The 2019 Computational Psychiatry Course speakers.
On July 29-30, the Department of Psychiatry hosted the 2019 Computational Psychiatry Course at The Metropolitan Museum of Art with support from the Icahn School of Medicine at Mount Sinai and IBM Research. The first day opened with a speech from René Kahn, MD, PhD, Chair of Psychiatry and Behavioral Health at the Icahn School of Medicine at Mount Sinai. He addressed the promise of computational models in psychiatry: we understand psychiatric disease more than ever, but we have no cures, and to create cures we need new ideas, large samples, and new techniques—enter computational psychiatry. He emphasized the predictive clinical utility of these models, such as predicting onset of psychosis in high-risk subjects, predicting treatment response, and predicting course of illness. The keynote addressed was given at the end of the second day by Matthew Botvinick, MD, PhD, Director of Neuroscience Research at DeepMind, on deep reinforcement learning. “Deep reinforcement learning is not an architecture or even really an algorithm, ” he said. “It’s a framework, and a huge amount of variability and diversity can be explored within it.”
The rest of the course lectures are listed below.
Day 1: Theory
Theoretical Approaches to Function and Dysfunction
Peter Dayan, PhD, Max Planck Institute for Biological Cybernetics
Computational and Algorithmic Accounts of Inference and Choice—Inference About States
Chris Mathys, MSc, MSc, PhD, Scuola Internazionale Superiore di Studi Avanzati
Model-Free and Model-Based Learning
Nathanial Daw, PhD, Princeton University
Social Exchange Games to Study Human Behavior
Read Montague, PhD, Virginia Tech
Trial-by-Trial Model Fitting
Yael Niv, PhD, Princeton University
Modelling Example: A Line by Line Lesson
Yael Niv, PhD, Princeton University
Natural Language Processing for Brain Disorders
Guillermo Cecchi, PhD, IBM Research
Computationally-Relevant NIH Funding Opportunities
Michele Ferrante, PhD, National Institute of Mental Health
Panel Discussion
Jean Zarate, PhD, Nature Neuroscience
Participants:
Daniela Schiller, PhD, Icahn School of Medicine at Mount Sinai
Yael Niv, PhD, Princeton University
Sonia Bishop, PhD, University of California, Berkeley
Rick Adams, PhD, University College London
Matthew Botvinick, MD, PhD, DeepMind
Day 2: Application
Brain Computations in Schizophrenia
Rick Adams, PhD, University College London
Autism Spectrum Disorder
Becky Lawson, PhD, University of Cambridge
Depression
Robb Rutledge, PhD, University College London
Anxiety and Decision-Making Under Uncertainty
Sonia Bishop, PhD, University of California, Berkeley
Neural Computations in the Aftermath of Trauma
Daniela Schiller, PhD, Icahn School of Medicine at Mount Sinai
Addiction
Xiaosi Gu, PhD, Icahn School of Medicine at Mount Sinai
Deep Phenotyping
Read Montague, PhD, Virginia Tech