A framework and toolkit for understanding impulsive action

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What is the importance? Impulsivity is a key factor in understanding individual behaviour in many spheres, from economics to health and wellbeing, from psychiatry to social disorder. It is associated with many problem behaviours, such as alcoholism, obesity, ADHD, binge drinking or eating, drug misuse, gambling, aggression, violent or sexual abuse and risky sex. Advances in understanding the different aspects of impulsivity - and how best to measure them - will have immediate application for attempts to modify these behaviours. Our focus. Tasks that measure impulsivity divide into two types: those measuring performance in the control or inhibition of responses, and those measuring preferences for risk or reward immediacy. We concentrate on the former category: response control. What is the need? Response control tasks are increasingly popular, since they are thought to tap basic mechanisms underlying a variety of problematic behaviours (as mentioned above). However, progress is inefficient because we lack a clear framework for understanding why people differ in these tasks, and what such differences actually mean for real-world behaviour. The basic conclusion is that people differ in their ability to inhibit habitual responses, but this leaves unexplained why people's performance does not correlate very well across different ways of testing this ability. As increasing numbers of studies use these measures, research money is wasted because there is no commensurate advance in understanding.How will we solve this problem? 1. Underpinning. Part of the problem is that some essential work on these tasks has not been done. Most of the tasks have been transferred from studies of group averages, where individual differences are treated as irrelevant. Thus we do not even know which tasks best reflect stable traits (and how many trials are needed to do so). Nor do we know whether the important thing for generalisable response control is how quickly people catch on to the task, or how well they perform once the task is well practised. 2. Applying computational modelling to provide a new framework. Part of the problem is that the tasks assess surrogates of what we really want to measure - the underlying cognitive mechanisms that contribute to impulsive behaviour. There are at least two separate factors related to impulsivity that influence performance on these tasks - how cautious someone is and how good they are at inhibiting the wrong response (or selecting the right one). When these factors interact, the results become difficult to interpret, and the approach of using patterns of correlation across different tasks to extract underlying variables has proved insufficient in this case. We will instead use computational models of action decision, which utilise the full richness of the behavioural data, and can help us to understand us how complex and counterintuitive results occur. 3. Tools to inform intervention. In order to successfully help people with different kinds of detrimental impulsivity (whether in the context of addiction, violence, debt, school performance or many other areas), researchers, professional psychologists, economists, clinicians, etc., need tools that distil the best scientific knowledge into packages that can be easily administered without specialist knowledge (e.g., of computational modelling). We will translate our findings into such tools: the Model-Based Impulsivity Toolkit (ModBIT).