Statistical diversity distinguishes global states of consciousness

Abstract

Application of complexity measures to neurophysiological time series has seen increased use in recent years to identify neural correlates of global states of consciousness. Lempel-Ziv complexity is currently the de-facto complexity measure used in these investigations. However, by simply counting the number of patterns, this measure theoretically takes its maximum value for data that are completely random. Recently, a measure of statistical complexity - which calculates the diversity of statistical interactions - has been devised which aims to account for and remove randomness seen in data. It was recently found that this measure decreases during anaesthesia in fruit flies. This paper investigates this statistical complexity measure on human neurophysiology data from different stages of sleep, and from individuals under the effects of three psychedelic substances: ketamine, lysergic acid diethylamide (LSD), and psilocybin. Results indicate that statistical complexity: (i) differentiates the different stages of sleep analogously to Lempel-Ziv complexity; (ii) increases relative to placebo for all three psychedelic substances. Thus, statistical complexity is a useful alternative measure for investigating the complexity of neural activity associated with different states of consciousness.