Dynamic Changes in Risky Decision-Making Predict Imminent Heroin Use in Opioid Users Studied Longitudinally Through the First Months of Treatment

Anna Konova, Silvia Lopez-Guzman, Adelya Urmanche, Stephen Ross, Kenway Louie, John Rotrosen, Paul Glimcher

Research output: Contribution to journalMeeting Abstract

Abstract

Background Opioid overdose is now the leading cause of accidental death in the U.S. Opioid use during treatment increases overdose risk; thus, identifying predictors of opioid use in treatment-seekers at a timescale amenable to intervention is a priority. Here we tested the hypothesis that the value of risky prospects is enhanced when individuals are most vulnerable to use heroin. Methods 79 treatment-seekers completed 1-15 sessions over 7 months (mean/subject=6, SD=3.9). At each session, subjects made decisions about risks and rewards, and we objectively monitored heroin use. We modeled subjects' decisions as two parameters: risk tolerance and ambiguity tolerance, capturing behavior involving known and unknown risk, respectively. This allowed us to predict heroin use from session-to-session change in the parameters via time-lagged mixed-effects logistic regression. 12 subjects (study ongoing) additionally completed the same procedures during multi-band fMRI. Results Of 605 total sessions, 288 (47%) were heroin positive. Only an increase in ambiguity tolerance was predictive of prospective heroin use at the timescale examined [t(577)=3.39, P<0.001], supporting our hypothesis that the value of the (more) risky prospects is enhanced when individuals are most vulnerable. The fMRI data revealed activity in the striatum and VMPFC encoded the value of the ambiguous prospects. This in turn correlated with striatum-VMPFC connectivity at rest, together suggesting coordinated activity in the brain’s valuation system might underlie both the observed behavior change and heroin use vulnerability. Conclusions Treatment-monitoring and -intervention efforts targeting decision-making (and thus the valuation system) may help reduce incidence of relapse in a population at risk for overdose death.
Original languageEnglish (US)
Pages (from-to)S31
JournalBiological Psychiatry
Volume83
Issue number9
DOIs
StatePublished - May 1 2018

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