title: A Bayesian approach for estimating the probability of trigger failures in the stop-signal paradigm.
abstract: Response inhibition is frequently investigated using the stop-signal paradigm, where participants perform a two-choice response time task that is occasionally interrupted by a stop signal instructing them to withhold their response. Stop-signal performance is formalized as a race between a go and a stop process. If the go process wins, the response is executed; if the stop process wins, the response is inhibited. Successful inhibition requires fast stop responses and a high probability of triggering the stop process. Existing methods allow for the estimation of the latency of the stop response, but are unable to identify deficiencies in triggering the stop process. We introduce a Bayesian model that addresses this limitation and enables researchers to simultaneously estimate the probability of trigger failures and the entire distribution of stopping latencies. We demonstrate that trigger failures are clearly present in two previous studies, and that ignoring them distorts estimates of stopping latencies. The parameter estimation routine is implemented in the BEESTS software (Matzke et al., Front. Quantitative Psych. Measurement, 4, 918; 2013a) and is available at http://dora.erbe-matzke.com/software.html .
authors.affiliation: Department of Psychology, University of Amsterdam, Weesperplein 4, 1018, XA, Amsterdam, The Netherlands. d.matzke@uva.nl.
authors.forename: Dora
authors.initials: D
authors.lastname: Matzke
authors.affiliation: Department of Psychology, University of Amsterdam, Weesperplein 4, 1018, XA, Amsterdam, The Netherlands.
authors.forename: Jonathon
authors.initials: J
authors.lastname: Love
authors.affiliation: School of Medicine, Division of Psychology, University of Tasmania, Tasmania, Australia.|School of Psychology, University of Newcastle, Callaghan, NSW, Australia.
authors.forename: Andrew
authors.initials: A
authors.lastname: Heathcote
mesh_terms: D000328:Adult; D001499:Bayes Theorem; D002755:Choice Behavior / Q000502:physiology*; D006801:Humans; D007266:Inhibition, Psychological; D015233:Models, Statistical; D011336:Probability; D011930:Reaction Time / Q000502:physiology*; D013647:Task Performance and Analysis
keywords: Bayesian hierarchical modeling; Ex-Gaussian distribution; Response inhibition; Stop-signal RT distribution; Stop-signal paradigm; Trigger failure
references.citation: Behav Res Methods Instrum Comput. 2004 May;36(2):277-90
references.pmid: 15354694
references.citation: Behav Res Methods Instrum Comput. 2004 Nov;36(4):678-94
references.pmid: 15641415
references.citation: Neuroimage. 2012 Mar;60(1):370-5
references.pmid: 22227131
references.citation: Vision Res. 2001 Jul;41(15):1951-68
references.pmid: 11412886
references.citation: Psychol Sci. 2013 Mar 1;24(3):352-62
references.pmid: 23399493
references.citation: J Exp Psychol Gen. 2013 Nov;142(4):1047-73
references.pmid: 23163766
references.citation: Psychon Bull Rev. 2008 Dec;15(6):1209-17
references.pmid: 19001592
references.citation: Psychon Bull Rev. 2005 Apr;12(2):195-223
references.pmid: 16082801
references.citation: Psychon Bull Rev. 2009 Oct;16(5):798-817
references.pmid: 19815782
references.citation: Front Psychol. 2013 Dec 10;4:918
references.pmid: 24339819
references.citation: Psychometrika. 2015 Mar;80(1):205-35
references.pmid: 24277381
references.citation: Psychol Med. 2002 Feb;32(2):287-97
references.pmid: 11866323
references.citation: Behav Res Methods. 2008 May;40(2):479-83
references.pmid: 18522058
references.citation: Dev Psychol. 1999 Jan;35(1):205-13
references.pmid: 9923475
references.citation: J Exp Psychol Learn Mem Cogn. 2011 Mar;37(2):392-404
references.pmid: 21171806
references.citation: Acta Psychol (Amst). 2003 Feb;112(2):105-42
references.pmid: 12521663
references.citation: J Exp Psychol Gen. 2008 May;137(2):370-89
references.pmid: 18473664
references.citation: Psychol Rev. 2014 Jan;121(1):66-95
references.pmid: 24490789
references.citation: Biol Psychol. 2012 Jan;89(1):220-31
references.pmid: 22027085