Abstinence Alters Triple Network Dynamics in Moderate-to-Heavy Drinkers

Alcohol misuse is a significant public health concern, yet little is known about the neural dynamics associated with habitual heavy drinking, particularly during abstinence. The Triple Network Model, comprising the salience network (SN), default mode network (DMN), and central executive network (CEN), provides a framework for understanding large-scale brain network dysfunction associated with heavy alcohol use. Using resting-state fMRI and a Hidden Semi-Markov Model (HSMM), we examined dynamic brain state changes in moderate-to-heavy drinkers (n = 38) across two conditions: typical drinking and alcohol abstinence. Our findings revealed six distinct brain states, with significant differences in state occupancy, transitions, and duration between drinking conditions. Abstinence was associated with decreased time spent in a DMN-dominant state, a lower probability of transitioning to a state with high SN activation, and more frequent but shorter durations in a state without a distinct dominant network. These results suggest alcohol abstinence alters the temporal dynamics of these brain networks, potentially disrupting attention shifting and cognitive control mechanisms that may contribute to relapse risk. Understanding these neural adaptations will provide critical insight into the neurobiology of habitual heavy drinking and inform potential targets for future interventions.