Investigating hierarchical control among functional networks disrupted by Opioid Use Disorder using effective connectivity
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Published version
Author(s)
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Journal Article
Abstract
Opioid use disorder (OUD) poses a significant public health challenge. Developing a better understanding of the brain mechanisms and potential markers of OUD would facilitate the development of therapeutic interventions. While we recently showed that between-network connectivity is disrupted in people with OUD compared with healthy controls, it remains unclear what mechanisms may drive these disruptions and how dysfunctional interactions propagate across large scale functional networks. To advance the mechanistic understanding of the disrupted processes in OUD, this study used Effective Connectivity (EC) to quantify disrupted hierarchical control among functional networks governing cognition, attention, and reward. We also explored whether whole-brain patterns of EC were effective markers to distinguish people with severe OUD from controls. We hypothesised that the ventromedial network (VMN) would drive dysfunction in cognitive and attentional networks in people with OUD. Task-fMRI data was collected from healthy controls (HC; n=22) and OUD participants on methadone maintenance treatment (OUD; n=25), during a heroin cue reactivity (CR) and monetary incentive delay (MID) task. Following brain parcellation (214 regions) and network assignment (7 functional networks), EC was quantified using large scale nonlinear Granger causality. Dimensionality reduction was performed using uniform manifold approximation and projection, followed by hierarchical density-based spatial clustering of applications with noise to assess whether EC patterns could form clusters corresponding to group labels.
Contrary to our hypothesis, the VMN did not drive dysfunction in cognitive and attentional networks. Instead, edges with significantly stronger EC in HC vs OUD participants were within and between the control, somatomotor, and default mode networks. EC patterns were unable to form distinct clusters that corresponded to clinical groups; instead, clusters separated by task. Little evidence was found that disrupted VMN-mediated reward drove dysregulated whole-brain function in OUD.
Contrary to our hypothesis, the VMN did not drive dysfunction in cognitive and attentional networks. Instead, edges with significantly stronger EC in HC vs OUD participants were within and between the control, somatomotor, and default mode networks. EC patterns were unable to form distinct clusters that corresponded to clinical groups; instead, clusters separated by task. Little evidence was found that disrupted VMN-mediated reward drove dysregulated whole-brain function in OUD.
Date Issued
2026-08-31
Date Acceptance
2026-08-28
Citation
Imaging Neuroscience, 2026
ISSN
2837-6056
Publisher
The MIT Press
Journal / Book Title
Imaging Neuroscience
Copyright Statement
© 2026 The Authors. Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/legalcode.
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Publication Status
Published online
Date Publish Online
2026-08-31