Toward neuromarkers for tailored smoking cessation treatments

Abstract

Neurobiological models of addiction attribute vulnerability to compulsive drug use to dysregulated activity within the neural networks that underlie reward and executive functions. Empirical evidence suggests that (a) attributing high motivational salience to drug-related stimuli leads to compulsive drug seeking and (b) cognitive control deficits lead to compulsive drug taking. Noninvasive neuroimaging techniques enable brain activity monitoring during affective and cognitive processing and could pave the way to precision medicine for substance use disorders. Identifying robust neuromarkers of affective and cognitive dysregulation would allow clinicians to personalize treatments by targeting individual psychophysiological vulnerabilities. However, methodological choices have biased the field toward experimental paradigms that cannot optimally assess individual differences in the motivational salience of drug-related cues and in the ability to control drug-related decisions, hindering the identification of clinically relevant neuromarkers. Here we show that (a) accounting for neuroaffective reactivity to non-drug-related motivationally relevant stimuli when measuring the attribution of motivational salience to drug-related cues, and (b) assessing brain activity while participants make drug-related decisions with immediate consequences, yield replicable neuromarkers with potential clinical relevance. While we use tobacco use disorder as a model, we also show that the methodological issues highlighted here are relevant to other disorders characterized by maladaptive appetitive behaviors.