Altered Brain Complexity in Women with Primary Dysmenorrhea: A Resting-State Magneto-Encephalography Study Using Multiscale Entropy Analysis
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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-12-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/19/12/680 |
| _version_ | 1811303145705308160 |
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| author | Intan Low Po-Chih Kuo Yu-Hsiang Liu Cheng-Lin Tsai Hsiang-Tai Chao Jen-Chuen Hsieh Li-Fen Chen Yong-Sheng Chen |
| author_facet | Intan Low Po-Chih Kuo Yu-Hsiang Liu Cheng-Lin Tsai Hsiang-Tai Chao Jen-Chuen Hsieh Li-Fen Chen Yong-Sheng Chen |
| author_sort | Intan Low |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T07:41:36Z |
| format | Article |
| id | doaj.art-90c175b639324f10b28440906330326e |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-13T07:41:36Z |
| publishDate | 2017-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-90c175b639324f10b28440906330326e2022-12-22T02:55:51ZengMDPI AGEntropy1099-43002017-12-01191268010.3390/e19120680e19120680Altered Brain Complexity in Women with Primary Dysmenorrhea: A Resting-State Magneto-Encephalography Study Using Multiscale Entropy AnalysisIntan Low0Po-Chih Kuo1Yu-Hsiang Liu2Cheng-Lin Tsai3Hsiang-Tai Chao4Jen-Chuen Hsieh5Li-Fen Chen6Yong-Sheng Chen7Institute of Biomedical Informatics, National Yang-Ming University, Taipei 11221, TaiwanDepartment of Computer Science, National Chiao Tung University, Hsinchu 30010, TaiwanInstitute of Brain Science, National Yang-Ming University, Taipei 11221, TaiwanInstitute of Biomedical Informatics, National Yang-Ming University, Taipei 11221, TaiwanDepartment of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei 11217, TaiwanInstitute of Brain Science, National Yang-Ming University, Taipei 11221, TaiwanInstitute of Biomedical Informatics, National Yang-Ming University, Taipei 11221, TaiwanDepartment of Computer Science, National Chiao Tung University, Hsinchu 30010, TaiwanHow 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.https://www.mdpi.com/1099-4300/19/12/680multiscale sample entropychronic painprimary dysmenorrheacomplexitymagnetoencephalographyresting-state network |
| spellingShingle | Intan Low Po-Chih Kuo Yu-Hsiang Liu Cheng-Lin Tsai Hsiang-Tai Chao Jen-Chuen Hsieh Li-Fen Chen Yong-Sheng Chen Altered Brain Complexity in Women with Primary Dysmenorrhea: A Resting-State Magneto-Encephalography Study Using Multiscale Entropy Analysis Entropy multiscale sample entropy chronic pain primary dysmenorrhea complexity magnetoencephalography resting-state network |
| title | Altered Brain Complexity in Women with Primary Dysmenorrhea: A Resting-State Magneto-Encephalography Study Using Multiscale Entropy Analysis |
| title_full | Altered Brain Complexity in Women with Primary Dysmenorrhea: A Resting-State Magneto-Encephalography Study Using Multiscale Entropy Analysis |
| title_fullStr | Altered Brain Complexity in Women with Primary Dysmenorrhea: A Resting-State Magneto-Encephalography Study Using Multiscale Entropy Analysis |
| title_full_unstemmed | Altered Brain Complexity in Women with Primary Dysmenorrhea: A Resting-State Magneto-Encephalography Study Using Multiscale Entropy Analysis |
| title_short | Altered Brain Complexity in Women with Primary Dysmenorrhea: A Resting-State Magneto-Encephalography Study Using Multiscale Entropy Analysis |
| title_sort | altered brain complexity in women with primary dysmenorrhea a resting state magneto encephalography study using multiscale entropy analysis |
| topic | multiscale sample entropy chronic pain primary dysmenorrhea complexity magnetoencephalography resting-state network |
| url | https://www.mdpi.com/1099-4300/19/12/680 |
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