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Scaling prediction errors to reward variability benefits error-driven learning in humans
Effective error-driven learning requires individuals to adapt learning to environmental reward variability. The adaptive mechanism may involve decays in learning rate across subsequent trials, as shown previously, and rescaling of reward prediction errors. The present study investigated the influenc...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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American Physiological Society
2015
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4563025/ https://www.ncbi.nlm.nih.gov/pubmed/26180123 http://dx.doi.org/10.1152/jn.00483.2015 |