Reinforcement learning in depression: A review of computational research

@article{Chen2015ReinforcementLI,
  title={Reinforcement learning in depression: A review of computational research},
  author={Chong Chen and Taiki Takahashi and Shin Ichi Nakagawa and Takeshi Inoue and Ichiro Kusumi},
  journal={Neuroscience & Biobehavioral Reviews},
  year={2015},
  volume={55},
  pages={247-267}
}
Despite being considered primarily a mood disorder, major depressive disorder (MDD) is characterized by cognitive and decision making deficits. Recent research has employed computational models of reinforcement learning (RL) to address these deficits. The computational approach has the advantage in making explicit predictions about learning and behavior, specifying the process parameters of RL, differentiating between model-free and model-based RL, and the computational model-based functional… CONTINUE READING

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