Abstract
Abnormal resting‐state functional connectivity, as measured by functional magnetic resonance imaging (MRI), has been reported in alcohol use disorders (AUD), but findings are so far inconsistent. Here, we exploited recent developments in graph‐theoretical analyses, enabling improved resolution and fine‐grained representation of brain networks, to investigate functional connectivity in 35 recently detoxified alcohol dependent patients versus 34 healthy controls. Specifically, we focused on the modular organization, that is, the presence of tightly connected substructures within a network, and on the identification of brain regions responsible for network integration using an unbiased approach based on a large‐scale network composed of more than 600 a priori defined nodes. We found significant reductions in global connectivity and region‐specific disruption in the network topology in patients compared with controls. Specifically, the basal brain and the insular–supramarginal cortices, which form tightly coupled modules in healthy subjects, were fragmented in patients. Further, patients showed a strong increase in the centrality of the anterior insula, which exhibited stronger connectivity to distal cortical regions and weaker connectivity to the posterior insula. Anterior insula centrality, a measure of the integrative role of a region, was significantly associated with increased risk of relapse. Exploratory analysis suggests partial recovery of modular structure and insular connectivity in patients after 2 weeks. These findings support the hypothesis that, at least during the early stages of abstinence, the anterior insula may drive exaggerated integration of interoceptive states in AUD patients with possible consequences for decision making and emotional states and that functional connectivity is dynamically changing during treatment.
Highlights
Alcohol use disorder (AUD)— called ‘alcoholism’—is among the most prevalent and severe psychiatric conditions worldwide,[1] with many affected individuals drinking at levels that result in lifethreatening conditions.[2]
An overall view on brain activity and identification of large-scale functional connectivity networks can be obtained from resting-state functional magnetic resonance imaging
In the combined group of 29 patients participating in the naturalistic open-label treatment, intensive withdrawal treatment (IWT) alone or in combination with NTX, we observed a modest but significant increase in the global strength of functional connectivity, with a right shift of the edge weight histogram (Figure S4)
Summary
Alcohol use disorder (AUD)— called ‘alcoholism’—is among the most prevalent and severe psychiatric conditions worldwide,[1] with many affected individuals drinking at levels that result in lifethreatening conditions.[2]. We have demonstrated the deleterious effects of these shortcomings, including a resolution limit that prevents detection of modules that are smaller than a scale determined by the size of the entire network.[19,20] we have shown that these limitations can be overcome by recent approaches based on graph information theory,[21,22,23] providing sharper tools to assess the modular organization of functional connectivity networks[19,20] and to apply advanced network statistics for comparing experimental conditions.[24] We leverage these important methodological advances to identify topological differences in large-scale brain networks (>600 a priori defined nodes25) of AUD patients and healthy controls. We leverage these important methodological advances to identify topological differences in large-scale brain networks (>600 a priori defined nodes25) of AUD patients and healthy controls. rsfMRI data were obtained from a recently published clinical trial in treatment-seeking patients that after a baseline assessment offered add-on treatment with the approved anticraving medication naltrexone (NTX) in a naturalistic, longitudinal open-label design.[26,27,28] In this data set, we explore the stability and potential susceptibility to therapeutic intervention of resting-state networks in AUD patients
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