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Intro
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Classroom Contents
Connectome-Based Modeling of Real World Clinical Outcomes in Addictions
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- 1 Intro
- 2 Clinical reality
- 3 Neuroimaging of addiction outcomes
- 4 Limitations
- 5 Machine learning (aka predictive modeling)
- 6 Study design
- 7 Brain state manipulation improves prediction
- 8 Monetary incentive delay task
- 9 Model validation - predictive accuracy
- 10 Abstinence networks
- 11 Short versus long-range connectivity
- 12 Post-treatment networks predict abstinence
- 13 Cognitive control (Stroop) task
- 14 Opioid network connectivity
- 15 Theoretical opioid network model
- 16 Network identification is brain-state dependent
- 17 Cocaine network across drugs and brain states
- 18 Opioid network across drugs and brain states
- 19 Post-treatment connectivity predicts opioid use
- 20 Pathology versus prediction
- 21 Theoretical model
- 22 Healthy controls
- 23 Protracted neural change?
- 24 Second external replication
- 25 Best' metric depends on the question
- 26 Clinical workflow
- 27 Elucidation as a goal of prediction
