Measures of entropy and complexity in altered states of consciousness

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.

Study at a glance

Abstract

Quantification of complexity in neurophysiological signals has been studied using different methods, especially those from information or dynamical system theory. These studies have revealed a dependence on different states of consciousness, and in particular that wakefulness is characterized by a greater complexity of brain signals, perhaps due to the necessity for the brain to handle varied sensorimotor information. Thus, these frameworks are very useful in attempts to quantify cognitive states. We set out to analyze different types of signals obtained from scalp electroencephalography (EEG), intracranial EEG and magnetoencephalography recording in subjects during different states of consciousness: resting wakefulness, different sleep stages and epileptic seizures. The signals were analyzed using a statistical (permutation entropy) and a deterministic (permutation Lempel-Ziv complexity) analytical method. The results are presented in complexity versus entropy graphs, showing that the values of entropy and complexity of the signals tend to be greatest when the subjects are in fully alert states, falling in states with loss of awareness or consciousness. These findings were robust for all three types of recordings. We propose that the investigation of the structure of cognition using the frameworks of complexity will reveal mechanistic aspects of brain dynamics associated not only with altered states of consciousness but also with normal and pathological conditions.