Week-to-Week Fluctuations in Risky Decision Making Track Heroin Use in Treatment-Seeking Opioid Users
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Background: The degree to which opioid replacementtherapy (e.g., methadone), the gold standard in opioidaddiction management, is effective at reducing illicit opioiduse depends on how well titrated it is for the current needs ofan individual. However, good proximal predictors of whenan individual is at risk for relapse—and therefore in need ofadditional behavioral and/or pharmacological intervention—are currently lacking. Here, we use standard computationallydriven neuroeconomic measurements to decompose the risktaking behavior of opioid users undergoing opioid replacementtherapy, as a way to identify behavioral markers thatmight predict illicit opioid use.Methods: We had individuals starting opioid replacementtherapy (i.e., who were within 4 weeks of treatmentinitiation) perform simple and easy-to-automate monetarydecision making tasks weekly (and then every other week)over several months of treatment. We established when oursubjects returned to illicit opioid (or any drug) use by bothself-report and randomly administered (at least 1/week)urine toxicology tests. A matched sample of drug-freecommunity controls also completed the decision makingtasks. These subjects both served as a baseline control groupas well as allowed us to assess the test-retest reliability of ourmeasurements. A subset of subjects from both groups alsocompleted the tasks while we acquired functional magneticresonance imaging (MRI) data at two time points: once at thebeginning of the treatment and again 8-12 weeks later. Themeasurements we used are based on a standard neuroeconomicmodel that decomposes the behavior of each subjectinto two parameters: “risk attitude” and “ambiguity attitude”,indexing how sensitive that subject is to known andunknown risks, respectively. We computed these parametersfor each subject at each study session, and using generalizedlinear mixed models, we examined how fluctuations in theseparameters related retrospectively and prospectively to illicitopioid use events.Results: We find a high degree of test-retest reliability acrossthe study sessions for both parameters. Attesting to thedistinct aspects of risky decision making captured by theseparameters, we find that only sudden increases in an opioiddependentsubject’s willingness to take risks in our taskcorrelated with, and in some cases preceded, illicit opioiduse. But importantly, we find both parameters are notstationary in the opioid-dependent subjects: both parametersfluctuate as individuals approach and recover from opioiduse events in a way not seen in controls. Both risk andambiguity tolerance increases surrounding opioid use, albeitat different rates.Conclusions: These data suggest that risk attitudes, whichcan be quickly and easily measured by our behavioral tasks,might be suitable behavioral markers—and perhaps evenpredictors—of relapse in opioid addiction. Our ongoingwork seeks to examine the neurobiological basis of thisrelationship between risky decision making and drug use.Based on previous findings in health with these tasks, weanticipate a common neural mechanism of the risk andambiguity parameters to include activation in regions thatform the brain’s valuation network (striatum, ventromedialprefrontal cortex), and distinct mechanisms to includeactivation in the insular cortex (for risk attitudes) andamygdala (for ambiguity attitudes).