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Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
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A Quantitative Comparison of Two Methods for Higher-Order EEG Microstate Syntax Analysis.

Frederic von Wegner1, Gesine Hermann2, Inken Tödt3

  • 1School of Biomedical Sciences, University of New South Wales (UNSW), Wallace Wurth, Kensington, 2052, NSW, Australia. f.vonwegner@unsw.edu.au.

Brain Topography
|April 24, 2026
PubMed
Summary
This summary is machine-generated.

Entropy rate (ER) and sample entropy (SE) quantify electroencephalography (EEG) microstate sequence complexity. Alzheimer's patients show altered syntax in continuous and jump sequences, but differences vanish when normalized to first-order syntax.

Keywords:
EEG microstatesElectroencephalography (EEG)Entropy rateHigher-order syntaxSample entropy

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Information Theory

Background:

  • Electroencephalography (EEG) microstate sequences are used to study brain dynamics.
  • Entropy rate (ER) and sample entropy (SE) are metrics for quantifying sequence complexity.
  • Alzheimer's disease (AD) is associated with alterations in brain activity patterns.

Purpose of the Study:

  • To theoretically and numerically compare ER and SE for EEG microstate sequences.
  • To investigate higher-order syntax properties in EEG microstates from AD patients and controls.
  • To introduce a novel normalized syntax metric to assess syntax order-dependent differences.

Main Methods:

  • Derived theoretical ER and SE for first-order Markov processes as a null hypothesis.
  • Applied ER and SE to resting-state EEG microstate sequences from AD and control groups.
  • Analyzed both continuous and jump microstate sequences, and introduced a normalized syntax metric.

Main Results:

  • ER serves as an upper bound to SE under the Markov approximation.
  • EEG microstate sequences exhibit significant higher-order syntax properties in both groups.
  • Continuous sequences showed lower entropy in AD, while jump sequences showed higher entropy; normalization eliminated group differences.

Conclusions:

  • EEG microstate sequences possess higher-order syntax properties.
  • Continuous and jump microstate sequences exhibit distinct syntax.
  • Group differences in microstate syntax are dependent on the order of analysis and disappear upon normalization.