clinical scales. P300 latencies were significantly delayed in patients compared to healthy controls (P < 0.05). Clinical assessment scores were significantly inter-correlated and correlated significantly with P300 latencies (P < 0.05). In sub-acute and chronic care settings, the HCS provided a physiological measure of neurocognitive processing at POC for patients with severe acquired brain injury, including those with disorders of consciousness.

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“…We expanded the role of ERPs in residual awareness detection by describing the effects of Non-Invasive Brain Stimulation (NIBS) (including transcranial magnetic (TMS) and direct/alternating current stimulation (tDCS and tACS, respectively)) on the spectral properties of ERPs elicited by visual and auditory stimulation (according to an acoustical and/or visual discrimination paradigm (P300)) in patients with DoC. The rationale of assessing the spectral content of ERPs with regard to the missing diagnosis of fLIS relied on the fact that specific ERPs features express the underling network processes that generate ERPs [90][91][92][93][94]. Even though these networks are not necessarily relevant for awareness to emerge, spectrum power, coherence, entropy spectrum, non-linear analysis, information theory, and functional connectivity were the most useful features to differentiate consciousness levels, predict outcome, and measure patients' brain responses to brain interventions [62,76,95].…”

Section: Evoked Potentialsmentioning

confidence: 99%

Toward Improving Diagnostic Strategies in Chronic Disorders of Consciousness: An Overview on the (Re-)Emergent Role of Neurophysiology

Billeri

Filoni²,

Russo³

et al. 2020

Brain Sciences

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The differential diagnosis of patients with Disorder of Consciousness (DoC), in particular in the chronic phase, is significantly difficult. Actually, about 40% of patients with unresponsive wakefulness syndrome (UWS) and the minimally conscious state (MCS) are misdiagnosed. Indeed, only advanced paraclinical approaches, including advanced EEG analyses, can allow achieving a more reliable diagnosis, that is, discovering residual traces of awareness in patients with UWS (namely, functional Locked-In Syndrome (fLIS)). These approaches aim at capturing the residual brain network models, at rest or that may be activated in response to relevant stimuli, which may be appropriate for awareness to emerge (despite their insufficiency to generate purposeful motor behaviors). For this, different brain network models have been studied in patients with DoC by using sensory stimuli (i.e., passive tasks), probing response to commands (i.e., active tasks), and during resting-state. Since it can be difficult for patients with DoC to perform even simple active tasks, this scoping review aims at summarizing the current, innovative neurophysiological examination methods in resting state/passive modality to differentiate and prognosticate patients with DoC. We conclude that the electrophysiologically-based diagnostic procedures represent an important resource for diagnosis, prognosis, and, therefore, management of patients with DoC, using advance passive and resting state paradigm analyses for the patients who lie in the “greyzones” between MCS, UWS, and fLIS.

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

Cited by 78 publications

References 77 publications

Biomarkers and neuromodulation techniques in substance use disorders

Biomarkers and neuromodulation techniques in substance use disorders

Point-of-care brain injury evaluation of conscious awareness: wide scale deployment of portable HCS EEG evaluation

Toward Improving Diagnostic Strategies in Chronic Disorders of Consciousness: An Overview on the (Re-)Emergent Role of Neurophysiology

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