Will Hopper (https://people.umass.edu/whopper/) will present “Comparing discrete and continuous evidence models of recognition memory response times”  on 2/6 at 12:00 in Tobin 521B (abstract below). All are welcome.

Memory theorists have long debated whether recognition decisions are mediated by considering the strength of a continuous memory strength signal, or by entering discrete evidence states. Historically, only models which utilized a continuous memory strength signal were able to account for both the distribution of response times and choice probabilities of recognition decisions. Recently, discrete state models have been extended to account for response times distributions, assuming the observed response times arise as a mixture of latent response time distributions associated with each discrete evidence state (Heck & Erdfelder, 2016, Starns, 2018). Here, we compare models from each class (the discrete-race model and the Ratcliff diffusion model), testing their ability to account for both speeded and unspeeded recognition decisions for items tested multiple times within a session. We conclude that the Ratcliff diffusion model provides a better account of the data, as the discrete-race model overestimates memory strength on unspeeded tests in order to describe the response times on speeded tests.