Sherry Yueyi Jiang

Professor Anjali Thapar

Department of Psychology

Comparison of two diffusion models on item recognition memory task

Previous studies by Thapar and colleagues have suggested that the diffusion model (DM) can be applied to tasks such as item recognition memory task to investigate the neural mechanisms of episodic memory in younger and older adults. The major advantage of the DM is that it integrates and analyzes the distributions of reaction time (RT) and accuracy simultaneously to estimate a set of parameters, which allows for more precise conclusions about the underlying cognitive processes in the experiment. The central goal of this pilot study is to compare two different versions of the DM – HDDM (hierarchical drift diffusion model) and Fast-dm for the estimation of the diffusion model parameters, and see whether one software fits the actual data of the memory experiment better than the other. Specifically, we will first take the memory performance data (e.g. correct and erroneous responses and RT) from a subset of 40 younger adults consisting of 20 high medial-temporal lobe (MTL) and 20 low MTL functioning adults. Then, we will use HDDM and Fast-dm separately to estimate the cognitive parameters underlying memory performance in item recognition memory at both the individual and group levels. Finally, we will compare the fitted models based on the estimated parameters to the actual data to determine how these fitting methods work on the recognition memory task.