How does the brain generalize learned event-pain relationships to novel contexts?

Pain is a complex unpleasant experience that varies from a person to another. Learning, priors and expectations are known to have a substantial influence on subjective pain experience. For example, having expectations or being told that an event will be painful can be sufficient to shift a person’s pain experience into a more painful realm. When such modulation of pain occurs, changes of pain-processing systems in the spinal cord and in the brain can be observed using neuroimaging methods. This project uses functional Magnetic Resonance to unveil how the brain can learn to associate some situations with high pain outcomes while discriminating other situations to be associated with lower painful outcomes. The use of innovative AI-based statistical algorithms (such as machine learning and predictive models) will be at the heart of the project. We expect to find which brain regions are involved in producing a different pain experience in response to different conditions of learning.

Faculty Supervisor:

Pierre Rainville

Student:

Partner:

Centre de recherche de neuroscience de Lyon

Discipline:

Sociology

Sector:

Health and Related Sciences & Technology; Life Sciences (not health); Artificial Intelligence

University:

Université de Montréal

Program: