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A cautionary note on evidence-accumulation models of response inhibition in the stop-signal paradigm


Matzke, D and Logan, GD and Heathcote, A, A cautionary note on evidence-accumulation models of response inhibition in the stop-signal paradigm, Computational Brain & Behavior, 3 pp. 269-288. ISSN 2522-0861 (2020) [Refereed Article]


Copyright Statement

Copyright 2020 The Authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)

DOI: doi:10.1007/s42113-020-00075-x


The stop-signal paradigm is a popular procedure to investigate response inhibition–the ability to stop ongoing responses. It consists of a choice response time (RT) task that is occasionally interrupted by a stop stimulus signaling participants to withhold their response. Performance in the stopsignal paradigm is often formalized as race between a set of go runners triggered by the choice stimulus and a stop runner triggered by the stop signal. We investigated whether evidence-accumulation processes, which have been widely used in choice RT analysis, can serve as the runners in the stop-signal race model and support the estimation of psychologically meaningful parameters. We examined two types of the evidence-accumulation architectures: the racing Wald model (Logan, Van Zandt, Verbruggen, & Wagenmakers, 2014) and a novel proposal based on the Lognormal race (Heathcote & Love, 2012). Using a series of simulation studies and fits to empirical data, we found that these models are not measurement models in the sense that the data-generating parameters cannot be recovered in realistic experimental designs.

Item Details

Item Type:Refereed Article
Keywords:evidence-accumulation models, lognormal distribution, response inhibition, stop-signal paradigm, Wald Distribution
Research Division:Psychology
Research Group:Cognitive and computational psychology
Research Field:Decision making
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in psychology
UTAS Author:Heathcote, A (Professor Andrew Heathcote)
ID Code:137934
Year Published:2020
Deposited By:Psychology
Deposited On:2020-03-16
Last Modified:2021-03-24
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