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  • 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.

  • Lorey, B., Naumann, T., Pilgramm, S., Petermann, C., Bischoff, M., Zentgraf, K., Stark, R., Vaitl, D., & Munzert, J. (2014). Neural simulation of actions: effector- versus action-specific motor maps within the human premotor and posterior parietal area? Human Brain Mapping, 35(4), 1212–1225. https://doi.org/10.1002/hbm.22246

    This study addresses the controversy over how motor maps are organized during action simulation by examining whether action simulation states, that is, motor imagery and action observation, run on either effector-specific and/or action-specific motor maps. Subjects had to observe or imagine three types of movements effected by the right hand or the right foot with different action goals. The functional magnetic resonance imaging results showed an action-specific organization within premotor and posterior parietal areas of both hemispheres during action simulation, especially during action observation. There were also less pronounced effector-specific activation sites during both simulation processes. It is concluded that the premotor and parietal areas contain multiple motor maps rather than a single, continuous map of the body. The forms of simulation (observation, imagery), the task contexts (movements related to an object, with usual/unusual effector), and the underlying reason for performing the simulation (rate your subjective success afterwards) lead to the specific use of different representational motor maps within both regions. In our experimental setting, action-specific maps are dominant especially, during action observation, whereas effector-specific maps are recruited to only a lesser degree.

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