Characterisation of Pain in patients with musculoskeletal disease: a prospective, Longitudinal, observational study with an . Embedded feasibility window of opportunity Sleep Study (PAIN-LESS)

Research summary

We address whether maladaptive learning systems contribute to the maintenance of chronic pain. This has been difficult to answer because learning comprises a set of complex,interacting processes,and hence difficult to evaluate and quantify. Based on computational models of learning,we have designed a suite of tasks and analysis tools that probe domaingeneral value-based and sensorimotor learning. These are implemented online as a set of tablet-based computer games that can be applied easily and widely in observational or longitudinal clinical studies in domestic settings. We will study whether learning metrics can predict clinical outcomes in: i) a longitudinal study of patients with fibromyalgia, undergoing an NHS pain rehabilitation program. We will measure neural changes (using resting-state fMRI) and physical outcomes using a novel video-based tool to quantify movement during physiotherapy exercises. The proposed project will have a lasting impact: building a self-sustaining data generating infrastructure focused on learning mechanisms; providing a technological platform to support innovation in non-pharmacological treatment; and building a UK pain neuroscience and engineering community focused on chronic pain.

Principal Investigator

Dr Anushka Soni

Contact us

Email: fibromyalgia@ndcn.ox.ac.uk

IRAS number

252762