Connectome-based prediction of craving in gambling disorder and cocaine use disorder.

Abstract

Introduction: Craving, involving intense and urgent desires to engage in specific behaviours, is a feature of addictions. Multiple studies implicate regions of salience/limbic networks and basal ganglia, fronto-parietal, medial frontal regions in craving in addictions. However, prior studies have not identified common neural networks that reliably predict craving across substance and behavioural addictions.

Methods: Functional magnetic resonance imaging during an audiovisual cue-reactivity task and connectome-based predictive modelling (CPM), a data-driven method for generating brain-behavioural models, were used to study individuals with cocaine-use disorder and gambling disorder. Functions of nodes and networks relevant to craving were identified and interpreted based on meta-analytic data.

Results: Craving was predicted by neural connectivity across disorders. The highest degree nodes were mostly located in the prefrontal cortex. Overall, the prediction model included complex networks including motor/sensory, fronto-parietal, and default-mode networks. The decoding revealed high functional associations with components of memory, valence ratings, physiological responses, and finger movement/motor imagery.

Conclusions: Craving could be predicted across substance and behavioural addictions. The model may reflect general neural mechanisms of craving despite specificities of individual disorders. Prefrontal regions associated with working memory and autobiographical memory seem important in predicting craving. For further validation, the model should be tested in diverse samples and contexts.