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The goal of the present study was to examine the contributions of associative strength and similarity in terms of shared features to the production of false memories in the Deese/Roediger-McDermott list-learning paradigm. Whereas the activation/monitoring account suggests that false memories are driven by automatic associative activation from list items to nonpresented lures, combined with errors in source monitoring, other accounts (e.g., fuzzy trace theory, global-matching models) emphasize the importance of semantic-level similarity, and thus predict that shared features between list and lure items will increase false memory. Participants studied lists of nine items related to a nonpresented lure. Half of the lists consisted of items that were associated but did not share features with the lure, and the other half included items that were equally associated but also shared features with the lure (in many cases, these were taxonomically related items). The two types of lists were carefully matched in terms of a variety of lexical and semantic factors, and the same lures were used across list types. In two experiments, false recognition of the critical lures was greater following the study of lists that shared features with the critical lure, suggesting that similarity at a categorical or taxonomic level contributes to false memory above and beyond associative strength. We refer to this phenomenon as a "feature boost" that reflects additive effects of shared meaning and association strength and is generally consistent with accounts of false memory that have emphasized thematic or feature-level similarity among studied and nonstudied representations.

Categorical and associative relations increase false memory relative to purely associative relations