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Robust averaging protects decisions from noise in neural computations
An ideal observer will give equivalent weight to sources of information that are equally reliable. However, when averaging visual information, human observers tend to downweight or discount features that are relatively outlying or deviant (‘robust averaging’). Why humans adopt an integration policy...
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| 出版年: | PLoS Comput Biol |
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| 主要な著者: | , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Public Library of Science
2017
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5589265/ https://ncbi.nlm.nih.gov/pubmed/28841644 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pcbi.1005723 |
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