Regulation of Craving: Clinical Trial and Neural Mechanisms

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Abstract/Project Summary Heavy drinking in young adults (YA) is prevalent, and associated with serious negative consequences including mortality and risk for alcohol use disorders (AUD) 1-7. However, existing interventions have shown modest efficacy 8-14, and innovative interventions are needed. YA interventions have potential for broad impact if they are brief, computerized (especially web-based), and target core neurocognitive mechanisms underlying heavy drinking 14,15. Two such mechanisms are craving and regulation of craving. Defined in DSM-5 as “a strong desire” 16, craving is prospectively associated with and predicts drinking (e.g.,17- 25, including in YAs (e.g., 26-29). Importantly, alcohol-associated cues increase craving 30; such cue-induced craving is also prospectively associated with and predicts drinking(e.g.,31-35), including in YA 32,33,36,37. These data implicate cue-induced craving as a core mechanism underlying drinking 38. Consistently, skills training in regulation of craving is an important feature of many interventions 39-44, including cognitive-behavioral therapy (CBT) 45 and mindfulness-based treatments (MBT) 46,47. Further, regulation of craving directly relates to reductions in craving and drinking, and better treatment outcomes(e.g., 34,41,42,48-52), including in YA 53. These data implicate regulation of craving as a core mechanism underlying change in drinking/abstinence 54. We developed the Regulation of Craving (ROC) task to investigate cognitive, affective, and neural mechanisms associated with craving and its regulation across substances 55-61. In one study, alcohol drinkers were exposed to alcohol images60. On craving trials, they experienced cue-induced craving and exhibited neural activity in regions including ventral striatum and ventromedial prefrontal cortex 62-64. On regulation trials they used a treatment-based strategy to modulate their craving. We found that self-reported craving and craving-related neural activity were significantly reduced during regulation 60. However, across studies we found that the neural mechanisms by which regulation operates depend on the strategy used. Specifically, regulation with CBT strategies (e.g., ‘think of the negative consequences of drinking’) depends on the PFC 56,60,65 while regulation with MBT strategies (e.g., ‘notice and accept craving without judgment’) does not 57,66,67. Based on this, we developed two brief, web-based, mechanism-focused interventions: CBT-based and MBT-based Regulation of Craving Training (ROC-T) 58,68,69, in which participants repeatedly practice regulating craving in the presence of alcohol images. We propose to evaluate the efficacy of ROC-T and its mechanisms by randomizing 177 YA heavy drinkers to 4x45 minute sessions of (1) CBT-ROC-T, (2) MBT- ROC-T, or (3) CONTROL (no strategy). Alcohol use will be measured via Timeline Followback 70 for 10 weeks as well as a wearable transdermal sensor 71,72. Pre- and post-training, we will evaluate cognitive, affective, and neural mechanisms underlying ROC-T using the ROC task and fMRI. The current project has the potential to significantly advance mechanism-targeted interventions for heavy drinking, AUD, and other addictive disorders.