Quantitative EEG features related to the edge of criticality hypothesis and their predictive value of neurological outcome after coma

In this work, we investigate the edge of criticality hypothesis in a large eeg cohort consisting of awake, anesthesized, comatose, and epileptic patients. The hypothesis connects the wakefulness of patients to the complexity and chaoticity of brain dynamics. Diverse metrics from complexity, entropy, and chaoticity analysis are applied to minimally processed eeg to compare our findings to the hypothesis from the literature. We found a relationship between the complexity of EEG signals and wakefulness. However, we could also show that there is no one-to-one relation between these two measures.