A consensus guide to capturing the ability to inhibit actions and impulsive behaviors in the stop-signal task
journal contributionposted on 2023-07-26, 14:39 authored by Frederick Verbruggen, Adam R. Aron, Guido P. H. Band, Christian Beste, Patrick G. Bissett, Adam T. Brockett, Joshua W. Brown, Samuel R. Chamberlain, Christopher D. Chambers, Hans Colonius, Lorenza S. Colzato, Brian D. Corneil, James P. Coxon, Annie Dupuis, Dawn M. Eagle, Hugh Garavan, Ian Greenhouse, Andrew Heathcote, René J. Huster, Sara Jahfari, J. Leon Kenemans, Inge Leunissen, Chiang-Shan R. Li, Gordon D. Logan, Dora Matzke, Sharon Morein-Zamir, Aditya Murthy, Martin Paré, Russell A. Poldrack, K. Richard Ridderinkhof, Trevor W. Robbins, Matthew Roesch, Katya Rubia, Russell J. Schachar, Jeffrey D. Schall, Ann-Kathrin Stock, Nicole C. Swann, Katharine N. Thakkar, Maurits W. van der Molen, Luc Vermeylen, Matthijs Vink, Jan R. Wessel, Robert Whelan, Bram B. Zandbelt, C. Nico Boehler
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 12 easy-to-implement consensus recommendations and point out the problems that can arise when they 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.
Number of pages26
- Published version