Effects of varenicline and cognitive bias modification on neural response to smoking-related cues: study protocol for a randomized controlled study

Neuroimaging the Effectiveness of Substance Use Disorder Treatments

Neuroimaging techniques to measure the function and biochemistry of the human brain such as positron emission tomography (PET), proton magnetic resonance spectroscopy ((1)H MRS), and functional magnetic resonance imaging (fMRI), are powerful tools for assessing neurobiological mechanisms underlying the response to treatments in substance use disorders. Here, we review the neuroimaging literature on pharmacological and behavioral treatment in substance use disorder. We focus on neural effects of medications that reduce craving (e.g., naltrexone, bupropion hydrochloride, baclofen, methadone, varenicline) and that improve cognitive control (e.g., modafinil, N-acetylcysteine), of behavioral treatments for substance use disorders (e.g., cognitive bias modification training, virtual reality, motivational interventions) and neuromodulatory interventions such as neurofeedback and transcranial magnetic stimulation. A consistent finding for the effectiveness of therapeutic interventions identifies the improvement of executive control networks and the dampening of limbic activation, highlighting their values as targets for therapeutic interventions in substance use disorders.

Belief about nicotine selectively modulates value and reward prediction error signals in smokers

Little is known about how prior beliefs impact biophysically described processes in the presence of neuroactive drugs, which presents a profound challenge to the understanding of the mechanisms and treatments of addiction. We engineered smokers' prior beliefs about the presence of nicotine in a cigarette smoked before a functional magnetic resonance imaging session where subjects carried out a sequential choice task. Using a model-based approach, we show that smokers' beliefs about nicotine specifically modulated learning signals (value and reward prediction error) defined by a computational model of mesolimbic dopamine systems. Belief of "no nicotine in cigarette" (compared with "nicotine in cigarette") strongly diminished neural responses in the striatum to value and reward prediction errors and reduced the impact of both on smokers' choices. These effects of belief could not be explained by global changes in visual attention and were specific to value and reward prediction errors. Thus, by modulating the expression of computationally explicit signals important for valuation and choice, beliefs can override the physical presence of a potent neuroactive compound like nicotine. These selective effects of belief demonstrate that belief can modulate model-based parameters important for learning. The implications of these findings may be far ranging because belief-dependent effects on learning signals could impact a host of other behaviors in addiction as well as in other mental health problems.