Source-level α periodic power in visual and default mode networks predicts topiramate treatment response in migraine.

Migraine varies greatly among patients, making treatment responses unpredictable. This study focused on topiramate, a common preventive treatment. The dose-escalation strategy complicates early evaluation of its effectiveness. Identifying neurobiological markers is crucial for personalized therapy. Researchers analyzed electroencephalography (EEG) features to find predictors of treatment response. A total of 112 patients with episodic migraine participated in this research. They underwent EEG assessment before starting three months of topiramate treatment. The study utilized advanced modeling techniques, including XGBoost, to develop predictive models. The model achieved an area under the curve of 0.859 for identifying responders. Key findings showed that periodic α-band power in specific brain regions correlated with treatment outcomes. Joint analysis of the visual network and default mode network explained 26% of treatment response variance. Higher α power indicated a poorer clinical response. These findings support personalized migraine prevention strategies based on neurobiological markers. Clinical relevance: This research indicates that periodic α activity may guide personalized migraine treatment.