An expectancy model for memory search

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Abstract
A model for memory search is proposed in which S first forms an “expectancy” regarding the item to be tested on the next trial, then carries out a memory search. It is proposed that an expected item is encoded faster (or perhaps responded to more quickly), but the memory scanning process for expected and nonexpected items is otherwise identical. Assuming a serial exhaustive scanning process, we were able to fit much of the data in the literature. In addition, we tested the model by having S give his expectancy aloud before each trial. The data showed about a 100-msec advantage for expected items that did not interact with memory load. The model fit this data reasonably well.

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