Turk-Browne Nicholas B
Department of Psychology, Princeton University, Green Hall, Princeton, NJ 08540, USA.
Nebr Symp Motiv. 2012;59:117-46. doi: 10.1007/978-1-4614-4794-8_6.
Statistical learning refers to an unconscious cognitive process in which repeated patterns, or regularities, are extracted from the sensory environment. In this chapter, I describe what is currently known about statistical learning. First, I classify types of regularities that exist in the visual environment. Second, I introduce a family of experimental paradigms that have been used to study statistical learning in the laboratory. Third, I review a series of behavioral and functional neuroimaging studies that seek to uncover the underlying nature of statistical learning. Finally, I consider ways in which statistical learning may be important for perception, attention, and visual search. The goals of this chapter are thus to highlight the prevalence of regularities, to explain how they are extracted by the mind and brain, and to suggest that the resulting knowledge has widespread consequences for other aspects of cognition.
统计学习是指一种无意识的认知过程,在这个过程中,重复的模式或规律会从感官环境中被提取出来。在本章中,我将描述目前关于统计学习的已知情况。首先,我对视觉环境中存在的规律类型进行分类。其次,我介绍一系列已被用于在实验室中研究统计学习的实验范式。第三,我回顾一系列行为和功能性神经成像研究,这些研究旨在揭示统计学习的潜在本质。最后,我思考统计学习可能对感知、注意力和视觉搜索具有重要意义的方式。因此,本章的目标是强调规律的普遍性,解释它们是如何被心智和大脑提取的,并表明由此产生的知识对认知的其他方面具有广泛的影响。