Psychiatry: Insights into depression through normative decision-making models

Decision making lies at the very heart of many psychiatric diseases. It is also a central theoretical concern in a wide variety of fields and has undergone detailed, in-depth, analyses. We take as an example Major Depressive Disorder (MDD), applying insights from a Bayesian reinforcement learning framework. We focus on anhedonia and helplessness. Helplessness--a core element in the conceptualizations of MDD that has lead to major advances in its treatment, pharmacological and neurobiological understanding--is formalized as a simple prior over the outcome entropy of actions in uncertain environments. Anhedonia, which is an equally fundamental aspect of the disease, is related to the effective reward size. These formulations allow for the design of specific tasks to measure anhedonia and helplessness behaviorally. We show that these behavioral measures capture explicit, questionnaire-based cognitions. We also provide evidence that these tasks may allow classification of subjects into he...

• Type: Conference
• Year: 2008
• Where: NIPS
• Authors: Quentin J. M. Huys, Joshua T. Vogelstein, Peter Dayan
• Keywords: Decision Making, Fact Follow Mdd, Information Technology, Maladaptive Behaviors, NIPS 2008