MAPs: Methods And Primers for Computational Psychiatry and Neuroeconomics

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.

Please subscribe to the MAPs workshop via google group. Zoom links will also be posted on the respective talk webpages.

A Primer on Topological Data Analysis and Graph Signal Processing for Neuroimaging Data: Geometry Scattering Trajectory Homology (GSTH) toolbox

Date	Speaker and Title
June 6, 4:00 pm -5:30 pm	Dhananjay Bhaskar, PhD, Department of Genetics, Yale School of Medicine In the first session, we will give an overview of aims and basics of topological data analysis.
June 13, 4:00 pm -5:30 pm	Rahul Singh, PhD, Yale Wu Tsai Neuroscience Institute, Yale University In the second session, we will introduce graph signal processing methods.
June 20, 4:00 pm -6:00 pm	Dhananjay Bhaskar, PhD, Department of Genetics, Yale School of Medicine Brian Zaboski, PhD, Department of Genetics, Yale School of Medicine In the third session, we will introduce the Geometry Scattering Trajectory Homology (GSTH) approach and discuss some applications for clinical research.
June 27, 4:00 pm -6:00 pm	Dhananjay Bhaskar, PhD, Department of Genetics, Yale School of Medicine Rahul Singh, PhD, Yale Wu Tsai Neuroscience Institute, Yale University The fourth session will be the practical tutorial in GSTH using real data.

Note: If you are interested in attending the practical tutorial in GSTH (session 4) please contact helen.pushkarskaya@yale.edu. All recordings will be posted online.

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.