Goal Narrowing Drives Compulsive Decision Making in Patients with Methamphetamine Use Disorder: A Cross-Sectional Study of Neural and Behavioral Correlates

Background Methamphetamine use disorder (MUD) is characterized by compulsive drug use, which has been attributed to compulsive decision-making related to drug-use events, with either exaggerated habit formation or excessive goal-directed selection contributing to it. However, the specific behavioral mechanism in MUD patients and their underlying neurophysiological mechanisms remain unclear. This study tried to fill this gap. Methods This cross-sectional study enrolled 54 MUD patients and 27 healthy volunteers. Patients were divided into Mild (N = 27) and Moderate-Severe (N = 27) groups according to DSM-5 criteria. Participants completed a monetary probability reward task with electroencephalography recording. Reinforcement learning model was used to address behavioral deficits, and event-related potentials (ERPs), time-frequency analysis and source localization were applied to identify differential electrophysiological signals and brain regions. Results Compared with healthy participants, Moderate-Severe MUD patients exhibited inflexible reward-seeking behaviors correlated with greater loss of control over drug use. ERP analysis revealed an abnormal component in the left frontal lobe within the early 200ms overlapping in time with feedback-related negativity, and the theta power was greater in incongruent than in congruent conditions, driven by hyperactivation in caudate nucleus correlated with inflexible reward-seeking and loss of control over drug use. Conclusions This study demonstrates that MUD patients, depending on the severity of their condition, exhibit distinct behavioral and neurophysiological patterns in processing reward and punishment signals. Goal Narrowing may underlie the compulsive decision-making, manifesting as extreme reward pursuit and hyperactivation of caudate nucleus. Developing targeted interventions for abnormal behavioral and electrophysiological signals may be beneficial in future research.