Complexity Measures for EEG Microstate Sequences: Concepts and Algorithms.

ABSTRACT: EEG microstate sequence analysis quantifies properties of ongoing brain electrical activity which is known to exhibit complex dynamics across many time scales. In this report we review recent developments in quantifying microstate sequence complexity, we classify these approaches with regard to different complexity concepts, and we evaluate excess entropy as a yet unexplored quantity in microstate research. We determined the quantities entropy rate, excess entropy, Lempel-Ziv complexity (LZC), and Hurst exponents on Potts model data, a discrete statistical mechanics model with a temperature-controlled phase transition. We then applied the same techniques to EEG microstate sequences from wakefulness and non-REM sleep stages and used first-order Markov surrogate data to determine which time

SUBMITTER: von Wegner F 

PROVIDER: S-EPMC10884068 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature