Krembil Centre for Neuroinformatics Summer School
Solving Problems in Mental Health using Multi-Scale Computational Neuroscience
Distribution Date: June 2022
Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health
Topics
Introductory Concepts
A collection of lectures on overaching concepts in Neuroinformatics Research.
Topic | Instructor | Video | Slides | |
|---|---|---|---|---|
A Multiscale Approach to Brain Disorders | YouTube (1:09:33) | slides | ||
Problems and opportunities in the diagnosis and treatment of major depression | YouTube (1:29:28) | slides |
Computing Fundamentals
For those who need more help with computing fundamentals - going into the later content. We recommend content available from the KCNI Scientific Computing Working Group.
| Topic | Tutorial Videos / Online Tutorials | Prerequisit to | |
|---|---|---|---|
| R | R Workshop Material (Apr-Jun 2022) |
| |
| Python | Introduction to Python |
| |
| Git/Github | Introduction to Git and GitLab | ||
| Linux/Bash | Introduction to Linux and Bash (Youtube) | ||
many recordings available via from last falls series. 2021 Fall - SCWG Workshop Recordings
Reproducible Science (including Git, Docker and Binder)
Applied Ethics in Machine Learning and Mental Health
Topic | Video | Materials | |
|---|---|---|---|
Lecture 1: Introduction to AI Ethics -Daniel Buchman | Watch on YouTube (1:22:07) | slides | |
Lecture 2: Fairness and Health Equity -Laura Sikstrom | Watch on Youtube (1:06:36) | slides | |
Workshop 1: Research Design, Data Collection, Model Construction and Validation -Part 2: Intersectional Bias AssessmentMarta Maslej & Laura Sikstrom | Watch on Youtube (52:27) | ||
All videos previously recorded July 6th, 2021 as part of the KCNI Summer School
Digital Health for Mental Health
Dr. Abhishek (Abhi) Pratap
Independent Scientist & Lead of the Augmented Intelligence and Digital Tech for Mental Health (AID 4 Mental Heath) Lab,
The Krembil Centre for Neuroinformatics, Campbell Family Mental Health Research Institute, CAMH
Computing environment: Python (jupyter)
Session | Instructor | Video | Materials |
|---|---|---|---|
Lecture 1: Digital Health for Mental health | Abhi Pratap | Youtube (1:20:28) | |
Workshop 1: accessing reproducible datasets from Synapse as part of integrated workflow | Abhi Pratap | YouTube (1:15:12) |
The workshop demostates how to work with the Synapse platform.
Fundamental Methods for Genomic Analysis
Presented by Dr Dan, Felsky - Independent Scientist and Head of Whole Person Modelling at KCNI, Assistant Professor in the Department of Psychiatry, University of Toronto. Assistant Professor at the Dalla Lana School of Public Health, University of Toronto.
- Dr Felsky has a PhD in neuroimaging and genetics of Alzheimer’s disease at U of T, Postdocs in computational neuroimmunology and bioinformatics at Broad Institute, Harvard Medical School & Columbia University.
Session | Instructor | Video | Materials |
|---|---|---|---|
Lecture 1: Basics of genotype, central dogma, GWAS, and polygenic risk scores | Dan Felsky | YouTube (1:28:17) | |
Workshop 1: Managing genotype data using PLINK | Dan Felsky | YouTube (1:27:18) | code (GitHub) |
| Workshop 2: Calculation of polygenic risk scores in PRSice | Dan Felsky | YouTube (1:53:34) | code (GitHub) |
| Considering population stratification and admixture in modern GWAS; concepts and tools | Dan Felsky | Register for the live webinar |
All videos previously recorded July July 7th, 2021 as part of the KCNI Summer School
Fundamental Methods for Single-Cell Transcriptome Analysis
Presented by Shreejoy Tripathy & the Computational Genomics Lab
- Independent Scientist and Head of Computational Genomics at KCNI, Assistant Professor in the Department of Psychiatry, University of Toronto., Assistant Professor in the Department of Physiology, University of Toronto
- PhD in Computational Neuroscience from Carnegie Mellon and Post-doc in neuroinformatics and bioinformatics at University of British Columbia.
Session | Instructor | Video | Materials |
|---|---|---|---|
Lecture 1: Transcriptomics at the single-cell and bulk level level | Shreejoy Tripathy | YouTube (1:29:08) | slides |
Workshop 1: Intro to transcriptomic data types, including single-cell and bulk RNAseq | Sonny Chen | YouTube (1:19:17) | |
Workshop 2: Explore cellular changes in major depression using bulk and single-cell RNAseq data | Keon Arbabi | YouTube (1:15:14) |
All videos previously recorded July 7th, 2021 as part of the KCNI Summer School
TA's: Keon Arbabi, Sonny Chen, Micaela Consens, Amin Kharaghani
Simulating Brain Microcircuit Activity and Signals in Mental Health
Register for Virtual Q&A - June 23, 2022 3:30pm EST
Presented by Etay Hay and Brain Circuit Modelling Group
Session | Instructors | Video | Materials |
|---|---|---|---|
Lecture 1: Simulating brain microcircuit activity in mental health | Etay Hay & Frank Mazza | YouTube (1:20:43) | slides |
Lecture 2: Simulating EEG from brain microcircuits in mental health | Etay Hay & Frank Mazza | YouTube (1:11:04) | slides |
Workshop 1: Simulating and analyzing spiking from neurons and microcircuits | Etay Hay & Frank Mazza | YouTube (1:39:51) | |
Workshop 2: Simulating and analyzing EEG signals from brain microcircuits | Etay Hay & Frank Mazza | YouTube (1:30:41) |
All videos previously recorded July 8th, 2021 as part of the KCNI Summer School
Neuroimaging Connectomics
Presented by:
John Griffiths Ph.D - Lead - Whole Brain Modeling Group, Krembil Centre for Neuroinformatics - CAMH, Assistant Professor, University of Toronto Depts. Psychiatry & Medical Sciences, Twitter: @neurodidact, Github: @JohnGriffiths, @GriffithsLab, Website: grifflab.com
Erin Dickie Ph.D - Education and Knowledge Lead - KCNI, Scientist - Kimel Family Translational Imaging-Genetics Lab, Twitter: @ErinWDickie ,Github: @edickie
Session | Instructors | Video | Materials |
|---|---|---|---|
Lecture 1: Introduction to neuroimaging connectomics | Erin Dickie & John Griffiths | YouTube (1:47:22) | slides |
Workshop 1: Calculating Neuroimaging Connectomes | Erin Dickie & John Griffiths | YouTube (1:39:04) |
Whole-Brain Modelling
Presented by:
John Griffiths Ph.D - Lead - Whole Brain Modeling Group, Krembil Centre for Neuroinformatics - CAMH, Assistant Professor, University of Toronto Depts. Psychiatry & Medical Sciences, Twitter: @neurodidact, Github: @JohnGriffiths, @GriffithsLab, Website: grifflab.com
Session | Instructors | Video | Materials |
|---|---|---|---|
Lecture 2: Intro to whole-brain modelling (Lecture) | John Griffiths | YouTube (1:24:44) | |
Workshop 2: simulating whole-brain activity, EEG, evoked responses, brain stimulation | John Griffiths | YouTube (1:16:10) |
All videos previously recorded July 9th, 2021 as part of the KCNI Summer School
Bayesian Models of Learning and Integration of Neuroimaging Data
Presented by Andreea Diaconescu and the Cognitive Network Modelling (CogNeMo) Group
Coding Language: MATLAB more setup info
Session | Instructor | Video | Materials |
|---|---|---|---|
Lecture 1: Modelling Cognition using Bayesian Inference | Andreea Diaconescu | YouTube (1:28:14) | slides |
Workshop 1: Modelling Abnormal Beliefs | Daniel Hauke | YouTube (1:15:04) | code (github) |
Lecture 2: Integration of Neuroimaging: Dynamic Causal Modelling for fMRI and EEG Data | Andreea Diaconescu, Colleen Charlton | YouTube (1:32:42) | slides |
Workshop 2: Dynamic Causal Modelling for fMRI: Extensions and Simulations | Peter Bedford, Povilas Karvelis | YouTube (1:22:21) | code (github) |
All videos previously recorded July 12th, 2021 as part of the KCNI Summer School
TA's: Colleen Charlton, Daniel Hauke, Peter Bedford, Povilas Karvelis
Population-Based Data Resources & Integrative Research Methods
Session | Instructor | Video | Materials | |
|---|---|---|---|---|
Lecture 1: Population-based resources and the BrainHealth Databank | Joanna Yu | YouTube | slides | |
Workshop 1: Introduction to interactive methods | Daniel Felsky | YouTube (1:24:30) | ||
Lecture 2: Types of integrative research and Whole Person Modelling | Daniel Felsky | YouTube (1:28:14) | ||
Workshop 2: SNF / Subtyping | Daniel Felsky | YouTube (1:21:38) |