A frequentist mixture modeling of stop signal reaction times

The stop signal reaction time (SSRT), a measure of the latency of the stop signal process, has been theoretically formulated using a horse race model of go and stop signal processes by the American scientist Gordon Logan (1994). The SSRT assumes equal impact of the preceding trial type (go/stop) on its measurement. In the case of a violation of this assumption, we consider estimation of SSRT based on the idea of earlier analysis of cluster type go reaction times (GORT) and linear mixed model (LMM) data analysis results. Two clusters of trials were considered including those trials preceded by a go trial and other trials preceded by a stop trial. Given disparities between cluster type SSRTs, we need to consider some new indexes considering the unused cluster type information in the calculations. We introduce mixture SSRT and weighted SSRT as two new distinct indexes of SSRT that address the violated assumption. Mixture SSRT and weighted SSRT are theoretically asymptotically equivalent under special conditions. An example of stop single task (SST) real data is presented to show equivalency of these two new SSRT indexes and their larger magnitude compared to Logan's single 1994 SSRT. Abbreviations: ADHD: attention deficit hyperactivity disorder; ExG: Ex-Gaussiandistribution; GORT: reaction time in a go trial; GORTA: reaction time in a type A gotrial; GORTB: reaction time in a type B go trial; LMM: linear mixed model; SWAN:strengths and weakness of ADHD symptoms and normal behavior rating scale; SSD: stop signal delay; SR: signal respond; SRRT: reaction time in a failedstop trial; SSRT: stop signal reaction times in a stop trial; SST: stop signaltask.

[1]  G. Logan,et al.  Impulsivity and Inhibitory Control , 1997 .

[2]  L. Thorell,et al.  Motor Response Inhibition and Execution in the Stop-Signal Task: Development and Relation to ADHD Behaviors , 2007, Child neuropsychology : a journal on normal and abnormal development in childhood and adolescence.

[3]  G. Logan On the ability to inhibit thought and action , 1984 .

[4]  J. Monterosso,et al.  Deficits in response inhibition associated with chronic methamphetamine abuse. , 2005, Drug and alcohol dependence.

[5]  G. Logan,et al.  Inhibitory control in mind and brain: an interactive race model of countermanding saccades. , 2007, Psychological review.

[6]  Hans Colonius,et al.  A Note on the Stop-Signal Paradigm, or How to Observe the Unobservable , 1990 .

[7]  Scott D. Brown,et al.  Bayesian parametric estimation of stop-signal reaction time distributions. , 2013, Journal of experimental psychology. General.

[8]  Andrew Heathcote,et al.  RTSYS: A DOS application for the analysis of reaction time data , 1996 .

[9]  S. Vanduffel,et al.  Quantile of a Mixture with Application to Model Risk Assessment , 2015 .

[10]  J. Swanson,et al.  Response Inhibition and ADHD Traits: Correlates and Heritability in a Community Sample , 2013, Journal of abnormal child psychology.

[11]  G. Logan,et al.  Models of response inhibition in the stop-signal and stop-change paradigms , 2009, Neuroscience & Biobehavioral Reviews.

[12]  S. Ciasca,et al.  Development and applications of the SWAN rating scale for assessment of attention deficit hyperactivity disorder: a literature review , 2015, Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas.

[13]  Gordon D Logan,et al.  Horse-race model simulations of the stop-signal procedure. , 2003, Acta psychologica.

[14]  M. Rieger,et al.  Inhibition of ongoing responses in patients with Parkinson’s disease , 2004, Journal of Neurology, Neurosurgery & Psychiatry.

[15]  Gordon D Logan,et al.  Evidence for an Error Monitoring Deficit in Attention Deficit Hyperactivity Disorder , 2004, Journal of abnormal child psychology.