Measures of entropy and complexity in altered states of consciousness
Cognitive Neurodynamics October 20, 2017 D. M. Mateos, R. Guevara Erra, R. Wennberg et al. 124 citations
Brain signals are most complex when people are fully awake and alert, and complexity decreases during sleep and epileptic seizures. Researchers analyzed electroencephalography (EEG), intracranial EEG, and magnetoencephalography recordings from subjects during resting wakefulness, different sleep stages, and seizures. They used permutation entropy and permutation Lempel-Ziv complexity to measure signal complexity. Complexity-versus-entropy graphs showed that both measures were highest during wakefulness and fell during states with reduced awareness. These patterns held across all three recording types. The authors suggest that studying the structure of cognition through complexity frameworks can reveal brain dynamics underlying normal, altered, and pathological states of consciousness.