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Procedural and Declarative Category Learning Simultaneously Contribute to Downstream Processes

Abstract

Studies on interactions between procedural and declarative learning have focused on largely on competition during encoding, consolidation, or use (retrieval). Less attention has been paid to interactions between the representations created by each system. In a behavioral study, we demonstrated that information from both declarative and procedural learning can contribute to response selection. Participants were instructed to use a completely diagnostic, verbalizable, shape-based rule to categorize exemplars and received feedback after each trial. However, the categories also differed probabilistically in their color distributions. Participants used both color (learned procedurally) and shape (learned declaratively) to categorize exemplars, making faster responses when both sources indicated the same category judgement, and slower when they conflicted. Debriefing confirmed that most participants were unaware of the color distributions (aware participants were analyzed separately). This result suggests that both the color (procedural) and shape (declarative) information contributed to response selection.

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