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Cognitive Strategies Regulate Fictive, but not Reward Prediction Error Signals in a Sequential Investment Task
Computational models of reward processing suggest that foregone or fictive outcomes serve as important information sources for learning and augment those generated by experienced rewards (e.g. reward prediction errors). An outstanding question is how these learning signals interact with top-down cog...
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| Main Authors: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
BlackWell Publishing Ltd
2014
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| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4105325/ https://ncbi.nlm.nih.gov/pubmed/24382784 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/hbm.22433 |
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