In most recognition models a decision is based on a global measure often termed familiarity. However, a response criterion is free to vary across lists varying in length and strength, making familiarity changes immeasurable. We presented a single list with a mixture of exemplars from many categories, so that the criterion would be unlikely to vary with length or strength of the category of the test item. False alarms rose with category length but not category strength, suggesting that familiarity does not change much with changes in strength of other items but grows when additional items are studied. The results were well fit by an extension of the search of associative memory (SAM) model presented by R. M. Shiffrin, R. Ratcliff, and S. E. Clark (1990).

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