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

1
Institute of Biomedical Informatics, National Yang-Ming University, Taipei 11221, Taiwan
2
Department of Computer Science, National Chiao Tung University, Hsinchu 30010, Taiwan
3
Institute of Brain Science, National Yang-Ming University, Taipei 11221, Taiwan
4
Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei 11217, Taiwan
5
Integrated Brain Research Unit, Department of Medical Research, Taipei Veterans General Hospital, Taipei 11217, Taiwan
6
Institute of Biomedical Engineering, National Chiao Tung University, Hsinchu 30010, Taiwan
*
Authors to whom correspondence should be addressed.
Entropy 2017, 19(12), 680; https://doi.org/10.3390/e19120680
Received: 30 September 2017 / Revised: 20 November 2017 / Accepted: 6 December 2017 / Published: 11 December 2017
(This article belongs to the Special Issue Information Theory Applied to Physiological Signals)
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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. View Full-Text
Keywords: multiscale sample entropy; chronic pain; primary dysmenorrhea; complexity; magnetoencephalography; resting-state network multiscale sample entropy; chronic pain; primary dysmenorrhea; complexity; magnetoencephalography; resting-state network
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Low, I.; Kuo, P.-C.; Liu, Y.-H.; Tsai, C.-L.; Chao, H.-T.; Hsieh, J.-C.; Chen, L.-F.; Chen, Y.-S. Altered Brain Complexity in Women with Primary Dysmenorrhea: A Resting-State Magneto-Encephalography Study Using Multiscale Entropy Analysis. Entropy 2017, 19, 680.

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