Our research aim is to understand memory and feelings mechanistically, and to be able to predict mathematically, how an individual would feel and which one of their past experiences would come to mind. We have developed a theoretical framework for emotional memory, building on retrieved-context memory models, called the emotional Context Maintenance and Retrieval model. This is a mathematical model that predicts what an individual will recall. We have built a mathematical model that predict how someone would feel given who they are, what they know, and what they experience.This work is inspired by the predictive coding or Bayesian Brain" framework
