Our environment contains regularities distributed in space and time that can be detected by way of statistical learning. This unsupervised learning occurs without intent or awareness, but little is known about how it relates to other types of learning, how it affects perceptual processing, and how quickly it can occur. Here we use fMRI during statistical learning to explore these questions. Participants viewed statistically structured versus unstructured sequences of shapes while performing a task unrelated to the structure. Robust neural responses to statistical structure were observed, and these responses were notable in four ways: First, responses to structure were observed in the striatum and medial temporal lobe, suggesting that statistical learning may be related to other forms of associative learning and relational memory. Second, statistical regularities yielded greater activation in category-specific visual regions (object-selective lateral occipital cortex and word-selective ventral occipito-temporal cortex), demonstrating that these regions are sensitive to information distributed in time. Third, evidence of learning emerged early during familiarization, showing that statistical learning can operate very quickly and with little exposure. Finally, neural signatures of learning were dissociable from subsequent explicit familiarity, suggesting that learning can occur in the absence of awareness. Overall, our findings help elucidate the underlying nature of statistical learning.

译文

我们的环境包含在空间和时间上分布的规律性,可以通过统计学习来检测。这种无监督的学习是在没有意图或意识的情况下发生的,但是对于它与其他类型的学习如何相关,它如何影响感知处理以及它发生的速度知之甚少。在这里,我们在统计学习期间使用功能磁共振成像来探索这些问题。参与者在执行与结构无关的任务时,查看了统计上结构化的形状序列和非结构化的形状序列。观察到对统计结构的强大神经反应,并且这些反应在四个方面是显着的: 首先,在纹状体和内侧颞叶中观察到对结构的反应,这表明统计学习可能与其他形式的联想学习和关系记忆有关。其次,统计规律在特定类别的视觉区域 (对象选择性的外侧枕叶皮层和单词选择性的腹枕叶颞叶皮层) 中产生了更大的激活,表明这些区域对时间分布的信息敏感。第三,学习的证据在熟悉过程中很早就出现了,这表明统计学习可以非常快地进行并且几乎没有接触。最后,学习的神经特征与随后的明确熟悉程度是分离的,这表明学习可以在没有意识的情况下进行。总的来说,我们的发现有助于阐明统计学习的基本性质。

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