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.
Department of Psychology, University of Texas at Austin, United States.
Nathaniel J
NJ
Blanco
A Ross
AR
Otto
W Todd
WT
Maddox
Christopher G
CG
Beevers
Bradley C
BC
Love
D000328:Adult; D002755:Choice Behavior / Q000502:physiology; D003657:Decision Making / Q000502:physiology*; D003863:Depression / Q000503:physiopathology*; D005106:Exploratory Behavior / Q000502:physiology*; D006801:Humans; D008960:Models, Psychological; D012054:Reinforcement, Psychology; D055815:Young Adult
Cognitive modeling; Depression; Dynamic decision making; Exploration vs. exploitation; Reinforcement learning