A model of working memory capacity in the radial-arm maze task

The radial arm maze is one of the most commonly used tests for assessing working memory in laboratory animals. However, to date, there exists no quantitative method of estimating working memory capacity from performance on this task. Here, we present a mathematical model of performance on the radial arm maze from which we can derive estimates of capacity. We derive explicit results for the two most commonly used measures of performance as functions of number of arms in the maze and memory capacity, assuming a uniform random search. We simulate random non-uniform search strategies. Comparing our model to previous experiments, we show that our model predicts a working memory capacity in the range of 3-9 at the level of performance observed in these experiments. This estimate is within the typical estimate of human working memory capacity. Performance of rats on large mazes (e.g. 48 arms) has been used as evidence that the working memory capacity of rats may be significantly larger than that of humans. We report that memory capacity in the range 3-9 is sufficient to explain the performance of rats in very large radial mazes. Furthermore, when we simulate non-uniform random search strategies observed in the experiments, the resulting estimates do not differ significantly from those assuming a uniform random search. We conclude that a list-based model of working memory with modest capacity is more powerful than previously expected.