AUTHOR=Zhe Xia , Zhang Hailian , Tang Min , Lei Xiaoyan , Zhang Xiaoling , Jin Chenwang 

TITLE=Brain functional connectivity patterns associated with symptoms of vestibular migraine

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 17 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2023.1231273

DOI=10.3389/fnins.2023.1231273

ISSN=1662-453X

ABSTRACT=Background: Several functional magnetic resonance imaging (fMRI) investigations of patients with vestibular migraine (VM) have revealed abnormal functionality in different networks, indicating that this neurological illnessVM is related to alterations in brain function. We sought to investigate the resting-state functional connectivity (FC) patterns in VM during the interictal period in VM by combining data-driven voxelwise degree centrality (DC) calculations and seed-based FC analyses, and thereby determine the associations between cerebral function and clinical symptoms. Methods: Thirty-eight patients with VM and 33 matched normal controls were recruited. DC was calculated and compared between the groups, and the FC of locations with showing DC alterations was further tested via using a seed-based technique. The participants' clinical indicators were correlated with the DC and FC values of the brain areas. Results: In contrast to the control group, the VM group showed considerably lower DC values in the bilateral medial prefrontal cortex (mPFC) and significantly higher DC values in the right occipital lobe. In the seed-based FC analyses, revealed thatpatients with VM patients demonstrated decreased fewer connections of the bilateral mPFC connections with the bilateral posterior cingulate cortex, right parahippocampus, right cerebellar posterior lobe, bilateral cuneus, and left precuneus. In addition, clinical data from patients, such as pain intensity, episode frequency, and the Dizziness Handicap Inventory score, were negatively related to these FC and DC impairments. Conclusion: Our findings showed changes in the default mode network and visual cortex in patients with VM. The present investigation, providing further insights into the complexity of the mechanisms underlying VM.