Impaired default mode network connectivity and deviated dorsal-ventral attention networks in catamenial epilepsy

This study investigated alterations in resting-state brain networks in catamenial epilepsy (CE) and their associations with serum sex hormone levels.

First, we constructedfunctional networks based on resting-state fMRI datato compute nodal attributes and identify brain regions exhibiting significant group differences. Subsequently, independent component analysis (ICA) identified important networks and characterized their connectivity patterns. Finally, associations between these network metrics and sex hormone levels were examined.

A total of45 patientswere included in the final analysis, comprising19with CE,26with non-catamenial epilepsy (NCE), and27healthy controls (HC). Nodal efficiency (Ne) differed significantly in key brain regions between patient group and HC group, including the right precentral gyrus (PreCG.R), left and right calcarine cortex (CAL.L and CAL.R), left lingual gyrus (LING.L), right superior parietal gyrus (SPG.R), right inferior parietal lobule (IPL.R) and left precuneus (PCUN.L). While connectivity between the default mode network (DMN) and sensory networks (visual/auditory) was generally weakened in epilepsy patients, CE specifically exhibited a reconfigured attention-network profile: strengthened connectivity between the dorsal attention network (DAN) and auditory network (AN), and weakened connectivity between the ventral attention network (VAN) and visual network (VN). After correction for multiple comparisons, partial correlation analysis controlling for age revealed no statistically significant correlations between sex hormones and brain network metrics.

CE patients exhibited decreased Ne in critical regions of the AN, DMN and VN, alongside predominant disruptions in DMN connectivity. These alterations may be partially compensated by increased connectivity in the DAN, giving rise to a unique network pathological pattern. The regulatory effects of sex hormones on brain networks require further confirmation in large-scale longitudinal studies.