Fig. 5

Quantitative EEG analysis of resting state EEG in patients with acute and chronic disorders of consciousness. a Stratification was based on three behavioral assessments: coma, eyes open/attending, and following commands. Spectral power plots (rows 1–4) and Posterior PSD plots (row 5) were analyzed accordingly. Statistical analyses were carried out to assess the grouped effects at each electrode among different behavioral states, with gray in the right three columns indicating P < 0.05. An increase in diffuse delta (row 1) and posterior theta (row 2) was observed between coma and arousal states. Progressively increasing posterior alpha (row 3) and central gamma (row 4) were evident between assessments consistent with coma, arousal, and awareness. Higher levels of consciousness were associated with an overall increase in power across all frequency bands, as indicated by the posterior PSD plots (row 5). b Complexity and coherence measures included PE theta (row 1), PE alpha (row 2), wSMI theta (row 3), and wPPC alpha (row 4), which correlated with the three best behavioral assessments stratified by time. wSMI theta and wPPC alpha, as connectivity measures, are represented using distinct color maps. Statistical analyses to compare the grouped effects at each electrode across various behavioral states are presented in the right three columns, where grey indicates P < 0.05. In complexity measures, theta and alpha frequency PE were significantly higher in patients who were aware, especially in the parieto-occipital regions for alpha frequencies (rows 1 and 2). Regarding information-sharing measures, slight differences in wSMI theta (row 3) were noted among the behavioral states. WPPC in alpha frequencies increased from coma to awareness (row 4), with a significant rise in central channels in aware patients compared to those in coma. c A comparison of SAH data (a, b) with data from patients with chronic disorders of consciousness due to TBI reveals that the frequency power of the alpha (|α|_n) and theta PE in VS and MCS is similarly distributed to those in the acute phase of SAH. d On the x-axis, the prediction based on EEG was shown as VS or MCS. On the y-axis, the clinical diagnosis was shown as VS, MCS or CS/Healthy. Each cell provides the count of recordings along with their corresponding percentages for each clinical state category. In most instances, EEG-based classification aligns with the clinical diagnosis for patients with VS and MCS. The pie charts illustrate the clinical outcomes for patients clinically diagnosed with VS, based on whether EEG assessments categorized them as VS or in a higher state of consciousness such as MCS or CS. As shown in green, the probability of improvement was significantly higher in MCS patients diagnosed with EEG (P = 0.02). PSD: power spectral density; PE: permutation entropy; wSMI: weighted symbolic mutual information; wPPC: weighted pairwise phase consistency; SAH: subarachnoid hemorrhage; TBI: traumatic brain injury; CNV: contingent negative variation; MMN: mismatch negativity; ΔP3b: P300b; |δ|_n: normalized power in delta band; |α|_n: normalized power in alpha band; SE: spectral entropy; PEθ: permutation entropy in theta band; K: Komolgorov-Chaitin Complexity. EEG: electroencephalogram; VS: vegetative state; CS: conscious state. Adapted from Claassen et al. [153] and Sitt et al. [122]