MAPs: Methods And Primers for Computational Psychiatry and Neuroeconomics

Why do we do it and how do we start?

Clinical scientists are often overwhelmed by the complexity of large datasets and the challenges of integrating many types of data within hypothesis-testing frameworks in the pursuit of deep insights into etiology, pathophysiology, and treatment of psychopathologies. The application of recently developed analytic and mathematical modeling approaches to psychiatry, “computational psychiatry” shows promise in addressing these challenges.

However, among entry barriers for those considering computational psychiatry approaches are a relative lack of computational background and perceived difficulties of employing computational tools. This seminar series aims to lower such barriers by providing information about WHY and HOW to use computational psychiatry approaches. Speakers (both experienced and beginners) will present their computational projects; they will also discuss step-by-step instructions of how to start, available supporting resources, and common difficulties and best practices. MAPs is sponsored by the Department of Psychiatry, Yale School of Medicine. Faculty Organizers: Youngsun Cho, Sarah Fineberg, Al Powers, and Helen Pushkarskaya.

The workshop meets monthly on selected Thursdays from 4:00 – 5:00 pm. Due to the COVID-19 pandemic, workshop sessions will be held virtually on Zoom. Please subscribe to the MAPs workshop via google group: yale-maps@googlegroups.com. Zoom links will also be posted on the respective talk webpages.

Summer 2023 Schedule

A Practical Introduction into Dynamic Causal Modeling

Date	Speaker and Title
June 1, 12 - 1pm	Kangjoo Lee, PhD, Yale psychiatry In the first session, we will give an overview of functional localization – identifying where in the brain neural activity occurs. We will focus on the General Linear Model (GLM), in conjunction with a simple auditory task fMRI experiment
June 8, 12 - 1pm	Peter Zeidman, PhD, University College of London In the second session, we will introduce dynamic causal modelling (DCM), a framework for inferring the dynamic interactions among brain regions.
June 15, 12 - 1pm	Peter Zeidman, PhD, University College of London The third session will be a practical workshop, where we will illustrate applying the GLM and DCM to investigate individual differences in effective connectivity. All analyses will be illustrated using the open source Statistical Parametric Mapping (SPM) software package, which is a toolbox for MATLAB. Nevertheless, many of the principles we will cover are common across analysis packages.

Note: Participation in the third session is by invitations only (contact helen.pushkarskaya@yale.edu). Recordings will be posted online. All tutorial participants will offer additional follow up practical tutorials during the following weeks. To sign up for these tutorials or to invite instructors to your research group, please sign up here.

Spring 2022 Schedule

Date	Speaker and Title
February 3, 2022	Dustin Scheinost, Dept. Radiology & Biomedical Imaging, Biomedical Engineering, Statistics & Data Science, and at the Yale Child Study Center, Yale School of Medicine; The Multi-modal Imaging, Neuroinformatics, & Data Science (MINDS) Lab. Title: “Ten simple rules for predictive models.”
April 7, 2022	Alfred P. Kaye and Eyiyemisi Damisah, Department of Psychiatry, Yale University School of Medicine. Title: “Pupillometry and intracranial recordings in Psychiatry Research.”
May 5, 2022	Stefanie Enriquez-Geppert, Dep. of Clinical Neuropsychology, Faculty of Behavioural and Social Sciences, University of Groningen & Dep. of Biomedical Sciences of Cells & Systems, Section of Cognitive Neuropsychiatry, University Medical Center Groningen. Title: “EEG-Neurofeedback as a Tool to Modulate Cognition and Behavior: A Review Tutorial.”

Fall 2021 Schedule

Date	Speaker and Title
October 7, 2021: NOTE Special time 3:30 - 5:00 pm	Thomas Keegan, the Lab Director of the Human Nature Lab (PI Dr. Nicholas A. Christakis), Yale Institute for Network Science, Yale University. Title: "Trellis and breadboard: Software tools for social networks research.”
November 4, 2021: NOTE Special time 2:00 - 5:00 pm	Ryan Smith, Associate Investigator, Laureate Institute for Brain Research, Tulsa, Oklahoma. Title: "Active Inference and its Application to Empirical Data.”
December 2, 2021	Juliet Beni Edgcomb, Division of Child and Adolescent Psychiatry, Semel Institute for Neuroscience & Human Behavior, Department of Psychiatry & Biobehavioral Sciences, UCLA David Geffen School of Medicine. Title: "Leveraging Clinical Informatics to Improve Mental Health Care.”

Spring 2021 Schedule

Date	Speaker and Title
January 7, 2021	Rick A Adams, PhD, MRC Fellow, Dept Computer Science & Max Planck UCL Centre for Computational Psychiatry. Title: "What is E/I imbalance? Clarifying the fundamental circuit dysfunction in schizophrenia using biophysical modelling of multiple imaging paradigms.”
February 4, 2021	Chris Mathys, PhD, Interacting Minds Centre, Aarhus University. Title: "Hierarchical Gaussian Filters (HGFs) for behavioral modelling in computational psychiatry."
March 4, 2021	Michael J. Frank, PhD, Cognitive, Linguistic & Psychological Sciences; Neuroscience Graduate Program; Director, Carney Center for Computational Brain Science; Carney Institute for Brain Science, Psychiatry and Human Behavior, Brown University. Title: "Drift diffusion model and beyond for linking brain to behavioral data in patient populations."
April 1, 2021	!! LONG FORMAT: 3 HOUR 2-PARTS WORKSHOP !! Yael Niv, PhD, Professor of Psychology and Neuroscience; Princeton Neuroscience Institute; Princeton University. Title: "Fitting dynamic models of learning to trial-by-trial behavioral data." Part I, 2:00-3:15 pm -- Bayesian inference and working with probabilities. Part II, 3:30-5:00 pm -- Reinforcement Learning models and trial-by-trial model fitting. Please join in for either or both parts.
May 6, 2021	Michael Hallquist, PhD, Associate Professor; Department of Psychology and Neuroscience; University of North Carolina at Chapel Hill Title: The Multilevel Event-related Deconvolved Signal Analysis (MEDuSA) of trial-to-trial variation in neural task-based activity

Fall 2020 Schedule

Date	Speaker and Title
October 1, 2020	Alan Anticevic, PhD, Department of Psychiatry, Division of Neurocognition, Neurocomputation, and Neurogenetics (N3), Yale School of Medicine. Title: "QuNex, a neuroimaging processing suite”
November 5, 2020	John Murray, PhD, Department of Psychiatry, Division of Neurocognition, Neurocomputation, and Neurogenetics (N3), Yale School of Medicine. Title: "A flexible framework for simulating and fitting generalized drift-diffusion models.”
December 10, 2020	Xiaosi Gu, PhD, Director, Computational Psychiatry Unit, Friedman Brain Institute & Addiction Institute, Icahn School of Medicine at Mount Sinai. Title: "Modeling the social brain.”