The influence and manipulation of resting-state brain networks in alcohol use disorder

Alcohol use disorder is common, and treatments are currently inadequate. Some of the acute effects of alcohol on the brain, such as altering the decision-making and future thinking capacities, mirror the effects of chronic alcohol use. Therefore, interventions that can address these shortcomings may be useful for reducing the negative effects of alcohol use disorder in combination with other therapies. The signature of those interventions may also be evident in the signature of large-scale, dynamic brain networks, which can show whether an intervention is effective. One such intervention is episodic future thinking, which has been shown to reduce delay discounting and orient people toward pro-social, long-term outcomes. To better understand decision making in high-risk individuals, we examined delay discounting in an adolescent population. When the decision-making faculties were challenged with difficult choices, adolescents made decisions inconsistent with their predicted preference, complemented by increased brain activity in the central executive network and salience network. Using these results and the hypothesis that the default mode network would be implicated in future thinking and intertemporal choice, we examined the neural effects of a brief behavioral intervention, episodic future thinking, that seeks to address these impairments. We showed that episodic future thinking has both acute and longer-lasting effects on consequential brain networks at rest and during delay discounting compared to a control episodic thinking condition in alcohol use disorder. Our failure to show group differences in default mode network prompted us to scrutinize it more carefully, from a position where we could measure the ability to self-regulate the network rather than its resting-state tendency. We implemented a real-time fMRI experiment to test the degree to which people along the alcohol use severity spectrum can self-regulate this network. Our results showed that default mode network suppression is impaired as alcohol use disorder severity increases. In the process, we showed that direct examination of resting-state networks with these methods will provide more information than measuring them at rest alone. We also characterized the default mode network along the real-time fMRI pipeline to show the whole-brain spatial pattern of regions associated and unassociated with the network. Our results indicate that resting-state brain networks are important markers for outcomes in alcohol use disorder and that they can be manipulated under experimental conditions, potentially to the benefit of the afflicted individual.