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 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 present goal is to facilitate a more accurate use of the stop-signal task. To this end, we provide twelve easy-to-implement consensus recommendations and point out the problems that can arise when these are not followed. This article is furthermore accompanied by 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 world faces a climate emergency. Humanity must make urgent reductions in greenhouse gas emissions to stave off further global heating. In this article, we consider the actions that can be taken by neuroscientists, as individuals and as members of institutions and professional bodies and societies. We discuss flying less, the uncertain merits of carbon offsets, virtual conferencing and how climate justice must apply to questions of travel. We also consider emissions from lab research, and how neuroscientists can shape institutional policy on emissions reductions across myriad aspects of operations, including banking, investment and funding decisions. A radical culture change is needed to address the climate emergency. We encourage neuroscientists to put emissions reductions at the centre of their everyday professional activities.

When a unexpected event, such as a car honking, occurs in daily life, it often disrupts our train of thought. In the lab, this effect was recently modeled with a task in which verbal working memory (WM) was disrupted by unexpected auditory events (Wessel et al., 2016). Here, we tested whether this effect extends to a different type of WM, viz. visuomotor. We found that unexpected auditory events similarly decremented visuomotor WM. Moreover, this effect persisted for many more trials than previously shown, and the effect occurred for two types of unexpected auditory event. Furthermore, we found that unexpected events decremented WM by decreasing the quantity, but not necessarily the quality, of the items stored. These studies show a statistically robust, and across time enduring, impact of unexpected events on visuomotor WM. They also show an increase of guessing, consistent with a neuroscience-inspired theory that unexpected events ‘wipe out’ WM by stopping the ongoing maintenance of the trace.

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