Response inhibition is a hallmark of executive control. The concept refers to the suppression of nolonger required or inappropriate actions, which supports flexible and goal-directed behavior in everchanging environments. The stop-signal paradigm is most suitable for the study of response inhibition in a laboratory setting. The paradigm has become increasingly popular in cognitive psychology, cognitive neuroscience and psychopathology. We review recent findings in the stop-signal literature with the specific aim of demonstrating how each of these different fields contributes to better understanding of the processes involved in inhibiting a response and monitoring stopping performance, and more generally, discovering how behavior is controlled.People can readily stop talking, walking, typing, etc., in response to changes in internal states or changes in the environment. This ability to inhibit inappropriate or irrelevant responses is a hallmark of executive control. The role of inhibition in many experimental paradigms is debated, but most researchers agree that some kind of inhibition is involved in deliberately stopping a motor response. In this article, we focus on the stop-signal paradigm [1], which has proven to be a useful tool for the study of response inhibition in cognitive psychology, cognitive neuroscience and psychopathology. We review recent developments in the stop-signal paradigm in these different fields. The focus is primarily on the inhibition of manual responses. Studies of oculomotor inhibition are discussed in Box 1. Successful stopping: Inhibition and performance monitoringIn the stop-signal paradigm, subjects perform a go task, such as reporting the identity of a stimulus. Occasionally, the go stimulus is followed by a stop signal, which instructs subjects to withhold the response (see Figure 1). Stopping a response requires a fast control mechanism that prevents the execution of the motor response [1]. This process interacts with slower control mechanisms that monitor and adjust performance [2]. The race between going and stoppingPerformance in the stop-signal paradigm is modeled as a race between a go process, which is triggered by the presentation of the go stimulus, and a stop process, which is triggered by the presentation of the stop signal. When the stop process finishes before the go process, the response is inhibited; when the go processes finishes before the stop process, the response is emitted. The latency of the stop process (stop-signal reaction time; SSRT) is covert and must

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.

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 (1984) 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, Palmeri, Logan & Schall, 2007). 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.