Galcanezumab (GCA) is a well-tolerated monoclonal antibody developed for migraine prophylaxis. This study further explores GCA-induced central changes by investigating the metabolic-electrical brain interaction and network properties.
We employed a multimodal approach combining electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), along with high-order connectivity analysis obtained using Partial information Decomposition (PID), and explored the relationship between neurophysiological measures and long-term clinical effects of GCA in 20 patients under GCA therapy . Clinical outcomes were reassessed after one year of treatment (1Y). Ten healthy controls also underwent EEG/fNIRS recordings. EEG and fNIRS signals were analyzed and harmonized. We computed global network properties including strength, global efficiency, clustering coefficient, sinergy and redundancy.
For both EEG and fNIRS data, we found lower strength and clustering coefficients in patients than in controls at all time points $(p
