A cerebellar mechanism for learning prior distributions of time intervals
Human timing behavior is biased towards previously encountered intervals and is predicted by Bayesian models. Here, the authors develop a computational model based in properties of the cerebellum to show how we might encode time estimates based on prior experience.
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| Auteurs principaux: | , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2018
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/99408eb0b9f447f8b7ecd40e18e23f5b |
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| Résumé: | Human timing behavior is biased towards previously encountered intervals and is predicted by Bayesian models. Here, the authors develop a computational model based in properties of the cerebellum to show how we might encode time estimates based on prior experience. |
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