The Krembil Centre for Neuroinformatics is excited to publish a free, globally accessible, series of videos and interactive coding tutorials for self-directed on-line learning (click here for an index of materials) of techniques for integrating multi-scale neuroscience data. This series is designed to introduce participants to the concepts and methods behind psychiatric neuroinformatics - encompassing genetics, brain structure and function, and cognition. In addition, participants will uncover the links between modalities of human genomics, neuronal electrophysiology, structural and functional neuroimaging, and observed behaviour that KCNI scientists are integrating through a series of virtual modules and a group-based project using real-world data types to study mental illness.
This unique learning opportunity will prepare participants to handle and analyze multiple data types in hopes that their own research may benefit from collaborative, multi-modal approaches. Critically, participants will also learn about best practices for data management and quality control in the context of integrative analysis.
Requirements and Prerequisites
Applications from graduate students, post-graduate research and clinical fellows, and early-career scientists will be considered. Researchers from diverse backgrounds (e.g. medicine, computer science, biology, psychology, engineering etc.) are encouraged to apply. To ensure that all attendees can fully follow and benefit from the practical assignments, fundamental and demonstrable experience in R and Python is a minimum requirement.
Participants will be introduced to all the topics listed below via our virtual learning materials and online Q&A sessions.
- Understand the fundamental concept of Psychiatric genetics
- Learn how to integrate psychiatric genetics with multi-omics data (incl. Single-cell transcriptomics)
- Learn how to model whole-brain macro-connectomics and neural dynamics
- Learn how to apply Bayesian models of perception & learning used to neuroimaging & electrophysiological data
- Integrate Psychiatric epidemiology and apply Population-based subtyping
- Ethics, fairness and health equity in Al and healthcare
- Understand collection and analysis of real-world data in mental health
Students will be provided with a collection of virtual didactic teaching (lectures) and hands-on tutorial components to engage critical thinking and develop practical skills in crucial selected areas. Lessons will be led by members and affiliates of the KCNI team, including faculty at the University of Toronto’s Department of Psychiatry.
Certification and Accreditation
None (We are looking into IMS accreditation.)