Modeling lexical access in ACT-R

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One robust parameter affecting latencies and accuracies in lexical decision tasks is frequency. Since Howes and Solomon (1951), it is accepted that lexical access can be approximated as a log-function of frequency. In their Exp. 1, Murray and Forster (2004) (M&F) collected responses and response times in a lexical decision task using words from 16 frequency bands, and showed that log-frequency provides an imperfect fit to the data. We provide an ACT-R model of the M&F data and embed it in a Bayesian model to estimate its parameters. The results cast doubt on some common assumptions in ACT-R psycholinguistic models.

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