Regularity detection, or statistical learning, is regarded as a fundamental component of our cognitive system. To test the ability of human participants to detect regularity in a more ecological situation (i.e., mixed with random information), we used a simple letter-naming paradigm in which participants were instructed to name single letters presented one at a time on a computer screen. The regularity consisted of a triplet of letters that were systematically presented in that order. Participants were not told about the presence of this regularity. A variable number of random letters were presented between two repetitions of the regular triplet, making this paradigm similar to a Hebb repetition task. Hence, in this Hebb-naming task, we predicted that if any learning of the triplet occurred, naming times for the predictable letters in the triplet would decrease as the number of triplet repetitions increased. Surprisingly, across four experiments, detection of the regularity only occurred under very specific experimental conditions and was far from a trivial task. Our study provides new evidence regarding the limits of statistical learning and the critical role of contextual information in the detection (or not) of repeated patterns.

译文

:规律性检测或统计学习被视为我们认知系统的基本组成部分。为了测试人类参与者在更生态的情况下(例如,与随机信息混合)检测规律性的能力,我们使用了一种简单的字母命名范例,其中指示参与者命名在计算机屏幕上一次显示的单个字母。规则性由按字母顺序排列的三联字母组成。没有告诉参与者这种规律性的存在。在常规三联体的两次重复之间出现了可变数量的随机字母,使这种范例类似于Hebb重复任务。因此,在此Hebb命名任务中,我们预测,如果对三联体进行了任何学习,则随着三联体重复次数的增加,三联体中可预测字母的命名时间将减少。出乎意料的是,在四个实验中,规律性的检测仅在非常特定的实验条件下进行,而这绝非易事。我们的研究提供了有关统计学习的局限性以及上下文信息在检测(或不检测)重复模式中的关键作用的新证据。

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