The implied order of a ranked set of visual images can be learned without reliance on information that explicitly signals their order. Such learning is difficult to explain by associative mechanisms, but can be accounted for by cognitive representations and processes such as transitive inference. Our study sought to determine if those processes also apply to learning categories of images. We asked whether participants can (a) infer that stimulus images belonged to familiar categories, even when the images for each trial were unique, and (b) sort those categories into an ordering that obeys transitivity. Participants received minimal verbal instruction and a single session of training. Despite this, they learned the implied order of lists of fixed stimuli and lists of ordered categories, using trial-unique exemplars. We trained two groups, one for which stimuli were constant throughout training and testing (n = 60), and one for which exemplars of each category were trial-unique (n = 50). Our findings suggest that differing cognitive processes may underpin serial learning when learning about specific stimuli as opposed to stimulus categories.

可以在不依赖明确表示其顺序的信息的情况下学习一组已排序的视觉图像的隐含顺序。这种学习很难用联想机制来解释，但可以通过认知表征和传递推理等过程来解释。我们的研究试图确定这些过程是否也适用于学习图像类别。我们询问参与者是否可以 (a) 推断刺激图像属于熟悉的类别，即使每个试验的图像都是独一无二的，并且 (b) 将这些类别分类为服从传递性的排序。参与者接受了最少的口头指导和一次培训。尽管如此，他们还是使用试验独特的样本学习了固定刺激列表和有序类别列表的隐含顺序。我们训练了两组，n = 60），每个类别的样本都是独一无二的（n = 50）。我们的研究结果表明，在学习特定刺激而不是刺激类别时，不同的认知过程可能会支持连续学习。