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One class of multiple-system models of category learning posits that within a single category-learning task people can learn to utilize different systems with different category representations to classify different stimuli. This is referred to as stimulus-dependent representation (SDR). The use of SDR implies that learners switch from subtask to subtask as trials demand. Thus, the use of SDR can be assessed via slowed response times, following a representation switch. Additionally, the use of SDR requires control of executive attention to keep inactive representations from interfering with the current response. Subjects were given a category learning task composed of one- and two-dimensional substructures. Control of executive attention was measured using a working memory capacity (WMC) task. Subjects most likely to be using SDR showed greater slowing of responses following a substructure switch and a greater correlation between learning performance and WMC. These results provide support for the principle of SDR in category learning and the reliance of SDR on executive attention. [ABSTRACT FROM AUTHOR]

Influences of feature-feature statistical co-occurrences and causal relations have been found in some circumstances, but not others. We hypothesized that detecting an influence of these knowledge types hinges crucially on the congruence between the task and type of knowledge. We show that both knowledge types influence tasks that tap feature relatedness. Detailed descriptions of causal theories were collected, and co-occurrence statistics were based on feature production norms. Regression analyses tested the influences of these knowledge types in untimed relatedness ratings and speeded relatedness decisions for 65 feature pairs spanning a range of correlational strength. Both knowledge types influenced both tasks, demonstrating that causal theories and statistical co-occurrences between features influence conceptual computations. [ABSTRACT FROM AUTHOR]

The nature of the reference frame used to remember location sequences in a computer-presented version of spatial span was investigated by moving the template (a rectangular frame enclosing nine target squares) across the screen during presentation and/or during recall. Movement of the display during presentation substantially impaired memory in comparison with a stationary display (Experiment 1). However, there was no effect of template movement during recall (Experiment 2). In Experiments 3 and 4, the template was moved through the same screen locations during presentation and recall. When the extrinsic, or screen location, of each position was repeated identically on each trial but the sequence on the template varied, learning was not facilitated (Experiment 3). When the template sequences were repeated across trials but extrinsic location varied, the sequences were rapidly learned (Experiment 4). In this version of spatial span, location sequences appear to be encoded in an intrinsic frame of reference that is based on the template. Movement of the template during encoding impairs this process, possibly because concurrent attention shifts prevent the encoding of locations. The results are discussed with respect to recent studies of positional encoding in which multiple reference frames were available. [ABSTRACT FROM AUTHOR]

Solving training problems with nonspecific goals (NG; i.e., solving for all possible unknown values) often results in better transfer than solving training problems with standard goals (SG; Le., solving for one particular unknown value). In this study, we evaluated an attentional focus explanation of the goal specificity effect. According to the attentional focus view, solving NG problems causes attention to be directed to local relations among successive problem states, whereas solving SG problems causes attention to be directed to relations between the various problem states and the goal state. Attention to the former is thought to enhance structural knowledge about the problem domain and thus promote transfer, Results supported this view because structurally different transfer problems were solved faster following NG training than following SG training. Moreover, structural knowledge representations revealed more links depicting local relations following NG training and more links to the training goal following SG training. As predicted, these effects were obtained only by domain novices. [ABSTRACT FROM AUTHOR]

Categories are learned in many ways, but studies of category learning have generally focused on classification learning. This focus may limit the understanding of categorization processes. Two experiments were conducted in which participants learned categories of animals by predicting how much food each animal would eat We refer to this as indirect category learning, because the task and the feedback were not directly related to category membership, yet category learning was necessary for good performance in the task. In the first experiment, we compared the performance of participants who learned the categories indirectly with the performance of participants who first learned to classify the objects. In the second experiment, we replicated the basic findings and examined attention to different features during the learning task. In both experiment, participants who learned in the Prediction-only condition displayed a broader distribution of attention than participants who learned in the classification-and-prediction condition did. Some participants in the Prediction-only group learned the family resemblance structure of the categories, even when a perfect criterial attribute was present. In contrast, participants who first learned to classify the objects tended to learn the criterial attribute. [ABSTRACT FROM AUTHOR]