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dc.contributor.authorLow, Intanen_US
dc.contributor.authorKuo, Po-Chihen_US
dc.contributor.authorLiu, Yu-Hsiangen_US
dc.contributor.authorTsai, Cheng-Linen_US
dc.contributor.authorChao, Hsiang-Taien_US
dc.contributor.authorHsieh, Jen-Chuenen_US
dc.contributor.authorChen, Li-Fenen_US
dc.contributor.authorChen, Yong-Shengen_US
dc.date.accessioned2019-04-03T06:41:31Z-
dc.date.available2019-04-03T06:41:31Z-
dc.date.issued2017-12-01en_US
dc.identifier.issn1099-4300en_US
dc.identifier.urihttp://dx.doi.org/10.3390/e19120680en_US
dc.identifier.urihttp://hdl.handle.net/11536/144312-
dc.description.abstractHow 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.en_US
dc.language.isoen_USen_US
dc.subjectmultiscale sample entropyen_US
dc.subjectchronic painen_US
dc.subjectprimary dysmenorrheaen_US
dc.subjectcomplexityen_US
dc.subjectmagnetoencephalographyen_US
dc.subjectresting-state networken_US
dc.titleAltered Brain Complexity in Women with Primary Dysmenorrhea: A Resting-State Magneto-Encephalography Study Using Multiscale Entropy Analysisen_US
dc.typeArticleen_US
dc.identifier.doi10.3390/e19120680en_US
dc.identifier.journalENTROPYen_US
dc.citation.volume19en_US
dc.citation.issue12en_US
dc.citation.spage0en_US
dc.citation.epage0en_US
dc.contributor.department分子醫學與生物工程研究所zh_TW
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentInstitute of Molecular Medicine and Bioengineeringen_US
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000419007900049en_US
dc.citation.woscount2en_US
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