EEG connectivity features associated with fibromyalgia revealed by machine learning

EEG-based functional connectivity features associated with fibromyalgia, identified using machine learning in the gamma band at the sensor level, can distinguish between fibromyalgia participants and healthy controls with 99.57% accuracy. These findings advance our understanding of the brain-based mechanisms of fibromyalgia and provide novel targets for future non-invasive neuromodulation and neurofeedback trials. However, future studies need to replicate these findings in independent EEG datasets in people with fibromyalgia as well as compare with other clinical populations.