Predicting Stimulant Use Relapse using Neuroimaging Techniques
Project Principal Investigator/s:
Michael Maurer
Funding Agency:
National Institutes of Health/National Institute on Drug Abuse
Amount Awarded:
31, 156
Period of Performance:
09/2017 - 08/2019
Goals and Aims of Study
Using the world’s largest forensic database, which includes clinical and neuropsychological measures, electrophysiological measures, functional neuroimaging, and functional network connectivity measures, the primary goal of this project will be to delineate specific risk factors predictive of eventual stimulant use relapse propensity. This will be accomplished by integrating models incorporating logistic and Cox proportional-hazard regressions, and cross-validation machine learning pattern classifiers to predict stimulant use relapse one year after institutional release with an at-risk sample of adult incarcerated offenders.