Main description:

Addiction can be understood as a learned behavior resulting from processes of Pavlovian and operant conditioning, Alcohol and other drugs of abuse stimulate dopamine release and thus reinforce drug consumption, and contextual and specific cues associated with drug intake can become Pavlovian conditioned stimuli that facilitate approach behavior.
Novel mathematical tools such as modeling of decision making and model comparison reveal the computational and neuronal steps taken in decision making and their alterations in drug addiction. These approaches allow for a much more specific association between computational steps in decision making and neurobiological correlates during information processing.
The papers in this publication describe these approaches and discuss their perspective and limitations. Therefore, this special issue provides valuable reading for addiction researchers and neuroscientists who work in the field of decision making, reward learning and the clinical treatment of addiction.