A nonlinear updating algorithm captures suboptimal inference in the presence of signal-dependent noise
Abstract Bayesian models have advanced the idea that humans combine prior beliefs and sensory observations to optimize behavior. How the brain implements Bayes-optimal inference, however, remains poorly understood. Simple behavioral tasks suggest that the brain can flexibly represent probability dis...
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| Auteurs principaux: | , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2018
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| Accès en ligne: | https://doaj.org/article/f163ec5b6de640b5b546097fecc19846 |
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