Children’s improved performance with age in analogy tasks has been explained by an increase in semantic knowledge of the items and the relations between them or by the development of an increased ability to inhibit irrelevant information. We tested the so-called “unbalanced attentional focus hypothesis” that claims that a failure to choose the “analogical” match can be the result of a difficulty to focus on all the relevant information available. Previous eye-tracking research has suggested, in analogies of the A:B::C:D format, that 5–6 year-olds organize their search around the C item. They focused significantly less than adults on the A:B pair, thereby hindering their discovering the relation(s) between A and B. We hypothesized that inducing them to focus their attention on the A:B pair at the beginning of the trial would affect their performance. In Experiment 1, increasing children’s focus on the A:B pair did, indeed, lead to better performance. In contrast, in Experiment 2, focusing their attention on the A:B pair impaired performance when the most salient relation holding between A and B was, in fact, irrelevant for the analogy. By contrast, the obvious-but-irrelevant relation in the A:B pair had no negative effect on performance when no explicit A:B focusing was induced. These results are discussed in terms of the temporal organization of the task and availability of information, and of children’s difficulties to disengage from the main goal of the task, when necessary.

In recent years, eyetracking has begun to be used to study the dynamics of analogy making. Numerous scanpathcomparison algorithms and machine-learning techniques are available that can be applied to the raw eyetracking data. We show how scanpath-comparison algorithms, combined with multidimensional scaling and a classification algorithm, can be used to resolve an outstanding question in analogy making-namely, whether or not children's and adults' strategies in solving analogy problems are different. (They are.) We show which of these scanpath-comparison algorithms is best suited to the kinds of analogy problems that have formed the basis of much analogy-making research over the years. Furthermore, we use machine-learning classification algorithms to examine the item-to-item saccade vectors making up these scanpaths. We show which of these algorithms best predicts, from very early on in a trial, on the basis of the frequency of various item-to-item saccades, whether a child or an adult is doing the problem. This type of analysis can also be used to predict, on the basis of the item-to-item saccade dynamics in the first third of a trial, whether or not a problem will be solved correctly.Keywords Eyetracking algorithms . Jarodzka algorithm . LDA . SVM . Analogy strategies Traditionally, analogy making has been studied statically. Participants typically see a pair of related images (the Bbase pair^), along with a third image and a number of candidate target images. One of these target images-the Bcorrect analogical match^-is supposed to be related to the third image in the same way that the base items were related to one another. The participant's task is to identify the correct analogical match. Correct and incorrect answers (and, sometimes, reaction times) are recorded and analyzed. However, these studies could not capture-and in fairness, were not designed to capture-the dynamic aspects of solving an analogy problem. As such, they shed essentially no light on the question of what strategies were adopted during the course of solving analogy problems.In this article, we introduce a novel means of studying the dynamic aspects of analogy making in both children and adults. The proposed methodology involves combining eyetracking, multidimensional scaling (MDS), and neuralnetwork classification algorithms, as well as using machinelearning algorithms to analyze the component vectors making up participants' scanpaths. In what follows, we will briefly describe each of these techniques and show how they can be combined successfully in the context of analogy making.Although the purpose of this article is, first and foremost, a methodological one, it is important to note that the development of these techniques has allowed us (French & Thibaut, 2014;Thibaut & French, 2016;Thibaut, French, Missault, Gérard, & Glady, 2011) to answer, for what we believe to be the first time, a long-standing question in the field of analogymaking-namely, do children and adults use the same (or very similar) search-space strategies when...

Behavioral flexibility that requires behavioral inhibition has important fitness consequences. One task commonly used to assess behavioral inhibition is the reverse-reward task in which the subject is rewarded by the non selected items. Lemurs were tested for their ability to solve the qualitative version of the reverse-reward task with the choice between identical quantities of different food items instead of different quantities of the same food. Two of four subjects mastered the task without a correction procedure and were able to generalize the acquired rule to novel combinations of food. One of the two subjects competent on the quality version of the task could transfer this ability to different quantities of the same food. Our results are compared to lemurs’ performances when tested under the quantitative version in a previous study and those of capuchin monkeys tested under a similar paradigm. The whole results suggest that the qualitative version of the reverse-reward task may be easier to master than its quantitative counterpart and that lemurs perform better than capuchin monkeys as they were able to later transfer the learning rule to the quantitative version of the task.