Title: Altered Brain Complexity in Women with Primary Dysmenorrhea: A Resting-State Magneto-Encephalography Study Using Multiscale Entropy Analysis
Authors: Low, Intan
Kuo, Po-Chih
Liu, Yu-Hsiang
Tsai, Cheng-Lin
Chao, Hsiang-Tai
Hsieh, Jen-Chuen
Chen, Li-Fen
Chen, Yong-Sheng
Institute of Molecular Medicine and Bioengineering
Department of Computer Science
Keywords: multiscale sample entropy;chronic pain;primary dysmenorrhea;complexity;magnetoencephalography;resting-state network
Issue Date: 1-Dec-2017
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.
URI: http://dx.doi.org/10.3390/e19120680
ISSN: 1099-4300
DOI: 10.3390/e19120680
Journal: ENTROPY
Volume: 19
Appears in Collections:Articles