Working-memory capacity protects model-based learning from stress.

  title={Working-memory capacity protects model-based learning from stress.},
  author={A. Ross Otto and Candace M. Raio and Alice Chiang and Elizabeth A. Phelps and Nathaniel D. Daw},
  journal={Proceedings of the National Academy of Sciences of the United States of America},
  volume={110 52},
Accounts of decision-making have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental advances suggest that this classic distinction between habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning, called model-free and model-based learning. Popular neurocomputational accounts of reward processing emphasize the… CONTINUE READING
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