Learning What to See in a Changing World
Learning What to See in a Changing World
复制标题
学习在不断变化的世界中看到什么
DOI：
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发表时间：
2016
影响因子：
2.9
通讯作者：
P. Sterzer
中科院分区：
文献类型：
--
作者：
K. Schmack;V. Weilnhammer;J. Heinzle;K. Stephan;P. Sterzer
视觉感知在很大程度上受到期望的影响，但人们对如何在我们的动态感官环境中习得这种感知期望却知之甚少。在这里，我们应用贝叶斯框架来研究感知期望是否从持续经验的不同方面不断更新。在两个实验中，人类观察者执行了一项联想学习任务，其中诱发了对模糊刺激出现的快速变化的期望。我们发现，对模糊刺激的感知会因习得的关联和先前的感知结果而产生偏差。计算模型表明，感知最好通过一个模型来解释，该模型不断更新来自联想学习和感知历史的先验，并以概率的方式将这些先验与当前的感觉信息相结合。我们的研究结果表明，视觉感知的构建是一个高度动态的过程，它以与贝叶斯学习和推理一致的方式融合了来自不同来源的快速变化的期望。
Visual perception is strongly shaped by expectations, but it is poorly understood how such perceptual expectations are learned in our dynamic sensory environment. Here, we applied a Bayesian framework to investigate whether perceptual expectations are continuously updated from different aspects of ongoing experience. In two experiments, human observers performed an associative learning task in which rapidly changing expectations about the appearance of ambiguous stimuli were induced. We found that perception of ambiguous stimuli was biased by both learned associations and previous perceptual outcomes. Computational modeling revealed that perception was best explained by a model that continuously updated priors from associative learning and perceptual history and combined these priors with the current sensory information in a probabilistic manner. Our findings suggest that the construction of visual perception is a highly dynamic process that incorporates rapidly changing expectations from different sources in a manner consistent with Bayesian learning and inference.
影响因子：
5.3
作者：
Schmack, Katharina;de Castro, Ana Gomez-Carrillo;Sterzer, Philipp
通讯作者：
Sterzer, Philipp
DOI：
10.1073/pnas.0506728103
发表时间：
2006-01-10
影响因子：
11.1
作者：
Qi, HJ;Saunders, JA;Backus, BT
通讯作者：
Backus, BT