Principles of fMRI 2

Principles of fMRI 2

This course is part of Neuroscience and Neuroimaging Specialization

Instructors: Martin Lindquist, PhD, MSc

18,436 already enrolled

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4 modules

Gain insight into a topic and learn the fundamentals.

249 reviews

9 hours to complete

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

249 reviews

9 hours to complete

Flexible schedule

Learn at your own pace

Skills you'll gain

Tools you'll learn

Matlab

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 assignments

Taught in English

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This course is part of the Neuroscience and Neuroimaging Specialization

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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

Instructor ratings

(39 ratings)

Martin Lindquist, PhD, MSc

Johns Hopkins University

2 Courses 48,688 learners

Offered by

Johns Hopkins University

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Reviewed on Feb 11, 2019

Great course and demonstration with real research examples.

Reviewed on Nov 11, 2018

Similar to the first installment of the series. I found this course enlightening and easily digestible, especially considering the advance material it discusses. Overall enjoyable experience.

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.

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