Abstract
Migraine seriously affects the physical and mental health of patients because of its recurrence and the hypersensitivity to the environment that it causes. However, the pathogenesis and pathophysiology of migraine are not fully understood. We addressed this issue in the present study using an autodynamic functional connectome model (A-DFCM) with twice-clustering to compare dynamic functional connectome patterns (DFCPs) from resting-state functional magnetic resonance imaging data from migraine patients and normal control subjects. We used automatic localization of segment points to improve the efficiency of the model, and intergroup differences and network metrics were analyzed to identify the neural mechanisms of migraine. Using the A-DFCM model, we identified 17 DFCPs—including 1 that was specific and 16 that were general—based on intergroup differences. The specific DFCP was closely associated with neuronal dysfunction in migraine, whereas the general DFCPs showed that the 2 groups had similar functional topology as well as differences in the brain resting state. An analysis of network metrics revealed the critical brain regions in the specific DFCP; these were not only distributed in brain areas related to pain such as Brodmann area 1/2/3, basal ganglia, and thalamus but also located in regions that have been implicated in migraine symptoms such as the occipital lobe. An analysis of the dissimilarities in general DFCPs between the 2 groups identified 6 brain areas belonging to the so-called pain matrix. Our findings provide insight into the neural mechanisms of migraine while also identifying neuroimaging biomarkers that can aid in the diagnosis or monitoring of migraine patients.
Highlights
Migraine is a headache disorder characterized by pulsating recurrent pain attacks combined with nausea, vomiting, sleep disorder, and hypersensitivity to visual, auditory, olfactory, and somatosensory stimuli [1]
Resting-state functional magnetic resonance imaging technology is a noninvasive method for measuring the spontaneous activity of neurons [3] that has enabled the identification of several brain regions involved in the pathogenesis of migraine based on the amplitude of lowfrequency fluctuations (ALFFs) in the resting state [4]
DFCP4 showed a greater difference between the 2 groups than the other dynamic functional connectome patterns (DFCPs); the ratio distribution was broader in migraine patients than in normal control subjects, implying that DFCP4 comprised a large number of samples from the former but few from the latter and could be a DFCP specific to migraine
Summary
Migraine is a headache disorder characterized by pulsating recurrent pain attacks combined with nausea, vomiting, sleep disorder, and hypersensitivity to visual, auditory, olfactory, and somatosensory stimuli [1]. Resting-state functional magnetic resonance imaging (rsfMRI) technology is a noninvasive method for measuring the spontaneous activity of neurons [3] that has enabled the identification of several brain regions involved in the pathogenesis of migraine based on the amplitude of lowfrequency fluctuations (ALFFs) in the resting state [4]. ALFF abnormalities have been observed in multiple brain regions in migraine patients including the right insular lobe, prefrontal cortex (PFC), and medial (m)PFC [5]. Other studies have used regional homogeneity (ReHo) to analyze the synchronization of local activity in the brain [6] and have found altered ReHo values in multiple brain regions in migraine patients such as those related to pain [7,8,9].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
