Global matching models of recognition memory: How the models match the data

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Abstract
We present a review of global matching models of recognition memory, describing their theoretical origins and fundamental assumptions, focusing on two defining properties: (1) recognition is based solely on familiarity due to a match of test items to memory at a global level, and (2) multiple cues are combined interactively. We evaluate the models against relevant data bearing on issues including the representation of associative information, differences in verbal and environmental context effects, list-length, list-strength, and global similarity effects, and ROC functions. Two main modifications to the models are discussed: one based on the representation of associative information, and the other based on the addition of recall-like retrieval mechanisms.