Brain Functional Connectivity Signatures of Craving Across Substance Use Disorders: A Transdiagnostic Approach

Abstract

Craving is a hallmark feature of substance use disorders (SUDs) and a major risk factor for relapse, yet reliable biomarkers that enable individual-level prediction remain scarce. Here, we applied connectome-based predictive modeling (CPM) to resting-state functional magnetic resonance imaging (fMRI) data in a transdiagnostic sample of individuals with cannabis, opioid, or tobacco use disorder (n = 78). Using CPM, we identified a distributed functional brain network that reliably predicted self-reported craving. Computational lesion analyses revealed key contributions from the right medial orbitofrontal cortex, right dorsal posterior cingulate cortex, and left lateral medial frontal gyrus. Importantly, the craving network generalized across two independent datasets. In alcohol-dependent patients (n = 41), the identified craving network, along with its positive and negative subnetworks, predicted distinct cognitive and motivational components of craving. In a second external dataset of smokers (n = 28), the craving network predicted both nicotine craving after abstinence as well as intra-individual changes in craving between sated and craving states. Together, these findings provide evidence for a robust, transdiagnostic craving signature in SUDs. Future work should assess the networks predictive utility for longitudinal outcomes such as relapse risk and treatment response.