Abstract
Alterations within mesocorticolimbic terminal regions commonly occur with alcohol use disorder (AUD). As pathological drug-seeking behavior may arise as a consequence of alcohol-induced neuroadaptations, it is critical to understand how such changes increase the likelihood of relapse. This report examined resting-state functional connectivity (RSFC) using both a seed-based and model-free approach in individuals in treatment for AUD and how dysregulation of network connectivity contributes to treatment outcomes. In order to provide a mechanism by which neural networks promote relapse, interactive effects of mesocorticolimbic connectivity and AUD risk factors in treatment completers and non-completers were examined. AUD group showed stronger RSFC between striatum, insula, and anterior cingulate cortex than controls. Within the AUD group, non-completers compared to completers showed enhanced RSFC between (1) striatum–insula, (2) executive control network (ECN)–amygdala, and (3) basal ganglia/salience network and striatum, precuneus, and insula. Completers showed enhanced RSFC between striatum-right dorsolateral prefrontal cortex. Furthermore, completers and non-completers differed in relationships between RSFC and relapse risk factors, where non-completers exhibited positive associations between craving intensity and RSFC of striatum–insula and ECN–amygdala. These findings provide evidence for interactions between corticolimbic connectivity in AUD and craving and establish an important link between network connectivity and dynamic risk factors that contribute to relapse. Results demonstrate that relapse vulnerability is attributed to craving dysregulation manifested by enhanced connectivity in striato-limbic regions and diminished corticostriatal connectivity.
Highlights
Identification of neural phenotypes related to risk for relapse is important for understanding the nature of alcohol-use disorder (AUD) and its response to treatment
Greater and more expanded ACC–frontostriatal connectivity and expanded network connectivity is positively associated with visuospatial working memory and slower perceptual motor processing, respectively, while measures of depression and anxiety are related to restricted and expanded connectivity of reward and executive control network (ECN) [12]. While these findings provide a theoretical framework for how neural network adaptations in AUD and the relationship to cognitive or neuropsychiatric constructs may lead to relapse, the interactive effects of resting-state functional connectivity (RSFC), risk factors for relapse, and treatment outcomes have not been explored
There were no significant differences between Completers and Non-completers in age, sex, years of education, alcohol-use variables, or in the frequency of cigarette use but significant differences between controls and the AUD group were seen in age, sex, years of education, and smoking status (p < 0.05) (Table 1)
Summary
Identification of neural phenotypes related to risk for relapse is important for understanding the nature of alcohol-use disorder (AUD) and its response to treatment. AUD is associated with widespread neural adaptations, but how these changes correspond to phenotypes that promote relapse is unclear. Cognitive domains, such as executive control and reward processing, likely interact to contribute to the maintenance of alcohol seeking and problem drinking. Enhanced reward sensitivity and the Alcohol Dependence: RSFC, Craving, Relapse motivational drive that promote reward-seeking behavior may in part result from impairments in executive control. The behavioral sequelae of alterations in the balance of cognitive control and reward-seeking behavior are key features of substance-use disorders and common barriers to treatment success
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