Evidence map›Paper›PMID 40790284›Full record

ArticleBehavior research methods2025

Cognitive modeling of lure discriminability in the Mnemonic Similarity Task.

Tianye Ma, Weiwei Zhang

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Article in Behavior research methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Tianye MaDepartment of Psychology, University of California, 900 University Ave., Riverside, CA, 92521, USA. tianye.ma@email.ucr.edu.
Weiwei ZhangDepartment of Psychology, University of California, 900 University Ave., Riverside, CA, 92521, USA.

Funding

A Neurocognitive Mechanism for Precision of Visual Working Memory RepresentationsR01MH117132 · NIMH · UNIVERSITY OF CALIFORNIA RIVERSIDE · PI ZHANG, WEIWEI · 2018 to 2022
$1.4M
NIMH NIH HHS R01 MH117132
6 · The paper itself

Abstract

Lure discrimination in the Mnemonic Similarity Task (MST) has been widely used to measure pattern separation. However, the classic index of lure discrimination in the MST has arbitrary assumptions with limited supporting evidence. The present study has thus developed several models with different assumptions on the process underlying MST as well as the different model-derived indices of lure discrimination. Furthermore, we have assessed and compared these models in a measurement-based approach. We found that the model for the classic lure discrimination index fails to accurately predict the responses in an MST from > 150 participants. Instead, a new index based on the unidimensional signal detection model provides the best fits of the empirical dataset. This work highlights the value of model-based approaches in measuring lure discriminability in the MST.

Indexed as

CognitionDiscrimination, PsychologicalModels, PsychologicalAdultFemaleHumansMaleYoung AdultCognitive modelMSTPattern separationSDT

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.