Revisiting the variable memory model of visual search

How much memory does visual search have? A number of recent papers have explored this question from various points of view. In this paper, I propose a formal framework for comparing answers across different experimental paradigms. This framework is based on the "variable memory model" (Arani, Karwan, & Drury, 1984). This model has three parameters: Encoding probability (theta), recall probability (phi), and target identification probability (p'). The model can be used to generate cumulative distribution functions for reaction time (RT) or saccades. I compare the model to a dataset of RTs collected on a standard inefficient search for block 2s among block 5s. Assuming perfect identification (p' = 1), I found that mean encoding probability was .33, and mean recall probability .71. The variable memory model provides a common metric for characterizing the behaviour of observers in different laboratories, in terms that are easy to relate to the memory literature.