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


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Matzke, D, Logan, GD and Heathcote, A ORCID: 0000-0003-4324-5537 2020 , 'A cautionary note on evidence-accumulation models of response inhibition in the stop-signal paradigm' , Computational Brain & Behavior , doi: 10.1007/s42113-020-00075-x.

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The stop-signal paradigm is a popular procedure to investigate responseinhibition–the ability to stop ongoing responses. It consists of a choice responsetime (RT) task that is occasionally interrupted by a stop stimulussignaling participants to withhold their response. Performance in the stopsignalparadigm is often formalized as race between a set of go runners triggeredby the choice stimulus and a stop runner triggered by the stop signal.We investigated whether evidence-accumulation processes, which have beenwidely used in choice RT analysis, can serve as the runners in the stop-signalrace 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, wefound that these models are not measurement models in the sense that thedata-generating parameters cannot be recovered in realistic experimentaldesigns.

Item Type: Article
Authors/Creators:Matzke, D and Logan, GD and Heathcote, A
Keywords: evidence-accumulation models, lognormal distribution, response inhibition, stop-signal paradigm, Wald Distribution
Journal or Publication Title: Computational Brain & Behavior
Publisher: Springer
ISSN: 2522-0861
DOI / ID Number: 10.1007/s42113-020-00075-x
Copyright Information:

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

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