Explore cutting-edge research on predicting addiction outcomes using connectome-based modeling in this 42-minute lecture from the Computational Psychiatry 2020 conference. Delve into Sarah Yip's presentation from Yale University, which showcases how machine learning and predictive modeling techniques can overcome traditional limitations in clinical research. Learn about Connectome-based Predictive Modeling (CPM) and its application in forecasting real-world clinical outcomes for individuals with polysubstance use. Discover how this data-driven approach identifies specific brain networks underlying behavior, predicts cocaine and opioid abstinence, and demonstrates network stability over time. Gain insights into the dissociable anatomical substrates of different substance use types and the potential for translating these findings to clinical settings. Examine the study design, brain state manipulation techniques, and model validation methods used in this groundbreaking research.