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.

One of the major risk factors for global death and disability is alcohol, tobacco, and illicit drug use. While there is increasing knowledge with respect to individual factors promoting the initiation and maintenance of substance use disorders (SUDs), disease trajectories involved in losing and regaining control over drug intake (ReCoDe) are still not well described. Our newly formed German Collaborative Research Centre (CRC) on ReCoDe has an interdisciplinary approach funded by the German Research Foundation (DFG) with a 12‐year perspective. The main goals of our research consortium are (i) to identify triggers and modifying factors that longitudinally modulate the trajectories of losing and regaining control over drug consumption in real life, (ii) to study underlying behavioral, cognitive, and neurobiological mechanisms, and (iii) to implicate mechanism‐based interventions. These goals will be achieved by: (i) using mobile health (m‐health) tools to longitudinally monitor the effects of triggers (drug cues, stressors, and priming doses) and modify factors (eg, age, gender, physical activity, and cognitive control) on drug consumption patterns in real‐life conditions and in animal models of addiction; (ii) the identification and computational modeling of key mechanisms mediating the effects of such triggers and modifying factors on goal‐directed, habitual, and compulsive aspects of behavior from human studies and animal models; and (iii) developing and testing interventions that specifically target the underlying mechanisms for regaining control over drug intake.

Our daily life is characterized by multiple response options that need to be cascaded in order to avoid overstrain of restricted response selection resources. While response selection and goal activation in action cascading are likely driven by a process varying from serial to parallel processing, little is known about the underlying neural mechanisms that may underlie interindividual differences in these modes of response selection. To investigate these mechanisms, we used a stop–change paradigm for the recording of event-related potentials and standardized low resolution brain electromagnetic tomography source localizations in healthy subjects. Systematically varying the stimulus onset asynchrony (the temporal spacing of “stop” and “change” signals), we applied mathematical constraints to classify subjects in more parallel or more serial goal activators during action cascading. On that basis, the electrophysiological data show that processes linking stimulus processing and response execution, but not attentional processes, underlie interindividual differences in either serial or parallel response selection modes during action cascading. On a systems level, these processes were mediated via a distributed fronto-parietal network, including the anterior cingulate cortex (Brodman area 32, BA32) and the temporo-parietal junction (BA40). There was a linear relation between the individual degree of overlap in activated task goals and electrophysiological processes.

In 2016, the Alcohol Hangover Research Group defined the alcohol hangover as “the combination of mental and physical symptoms experienced the day after a single episode of heavy drinking, starting when blood alcohol concentration (BAC) approaches zero”. In the light of new findings and evidence, we carefully reviewed the different components of that definition. Several studies demonstrated that alcohol hangovers are not limited to heavy drinking occasions. Instead, data from both student and non-student samples revealed that at a group level, alcohol hangover may occur at much lower BAC levels than previously thought. Regression analysis further revealed that for individual drinkers, the occurrence of hangovers is more likely when subjects consume more alcohol than they usually do. However, hangovers may also occur at a drinker’s usual BAC, and in some cases even at lower BAC (e.g. in case of illness). We also carefully reviewed and modified other parts of the definition. Finally, hangovers are not necessarily limited to the ‘next day’. They can start at any time of day or night, whenever BAC approaches zero after a single dinking occasion. This may also be on the same day as the drinking occasion (e.g. when drinking in, or until the morning and subsequently having a hangover in the afternoon or evening). To better reflect the new insights and sharpen the description of the concept, we hereby propose to update the definition of the alcohol hangover as follows: “The alcohol hangover refers to the combination of negative mental and physical symptoms which can be experienced after a single episode of alcohol consumption, starting when blood alcohol concentration (BAC) approaches zero”, and recommend to use this new definition in future hangover research.