Avoidance learning and behavior in patients with addiction

Both aversive and appetitive learning are important for guiding behavior. The occurrence of negative outcomes can gradually lead to avoidance behavior, which is a common phenomenon in daily life. Exaggerated acquisition and maintenance of avoidance behavior is a key feature of many human psychopathologies, including substance use disorders. Nonetheless, much of the human research on the relationship between avoidance and addiction has employed self-report measures. Animal models have been useful in understanding how avoidance learning and behavior may contribute to drug use. However, to date, the translation of such empirical data to human populations has been limited. Thus, in addition to discussing relevant research from the human self-report and animal literatures, we also review studies on human avoidance that have been conducted using computer-based tasks, in an addicted population (with matched healthy controls). We argue that computer-based tasks provide an objective complement to self-report, and can help bridge the human and animal literature on avoidance, with broad implications for substance use, as well as other disorders.