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

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.

Interactions of BDNF Val66Met Polymorphism and Menstrual Pain on Brain Complexity

“…The participants were a subset of the participants from our multimodal imaging genetics (magnetic resonance imaging and magnetoencephalography) and behavioral studies of PDM at Taipei Veterans General Hospital in Taiwan (Lee et al, 2014 ; Wei et al, 2016a ; Wu et al, 2016 ; Low et al, 2017 ) who were eligible for neuroimaging studies. Written informed consent form and psychological inventories were approved by the ethics committee of Institutional Review Board of Taipei Veterans General Hospital, Taiwan.…”

“…MEG signals recorded from 204 planar gradiometers were further analyzed; MEG signals recorded from 102 magnetometers were excluded from further analyses due to their susceptibility to distant noises. Participants sat comfortably in a magnetically shielded room (Euroshield, Eura, Finland) with heads covered by the helmet and were instructed to relax, eliminate eye movements, and focus only on their breathing (Low et al, 2017 ).…”

“…Long-term PDM serves as a genuine model to study clinical pain with its natural cyclic painful (menstruation) and pain-free (periovulatory) states (Wei et al, 2016a ). Structural and functional brain alterations are reported in PDM females (PDMs), including hypotrophic and hypertrophic changes in gray matter volume (Tu et al, 2010 , 2013 ; Liu et al, 2016 ), white matter microstructural alterations (Liu J. et al, 2017 ), maladaptive descending pain modulatory system (Wei et al, 2016a ), shift of functional connectivity between resting-state networks (Wu et al, 2016 ; Liu P. et al, 2017 ), increased theta activity (Lee et al, 2017 ), and loss of brain complexity (Low et al, 2017 ) in brain regions related to sensory, affective, and cognitive dimensions of pain. Notably, genetic polymorphisms have been implicated to contribute to inter-subject variations in susceptibility to menstrual pain (Lee et al, 2014 ; Wei et al, 2016b , 2017 ), inviting more studies of neuroimaging genetics in PDM.…”

“…It is noteworthy that multiscale entropy (MSE) analysis (Costa et al, 2002 , 2005 ; Yang and Tsai, 2013 ; Courtiol et al, 2016 ) calculates a series of sample entropy over multiple time scales, which captures the temporal complexity characteristcs of time-series neural signals from microscopic to macroscopic aspects. Recently, MSE analysis has also been applied to brain signals (Heisz and McIntosh, 2013 ; Yang et al, 2013 ; Courtiol et al, 2016 ), pain (Sitges et al, 2010 ; Valencia et al, 2016 ; Liu Q. et al, 2017 ), and PDM studies (Kuo et al, 2017 ; Low et al, 2017 ). By applying MSE analysis on resting-state magnetoencephalography (MEG) signals acquired from PDMs during pain-free state, we observed a general loss of regional complexity in PDMs at brain regions related to chronic pain, including the limbic circuitry, default mode network, sensorimotor network, and salience network (Low et al, 2017 ).…”

“…Recently, MSE analysis has also been applied to brain signals (Heisz and McIntosh, 2013 ; Yang et al, 2013 ; Courtiol et al, 2016 ), pain (Sitges et al, 2010 ; Valencia et al, 2016 ; Liu Q. et al, 2017 ), and PDM studies (Kuo et al, 2017 ; Low et al, 2017 ). By applying MSE analysis on resting-state magnetoencephalography (MEG) signals acquired from PDMs during pain-free state, we observed a general loss of regional complexity in PDMs at brain regions related to chronic pain, including the limbic circuitry, default mode network, sensorimotor network, and salience network (Low et al, 2017 ). Our findings implicated the assaults of long-term menstrual pain on brain complexity and adaptability.…”