Review
Models of response inhibition in the stop-signal and stop-change paradigms

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Abstract

The stop-signal paradigm is very useful for the study of response inhibition. Stop-signal performance is typically described as a race between a go process, triggered by a go stimulus, and a stop process, triggered by the stop signal. Response inhibition depends on the relative finishing time of these two processes. Numerous studies have shown that the independent horse-race model of Logan and Cowan [Logan, G.D., Cowan, W.B., 1984. On the ability to inhibit thought and action: a theory of an act of control. Psychological Review 91, 295–327] accounts for the data very well. In the present article, we review the independent horse-race model and related models, such as the interactive horse-race model [Boucher, L., Palmeri, T.J., Logan, G.D., Schall, J.D., 2007. Inhibitory control in mind and brain: an interactive race model of countermanding saccades. Psychological Review 114, 376–397]. We present evidence that favors the independent horse-race model but also some evidence that challenges the model. We end with a discussion of recent models that elaborate the role of a stop process in inhibiting a response.

Section snippets

Early horse-race models of response inhibition

The idea that response inhibition depends on the relative finishing time of a go process and a stop process has always dominated the stop-signal literature. Vince (1948) showed that subjects could stop their response only when the delay between the go stimulus and the stop signal (stop-signal delay or SSD) was short (i.e., 50 ms). At longer delays (i.e., 100 ms and longer), response inhibition was very rare, which suggests that the stop process started too late to cancel the response. Lappin and

The independent horse-race model

Early horse-race models mainly focused on describing go and stop performance either qualitatively (Lappin and Eriksen, 1966) or with narrowly focused quantitative assumptions (Ollman, 1973). These models were limited in generality and lacked a precise description of the main variables of interest, namely the difficulty of the stop process and the latency of the stop process (stop-signal reaction time or SSRT). Unlike the latency of an overt choice response, the latency of the response to the

Independence of the go and stop process

The independent horse-race model assumes independence between the finishing times of the go process and stop process (Logan and Cowan, 1984). The independence assumption takes two forms: context independence (also referred to as signal independence) and stochastic independence. Context independence refers to the assumption that the go RT distribution is the same for no-stop-signal trials and stop-signal trials. Stochastic independence refers to the assumption that trial-by-trial variability in

The role of the stop process in inhibiting a response

Logan and Cowan (1984) described how respond inhibition depends on the relative finishing time of a go process and a stop process. Boucher et al., 2007a, Boucher et al., 2007b elaborated this idea and described how a stop unit strongly inhibits inhibit a go unit after an afferent delay. Central to these models is that a go response is inhibited by the activation of a stop process. An alternative to this idea is that a go response is inhibited by the preparation of an alternative go response. In

Concluding remarks

The stop-signal paradigm is very useful for the study of response inhibition in a laboratory setting judging from the widespread use of the paradigm in cognitive psychology, clinical psychology, cognitive neuroscience and neuropsychology. Performance in the stop-signal paradigm is typically described as a race between a go process and a stop process. This horse race was formalized by Logan and Cowan (1984). After more than 25 years, their independent horse-race model still offers a remarkably

Acknowledgments

Frederick Verbruggen is a Postdoctoral Fellow of the Research Foundation—Flanders. Gordon D. Logan is supported by grant BCS 0646588 from the National Science Foundation, grant no. FA9550-07-1-0192 from the Air Force Office of Scientific Research grant, and by National Institute of Mental Health Grant R01-MH073879-01. We thank Guido Band, Adam Aron and an anonymous reviewer for their useful comments on an earlier version of this manuscript.

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