The clinical relevance of neurocognitive measures in addiction

One of the major challenges in addiction treatment is relapse prevention, as rates of relapse following treatment remain very high across the main classes of drugs of abuse. Relapse prevention could be improved by a better understanding of the factors that influence treatment outcomes, including better predictors of risk of relapse following treatment. Recent developments in cognitive neuroscience point to neurocognitive measures (i.e., brain-imaging measures during cognitive-task performance) as potential predictors of relapse. These might even be better predictors than self-report measures, such as craving. We first give an overview of the current state of the field, and then discuss the outstanding challenges and future directions in this area of research.Substance-dependent individuals often relapse, despite their efforts to stay abstinent (1). Substance dependence is therefore characterized as a chronic relapsing disorder (2,3). For example, after 1-6 months follow-up, 40-80% of the heroin- and cocaine-dependent patients who were in treatment relapse (4-7). To improve treatment and treatment assignment for these patients it is important to gain knowledge about the psychological and biological processes underlying treatment outcome and relapse. The aim of this review is to describe the use of neurocognitive measures in addiction research in relation to the prediction of relapse, and discuss their clinical relevance. Since there is considerable overlap between the various substances of abuse, we attempt to focus on factors which are known to play a role in substance-use disorders in general (i.e., alcohol, cigarette smoking, stimulants, and opiates). Where research on a specific substance is described this is indicated