Computational Psychiatry:
a didactic introduction

Friday November 10: 8a – 5p

Jonathan Cohen, Princeton University
    The need and promise of Computational Psychiatry

Peter Dayan, University College London
    Bayesian decision theory

Anne Collins, University of California, Berkeley
    Reinforcement learning models

Danielle Bassett, University of Pennsylvania
    Network science approaches to neural function

Stephanie Jones, Brown University
    Modeling human neural dynamics in health and disease

Martin Paulus, Laureate Institute for Brain Research
    Connecting neuroscience with clinical care

Pearl Chiu, Virginia Polytechnic Institute & State University
    Computational Psychiatry of depression and PTSD

Philip Corlett, Yale University
    Predictive models of mental disease

Michael Frank, Brown University
    Reinforcement learning in action

Saturday November 11: 8a – 12p

Yael Niv, Princeton University
    Modeling mood disorders

Xiaosi Gu, University of Texas, Dallas
    Modeling subjective states and application to addiction

Stephen LaConte, Virginia Polytechnic Institute & State University
    Real-time fMRI and prediction of craving states

Rick Adams, University College London
    Schizophrenia models

Read Montague, Virginia Polytechnic Institute & State University, University College London
    Computational phenotyping in health and disease