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Neural correlates of cue-induced changes in decision-making distinguish subjects with gambling disorder from healthy controls

By Alexander Genauck, Caroline Matthis, Milan Andrejevic, Lukas Ballon, Francesca Chiarello, Katharina Duecker, Andreas Heinz, Norbert Kathmann, Nina Romanczuk-Seiferth

Posted 17 Dec 2018
bioRxiv DOI: 10.1101/498725 (published DOI: 10.1111/adb.12951)

Background: Just as substance use disorders (SUDs), gambling disorder (GD) is characterized by an increase in cue-dependent decision-making (similar to Pavlovian-to-instrumental transfer, PIT). PIT, as studied in SUDs and healthy subjects, is associated with altered communication between Nucleus Accumbens (NAcc), amygdala, and orbitofrontal cortex (OFC). These neural differences are, however, poorly understood. For example, it is unclear whether they are due to the physiological effects of substance abuse, or rather related to learning processes and/or other etiological factors like innate traits associated with addiction. We have thus investigated whether network activation patterns during a PIT task are also altered in GD, an addictive disorder not involving substance abuse. We have specifically studied which neural PIT patterns were best at distinguishing GD from HC subjects, all to improve our understanding of the neural signatures of GD and of addiction-related PIT in general. Methods: 30 GD and 30 HC subjects completed an affective decision-making task in a functional magnetic resonance imaging (fMRI) scanner. Gambling associated and other emotional cues were shown in the background during the task, allowing us to record multivariate neural PIT signatures focusing on a network of NAcc, amygdala and OFC. We built and tested a classifier based on these multivariate neural PIT signatures using cross-validated elastic net regression. Results and Discussion: As expected, GD subjects showed stronger PIT than HC subjects because they showed stronger increase in gamble acceptance when gambling cues were presented in the background. Classification based on neural PIT signatures yielded a significant AUC-ROC (0.70, p = 0.013). When inspecting the features of the classifier, we observed that GD showed stronger PIT-related functional connectivity between NAcc and amygdala elicited by gambling background cues, as well as between amygdala and OFC elicited by negative and positive cues. Conclusion: We propose that HC and GD subjects are distinguishable by PIT-related neural signatures including amygdala-NAcc-OFC functional connectivity. Our findings suggest that neural PIT alterations in addictive disorders might not depend on the physiological effect of a substance of abuse, but on related learning processes or even innate neural traits, also found in behavioral addictions.

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