Disrupted Control Architecture of Brain Network in Disorder of Consciousness

Resting-state EEG microstates as electrophysiological biomarkers in post-stroke disorder of consciousness

Introduction

Ischemic stroke patients commonly experience disorder of consciousness (DOC), leading to poorer discharge outcomes and higher mortality risks. Therefore, the identification of applicable electrophysiological biomarkers is crucial for the rapid diagnosis and evaluation of post-stroke disorder of consciousness (PS-DOC), while providing supportive evidence for cerebral neurology.

Methods

In our study, we conduct microstate analysis on resting-state electroencephalography (EEG) of 28 post-stroke patients with awake consciousness and 28 patients with PS-DOC, calculating the temporal features of microstates. Furthermore, we extract the Lempel-Ziv complexity of microstate sequences and the delta/alpha power ratio of EEG on spectral. Statistical analysis is performed to examine the distinctions in features between the two groups, followed by inputting the distinctive features into a support vector machine for the classification of PS-DOC.

Results

Both groups obtain four optimal topographies of EEG microstates, but notable distinctions are observed in microstate C. Within the PS-DOC group, there is a significant increase in the mean duration and coverage of microstates B and C, whereas microstate D displays a contrasting trend. Additionally, noteworthy variations are found in the delta/alpha ratio and Lempel-Ziv complexity between the two groups. The integration of the delta/alpha ratio with microstates' temporal and Lempel-Ziv complexity features demonstrates the highest performance in the classifier (Accuracy = 91.07%).

Discussion

Our results suggest that EEG microstates can provide insights into the abnormal brain network dynamics in DOC patients post-stroke. Integrating the temporal and Lempel-Ziv complexity microstate features with spectral features offers a deeper understanding of the neuro mechanisms underlying brain damage in patients with DOC, holding promise as effective electrophysiological biomarkers for diagnosing PS-DOC.

State-of-the-Art Evaluation of Acute Adult Disorders of Consciousness for the General Intensivist

OBJECTIVES

To provide a concise review of knowledge and practice pertaining to the diagnosis and initial management of unanticipated adult patient disorders of consciousness (DoC) by the general intensivist.

DATA SOURCES

Detailed search strategy using PubMed and OVID Medline for English language articles describing adult patient acute DoC diagnostic evaluation and initial management strategies including indications for transfer.

STUDY SELECTION

Descriptive and interventional studies that address acute adult DoC, their evaluation and initial management, indications for transfer, as well as outcome prognostication.

DATA EXTRACTION

Relevant descriptions or studies were reviewed, and the following aspects of each manuscript were identified, abstracted, and analyzed: setting, study population, aims, methods, results, and relevant implications for adult critical care practice.

DATA SYNTHESIS

Acute adult DoC may be categorized by etiology including structural, functional, infectious, inflammatory, and pharmacologic, the understanding of which drives diagnostic investigation, monitoring, acute therapy, and subsequent specialist care decisions including team-based local care as well as intra- and inter-facility transfer.

CONCLUSIONS

Acute adult DoC may be initially comprehensively addressed by the general intensivist using an etiology-driven and team-based approach. Certain clinical conditions, procedural expertise needs, or resource limitations inform transfer decision-making within a complex care facility or to one with greater complexity. Emerging collaborative science helps improve our current knowledge of acute DoC to better align therapies with underpinning etiologies.

Aberrant temporal correlations of ongoing oscillations in disorders of consciousness on multiple time scales

Changes in neural oscillation amplitude across states of consciousness has been widely reported, but little is known about the link between temporal dynamics of these oscillations on different time scales and consciousness levels. To address this question, we analyzed amplitude fluctuation of the oscillations extracted from spontaneous resting-state EEG recorded from the patients with disorders of consciousness (DOC) and healthy controls. Detrended fluctuation analysis (DFA) and measures of life-time and waiting-time were employed to characterize the temporal structure of EEG oscillations on long time scales (1-20 s) and short time scales (< 1 s), in groups with different consciousness states: patients in minimally conscious state (MCS), patients with unresponsive wakefulness syndrome (UWS) and healthy subjects. Results revealed increased DFA exponents that implies higher long-range temporal correlations (LRTC), especially in the central brain area in alpha and beta bands. On short time scales, declined bursts of oscillations were also observed. All the metrics exhibited lower individual variability in the UWS or MCS group, which may be attributed to the reduced spatial variability of oscillation dynamics. In addition, the temporal dynamics of EEG oscillations showed significant correlations with the behavioral responsiveness of patients. In summary, our findings shows that loss of consciousness is accompanied by alternation of temporal structure in neural oscillations on multiple time scales, and thus may help uncover the mechanism of underlying neuronal correlates of consciousness.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09852-9.