abstract Stephan Lewandowsky

Stephan Lewandowsky (University of Western Australia)

Working Memory and Categorization: Bridging Two Pillars of Cognition

Working memory is crucial for many higher-level cognitive functions, ranging from mental arithmetic to reasoning and problem solving. Likewise, the ability to learn and categorize novel concepts forms an indispensable part of human cognition, and many models of category learning rely heavily on memory. However, surprisingly little is known about the relationship between working memory and categorization, and modeling in category learning has thus far been largely uninformed by knowledge about people's memory processes. I present data from 4 large-scale studies that examined individual differences in working memory capacity (WMC) and related them to categorization performance. The results converge on several consistent conclusions: First, WMC is associated with category learning across a wide range of tasks and stimuli, including those that according to a multiple-systems-view of categorization should not rely on working memory. Second, allocation of dimensional attention - and therefore also the choice of categorization strategy - is not associated with WMC. Third, the re-coordination of partial modules of knowledge during 'knowledge restructuring' is associated with WMC. Taken together, the data challenge models that postulate separate memory systems for different categorization tasks, and they provide important constraints on models of categorization. The data also illuminate the relationship between the notion of 'executive attention' in working-memory research and the instantiations of attention in models of categorization.