Functional network hubs in vestibular migraine: a neuroimaging perspective.

Abstract

Objective: This study utilizes resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory analysis to identify key brain regions in vestibular migraine (VM), explore their associations with clinical symptoms, and examine the role of these functional network hubs in the pathophysiology of VM, offering novel insights and a theoretical basis for understanding its neural mechanisms and improving its clinical diagnosis and treatment.

Methods: We enrolled patients diagnosed with VM, individuals with Migraine without Aura (MwoA), and healthy control subjects, collecting both clinical and sociodemographic data alongside MRI data. Employing graph theory analysis, we focused on identifying critical hub nodes and networks within VM patients, using metrics like degree, betweenness centrality, and eigenvector centrality for our analysis.

Results: The study included 30 VM patients, 28 MwoA subjects, and 31 healthy controls. Analysis of rich-club coefficients across different levels of network sparsity indicated significantly lower normalized rich-club coefficients for VM and MwoA groups compared to healthy controls at a 65% sparsity threshold, particularly within a node degree range of 91 to 94. Notably, the temporal lobes, limbic system, and frontal lobes were predominant regions for rich-club nodes in the VM group, with significant increases in centrality metrics observed in the right posterior parahippocampal gyrus. These metrics in the hippocampus and parahippocampal gyrus showed a positive correlation with the intensity, duration, and progression of headache episodes in VM patients.

Conclusions: In vestibular migraine patients, critical hub nodes such as the hippocampus and parahippocampal gyrus are identified, potentially associated with emotional regulation, pain perception, and the memory of pain.