The influence of depression symptoms on exploratory decision-making

People with symptoms of depression show impairments in decision-making. One explanation is that they have difficulty maintaining rich representations of the task environment. We test this hypothesis in the context of exploratory choice. We analyze depressive and non-depressive participants' exploration strategies by comparing their choices to two computational models: (1) an “Ideal Actor” model that reflectively updates beliefs and plans ahead, employing a rich representation of the environment and (2) a “Naïve Reinforcement Learning” (RL) model that updates beliefs reflexively utilizing a minimal task representation. Relative to non-depressive participants, we find that depressive participants' choices are better described by the simple RL model. Further, depressive participants were more exploratory than non-depressives in their decision-making. Depressive symptoms appear to influence basic mechanisms supporting choice behavior by reducing use of rich task representations and hindering performance during exploratory decision-making.