Regional abnormalities of spontaneous brain activity in migraine: A coordinate‐based meta‐analysis

Many resting‐state functional magnetic resonance imaging (rs‐fMRI) studies have explored abnormal regional spontaneous brain activity in migraine. However, these results are inconsistent. To identify the consistent regions with abnormal neural activity, we meta‐analyzed these studies. We gathered whole‐brain rs‐fMRI studies measuring differences in the amplitude of low‐frequency fluctuations (ALFF), fractional ALFF (fALFF), or regional homogeneity (ReHo) methods. Then, we performed a voxel‐wise meta‐analysis to identify consistent abnormal neural activity in migraine by anisotropic effect size seed‐based d mapping (AES‐SDM). To confirm the AES‐SDM meta‐analysis results, we conducted two meta‐analyses: activation likelihood estimation (ALE) and multi‐level kernel density analysis (MKDA). We found that migraine showed increased regional neural activities in the bilateral postcentral gyrus (PoCG), left hippocampus (HIP.L), right pons, left superior frontal gyrus (SFG.L), triangular part of right inferior frontal gyrus (IFGtriang.R), right middle frontal gyrus (MFG.R), and left precentral gyrus (PreCG.L) and decreased regional intrinsic brain activities were exhibited in the right angular gyrus (ANG.R), left superior occipital gyrus (SOG.L), right lingual gyrus (LING.R). Moreover, the meta‐analysis of ALE further validated the abnormal neural activities in the PoCG, right pons, ANG.R, and HIP. Meta‐regression demonstrated that headache intensity was positively associated with the abnormal activities in the HIP.L, ANG.R, and LING.R. These findings suggest that migraine is associated with abnormal spontaneous brain activities of some pain‐related regions, which may contribute to a deeper understanding of the neural mechanism of migraine. Migraine is a common neurologic disorder. We identified consistent regional neural activity alteration in migraine patients using anisotropic effect‐size seed‐based d mapping (AES‐SDM), activation likelihood estimation (ALE), and multi‐level kernel density analysis (MKDA). The findings revealed consistent abnormal brain activities which deepen our understanding of the pathological mechanism of migraine.