A consensus guide to capturing the ability to inhibit actions and impulsive behaviors in the stop-signal task
- Ghent University, Belgium
- University of California, San Diego, United States
- Leiden University, Netherlands
- Technical University of Dresden, Germany
- Stanford University, United States
- University of Maryland, United States
- Indiana University, United States
- University of Cambridge, United Kingdom
- Cardiff University, United Kingdom
- Oldenburg University, Germany
- University of Western Ontario, Canada
- Monash University, Australia
- University of Toronto, Canada
- University of Vermont, United States
- University of Oregon, United States
- University of Tasmania, Australia
- University of Oslo, Norway
- Royal Netherlands Academy of Arts and Sciences (KNAW), Netherlands
- Utrecht University, Netherlands
- KU Leuven, Belgium
- Vanderbilt University, United States
- University of Amsterdam, Netherlands
- Anglia Ruskin University, United Kingdom
- Indian Institute of Science, India
- Yale University, United States
- Queen's University, Canada
- University of Maryland, College Park, United States
- King's College London, United Kingdom
- Dresden University of Technology, Germany
- Michigan State University, United States
- University of Iowa, United States
- Trinity College Dublin, Ireland
- Donders Institute, Netherlands
Abstract
Response inhibition is essential for navigating everyday life. Its derailment is considered integral to numerous neurological and psychiatric disorders, and more generally, to a wide range of behavioral and health problems. Response-inhibition efficiency furthermore correlates with treatment outcome in some of these conditions. The stop-signal task is an essential tool to determine how quickly response inhibition is implemented. Despite its apparent simplicity, there are many features (ranging from task design to data analysis) that vary across studies in ways that can easily compromise the validity of the obtained results. Our goal is to facilitate a more accurate use of the stop-signal task. To this end, we provide twelve easy-to-implement consensus recommendations and point out the problems that can arise when these are not followed. Furthermore we provide user-friendly open-source resources intended to inform statistical-power considerations, facilitate the correct implementation of the task, and assist in proper data analysis.
Data availability
The code used for the simulations and all simulated data can be found on Open Science Framework (https://osf.io/rmqaw/)
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Race model simulations to determine estimation bias and reliability of SSRT estimatesOpen Science Framework, DOI 10.17605/OSF.IO/JWSF9.
Article and author information
Author details
Frederick Verbruggen
Russell A Poldrack
Funding
H2020 European Research Council (769595)
- Frederick Verbruggen
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- David Badre, Brown University, United States
Publication history
- Received: February 22, 2019
- Accepted: April 9, 2019
- Accepted Manuscript published: April 29, 2019 (version 1)
- Version of Record published: May 23, 2019 (version 2)
Copyright
© 2019, Verbruggen et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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A consensus guide to capturing the ability to inhibit actions and impulsive behaviors in the stop-signal task
eLife 8:e46323.
https://doi.org/10.7554/eLife.46323
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