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.

The effect of seed location on functional connectivity: evidence from an image-based meta-analysis.

Introduction: Default mode network (DMN) is the most involved network in the study of brain development and brain diseases. Resting-state functional connectivity (rsFC) is the most used method to study DMN, but different studies are inconsistent in the selection of seed. To evaluate the effect of different seed selection on rsFC, we conducted an image-based meta-analysis (IBMA). Methods: We identified 59 coordinates of seed regions of interest (ROIs) within the default mode network (DMN) from 11 studies (retrieved from Web of Science and Pubmed) to calculate the functional connectivity; then, the uncorrected t maps were obtained from the statistical analyses. The IBMA was performed with the t maps. Results: We demonstrate that the overlap of meta-analytic maps across different seeds' ROIs within DMN is relatively low, which cautions us to be cautious with seeds' selection. Discussion: Future studies using the seed-based functional connectivity method should take the reproducibility of different seeds into account. The choice of seed may significantly affect the connectivity results.