Beliefs shape our perception of pain. Using non-invasive magnetic resonance imaging in humans, we investigate how beliefs are generated, maintained and revised in the brain and how they influence pain perception.
Don't miss the upcoming talk by Dr. Katja Wiech: Modifying patients' expectations to improve treatment outcomes. Wednesday, 03 May 2017, 1pm to 2pm
Mawby Room, Kellog College
More on the event here:
One of the main discoveries of modern pain research is that our perception of pain critically depends on beliefs we hold about pain. These beliefs can be related to the perceived cause of the pain, the feared consequences and our ability or disability to alleviate pain.
Research has shown that beliefs can aggravate pain but also have the potential to reduce it. Beliefs have therefore become a key target of research into new ways to prevent and treat chronic pain.
The aims of the pain & mind group are to:
- understand the formation of pain-relevant beliefs in the brain and how they are maintained or changed over time
- characterise the interface between beliefs as a cognitive construct and pain as a physical sensation.
Brain imaging has become a key tool in addressing these aims. We use magnetic resonance imaging (MRI) in humans to explore the neural basis of the influence of beliefs on pain in the brain. MRI is a non-invasive imaging technique that allows for the investigation of dynamic processes such as belief formation and revision in humans in real time.
To explore neural mechanisms underlying belief formation and updating, we combine neuroimaging with computational modelling which quantifies relevant psychological processes relevant based on behavioural measures such as response times, decision accuracies or physiological measures including pupil dilation and skin conductance response.
Learning about pain
This line of research attempts to understand how we learn about aversive experiences and pain in particular. Studies in patients suffering from chronic pain suggest that the way we learn, process and store information related to pain is often biased, which has been shown to prevent successful pain treatment. Improving our understanding of the dynamics behind pain-related learning therefore promises to help us improve treatment strategies.