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BackgroundA link has been shown between patent foramen ovale (PFO) and migraine, particularly migraine with aura. However, it is unknown if PFO might cause migraine by altering cortical excitability and neural network, which may lower the threshold of cortical spreading depression (CSD). This study aims to compare the spectrum power and functional connectivity of the alpha and beta bands of electroencephalography (EEG) across migraine patients with and without PFO.MethodsThirty-five migraine patients with PFO (PFO +), 35 migraine patients without PFO (PFO –) and 20 PFO patients without migraine (control) were enrolled in this cross-sectional analysis. 19-channel EEG was recorded for all patients under resting state and intermittent photic stimulation. Power spectrum density (PSD) and phase lag index (PLI) of alpha and beta bands were then calculated and compared between the three groups.ResultsDuring photic stimulation, the beta band PSD at the occipital area was substantially higher in PFO + migraine patients compared to PFO-migraine patients (p

Migraine is a common disease of the nervous system that seriously affects the quality of life of patients and constitutes a growing global health crisis. However, many limitations and challenges exist in migraine research, including the unclear etiology and the lack of specific biomarkers for diagnosis and treatment. Electroencephalography (EEG) is a neurophysiological technique for measuring brain activity. With the updating of data processing and analysis methods in recent years, EEG offers the possibility to explore altered brain functional patterns and brain network characteristics of migraines in depth. In this paper, we provide an overview of the methodology that can be applied to EEG data processing and analysis and a narrative review of EEG-based migraine-related research. To better understand the neural changes of migraine or to provide a new idea for the clinical diagnosis and treatment of migraine in the future, we discussed the study of EEG and evoked potential in migraine, compared the relevant research methods, and put forwards suggestions for future migraine EEG studies.