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Abstracts
  • Gowin, J. L., Ball, T. M., Wittmann, M., Tapert, S. F., & Paulus, M. P. (2015). Individualized relapse prediction: Personality measures and striatal and insular activity during reward-processing robustly predict relapse. Drug and Alcohol Dependence, 152, 93–101. https://doi.org/10.1016/j.drugalcdep.2015.04.018

    BACKGROUND: Nearly half of individuals with substance use disorders relapse in the year after treatment. A diagnostic tool to help clinicians make decisions regarding treatment does not exist for psychiatric conditions. Identifying individuals with high risk for relapse to substance use following abstinence has profound clinical consequences. This study aimed to develop neuroimaging as a robust tool to predict relapse. METHODS: 68 methamphetamine-dependent adults (15 female) were recruited from 28-day inpatient treatment. During treatment, participants completed a functional MRI scan that examined brain activation during reward processing. Patients were followed 1 year later to assess abstinence. We examined brain activation during reward processing between relapsing and abstaining individuals and employed three random forest prediction models (clinical and personality measures, neuroimaging measures, a combined model) to generate predictions for each participant regarding their relapse likelihood. RESULTS: 18 individuals relapsed. There were significant group by reward-size interactions for neural activation in the left insula and right striatum for rewards. Abstaining individuals showed increased activation for large, risky relative to small, safe rewards, whereas relapsing individuals failed to show differential activation between reward types. All three random forest models yielded good test characteristics such that a positive test for relapse yielded a likelihood ratio 2.63, whereas a negative test had a likelihood ratio of 0.48. CONCLUSIONS: These findings suggest that neuroimaging can be developed in combination with other measures as an instrument to predict relapse, advancing tools providers can use to make decisions about individualized treatment of substance use disorders.

  • Stewart, J. L., Connolly, C. G., May, A. C., Tapert, S. F., Wittmann, M., & Paulus, M. P. (2014). Cocaine dependent individuals with attenuated striatal activation during reinforcement learning are more susceptible to relapse. Psychiatry Research, 223(2), 129–139. https://doi.org/10.1016/j.pscychresns.2014.04.014

    Cocaine-dependent individuals show altered brain activation during decision making. It is unclear, however, whether these activation differences are related to relapse vulnerability. This study tested the hypothesis that brain-activation patterns during reinforcement learning are linked to relapse 1 year later in individuals entering treatment for cocaine dependence. Subjects performed a Paper-Scissors-Rock task during functional magnetic resonance imaging (fMRI). A year later, we examined whether subjects had remained abstinent (n=15) or relapsed (n=15). Although the groups did not differ on demographic characteristics, behavioral performance, or lifetime substance use, abstinent patients reported greater motivation to win than relapsed patients. The fMRI results indicated that compared with abstinent individuals, relapsed users exhibited lower activation in (1) bilateral inferior frontal gyrus and striatum during decision making more generally; and (2) bilateral middle frontal gyrus and anterior insula during reward contingency learning in particular. Moreover, whereas abstinent patients exhibited greater left middle frontal and striatal activation to wins than losses, relapsed users did not demonstrate modulation in these regions as a function of outcome valence. Thus, individuals at high risk for relapse relative to those who are able to abstain allocate fewer neural resources to action-outcome contingency formation and decision making, as well as having less motivation to win on a laboratory-based task.

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Last update from database: 04.06.25, 15:35 (UTC)