.png){kind=icon}
返回
Validating model-based Bayesian integration using prior-cost metamers
.png){kind=icon}
OA
AI
DOI：10.1073/pnas.2021531118.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
There are two competing views on how humans make decisions under uncertainty. Bayesian decision theory posits that humans optimize their behavior by establishing and integrating internal models of past sensory experiences (priors) and decision outcomes (cost functions). An alternative hypothesis posits that decisions are optimized through trial and error without explicit internal models for priors and cost functions. To distinguish between these possibilities, we introduce a paradigm that probes the sensitivity of humans to transitions between prior-cost pairs that demand the same optimal policy (metamers) but distinct internal models. We demonstrate the utility of our approach in two experiments that were classically explained by Bayesian theory. Our approach validates the Bayesian learning strategy in an interval timing task but not in a visuomotor rotation task. More generally, our work provides a domain-general approach for testing the circumstances under which humans explic-itly implement model-based Bayesian computations.
Keyword:
Bayesian integration
internal model
sensorimotor learning
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
P
IF:
9.1
论文数:
10.8W
被引数:
73.5W
机构
暂无机构信息
引用论文
Application of the small‐angle X‐ray scattering technique for the study of equilibrium enzyme‐substrate interactions of phenylalanyl‐tRNA synthetase from E. coli with tRNAPhe.png)
FEBS LettersOAAI
FEBS LettersIF0
OAAI分享收藏分享收藏Reverse osmosis molecular differentiation of organic liquids using carbon molecular sieve membranesScience
ScienceIF0
PREAI
分享收藏Posterior parietal cortex represents sensory history and mediates its effects on behaviour后顶叶皮层代表感觉史并介导其对行为的影响NATUREOAAI
NATUREIF48.5
OAAI分享收藏
查看更多内容