abrahamnunes / mst

Mnemonic Similarity Task

MST

Mnemonic Similarity Task

The goal of this repository is to provide the stimuli and source code used to run the Mnemonic Similarity Task (MST). I (Craig Stark) have coded the MST up for a number of different platforms over the years, but the goal here is to provide people with the current, cross-platform code used in the stand-alone C++ variant and the PsychoPy variant. These should be well- suited to behavioral testing and readily modified for things like fMRI or EEG testing. Bug fixes, enhancements, etc. are welcome!

The MST (formerly the BPSO or SPST – yes, it’s had a few names!) is a behavioral task designed to tax pattern separation. Pattern separation can really only be assessed by looking at representations of information and we clearly can’t do that behaviorally. But, the goal is to have a task that would place strong demands on a system that performed pattern separation and, in so doing, get some measure of this.

The task consists of assessing recognition memory performance for objects using not only the traditional targets and unrelated foils, but also using similar lures (that intentionally vary along several different dimensions). This certainly isn’t a unique concept. Here, however, we have developed the task since its creation (Kirwan & Stark, 2007, Learning & Memory) to create a set of well-matched stimuli that have been tested extensively both in our lab and in others. Note, the behavioral task is an explicit one that asks participants to respond “Old”, “Similar”, or “New” on each trial (we have done “Old” vs. “New” and even “R”, “K”, “N”). Typically, this has been done in a study-test variant, but we have (often while in the scanner) done a continuous version as well (Yassa et al., 2010, NeuroImage). A good place to turn for some of the behavioral comparisons is the S. Stark et al. (2015, Behavioral Neuroscience) paper.

Note: Binary builds are available on the lab website: https://faculty.sites.uci.edu/starklab/mnemonic-similarity-task-mst/