We explore different ways in which the human visual system can adapt for perceiving and categorizing the environment. There are various accounts of supervised (categorical) and unsupervised perceptual learning, and different perspectives on the functional relationship between perception and categorization. We suggest that common experimental designs are insufficient to differentiate between hypothesized perceptual learning mechanisms and reveal their possible interplay. We propose a relatively underutilized way of studying potential categorical effects on perception, and we test the predictions of different perceptual learning models using a two-dimensional, interleaved categorization-plus-reconstruction task. We find evidence that the human visual system adapts its encodings to the feature structure of the environment, uses categorical expectations for robust reconstruction, allocates encoding resources with respect to categorization utility, and adapts to prevent miscategorizations.

中文翻译：

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类别学习对感知重建的影响

我们探索人类视觉系统可以适应感知和分类环境的不同方式。有监督（分类）和无监督感知学习的各种描述，以及关于感知和分类之间功能关系的不同观点。我们建议常见的实验设计不足以区分假设的感知学习机制并揭示它们可能的相互作用。我们提出了一种相对未充分利用的研究对感知的潜在分类影响的方法，并且我们使用二维交错分类加重建任务测试了不同感知学习模型的预测。我们发现了人类视觉系统使其编码适应环境特征结构的证据，