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Principles of fMRI 2
  • Level Foundation
  • Duration 9 hours
  • Course by Johns Hopkins University
  • Offered by

About

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”.

Modules

Psychological and Behavioral Inference

    • 8 Videos
    • 1 Readings
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8 Videos

  • Module 1A: Crises in neuroscience and psychology: Problems and solutions
  • Module 1B: Crises in neuroscience and psychology: Problems and solutions
  • Module 2A: Pitfalls and Biases in Interpretation: Circularity, Reverse inference, Voodoo, and Beyond
  • Module 2B: Pitfalls and Biases in Interpretation: Circularity, Reverse inference, Voodoo, and Beyond
  • Module 3: Meta Analysis
  • Module 4: Using meta-analysis to improve inference
  • Module 5: Optimizing acquisition for your study goals
  • Module 6: Resting-state fMRI

1 Readings

  • Syllabus

Quiz

    • 1 Assignment
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1 Assignment

  • Quiz 1

Advanced Experimental Design

    • 4 Videos
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4 Videos

  • Module 7A: Advanced Experimental Design I - Fundamentals of design efficiency
  • Module 7B: Advanced Experimental Design I - Fundamentals of design efficiency
  • Module 8: Advanced Experimental Design II – Efficiency in fMRI
  • Module 9: Advanced Experimental Design III – Optimizing experimental designs with genetic algorithms

Advanced GLM Modeling

    • 7 Videos
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7 Videos

  • Module 10: Model building: Parametric modulators
  • Module 11: Basis Sets II: Smooth FIR, HTW, Basis sets at 2nd level
  • Module 12A: Multicolinearity and diagnostics
  • Module 12B: Multicolinearity and diagnostics
  • Module 13: Robust regression
  • Module 14A: Practical group analysis: Procedures and checks
  • Module 14B: Practical group analysis: Procedures and checks

Quiz

    • 1 Assignment
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1 Assignment

  • Quiz 2

Connectivity I: Functional Connectivity

    • 5 Videos
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5 Videos

  • Module 15: Brain Connectivity – different types
  • Module 16: Functional Connectivity
  • Module 17: Multivariate Decomposition Methods
  • Module 18: Dynamic Connectivity
  • Module 19: Network Analysis I – Graph theory

Connectivity II: Effective Connectivity

    • 3 Videos
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3 Videos

  • Module 20: Effective Connectivity
  • Module 21: Mediation, moderation, and structural models
  • Module 21B: Mediation, moderation, and structural models

Quiz

    • 1 Assignment
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1 Assignment

  • Quiz 3

Connectivity II: Directional Models

    • 3 Videos
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3 Videos

  • Module 22: Directed graphs: DCM
  • Module 23: Directed graphs: Granger causality
  • Module 24: Principles of causal inference

MVPA

    • 7 Videos
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7 Videos

  • Module 25: Multi-voxel Pattern Analysis: A neuroscientific perspective
  • Module 25B: Multi-voxel Pattern Analysis: A neuroscientific perspective
  • Module 26: MVPA Intro
  • Module 27: Performing MVPA I
  • Module 28: Performing MVPA II
  • Module 29: MVPA-PM Example – NPS - Expand: Social and physical pain
  • Module 29B: MVPA-PM Example – NPS - Expand: Social and physical pain

Quiz

    • 1 Assignment
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1 Assignment

  • Quiz 4

Auto Summary

Discover the interdisciplinary world of functional Magnetic Resonance Imaging (fMRI) with "Principles of fMRI 2" on Coursera. This foundational course delves into fMRI data analysis, perfect for psychologists, neuroscientists, and data scientists. Spanning 540 minutes, it offers Starter and Professional subscription options, making it accessible for all learners seeking to deepen their understanding of the human brain.

Martin Lindquist, PhD, MSc
Instructors

Martin Lindquist, PhD, MSc

Tor Wager, PhD
Instructors

Tor Wager, PhD