Altered Brain Complexity in Women with Primary Dysmenorrhea: A Resting-State Magneto-Encephalography Study Using Multiscale Entropy Analysis

Intan Low, Po Chih Kuo, Yu Hsiang Liu, Cheng Lin Tsai, Hsiang Tai Chao, Jen-Chuen Hsieh, Li-Fen Chen*, Yong-Sheng Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

How chronic pain affects brain functions remains unclear. As a potential indicator, brain complexity estimated by entropy-based methods may be helpful for revealing the underlying neurophysiological mechanism of chronic pain. In this study, complexity features with multiple time scales and spectral features were extracted from resting-state magnetoencephalographic signals of 156 female participants with/without primary dysmenorrhea (PDM) during pain-free state. Revealed by multiscale sample entropy (MSE), PDM patients (PDMs) exhibited loss of brain complexity in regions associated with sensory, affective, and evaluative components of pain, including sensorimotor, limbic, and salience networks. Significant correlations between MSE values and psychological states (depression and anxiety) were found in PDMs, which may indicate specific nonlinear disturbances in limbic and default mode network circuits after long-term menstrual pain. These findings suggest that MSE is an important measure of brain complexity and is potentially applicable to future diagnosis of chronic pain.

Original languageEnglish
Article number680
Pages (from-to)1-27
Number of pages27
JournalEntropy
Volume19
Issue number12
DOIs
StatePublished - Dec 2017

Keywords

  • Chronic pain
  • Complexity
  • Magnetoencephalography
  • Multiscale sample entropy
  • Primary dysmenorrhea
  • Resting-state network

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