Neurofeedback for Nociplastic Pain in Rheumatoid Arthritis (NECTAR): a Pilot Study

Rheumatoid arthritis (RA) is an autoimmune condition leading to inflammation and pain. Even after treating inflammation, RA patients experience persistent residual pain similar to fibromyalgia. Fibromyalgia can be treated with neurofeedback (NF), enabling individuals to self-regulate their brain activity using feedback from real-time electroencephalography (EEG) recordings. This study aims to (1) identify the mechanism of NF training on RA-fibromyalgia pain and associated brain biomarkers and (2) leverage machine learning for more accurate pain prediction in RA. Multichannel EEG data from 16 RA patients before and after ten sessions of NF will be compared with that of healthy participants to identify NF-responsive pain biomarkers. This work would enhance the selection of suitable therapeutic options based on individual characteristics, ultimately benefiting millions of RA patients experiencing uncontrollable non-inflammatory pain. Drawing from my experience as a clinician, engineer, and researcher with a musculoskeletal and neuro-mechanobiological modelling background, I am uniquely positioned to lead this study. I approach this work from the perspective of a person of Bangladeshi heritage and an aspiring female neurosurgeon in the UK. I seek funding to maintain academic momentum via a synergistic partnership with an ongoing EPSRC-funded project to further develop my scientific niche and obtain a clinical lectureship.