About this course: This course covers the analysis of Functional Magnetic Resonance Imaging (fMRI) data. It is a continuation of the course “Principles of fMRI, Part 1”
Created by: Johns Hopkins University, University of Colorado Boulder
Taught by: Martin Lindquist, PhD, MSc, Professor, Biostatistics
Bloomberg School of Public Health | Johns Hopkins University
Taught by: Tor Wager, PhD
Department of Psychology and Neuroscience, The Institute of Cognitive Science | University of Colorado at Boulder
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
Week 1
This week we will discuss psychological and behavioral inference, as well as advanced experimental design.
8 videos, 1 reading
- Reading: Syllabus
- Video: Module 1A: Crises in neuroscience and psychology: Problems and solutions
- Video: Module 1B: Crises in neuroscience and psychology: Problems and solutions
- Video: Module 2A: Pitfalls and Biases in Interpretation: Circularity, Reverse inference, Voodoo, and Beyond
- Video: Module 2B: Pitfalls and Biases in Interpretation: Circularity, Reverse inference, Voodoo, and Beyond
- Video: Module 3: Meta Analysis
- Video: Module 4: Using meta-analysis to improve inference
- Video: Module 5: Optimizing acquisition for your study goals
- Video: Module 6: Resting-state fMRI
Graded: Quiz 1
WEEK 2
Week 2
This week we will continue with advanced experimental design, and also discuss advanced GLM modeling.
11 videos
- Video: Module 7A: Advanced Experimental Design I - Fundamentals of design efficiency
- Video: Module 7B: Advanced Experimental Design I - Fundamentals of design efficiency
- Video: Module 8: Advanced Experimental Design II – Efficiency in fMRI
- Video: Module 9: Advanced Experimental Design III – Optimizing experimental designs with genetic algorithms
- Video: Module 10: Model building: Parametric modulators
- Video: Module 11: Basis Sets II: Smooth FIR, HTW, Basis sets at 2nd level
- Video: Module 12A: Multicolinearity and diagnostics
- Video: Module 12B: Multicolinearity and diagnostics
- Video: Module 13: Robust regression
- Video: Module 14A: Practical group analysis: Procedures and checks
- Video: Module 14B: Practical group analysis: Procedures and checks
Graded: Quiz 2
WEEK 3
Week 3
This week we will focus on brain connectivity.
8 videos
- Video: Module 15: Brain Connectivity – different types
- Video: Module 16: Functional Connectivity
- Video: Module 17: Multivariate Decomposition Methods
- Video: Module 18: Dynamic Connectivity
- Video: Module 19: Network Analysis I – Graph theory
- Video: Module 20: Effective Connectivity
- Video: Module 21: Mediation, moderation, and structural models
- Video: Module 21B: Mediation, moderation, and structural models
Graded: Quiz 3
WEEK 4
Week 4
This week we will focus on multi-voxel pattern analysis.
10 videos
- Video: Module 22: Directed graphs: DCM
- Video: Module 23: Directed graphs: Granger causality
- Video: Module 24: Principles of causal inference
- Video: Module 25: Multi-voxel Pattern Analysis: A neuroscientific perspective
- Video: Module 25B: Multi-voxel Pattern Analysis: A neuroscientific perspective
- Video: Module 26: MVPA Intro
- Video: Module 27: Performing MVPA I
- Video: Module 28: Performing MVPA II
- Video: Module 29: MVPA-PM Example – NPS - Expand: Social and physical pain
- Video: Module 29B: MVPA-PM Example – NPS - Expand: Social and physical pain
Graded: Quiz 4
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Creators
Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
University of Colorado Boulder
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
Ratings and Reviews
Very useful and interesting
Very interesting. I liked very much the last bit on MVPA.
Still very good course with a lot to offer especially parts covering new methods. The only downside for me were the mathematical parts by Martin which got complex, messy and seemed to be explained not as clear as in previous course. Some ecological, more experiment related examples could be useful to help understand mathematical operations and formulas.
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SG
pretty great