Principles of fMRI 2
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Principles of fMRI 2
This course is part of Neuroscience and Neuroimaging Specialization
18,672 already enrolled
Included with
Skills you'll gain
- Neurology
- Dimensionality Reduction
- Data Analysis
- Advanced Analytics
- Statistical Methods
- Statistical Modeling
- Network Analysis
- Psychology
- Statistical Inference
- Medical Imaging
- Time Series Analysis and Forecasting
- Magnetic Resonance Imaging
- Statistical Analysis
- Image Analysis
- Correlation Analysis
- Regression Analysis
- Model Evaluation
Details to know
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There are 4 modules in this course
Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique for investigating the living, functioning human brain as people perform tasks and experience mental states. It is a convergence point for multidisciplinary work from many disciplines. Psychologists, statisticians, physicists, computer scientists, neuroscientists, medical researchers, behavioral scientists, engineers, public health researchers, biologists, and others are coming together to advance our understanding of the human mind and brain. This course covers the analysis of Functional Magnetic Resonance Imaging (fMRI) data. It is a continuation of the course “Principles of fMRI, Part 1”.
This week we will discuss psychological and behavioral inference, as well as advanced experimental design.
What's included
8 videos1 reading1 assignment
8 videos•Total 103 minutes
- Module 1A: Crises in neuroscience and psychology: Problems and solutions•14 minutes
- Module 1B: Crises in neuroscience and psychology: Problems and solutions•15 minutes
- Module 2A: Pitfalls and Biases in Interpretation: Circularity, Reverse inference, Voodoo, and Beyond•12 minutes
- Module 2B: Pitfalls and Biases in Interpretation: Circularity, Reverse inference, Voodoo, and Beyond•13 minutes
- Module 3: Meta Analysis•11 minutes
- Module 4: Using meta-analysis to improve inference•12 minutes
- Module 5: Optimizing acquisition for your study goals•18 minutes
- Module 6: Resting-state fMRI•8 minutes
1 reading•Total 10 minutes
- Syllabus•10 minutes
1 assignment•Total 30 minutes
- Quiz 1•30 minutes
This week we will continue with advanced experimental design, and also discuss advanced GLM modeling.
What's included
11 videos1 assignment
11 videos•Total 119 minutes
- Module 7A: Advanced Experimental Design I - Fundamentals of design efficiency•10 minutes
- Module 7B: Advanced Experimental Design I - Fundamentals of design efficiency•13 minutes
- Module 8: Advanced Experimental Design II – Efficiency in fMRI•10 minutes
- Module 9: Advanced Experimental Design III – Optimizing experimental designs with genetic algorithms•13 minutes
- Module 10: Model building: Parametric modulators•9 minutes
- Module 11: Basis Sets II: Smooth FIR, HTW, Basis sets at 2nd level•11 minutes
- Module 12A: Multicolinearity and diagnostics•11 minutes
- Module 12B: Multicolinearity and diagnostics•9 minutes
- Module 13: Robust regression•15 minutes
- Module 14A: Practical group analysis: Procedures and checks•9 minutes
- Module 14B: Practical group analysis: Procedures and checks•10 minutes
1 assignment•Total 30 minutes
- Quiz 2•30 minutes
This week we will focus on brain connectivity.
What's included
8 videos1 assignment
8 videos•Total 77 minutes
- Module 15: Brain Connectivity – different types•6 minutes
- Module 16: Functional Connectivity•9 minutes
- Module 17: Multivariate Decomposition Methods•9 minutes
- Module 18: Dynamic Connectivity•9 minutes
- Module 19: Network Analysis I – Graph theory•10 minutes
- Module 20: Effective Connectivity•10 minutes
- Module 21: Mediation, moderation, and structural models•12 minutes
- Module 21B: Mediation, moderation, and structural models•12 minutes
1 assignment•Total 30 minutes
- Quiz 3•30 minutes
This week we will focus on multi-voxel pattern analysis.
What's included
10 videos1 assignment
10 videos•Total 90 minutes
- Module 22: Directed graphs: DCM•7 minutes
- Module 23: Directed graphs: Granger causality•10 minutes
- Module 24: Principles of causal inference•12 minutes
- Module 25: Multi-voxel Pattern Analysis: A neuroscientific perspective•11 minutes
- Module 25B: Multi-voxel Pattern Analysis: A neuroscientific perspective•7 minutes
- Module 26: MVPA Intro•10 minutes
- Module 27: Performing MVPA I•10 minutes
- Module 28: Performing MVPA II•5 minutes
- Module 29: MVPA-PM Example – NPS - Expand: Social and physical pain•11 minutes
- Module 29B: MVPA-PM Example – NPS - Expand: Social and physical pain•7 minutes
1 assignment•Total 30 minutes
- Quiz 4•30 minutes
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Instructors
Offered by
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- Status: Free TrialJ
Johns Hopkins University
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- Status: Free TrialJ
Johns Hopkins University
Course
- Status: Free TrialJ
Johns Hopkins University
Specialization
- Status: PreviewK
Korea Advanced Institute of Science and Technology(KAIST)
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Reviewed on May 23, 2019
Very good course. Best week is the last week. Its does a good overview of fMRI Statistical analysis and design of experiments.
Reviewed on Jul 29, 2019
Excellent, thorough explanation of the computations and theory underlying fMRI analysis. I particularly enjoyed the emphasis on MVPA. Thanks!
Reviewed on Nov 16, 2016
The course was ery good, I wish it also included working with sample fmri data.
Frequently asked questions
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.