Psychological theories of categorization generally focus on either rule-or exemplar-based explanations. We present 2 experiments that show evidence of both rule induction and exemplar encoding as well as a connectionist model, ATRn.rM, that specifies a mechanism for combining rule-and exemplar-based representation. In 2 experiments participants learned to classify items, most of which followed a simple rule, although there were a few frequently occurring exceptions. Experiment 1 examined how people extrapolate beyond the range of training. Experiment 2 examined the effect of instance frequency on generalization. Categorization behavior was well described by the model, in which exemplar representation is used for both rule and exception processing. A key element in correctly modeling these results was capturing the interaction between the rule-and exemplar-based representations by using shifts of attention between rules and exemplars. Many formal and folk psychological theories conceive of the mind as being composed of quasi-independent modules. From Freud to Fodor, the mind has been decomposed into constituent parts. Recently, a number of researchers have proposed modular theories of cognitive phenomena such as categorization (Ashby et al., in press;

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k One class of multiple-system models of category learning posits that within a single category-learning task p 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 repref sentations 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.

The word-frequency mirror effect (more hits and fewer false alarms for low-frequency than for high-frequency words) has intrigued memory researchers, and multiple accounts have been offered to explain the result. In this study, participants were differentially familiarized to various pseudowords in a familiarization phase that spanned multiple weeks. Recognition tests given during the first week of familiarization replicated a result of W. T. Maddox and W. K. Estes (1997) that failed to show the classic word-frequency mirror effect for pseudowords; however, recognition tests given toward the end of training showed the classic mirror pattern. In addition, a stimulus-frequency mirror effect for "remember" vs. "know" judgments was obtained. These data are consistent with an account of the mirror effect that posits the involvement of dual processes for episodic recognition.

It is well-accepted that eyewitness identification decisions based on relative judgments are less accurate than identification decisions based on absolute judgments. However, the theoretical foundation for this view has not been established. In this study relative and absolute judgments were compared through simulations of the WITNESS model (Clark, Appl Cogn Psychol 17:629-654, 2003) to address the question: Do suspect identifications based on absolute judgments have higher probative value than suspect identifications based on relative judgments? Simulations of the WITNESS model showed a consistent advantage for absolute judgments over relative judgments for suspect-matched lineups. However, simulations of same-foils lineups showed a complex interaction based on the accuracy of memory and the similarity relationships among lineup members.