Higher integration of reward, cognitive, and attention networks in people with Opioid Use Disorder.
Poster No:
1721
Submission Type:
Abstract Submission
Authors:
Danielle Kurtin1, Katherine Herlinger1, Alexandra Hayes2, Lexi Hand1, Leon Fonville1, Anne Lingford-Hughes1, Louise Paterson1
Institutions:
1Imperial College London, London, United Kingdom, 2Kings College London, London, United Kingdom
First Author:
Co-Author(s):
Introduction:
The cycles of relapse and remittance characterising Opioid Use Disorder (OUD) are driven by drug-induced changes in reward circuitry and incentive drives, which in turn effect decision making. This can be characterised as a disrupted relationship between reward circuitry (the VentroMedial Network (VMN)) and the functional networks associated with visualisation of drug consumption (Default Mode Network (DMN)), planning/strategizing to acquire the drug (Control/Cognitive networks), attention to drug-related stimuli and impulsive use (Salience Network) (Dunlop et al., 2017).
Methods:
To characterise how the neural correlates of reward processing are disrupted in OUD we collected fMRI data in Methadone Dependent participants (MD, n=22) and healthy controls (HC, n=22) during Monetary Incentive Delay (MID) and Cue Reactivity tasks. These tasks reliably show blunted VMN activity during non-drug, monetary rewards and heightened VMN responses to drug-related cues respectively (Hayes et al., 2020 ). Functional connectivity was captured via mutual information (miFC). Cortical regions were defined by transforming the 200-region Schaefer atlas to subject space; Freesurfer parcellation defined 14 subcortical regions. Since fMRI-based measures of brain function are linked to neurotransmitter receptor availability (Hansen et al., 2022), we additionally evaluated the relationship between group differences in miFC and MOR and D2 receptor density, given the importance of these receptors in the development of addiction (Volkow et al., 2011).
Results:
During the MID task, MD participants showed higher miFC in VMN regions (Ventral Striatum, medial prefrontal cortex (mPFC), and orbitofrontal cortex) to regions in attention (Frontal Eye Fields and Insula) and cognitive/control networks (PFC, Superior Parietal Lobule). HCs showed higher miFC between attentional networks to Visual and Somatomotor networks, as well as the DMN and thalamus, in line with two recent studies (Nestor et al., 2020; Nestor and Ersche, 2023) (Fig 1). These results indicate stronger integration among VMN, attention, and cognitive networks in MD participants, whereas connectivity among regions in attentional networks to visual, somatomotor, and DMN networks is lessened. Given the self-referential and interoceptive functions of the DMN, decreased integration of the DMN may result in a weakened ability to integrate reward-related outcomes, which is associated with the development of habitual consumption (Nestor and Ersche, 2023).
The results from the Cue Reactivity task provide further evidence that MD participants exhibit a strong neural framework supporting automatic responses to drug-related stimuli, since MD participants showed higher miFC in the same VMN regions to regions in attention and cognitive/control networks (Fig 1). These results suggest the relationship between drug-related cues and decision-making processes are driven by compulsive, automatic processes. This is supported by two studies in alcohol-dependent participants showing higher FC among VMN, attention, and cognitive/control networks was significantly correlated with markers of increased impulsivity (Zhu et al., 2017) and compulsivity (Strosche et al., 2021).
We found significant, positive relationships between the magnitude of higher miFC in MD vs HC participants and the sum of MOR and D2 receptor density during the Cue Reactivity task (Fig 2). This accords with the role of D2 receptors in the incentive salience of drug cues (Everitt and Robbins, 2016; Koob and Volkow, 2010).
The results from the Cue Reactivity task provide further evidence that MD participants exhibit a strong neural framework supporting automatic responses to drug-related stimuli, since MD participants showed higher miFC in the same VMN regions to regions in attention and cognitive/control networks (Fig 1). These results suggest the relationship between drug-related cues and decision-making processes are driven by compulsive, automatic processes. This is supported by two studies in alcohol-dependent participants showing higher FC among VMN, attention, and cognitive/control networks was significantly correlated with markers of increased impulsivity (Zhu et al., 2017) and compulsivity (Strosche et al., 2021).
We found significant, positive relationships between the magnitude of higher miFC in MD vs HC participants and the sum of MOR and D2 receptor density during the Cue Reactivity task (Fig 2). This accords with the role of D2 receptors in the incentive salience of drug cues (Everitt and Robbins, 2016; Koob and Volkow, 2010).
Conclusions:
In summary, the higher integration among reward, attentional, and cognitive networks in MD participants during both non-drug and drug-related tasks suggests maladaptive, drug-induced changes in reward circuitry influences other processes affected by addiction, such as attention and cognition. These mechanistic insights provide a foundation for future research to further characterise the relationship between the neural and behavioural correlates of addiction.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 2
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
fMRI Connectivity and Network Modeling 1
PET Modeling and Analysis
Keywords:
Addictions
FUNCTIONAL MRI
Positron Emission Tomography (PET)
Sub-Cortical
1|2Indicates the priority used for review
·Figure 1
·Figure 2
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