Substances of abuse are known to activate and disrupt neuronal circuits in the brain reward
system. We propose a simple and easily interpretable dynamical systems model to describe …

Maladaptive behavior in drug addiction is widely regarded as a result of neurocognitive
dysfunctions. Recently, there has been a growing trend to adopt computational methods to …

Dopaminergic signals play a mathematically precise role in reward-related learning, and
variations in dopaminergic signaling have been implicated in vulnerability to addiction …

Clinical and experimental observations show individual differences in the development of
addiction. Increasing evidence supports the hypothesis that dopamine receptor availability …

Addictive drugs have been hypothesized to access the same neurophysiological
mechanisms as natural learning systems. These natural learning systems can be modeled …

Control theory provides a powerful conceptual framework and mathematical armamentarium
for modeling addictive behavior. It is particularly appropriate for repetitive, rhythmic behavior …

Dysfunction in learning and motivational systems are thought to contribute to addictive
behaviours. Previous models have suggested that dopaminergic roles in learning and …

This chapter describes addiction as a failure of decision-making systems. Existing
computational theories of addiction have been based on temporal difference (TD) learning …

Non-pharmacological behavioral addictions, such as pathological gambling, videogaming,
social networking, or internet use, are becoming major public health concerns. It is not yet …

Incentive salience is a motivational magnet property attributed to reward-predicting
conditioned stimuli (cues). This property makes the cue and its associated unconditioned …