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Adaptive Design Optimization for the Mnemonic Similarity Task

J. Manuel Villarreal
University of California Irvine ~ Cognitive Sciences
Dr. Craig Stark
University of California, Irvine
Dr. Shauna Stark
University of California, Irvine
Michael Lee
University of California, Irvine ~ Cognitive Sciences

The Mnemonic Similarity Task (MST: Stark et al., 2019) is a modified recognition memory task designed to place strong demand on pattern separation. The sensitivity and reliability of the MST make it an extremely valuable tool in clinical settings, where it has been used to identify hippocampal dysfunction associated with healthy aging, dementia, schizophrenia, depression, and other disorders. As with any test used in a clinical setting, it is especially important for the MST to be administered as efficiently as possible. We apply adaptive design optimization methods (Myung et al., 2013) to optimize the presentation of test stimuli in accordance with previous responses.This optimization is based on a novel signal-detection model of an individual’s memory capabilities and decision-making processes. We demonstrate that the cognitive model is able to describe people’s behavior and measure their ability to separate patterns. We also demonstrate that the adaptive design optimization approach generally significantly reduces the number of test stimuli needed to provide these measures.



adaptive design optimization
mnemonic similarity task
recognition memory
SDT model Last updated 3 years ago

Very interesting talk! I have two questions: 1) Do you assume equal variances in your model? It seems like you do, based on the figure at t=3:05. John Wixted makes a convincing case that the correct model for recognition tasks like this is one with unequal variances, and Loiotile and Courney in their recent SDT analysis of this task also argue f...

Fabian Soto 4 comments
Cite this as:

Villarreal, J., Stark, C., Stark, S., & Lee, M. (2021, July). Adaptive Design Optimization for the Mnemonic Similarity Task. Paper presented at Virtual MathPsych/ICCM 2021. Via