Abstract
Chronic pain (CP) is estimated to affect at least one-third of the population in the United Kingdom. Fibromyalgia (FM) is one of the most disabling CP conditions. Epidemiological research suggests its global prevalence to be between 2-8%. The unknown pathogenesis, lack of biological markers to monitor its development, and lack of successful treatment make FM a crucial target of pre-clinical research.The goal of this project is twofold. The project aims to 1) identify robust neurological markers (i.e., electrochemical brain activity) by applying a combination of advanced electroencephalography (EEG) signal processing (i.e., functional connectivity of oscillatory activity) and neuroinflammatory (NI) responses (i.e., estimation of pro-inflammatory cytokines intake), through which 2) characterizing successfully and unsuccessfully treated FM patients (compared to age-matched healthy controls). These measures, seldom combined, have been successfully applied to the study of psychiatric conditions and sleep. Crucially, the identification of neurological markers at rest and during arousing sensory stimulation will allow us to estimate the relationship between these neurological markers and treatment effectiveness. This proposal is important because it aims to generate a robust pre-clinical neurological tool to identify FM and its relationship with measures of treatment effectiveness. The successful identification of neurological markers will improve the assessment of the development of maladaptive changes in FM and will kick-start further research on treatment effectiveness.This project is of great medical relevance as it will identify pathological signatures of FM that can then inform research on etiology and treatment of this condition.