We recently published two studies in the journal JAMA Psychiatry showing how computational models can be applied to understanding mood and its relation to behaviour. In the first study, we describe how basic reward processing is surprisingly intact in people with major depression in tasks that do not require significant learning. Our results were shown using brain scanning in the lab and in 1,833 players of our smartphone app, The Great Brain Experiment. These results suggest that the dopamine system that produces reward prediction errors is probably functioning normally in depression and that the reward-related symptoms of depression have a different cause.
In the second study, Liam Mason and Eran Eldar describe how symptoms of bipolar disorder could be explained by the idea that mood represents the momentum of rewards in the environment. When we are in a good mood, we may perceive rewards as better than they actually are. This bias of mood on how we experience our world may be beneficial because it helps us adapt quickly to a changing environment. However, people whose moods bias the perception of rewards too strongly may be more likely to experience greater mood swings, potentially resulting in extreme behaviour. Our simulations suggest that this theoretical framework could explain a range of symptoms observed in bipolar disorder.
The papers can be downloaded here. The research is supported by the Max Planck Society, the Wellcome Trust, and the UK Medical Research Council.