Managing disorders of consciousness: the role of electroencephalography

Bai, Yang; Lin, Yajun; Ziemann, Ulf

doi:10.1007/s00415-020-10095-z

Cited by 94 publications

(58 citation statements)

References 127 publications

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“…For example, they show a better association with consciousness compared to delta power (Frohlich, Toker, & Monti, 2021), alpha power (Esposito, Nielsen, & Paquette, 2004;Westmoreland, Klass, Sharbrough, & Reagan, 1975), or the P3b (Sergent et al, 2021). For this reason, measures of integration and differentiation, and their broad experimental validation as reliable indices of consciousness, are recognized as important advancements from a clinical (Bai, Lin, & Ziemann, 2020;Comanducci et al, 2020) and ethical (Bayne, Seth, & Massimini, 2020) standpoint; we think that they may also offer empirical ground for a more positive appraisal of their theoretical foundations. The groundbreaking, viewpoint theory of Merker et al explains several properties of the conscious field (the "conscious field" is defined as all that one is conscious of at one moment in time).…”

Section: Conflict Of Interest Nonementioning

confidence: 99%

Why evolve consciousness? Neural credit and blame allocation as a core function of consciousness

Fitch¹

2022

Behav Brain Sci

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I concur with Merker and colleague's critiques, suggesting that hypotheses about the evolutionary function of consciousness can help address them. Brains are parallel systems that function to compute possible actions and predict outcomes. I hypothesize that a core function of consciousness per se is the global feedback of information about those actions actually executed, supporting local learning via neuronal updating.

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Section: Conflict Of Interest Nonementioning

confidence: 99%

Why evolve consciousness? Neural credit and blame allocation as a core function of consciousness

Fitch¹

2022

Behav Brain Sci

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“…The use of high-density EEG (e.g., >60 channels) now provides a greater degree of spatial resolution ( 8 ). In addition to its clinical use in epilepsy, sleep disorders, and dementia with Lewy bodies ( 8 , 9 ), EEG has been used to investigate cortical activity and functional connectivity in stroke ( 10 , 11 ), consciousness disorders ( 12 ), Alzheimer's disease ( 13 ), Parkinson's disease ( 14 ), schizophrenia ( 15 ), and mood disorders ( 16 ).…”

Section: Introductionmentioning

confidence: 99%

Electroencephalogram (EEG) With or Without Transcranial Magnetic Stimulation (TMS) as Biomarkers for Post-stroke Recovery: A Narrative Review

et al. 2022

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Stroke is one of the leading causes of death and disability. Despite the high prevalence of stroke, characterizing the acute neural recovery patterns that follow stroke and predicting long-term recovery remains challenging. Objective methods to quantify and characterize neural injury are still lacking. Since neuroimaging methods have a poor temporal resolution, EEG has been used as a method for characterizing post-stroke recovery mechanisms for various deficits including motor, language, and cognition as well as predicting treatment response to experimental therapies. In addition, transcranial magnetic stimulation (TMS), a form of non-invasive brain stimulation, has been used in conjunction with EEG (TMS-EEG) to evaluate neurophysiology for a variety of indications. TMS-EEG has significant potential for exploring brain connectivity using focal TMS-evoked potentials and oscillations, which may allow for the system-specific delineation of recovery patterns after stroke. In this review, we summarize the use of EEG alone or in combination with TMS in post-stroke motor, language, cognition, and functional/global recovery. Overall, stroke leads to a reduction in higher frequency activity (≥8 Hz) and intra-hemispheric connectivity in the lesioned hemisphere, which creates an activity imbalance between non-lesioned and lesioned hemispheres. Compensatory activity in the non-lesioned hemisphere leads mostly to unfavorable outcomes and further aggravated interhemispheric imbalance. Balanced interhemispheric activity with increased intrahemispheric coherence in the lesioned networks correlates with improved post-stroke recovery. TMS-EEG studies reveal the clinical importance of cortical reactivity and functional connectivity within the sensorimotor cortex for motor recovery after stroke. Although post-stroke motor studies support the prognostic value of TMS-EEG, more studies are needed to determine its utility as a biomarker for recovery across domains including language, cognition, and hemispatial neglect. As a complement to MRI-based technologies, EEG-based technologies are accessible and valuable non-invasive clinical tools in stroke neurology.

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“…Several quantitative approaches, with uneven complexity, of EEG signal post-processing and elaboration, have been applied, including the analysis of power spectrum, complexity, entropy, or functional/effective connectivity. All these measures have the aim of suitably defining the degree of the dysfunction associated with the impaired consciousness or predicting the outcome (see recent reviews of [2][3][4][5][6]).…”

Section: Introductionmentioning

confidence: 99%

Entropy Metrics Correlating with Higher Residual Functioning in Patients with Chronic Disorders of Consciousness

et al. 2022

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To test the ability of different entropy measures to classify patients with different conditions of chronic disorder of consciousness, we applied the Lempel–Ziv complexity, the amplitude coalition entropy (ACE), and the synchrony coalition entropy (SCE) to the EEG signals recorded in 32 patients, clinically evaluated using the coma recovery scale revised (CRS-R). All the entropy measures indicated that differences found in the theta and alpha bands can distinguish patients in a minimal consciousness state (MCS) with respect to those in a vegetative state/unresponsive wakefulness state (VS/UWS). These differences were significant comparing the entropy measure performed on the anterior region of the left hemisphere and midline region. The values of theta-alpha entropy positively correlated with those of the CRS-R scores. Among the entropy measures, ACE most often highlighted significant differences. The higher values found in MCS were for the less impaired patients, according to their CRS-R, suggest that the preservation of signal entropy on the anterior region of the dominant hemisphere correlates with better preservation of consciousness, even in chronic conditions.

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Managing disorders of consciousness: the role of electroencephalography

Cited by 94 publications

References 127 publications

Why evolve consciousness? Neural credit and blame allocation as a core function of consciousness

Why evolve consciousness? Neural credit and blame allocation as a core function of consciousness

Electroencephalogram (EEG) With or Without Transcranial Magnetic Stimulation (TMS) as Biomarkers for Post-stroke Recovery: A Narrative Review

Entropy Metrics Correlating with Higher Residual Functioning in Patients with Chronic Disorders of Consciousness

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