Former postdoc in the lab. The aim of my project was to better understand how the perception of pain emerges from brain activity. Pain perception and associated brain responses are known to be highly sensitive to several contextual, cognitive and mood factors. In particular, prior expectations largely influence pain, as exemplified by powerful placebo and nocebo effects. These effects suggest that pain perception does not result from a direct readout of sensory inputs, but can be seen as the outcome of an inference process based on noisy observations, which necessitates an internal model accounting for endogenous modulations. Yet, there is no unifying framework explaining how prior expectations and incoming stimuli are combined in our brain to lead to pain perception. In this setting, my project aimed to shed light on the mechanisms governing the construction and updating of internal pain models. To reach this goal, I developed statistical models that can explain how human subjects combine prior information with incoming evidences to identify which inferential features are encoded in brain responses.